University of Southern California Dissertations and Theses

The Identification Of Accident-Proneness In Junior College Vocational Students And Industrial Employees

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The Identification Of Accident-Proneness In Junior College Vocational Students And Industrial Employees

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Content THE IDENTIFICATION OF ACCIDENT-PRONENESS IN JUNIOR COLLEGE VOCATIONAL STUDENTS AND INDUSTRIAL EMPLOYEES A Dissertation Presented to the Faculty of the School of Education University of Southern California In Partial Fulfillment of the Requirements for the Degree Doctor of Education by Arthur Frederick Steiner June 1970 70 - 25,065 STEINER, A rthur F r e d e r ic k , 1919- THE IDENTIFICATION O F ACCIDENT-PRONENESS IN JUNIOR COLLEGE VOCATIONAL STUDENTS A ND INDUSTRIAL EMPLOYEES. U n iv e r s ity o f S outhern C a lif o r n ia , Ed.D., 1970 E d u ca tio n , in d u s t r ia l University Microfilms, A X E R O X Company, Ann Arbor, Michigan Copyright by ARTHUR FREDERICK STEINER 1970 THIS DISSERTATION HAS BEEN MICROFILMED EXACTLY AS RECEIVED This dissertation, 'written under the direction of the Chairman of the candidate's Guidance Committee and approved by all members of the Committee, has been presented to and accepted by the Faculty of the School of Education in partial fulfillment of the requirements for the degree of Doctor of Education. Guidance Commit Chairman ACKNOWLEDGMENTS The author wishes to express his deepest gratitude to Professor Earl V. Pullias for his encouragement, assistance, and guidance through much of the author’s graduate work and throughout the undertaking of this study. Grateful recognition and appreciation is extended to Professors Myron Olson, Leslie Wilbur, and D. Welty Lefever for their valuable support, welcome encouragement, and critical analysis of the study. Furthermore, the author wishes to acknowledge the coopera tion of the Long Beach City College, the McDonnell-Douglas Aircraft Company, and the North American Rockwell Corporation for their assistance during the testing sequence of the study. For their contributions in reviewing the measuring instru ment, special gratitude is extended to Mr. Jack Barnes, State Safety Inspector, Division of Industrial Safety--Long Beach; Mr. David Etter, Safety Engineer, North American Rockwell Corporation, Downey, California; Mr. Raymond C. Hill, Director, Traffic Division—National Safety Council, Southern California Chapter; Mr. Clifford Kreager, Safety Superintendent, United States Naval Base, ii Long Beach, California; Mr. Lloyd Pillsbury, Head of Plant Safety, McDonnell-Douglas Aircraft Company, Long Beach, California; and Mr. Donald Rice, Safety Officer, City of Long Beach, Long Beach, California. Finally, the author desires to express indebtedness to his wife, son, and daughter for their sensitive understanding, considera tion, and encouragement during this long but exciting endeavor. TABLE OF CONTENTS Page ACKNOWLEDGMENTS................................................................... ii LIST OF TABLES.............................................................................. vi LIST OF ILLUSTRATIONS.............................................................. viii Chapter I. THE RESEARCH PROBLEM........................................ 1 Introduction Statement of the Problem The Procedure Limitations of the Study Definition of Terms Organization of the Research Report 1L REVIEW OF RELATED RESEARCH......................... 17 Introduction Developmental Concept of Accident-Proneness Psychological Factors Related to Accident- Proneness Personality Characteristics and Attitudes Related to Accident-Proneness III. PROCEDURE AND METHODOLOGY......................... 53 Introduction Sampling Procedure The Research Instrument The Safety Alertness Survey Treatment of Data iv Chapter Page IV. FINDINGS AND ANALYSIS........................................ 73 Introduction Summary of Findings Chapter Summary V. SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS................................................... 112 Summary Conclusions Recommendations APPENDIXES...................................................................................... 126 APPENDIX A .............................................................................. 127 APPENDIX B .............................................................................. 148 BIBLIOGRAPHY................................................................................ 185 v LIST OF TABLES Table Page 1. Tabulation of SAS Scores--Non-Accident Industrial G ro u p .............................................................. 76 2. Tabulation of SAS Scores--Accident Industrial Group................................................................. 77 3. Tabulation of SAS Scores—Student Accident G ro u p ................................................................. 78 4. Industrial Sample, Accident vs. Non-Accident D ata........................................................... 80 5. Comparison of Mean SAS Scores of Women Industrial Workers to Mean Scores of Total Sample . 85 6. Comparison of Means and Standard Deviations of Total Industrial and Total Student Sam ples................ 87 7. SAS Index As Related to A g e .......................................... 91 8. Instructor Rated "Unsafe"-"Safe" Students in Different Vocational C o u rses........................................ 94 9. Comparison of Mean SAS Scores and Standard Deviations of Rated Unsafe and Safe Students with SAS Mean Score and Standard Deviations of Total Sam ple................................................................. 95 10. Aeronautics—Airframe--High Risk............................... 99 11. Aeronautics—Powerplant--High Risk............................. 99 12. Architectural Drawing--Low Risk.................................. 100 vi Page 100 101 101 102 102 103 103 104 104 105 105 106 107 Auto Mechanics—High R isk .............. Carpentry--Medium Risk................... Diesel--Medium R isk ........................ Electronics--Low R isk ...................... Electromechanical--Medium Risk. . Industrial Electricity--Medium Risk Machine Tool—High R i s k ................ Mill Cabinet--High R is k ................... Refrigeration--Medium R is k ........... Sheet Metal--Medium R is k .............. Tool Design--Low Risk...................... Welding--High R is k ........................... SVIB--College Sample........................ vii LIST OF ILLUSTRATIONS Figure Page 1. Group I SAS Scores (Adventurous vs. Cautious Choices), Industrial and Student Accident Sample................................................................................ 81 2. Group II SAS Scores (General Safety Knowledge), Industrial and Student Accident S a m p le....................... 82 3. Group III SAS Scores (General Industrial Safety Knowledge), Industrial and Student Accident Sample ............................................................................. 83 4. Combined Total SAS Scores (Groups I, II, and III), Industrial and Student Accident Scores 84 viii CHAPTER I THE RESEARCH PROBLEM Introduction As a societal problem that influences the economy, indus trial progress and the individual, accidents have long been an area of investigation for specialists in psychology, engineering, medicine, economics, and sociology. Finding the problem of accident preven tion of ever-expanding concern for the industrial society, these professional investigators recognize that dedicated men and responsi ble programs are essential if the curtailment of accidents is to be achieved (29:18-19). In a recent news release entitled "On Job Accident Toll Is A Disgrace to Nation," Sylvia Porter, syndicated news columnist, stated: This year 14,000 or more Americans will lose their lives in accidents on their jobs. This year more than 2, 500,000 Americans will be disabled by diseases and accidents con nected with their work and more than 7,000,000 American workers will be injured in such accidents. This year's total cost of on-the-job accidents, including loss of wages, medical costs, production delays, e tc ., will probably top $7 billion. 1 2 Yet we can do something to slash the disgraceful on- the-job accident toll, save literally thousands of lives each year and prevent literally millions of injuries. Corporations which are members of 1 ^ National Safety Council and which have launched major accident prevention campaigns today have 70 per cent fewer on-the-job accidents than non-members. . . . But generally, apathy about the accident problem remains monumental. On the average, states spend only 400 a year per non-agricultural worker for industrial safety and some spend as little as 20. Corporations in general, too, are doing tragically little to protect employees. The United States Labor Department reported recently that out of 1, 399 companies doing business with the federal government which were inspected by federal engineers, 95 per cent were discovered violating minimum safety and health standards. (68:B-7) Many schools, too, are rem iss in their total effort to establish a meaningful and realistic program of safety awareness among their citizens. Consequently, the few hours of safety instruc tion each sem ester are inadequate to equip the student to function with prudence in the school environment (53:367). Given heavy emphasis only during the opening weeks of school, the safety program soon becomes the "forgotten lesson" for the remainder of the sem es ter by both teacher and student (71:21). Primarily, the schools must try to identify the student who represents the potential accident statistic. Should not the adminis trator, counselor, and instructor be equally concerned with a student's safety potential as with his capacity for intellectual and academic progress? However, it is clearly understood that the means for determining the academic proficiency for any student are available to school personnel, but instruments for determining degrees of accident probability within students are not. Placing the main emphasis of their research in the industrial instead of the educational setting, Ghiselli and Brown stressed the need to investigate the use of psychological testing as a means of identifying the potentially safe employee. Moreover, they cited the importance for industrial companies to allow the safety department some voice in the selection of new employees. They further expressed the concern that frequently a company lacks communication between the personnel and the safety departments (5:346). Like industry, the schools also need to establish a safety team, opening lines of communication between administration, counseling, and instruction. Thus, this study contributes directly to improving safety education in both the industrial and educational settings by (1) providing a special means of identifying the student or employee with an accident potential and (2) by recommending that this knowledge become an integral part of the safety program. To achieve these ends, a visual safety alertness test was created to identify and evaluate degrees of accident potential in junior college vocational students and industrial employees in certain southern California industrial plants. It was assumed that if a testing instrument was developed 4 that would identify individuals who indicated a lack of safety alertness and knowledge, appropriate action could be instigated to produce a reduction of their accident involvement. VanZelst alleged that when formal training preceded actual work performance a substantial lowering of new employee accident frequency rate was noted (63:317). Addressing himself to the same theme, Jenkins (1961) expressed the view that on-the-job observation and training allowed new employees to gain the necessary skills to function safely on the job even though they were identified as being accident-prone by virtue of scoring low on the Jenkins Job Attitudes Survey. However, should these employees continue to show evidence of not responding to the efforts of their supervisors, Jenkins believed it was advisable to initiate employee transfers to positions of less risk (33:62). Conse quently, it becomes advisable for those involved in vocational training to provide models of safety instruction that functionally relate to the learning experience undertaken. Statement of the Problem The research problem of this study was to develop a visual safety alertness survey which could be used to identify degrees of accident-proneness in junior college vocational students and industrial employees. In addition, the study problem called for the validation s of the designed instrument through the testing of randomly selected accident-nonaccident employees and various student groups. For purposes of identification the developed measuring tool is identified as the Safety Alertness Survey (SAS). Research questions. - -Investigation and consideration of the factors involved in the phenomenon of accident-proneness and its relationship to individuals has prompted a concern for the answers to the following questions: 1. Can the SAS identify degrees of accident potential in industrial workers and students of vocational education? 2. What differences are there in accident potential between the industrial and student groups? 3. What is the relationship between safety alertness and intelligence? 4. Does the young examinee show greater accident liability than the older examinee? 5. What is the relationship between the student's SAS index and the instructor's rating of student accident potential? 6. What is the relationship between the student's SAS score and his SV score as determined by the Strong Vocational Interest Battery? 7. What is the relationship between the student's SAS score (Group I) and the assigned risk level of the selected vocational choice? Research hypotheses. --As a result of the initial questions raised by this study, the following hypotheses have been established for experimental inquiry: 1. Accident potential can be identified by means of a photographic examination with a reasonable level of prediction. While the existing literature allowed one to accept or reject the use of testing devices as a means of determining an individual's accident potential, promising results from the Kunce investigations have provided encouragement for the use of the SAS measuring device (35:311). 2. There is a difference in the accident potential recorded among the groups of students and among the groups of industrial employees. Because of variations in educational achievement, safety instruction and age range, factors exist which will discriminate between student and industrial samples. 3. There is a positive correlation between accident potential and aptitude as determined by school intelligence testing. The relationship between the intelligence factor and accident potential has been thoroughly investigated. However, studies can be cited to support or reject the position that a significant relationship exists between intelligence and the accident incident. 4. Greater numbers of accidents are associated with the age group 16-45 than with the age group 46-75. The majority of studies under review state that the age factor is significantly related to the accident problem. Consequently, the assumption is made that the results of this investigation will confirm the findings of earlier experimentations. 5. There is a significant relationship between the SAS index and the instructor's rating of student accident potential. 6. The student's SV score (difference between aviator 8 and banker scores) as determined by the Strong Vocational Interest Battery shows a significant relationship with the student's SAS score. This hypothesis is based on the 1966-67 studies by Kunce, et al. , and their use of the SV 1B as a device to determine degrees of accident-proneness with individuals (38, 39, 40, 41, 42). 7. The student's SAS score (Group I) is positively related to the risk level assigned to their vocational choice. Importance of the study. - -The educational importance of this study focused on the development of a non-verbal visual evaluat ing device to determine degrees of accident potential within the study sample. At the present time an individual is identified as an accident liability only after a multiple accident record (61:398). However, the intended use ot the SAS measuring device was to identify the accident prone individual prior to the accident. The standard approach to student safety instruction in the United States has been to expose the student to a written safety test. The central theme of such a program suggested that by answering various technical questions regarding safety, the student would regulate his classroom actions accordingly. However, there are certain aspects of this approach that operate contrary to the expected and desired results. First, the test is invariably administered during the begin ning weeks of the sem ester. Consequently, the new student has had little opportunity to familiarize himself with subject terminology and equipment. During this initial phase of their education, certain students find the examination highly irrelevant and somewhat meaning' less. A second consideration of the written safety test involved the student's attitude toward the "academic approach" to the presentation of safety knowledge in a vocational laboratory. Experience has shown that educational motivations are closely allied with the "doing" or functional elements of the class. One is stimulated because of and reacts to the many exciting yet unexplained facilities in his new surroundings. Hence, all activities should support and strengthen the student's natural curiosity toward gaining pertinent knowledge. In this regard safety education is no exception. Finally, in many instances the industrial employee safety program becomes an equally frustrating venture. Typically, the large industrial complex will expose the new employee to a short orientation lecture by the plant safety engineer. This activity is usually incorporated within the total hiring process and is concluded 10 before the employee ever sees his assigned work station. However, it must be noted that certain companies are now extending their safety program to the worker and his activities in a more meaningful and practical way. The expressed information regarding safety indoctrination by schools and industry is cited not to belittle the attempts of these agencies. Rather, it is used to demonstrate the need to identify degrees of safety alertness within individuals so that a meaningful program of safety can be more closely tailored to the needs of the respective personnel. Numerous studies in the field of accident liability have emphasized the fact that certain persons have a higher accident liability than others (5:341). It is toward the identification of this group of people that this study is directed. The Procedure Safety Alertness Survey. - -The completed measuring instru ment consisted of a group of thirty photographic questions. Each question was composed of four color photographs (3-1/2" x 3-1/2”) secured to a white mounting board (12-1/4" x 13-1/4"). The questions were equally grouped into three distinct areas: (1) personal attitudes toward activities and occupational choice--ten questions; 11 (2) general safety knowledge--ten questions; and (3) general industrial safety--ten questions. Following the assembly of the photographs, the survey in its entirety was evaluated by qualified experts. The photographic ques tions were then processed as color slides for presentation to the examinees in group testing situations. Personal attitudes toward activities and occupational choice.— The area of personal attitudes toward activities and occupational choice attempted to classify the personality characteristics of the examinee into the categories of adventure or caution. Consequently, this group of photographic questions allowed the examinee to select between activities or occupations varying in degrees of adventure or caution. For instance, a question in this category might depict the following activities: (1) gardening, (2) chess game, (3) flying, and (4) tennis. The examinee would select the activity he would most like to participate in if he had the necessary qualifications. The identification of the adventurous versus cautious per sonality characteristics for purposes of determining degrees of accident potential within individuals was based on a recent investiga tion by Kunce (1967) in the area of vocational interests and accident proneness (38). In this pertinent study Kunce established a significant 12 relationship between an individual's index of accident proneness (AP) and his accident record. The AP score was obtained through the use of the Strong Vocational Interest Battery (SVIB) by subtracting the standard score of the banker's scale (evidence of caution) from that of the aviator's scale (evidence of adventure). Furthermore, additional Kunce, et a l. , investigations (39, 40, 41, 42) revealed that an individual's AP score was significantly related to the age of the subject, the occupational risk involved, and the length of employment (tenure) experienced. The Kunce studies also revealed that employees with an above average accident record were associated with a high risk occupation and a high AP score. In addition, those employees who had established a long period of employment tenure had achieved the lower AP scores. Consequently, the older employees recorded the lower AP scores (38:223-225). General safety knowledge category. - -The second group of ten questions dealt with the area of general safety knowledge and was incorporated into the survey to determine the extent of a person's awareness of safety during the course of his everyday activities. This group depicted areas of safety concerning the home, the auto mobile, the playground, recreational activities, etc. This question group attempted to measure the extent safety knowledge contributes to one's safe pattern of life. 13 General industrial safety category. - -The final ten questions depicted areas of general industrial safety such as industrial power tools, m aterial storage, construction work, etc. Limitations of the Study Study sample. --A major limitation of this study was related to the research sample. Because the measuring instrument originated with this study it became impractical (with the facilities for sampling and financial envolvement) to provide the quantity of sample that would be utilized by a commercially developed instrument. Conse quently, the sample has been limited to groups of junior college vocational students and employees from two large aerospace indus trial plants in the southern California community. SAS question quantity. - -A second limitation of the study concerned the number of photographic test questions that comprised the measuring instrument. Because numerous test sessions were scheduled with many groups, it was necessary to limit the total administrative operations of the examination to a one-hour class period. The thirty-question test was considered to be the maximum test length possible and still assure the adherence to accepted and sound testing procedures. Sex. - -The initial intent was to confine the study sample to 14 an all male population (in essence, this was almost accomplished-- 452 males, seven females). However, the sample at one industrial plant was composed of twenty-three employees, sixteen males, and seven females. The first consideration regarding these female examinees was in effect to declare their answer sheets void and eliminate them from the study records. But further investigation of these returns proved most interesting and revealed information of an unexpected nature. Statistically, the female sample was insufficient in numbers to attach any responsible significance to the findings. However, strong elements of consistency in the female responses warranted recording. This information is given in Chapter IV. Definitions of Terms Accident abatement. - -As used in this report the term "accident abatement" refers to the lessening of the number of accidents through organized and planned action by man. Accident involvement. - -Any person being directly or indirectly connected with the accident incident. Accident liability. --A more encompassing term than accident-proneness including not only the personal factors but also environmental influences relating to the predisposition of people to become involved in accidents (49:41). 15 Accident proneness. --A personal factor making certain members of any population grouping susceptible to the accident incident. Accident repeater. —Any person who has become involved in two or more accidents over a six-month period. Population. - -The total number of vocational city college students and industrial workers in the southern California area. Safety alertness. - -An awareness of the safety factor as it relates to life's situations and experiences. Safety surveillance. —An observation of individuals, either in groups or singular, engaged in normal educational or occupational activities by personnel trained in such activities. Sample. - -A subgroup selected from the population. Organization of the Research Report The following structural organization was established for this dissertation. Chapter I described the central problem and its supporting framework. In addition, it contained the major questions and hypotheses originating from the initial stages of the study. Chapter II presents a review of the literature as it related to the theme of the study. Chapter III explains the methodology and procedures as they were employed throughout the experimental 16 design of the report. Chapter IV analyzes and reports on the experi mental results obtained through the use of the Safety Alertness Survey. Chapter V contains a brief summarization of the report, discussion of the study findings and their implications and derived conclusions and recommendations. CHAPTER II REVIEW OF RELATED RESEARCH Introduction The topics of industrial safety, accident causation, and accident prevention have been investigated and reported on exten sively during the past fifty years. As a result, much literature is available to the researcher. However, an evaluation of the entire literature in these areas would be impractical. Therefore, the efforts in this chapter have been centered around the topic of accident-proneness with an emphasis placed on the following topics: (1) developmental concept of accident-proneness, (2) psychological factors related to accident- proneness, and (3) personality characteristics and attitudes related to accident-proneness. In addition, various environmental factors that relate to accident-proneness are reviewed. Developmental Concept of Accident-Proneness Greenwood and Woods (1919) were the first authors to 17 18 develop and present the accident-proneness theory. Their study investigated the following hypotheses: (1) industrial accidents were the result of pure chance--simple chance distribution; (2) although starting equally with other workers, after the accident incident, an individual's potential for another accident is not the same as his initial accident experience--biased distribution; and (3) all workers did not start on an equal basis, but certain employees were more susceptible to accidents than others--distribution of unequal liabil ities (66:4-5). Greenwood and Woods concluded that accident liability among workers was patterned on a non-chance basis. However, it must be noted that they refrained from reporting any excessive claims in their conclusions. Moreover, Vilardo reported that Greenwood and Woods attached cautious and conservative qualifications to their study findings (72:2). Commenting on the investigation of Greenwood and Woods, Mintz and Blum (1949) stated, It was discovered that more people had no accidents than might have been expected by chance. Conversely, it was discovered that more people had many accidents than would have been expected in accordance with a simple chance distribution. (50:195) In addition to the Greenwood and Woods study, Newbold (1926) also investigated the relationship of accident incident to 19 chance expectancy and found that accident liability statistics were not thoroughly comprehendable when analyzed on the basis of job hazard alone. Consequently, like Greenwood and Woods, Newbold was basically concerned in revealing a relationship of difference between chance expectancy and accident records. Commenting on these find ings, Mintz and Blum suggested that both the Newbold and Greenwood- Woods studies were successful and that their findings established the accident-proneness principle (50:195-96). Furthermore, as reported by Vilardo, Newbold stressed that an individual, upon having his first accident, alters his future accident liability either positively or negatively rather than being biased toward accidents as stressed by others (72:2). However, in an earlier paper Greenwood and Yule (1920) established that accident liability and accident record were not highly correlated. Nevertheless, Mintz reported that Cobb (1940) indicated a correlation between these two variables need not be necessarily high (49:41). Drake stated that both the Greenwood-Yule and Newbold research revealed a ”J" profile curve for the graphic distribution of accidents, which emphasized the fact that accident - incidence in any one group was experienced by relatively small numbers of the group (22:341). While references were made to the concept of accident 20 proneness in these former studies, the term "accident-proneness" can be traced to F anner and Chambers (1926). During their early studies, these men believed that test measures could be used to produce a predictive value in the area of accident-proneness. How ever, they later reported that tests were generally inadequate as a means to predict accidents involving workers in an industrial plant. This, in essence, contradicted the major findings of their earlier investigation (72:3). According to Vernon, the coining of another term, "law of recurrence, " was attributed to Marbe (1926). More over, M arbe's theory suggested that a person's accident probability can be projected by the quantity of past accidents (14:35). In addition, Slocombe and Bingham (1927) tried to isolate psychological differences among a group of accident and non-accident motor and bus operators. The results of this experiment revealed the following variables as being related to the accident habit: 1. Uncooperative attitudes 2. Operating habits 3. Relations with supervisors 4. Medical examinations 5. Home and family relations 6. Worry or ill health 7. Native aptitude (57) 21 Review. - -In review, this early investigational period into the concept of accident-proneness directed its efforts toward the theme that a certain segment of the population was more prone to accidents than the general populace. Many studies were conducted which eliminated the possibility of pure chance as being the distribu tional causation of accidents. Moreover, this period saw the begin ning of efforts to use various testing measures as a predictive tool for determining accident-proneness. In addition, it was during this period that attention was first directed toward the industrial accident repeater. One investigator called this trait the "accident habit" and cited the individual's greater probability of having accidents if he had experienced a previous accident (15:99). Furthermore, investigation during this period revealed that accident-proneness followed an individual from occu pation to occupation (13:182). Finally, the beginning studies on how various psychological factors contributed to the concept of accident- proneness were initiated (58:34). Psychological Factors Related to A ccide nt-Prone nesF Marbe (1935) suggested that certain factors contributed to the accident potential of the individual. He expressed the view that accident liability is closely associated with occupational types: the 22 coal miner would be subject to a greater risk factor than would the clerical member of an office staff, and the mountaineer would expose himself to greater risk than the individual enjoying a walk in the park. Thus, Marbe suggested that one's style of life, was related to the accident habit. Furthermore, Marbe hypothesized that certain individuals have an inherent factor of accident-proneness. Conse quently, he reasoned that such individuals would be prone to accidents regardless of the occupation or the activity in which he engaged (46:100). Testing for accident-proneness. --Marbe reported that an individual's accident-prone ingredients might be revealed through various testing procedures, allowing for appropriate training or reassignment to another occupational pursuit (Marbe at this point is in contradiction with his hypothesis concerning the inherent factor of accident-proneness). However, Marbe concluded that the task of isolating accident liability by testing procedures is a difficult one, to be sure. Conse quently, he believed that the test must be constructed with a particu lar occupation in mind, and it should be designed to consider the physical and mental operations of the job (46:103). Vernon (1936) agreed with Marbe as to the difficulty of devising adequate tests to measure the presence of accident-proneness. 23 Moreover, he cited the multi-faceted characteristic of the accident- proneness quality and the varying degrees to which each character istic influenced a specific accident incident, "Clearly, therefore, no single test could be sufficient to reveal his deficiencies, though in course of time it may be possible to devise a battery of tests which, when suitably combined, will afford the desired informatiori'(14:38). In addition, Vernon described the attempts of Farm er and Chambers (1926-29) to design test measurements for identification of the accident-prone individual. The efforts of these two investigators were confined to three areas of psychological functioning. First, they designed tests to determine degrees of sensori-motor skills which Farm er and Chambers labeled aestheto-kinetic coordination tests. These were three in number: dotting, reaction time, and pursuit meter. Secondly, Farm er and Chambers tested tempera mental instability through the observation of psychogalvanic reflex, ocular muscle balance, and trem or characteristics. Thirdly, they devised tests to determine rapid and accurate thought development within an individual. For this investigation, Farm er and Chambers utilized an intelligence test and a number-setting test (14:39). In addition, Farm er and Chambers revealed that the aestheto-kinetic coordination test results were in positive relationship to accident liability. However, their relationship to the intelligence factor 24 proved non-significant. Nevertheless, Ghiselli and Brown cited studies by both Schaefer and Henig which revealed a positive relationship between accident liability and intelligence test scores. Yet, their own invest igation failed to show a significant relationship between these two variables (5:347). In commenting on this issue, Larson, et al. , stated, "According to research, intelligence tests do not identify accident free workers from accident repeaters, except at the extremes" (9:20). According to Vernon, the Farm er and Chambers investiga tion into temperamental instability established a positive relationship between nervous instability and the accident habit (14:39). Farm er (1940) further clarified the role of psychological testing in the identification of accident liability when he stated, Nervous instability of this kind is known to affect sensori motor coordination which has been shown to be involved in accidents. Furthermore, it has been found that the best sensori-motor coordination tests for accident-proneness are those which impose on the subject an arbitrary time limit for a coordinated performance. (23:127) Thus, Farm er indicated that the subject who scored high on the sensori-m otor coordination test had a low accident involvement while the subject who scored low had a high rate of accident involvement. Hunter (1959) concurred with Farm er and implied that 25 defective neuro-muscular control and accident-proneness are positively correlated. Consequently, Hunter recommended the use of psychological testing to measure neuro-muscular control in relation to attention, muscular precision, and mobile coordination (8:84). In addition, Heinrich (1941) maintained that because of mental, psycho logical or physical deficiencies, individuals were unable to avoid the accident incident. Moreover, the individual with desirable physical and intellectual characteristics would record a positive safety record (6:392-93). However, believing that accident-prone ness can be estab lished, Drake (1940) proposed the hypothesis that individuals whose level of muscular reaction is above their level of perception are prone to more frequent and more severe accidents than are those individuals whose muscular reactions are below their perceptual level. (22:339-40) Drake's conclusions were the result of investigation involving female factory workers with accident records who were administered five manipulative tests, four of which were designed as a result of on- the-job analyses and observation. Two of the prepared examinations were of the motor manipulative type, while two were visual percep tive tests. Individual test scores were calculated on the basis of the time required to complete the various test operations. However, the fifth test was the O’Connor Tweezer Dexterity test which was utilized as a comparative measure for the four unstandardized Drake tests 26 (22:335). In addition, Drake computed an "accident index" for each subject by using the formula: * a - _ No. of Accidents x Severity /oo.om \ Accident Index - length of Service in Months (22'337) The results of Drake's investigations revealed that a high accident index was associated with subjects who scored higher on the motor tests than on the visual perceptive tests. Coincidentally, Drake observed that a low or zero accident index was associated with test scores that reflected a higher visual perception score as com pared to the motor manipulative score (22:337-38). Hence, this evidence affirmed the verification of Drake's above stated hypothesis. Also trying to identify the accident-prone individual, Ghiselli and Brown (1949) administered a group of paper and pencil tests plus an interest inventory to sixty-seven cab drivers and investigated the subject's record of operation. The tests which produced the highest validity coefficient were the dotting and tapping tests. These results were very sim ilar to the results obtained by the early investigations of Farm er and Chambers. However, the tests that required the subject to judge distances or to understand simple mechanical operation produced scores that were non-significant. Likewise, the relationship between an arithm etic test and accident liability proved to be useless in identifying the accident potential. 27 However, Ghiselli and Brown reported that the interest inventory was positively correlated to accident liability. (Chapter III describes the testing device used in this investigation which is based in part on the subject's activity and occupational interest) (26:546). Buchanan's (1950) investigation into the prediction of accident-proneness of motorcycle operators revealed a non-significant relationship between paper and pencil tests and the accident-prone motorcycle operator. Of the tests used, the most effective were the "visual attention" and dotting test. However, the dotting test as used by Buchanan produced a negative relationship to the criterion of accident-proneness, whereas the dotting test employed by Ghiselli and Brown revealed a high positive relationship to accident-proneness. Because Buchanan required a five-minute time period for his dotting test, he explained the converse results thusly, "It appears likely that the difference between the results obtained on the two tests is due to the time factor, Ghiselli and Brown using a limit of one-half minute" (70:69). Continuing to study the accident-prone individual, Larson, et al. (1955), acknowledged that visual acuity, reaction reflex, and manual dexterity have moderate degree of influence in the realm of employee safety. However, they stressed that this influence was affected by the task involved and its dependence upon these specific 28 skills (9:15). Mitchell (1956) concurred with the appraisal that a positive correlation existed between psychological tests and accident liability (51:22). Also, Crawford (1965) stated, Various tests of visual skills, reaction time, and dexterity may be applied to determine if the applicant has the psycho physical characteristics necessary to satisfy the job require ments. Many highly reliable psychological tests and apparatus to determine the general level of intelligence, aptitudes, specific job knowledge, interests, e tc ., can be used to screen out the not too obvious misfits. (20:561) Psychiatric examination as a determiner of accident-prone- ness. —Selling (1940) conducted psychiatric examinations on 500 traffic and accident offenders to determine the relationship between mental capacity (as established by psychiatric examination) and accident record. A breakdown of his study findings were as follows: Of the 500 subjects, 180 were classified below 70 IQ; eighty-one were classified between 70 and 79 IQ; eighty-four were classified between 80 and 89 IQ; 131 were classified between 90 and 109 IQ; seventeen were classified between 110 and 119 IQ; three were classified between 120 and 140 IQ; and four were not tested (56:68). Selling concluded his study with the following statement: In conclusion we might point out that the problem of the mental defective, neurotic, and psychotic driver is a serious one. Such cases are in the community, are detect- ible, and diagnosable. In most cases they should be removed from the highway and a procedure which permits of their detection, such as a traffic court, can also be made the means of securing their hospitalization and psychi atric treatment. (56:78) 29 However, the Buttiglieri and Guenette study of 1967 would tend to contradict the Selling report. Their investigation revealed that patients in the neuro-psychiatric wards of the Veterans Admin istration Hospital had accident records which did not differ signifi cantly from the California male driving pattern. In addition, they contended that to withhold the mental patient's privilege to drive on the basis of his traffic record would be an injustice. Furthermore, Buttigliere and Guenette stated, Undoubtedly, among these are individuals who could be rehabilitated more effectively if they obtained and exercised their driving privilege. This could be accomplished without adding to the already significant risks on the highway. (16:99) "X" psychological factor in accident-proneness. - -Adler (1941) believed, as did Marbe, that accident liability was closely associated with an "unknown factor" which is psychologically rather than occupationally oriented. Moreover, Dunbar reported the following: The Travelers Insurance Company found that from 80 per cent to 90 per cent of all accidents were caused not by faulty machinery nor by physical or mental defects in the person involved, but by an "X" factor in the personality. (3:76) Adler stated that a fundamental concern for the worker was to be engaged in an occupation that was harmoniously related to his psychological constitution. This opinion was shared by Taft (1958), 30 who stated, Attitude toward the job itself is very important. Anything that is related to morale is also related to accidents and this includes being in the right type of work. A person who really dislikes the work is a very good bet for having an accident. (69:31) Furthermore, Adler cited the interesting case of an accident repeater (revengful attitude group--see listing that follows) who was able to reverse a very poor safety work record to one of excellence. Moreover, this dramatic change resulted from the subject's becom ing financially able to retrain for a long desired profession. Of interest is the fact that the new profession was identified as one that had a higher accident rate than the former,, Adler's findings were based on the investigation of 130 workers who were considered accident repeaters. As a result of her research, she placed the study subjects into the following categories: Revengeful attitude (60) Unlucky (17) Alcoholics (13) Longing to be pampered (12) Over fearful (11) Feebleminded ( 8) Over ambitious ( 6) Organic diseases ( 3) (15:99) Furthermore, the LeShan and Brame (1953) investigation stressed the fact that a person may live a life that is free of 31 accidents yet become accident-prone from a period of two to five years, after which he returns again to the non-accident category (43:81). Emotional factors and accident-proneness. —Hersey proposed a "cycle theory" for accident-proneness, claiming that the emotional and physical cycles of workers are interrelated with the causation of accidents. Hersey's investigation disclosed that when the emotional and physical cycles of an individual are at a combined low level, the accident-prone potential was greatest. However, when the physical low was associated with a high emotional cycle, the accident danger was least likely to occur. "It is fortunate that these periods of such great accident-proneness occur only three or four times each year" (30:235). In addition, Hersey claimed that when the physical and emotional high cycles are associated, a time of safety concern existed but not to the degree indicated by the double low cycle. In addition, Hersey maintained that supervisory personnel should recognize the relationship between the employee's emotional and physical condition and his accident-proneness and should provide a working atmosphere that allows the employee to communicate with an understanding supervisor, thus relieving internal tensions. Once aware of the employee's condition, Hersey recommended that the supervisor and the employee's "leadman" carefully observe the 32 worker's activities while performing his job responsibilities. Finally, the supervisor should recommend placing the employee temporarily in a "least dangerous" job category if the personal safety of the employee or fellow workers were placed in jeopardy (30:235). K err (1957) cited his "Individual Goals Opportunity Alertness Theory" of safety which suggested that an individual would react with excellence in job performance if given the opportunity to establish reasonable attainable goals. This theory implied that the accident incident is closely associated to inferior work performance resulting from a psychologically deprived climate lacking in worker rewards. Experiencing a rich work atmosphere, the employee reacted with a high level of alertness which produced a high "level of work quality” and a low level of employee accident involvement (37:5). Also concerned with the emotional factors of accident- proneness, Stiles (1958) utilized a paper and pencil test in her experiment to evaluate childhood wishes and desires plus a psycho logical evaluation of children's drawings to establish a relationship between the child accident-repeater and unmet emotional needs. Her findings revealed that the accident repeater had a significantly greater number of unmet needs than the non-accident child. This positive relationship to the study criterion applied equally well to both evaluating devices. Stiles further reported that 33 the accident-repeating children tended to behave unmaturely, to be emotionally unstable, and to feel inadequate; they also worried over physical defects and displayed manifestations of nervousness in greater degree than the accident-free children. (60:19) Speaking of accidents involving children, Kasey (1966) stated that the results of investigations at the Children's Hospital Medical Center in Boston suggested that the condition of the family pattern at the time of the accident is a basic causational factor. Interruptions in the normal family pattern, such as a move to a new home, a family member death, a major illness, a breaking up of the m arriage caused elements of emotional stress within the child which were associated with the accident syndrome (34:23-24). Emphasizing the emotional factor of stress, Craig (1966) stated that "situational stress" was significantly related to the accident pattern and that further investigation into this element of human emotion was warranted. He proposed that human endeavor will tend to lose quality if the experience was activated by either too much or too little situational stimulation. Furthermore, he stressed that a satisfactory performance resulted from an environmental stimulant activating the nervous system. However, this stimulant cannot be of such intensity as to overload the nervous system as the resulting stress will be sufficient to interfere with the performance of the individual. Craig contended that under these conditions and in this 34 emotional state of stress the individual became a potential accident statistic. In addition, Craig identified the safety-prone individual as one who was cautious, alert, a logical thinker, sensitized, and a t tuned to existing danger signs (18:269, 270). In review. - -While not comprehensive, the m aterial included in this section does emphasize the varied investigational avenues explored in the attempt to further clarify the concept of accident- proneness. During the early studies many scholars explored the area of physio-psychological testing. The results of these investigations reflected both positive and negative conclusions; both the proponents and opponents of such testing were provided with support for their beliefs regarding the value of testing as a tool to predict accident liability. This section revealed certain investigations into human personality factors as they related to the accident incident. How ever, as this area is highly pertinent to the testing design of this dissertation, a more thorough review of the subject will be presented in the following pages. Personality Characteristics and Attitudes Related to Accident-Proneness The study of accident-proneness has undergone three distinct 35 developmental phases: (1) the identification of the accident-proneness phenomenon and its accompanying period of experimentation; (2) the period of exploration into the area of psychological testing and related factors; and (3) the investigation of personality traits and characteristics and the relevance of these factors to accident-prone ness. The following pages in this chapter will review some of the experimental efforts and accomplishments that relate personality traits with accident-proneness. Personality traits related to accident-proneness. - -Numerous investigators have attempted to establish the various character or personality traits as a means to identify the accident-prone individual. Early research was completed in this area by Marbe (1926) who proposed the hypothesis that each individual displayed a personal "accident disposition" that followed a constant pattern of activity. As stated by Marbe, It seems obvious that there are certain human deficiencies which predispose to accidents—such as inability to concen trate or to distribute attention, clumsiness, absentminded ness, slow reaction time, proneness to fatigue, or addiction to alcohol. (46:102) Pursuing this same theme of investigation, Slocombe and Bingham (1927) studied the employee accident records of the Boston Elevated Railroad Company in an attempt to determine if certain individuals were more prone to accidents than others. The study 36 revealed that employee attitude toward his job and passengers was a significant factor in the accident incident. Consequently, improper treatment of equipment, causing passenger inconvenience (running ahead of schedule, erratic starting and stopping motions, e tc .), incomplete and inaccurate records, and inaccurate and careless fare accounting were all associated with employees who had greater accident involvement. Furthermore, the Slocombe and Bingham study indicated that length of employee tenure (experience) was a factor of high significance in the accident incident. In addition, the study estab lished a relationship between health, age, and the accident incident. Later research into the area of accident liability confirmed the general findings of the Slocombe and Bingham study (57:255). The age and experience factors stressed in the Slocombe and Bingham investigations were reemphasized by Farm er (1940) who commented, Age plays an important part in accident incidence. It is fairly easy to measure this factor and it has been measured in various ways by numerous investigators. The results obtained from all sources are very consistent with one another. (23:121) Farm er stressed that as the employee gained experience there was a sharp reduction in the accident incident. Furthermore, he stated that as he gained experience the employee was growing older 37 and thus the age factor was closely related to accident-proneness (23:122). However, Ghiselli and Brown addressed themselves to this issue thusly, "The drop in accidents with increased time on the job then may be due in part or in whole, simply to the dropping out of the high accident operators" (5:358-59). After a five-year survey of all accident victims in a large New York hospital, Dunbar compiled the following personality profile for the accident-prone individual: 1. Far better than average health. 2. Impulsiveness of action under stress. 3. Failure to finish school. 4. Frequent change of jobs and many ups and downs in income. 5. Spontaneous and casual in social relations. 6. Apparently gets along well with members of the opposite sex, but irresponsible toward husband or wife or family. 7. Interest in machinery, sports, and gambling. 8. No interest in philosophy beyond a firm belief in fate. 9. Makes up mind quickly. 10. Coffee, alcohol, or cigarettes used to let off steam— not for sociability or to increase alertness or prolong working time. 11. Frequent conflicts with authorities. Ignores existence of authority as long as possible. 12. History of broken homes--his parents' or his own. (13:44-45). In addition, Dunbar stated that "the evidence of insurance companies suggests that in at least 80 per cent of accidents, the personality of the injured person was probably more responsible than machinery or training" (4:96). This same theme was presented 38 earlier by Bowers (1930) who reported the following: A study of 75,000 industrial accidents by the Travelers Insurance Company revealed the fact that only about 10 per cent of accidents are due to physical and mechanical causes, whereas, nearly 90 per cent are attributable to the human factor. (1:6) Further, Dunbar reported that the accident-prone individual may harbor deep resentment toward authority. Furthermore, the authority image may be an employer, church official, spouse, parents, relative, etc. Many of the accident-prone patients Dunbar interviewed revealed that they had experienced neurotic tendencies when they were children: These expressed themselves for some of the patients in the form of walking or talking in their sleep, in others as p er sistent lying, stealing, and truancy. Later these tendencies disappeared, apparently replaced by the accident habit. (4:109) A large number of the patients indicated that the impulse for high adventure was strong. In another volume Dunbar commented, "It may be more than coincidence that the accident-prones are outstand ing in the lengths to which they will go to avoid or to get even with authority" (3:659). Schulzinger (1956) reported that the youngster who experi enced acts of violence or who was dominated by excessively stern, demanding, argumentative, or inconsiderate parents would probably become the potential accident victim (13:14). Moreover, identical 39 findings were reported by LeShan and LeShan (1960) (44:17). In addition, Schulzinger commented on the Wong and Hobbs study whose results closely paralleled those of Dunbar. Their study, as did Dunbar's, revealed a definite dissim ilarity in personality types between the accident and non-accident individuals. The high-accident worker came most frequently from a broken home and showed evidence of conflict with authority in both childhood and adulthood as revealed by truancy at school, contact with the juvenile court, a history of irregu lar work and of being fired, a record of m arital discord and contact with social agencies. (13:51) Also attempting to identify personality differences and their relationship to accidents, Harris (1950) studied twenty-five industrial accident repeaters and twenty-five accident-free workers. Each of the subjects were administered numerous personality tests. How ever, the results failed to establish a significant difference in responses. Thus, Harris concluded, "It seems possible that accident-proneness, implying a psychological predisposition to get hurt may have been greatly overrated" (28:459). In contrast to the Harris study was a report by Conger, et al. (1957), which investigated 264 airmen stationed at Lowry Air Force Base in Denver, Colorado. The subjects were divided into the following groups: high-accident, mode rate-accident, and no accident. The high-accident individual was one who had been involved in two or more accidents within a four and one-half year period, one 40 of which took place during the year prior to the study testing. The middle accident group was composed of airmen with a record of only one accident in the four and one-half year period that preceded the investigation. Finally, the no-accident group was composed of a ir men who had a no-accident record for the four and one-half years preceding the testing. Of particular interest were the significant findings that this study revealed when the airmen were administered the Allport - Vernon Study of Values Survey. This measurement disclosed that the aesthetic, theoretical, and religious categories were meaningful discriminators in identifying the accident-prone. Moreover, an analysis of this study showed that those airmen in the no-accident group more frequently selected the religious value choices. However, the high accident group were more closely allied with the aesthetic and theoretical values (17:1072, 1074). This evidence led Conger to the following conclusions: The stable results achieved with this test in three successive samples, and its high predictive value suggests that differ ent types of individuals are represented in the accident and non-accident group. The rather surprising thing to the authors is that such marked differences between groups have been found on measures of values, while relatively slight differences have been found on most of the other paper and pencil tests. There is some suggestion, which may be reflected in the higher religious scores of the non-accident subjects, that they tend to accept conventional values to a greater extent; have less conflict, both internal (in the sense of super ego 41 conflict) and external (in the sense of environmental frustra tion) regarding the satisfaction of their needs; possess less elaborate psychological defense systems, and show less tendency, both as children and adults to engage in contentious or acting-out behavior. (17:1072, 1073) The Conger, et al. , study also employed MMPI test items which revealed that the non-accident subjects had less authoritarian conflicts in areas of delinquency, truancy, and minor offenses. In addition, it was noted that the non-accident subject was more religiously-oriented and willing to accept societal standards. Thus, it is assumed that the accident groups with the higher theoretical and aesthetic scores were related to a profile of less conventionality, greater psychological complexity, greater conflict orientation, greater disharmony with their immediate environment and a greater need to involve elaborate defenses against anxiety (17:1073). In addition, Ghiselli and Brown (1949) found that interest measures revealed some promise (especially the occupational level scales, outside occupational scales, and related occupational scales) as a predictor of accidents. However, their study revealed that a reaction time test of dotting and tapping established the highest validity coefficients. The Ghiselli and Brown study also reported no significant relationship between the accident criterion and (1) age, (2) education, and (3) prior driving experience (26:546). Also investigating the correlation between personality traits 42 and accidents-proneness, Larson, et al. (1955), implied that the individual with a predisposition for accidents could be identified prior to actual employment by surveying the prospective employee's past records. They suggest that the individual with an irregular employ ment history, previous accident pattern, history of hospital adm is sions, record of law infractions, and convictions all indicated the type of personality inadequacies that are associated with accident liability (9:9). In addition, the Larson, et al. , study suggested the following pattern of employee action generally evident prior to the accident incident: (1) excessive anchor chronic absences, (2) repeated visits to the medical department, (3) a series of superficial injuries, (4) a history of minor accidents, (5) frequent complaints and griev ances, (6) poor worker performance (shown by foreman and super visor reports), and (7) evidence of poor safety training, poor supervision, weak selection procedures, ineffective enforcement of safety procedures, and inadequate safety procedures (9:66). Jenkins (1956) and the Executive Analysis Corporation conducted a study in cooperation with twenty-one private business organizations, an a ir force base and a public utility company to determine the extent to which personality qualities were related to accident incidence. Personality and occupational interest tests were 43 administered to matched pairs of workers in various job classifica tions. Each pair consisted of an injury-repeater and a non-repeater performing the same work description. The general results of this study were encouraging and verified the belief that certain personality characteristics are allied to the accident incident. The study revealed that "many of these prim ary personality factors are apparently related to accidents for all the occupations studied" (32:30). The Jenkins study established seven syndromes for m easur ing the relationship of accident-proneness and personality factors: 1. Attentiveness. The injury-repeater's attention tends to be more easily distracted than the safe worker's from the task he is working on. 2. Judiciousness. The injury-repeater reveals a relative unawareness or lack of discernment of the need for acting prudently. 3. Group-dissociative independence. The injury- repeater tends to feel less inclined to accept or comply with rules, standards, and social customs. 4. Personal-social sensitivity. The injury-repeater's feelings and attitudes are less easily swayed by 44 either the feelings or the actions of other people. 5. Attitude toward pain. The injury-repeater tends not to mind being in pain and may even get a thrill out of it. He also tends to forget the pain he may have experienced in the past. 6. Self-assurance. The injury-repeater exhibits a kind of self-confidence that militates against the feelings that any forethought or preventive care may be needed. Instead, he tends to feel that complications are unlikely and that in any case he can handle them spontaneously should they arise. 7. Social orientation. The injury-repeater tends to have aggressive, self-assertive attitudes toward others. He is not so likely to be interested in teamwork or cooperating in the achievement of group goals (33. 56-57). Furthermore, Jenkins stated, It is possible that high scores in any single syndrome may identify an injury-repeater. Should the scores be high in all seven syndromes or sets of test scores, the greater is the assurance that the individual is accident-prone. (32:30) Davids and Mahoney (1957) were likewise concerned with the relationship of personality factors and accident-proneness. However, they devised a projective instrument (sentence completion 45 test) to analyze how personality characteristics affect accident- proneness. Their study subjects consisted of two groups of seven teen male industrial workers closely matched in "age, education, intelligence, socioeconomic background, and exposure to high- accident hazards" (21:303). The statistical characteristics of the high accident and non-accident groups were as follows: High-Accident Group Non-Accident Group Mean a g e ...................... 35.7 .................................35. 2 Mean education 11. 3.......... ................................ 11.1 Mean sco re................... 24. 5.......... ................................ 24. 9 (Wonderlic Personnel Test-- Form A) Moreover, the only variable of consequence among the study participants was the rate of accident incidence. During the period January, 1954, to December, 1955, the high-accident group was involved in a total of forty-seven reported accidents while during the same period of time the non-accident group was free from all accident involvement (21:303). In general, there were no statistically significant differences between the two groups on several negative personality dispositions, but there was a slight indication of positive association between high-accident-proneness and high scores on a cluster composed of the socially undesirable personality dispositions of egocentricity, anxiety, and resentment. (21:305) However, a most significant relationship was revealed 46 between inferior work attitude and accident liability. In addition, the high accident worker scored significantly weaker in the areas of optimism, sociocentricity and trustworthiness. The association between personality characteristics and accident incident have been further defined by Fine (1963) whose investigation established a significant relationship between the out going personality traits of the extrovert and automobile driver traffic accidents. Fine reasoned that the extrovert type, being less social ized than the introvert, would not be as inclined to adhere to the established rules of society. Consequently, he would become involved in greater numbers of automobile accidents and violations (24:95). Fine used 937 male college students as the subjects for his study. The subjects were classified on the basis of scores from Welsh's MMP1 derived Internalization Ratio into the categories (1) extrovert, (2) intermediate, and (3) introvert. Comparisons were made between the subject’s group classification and his driving record. An analysis of the study results provided a verification of the study hypothesis at a statistically significant level; the restrained, controlled, and withdrawal tendencies of the introvert personality were associated with non-accident involvement (24:99). In addition, Fordyce (1964) alleged that the impulse- 47 dominated individual, by virtue of acting in an imprudent manner, would be more susceptible to the serious accident pattern (25:321). Furthermore, Fordyce proposed that the prudent person is more apt to live for a longer period of time before becoming involved in an accident incident (25:324). An earlier study by Whitlock and Crannell (1949) reported that the accident cases in their investigation displayed less "neurotic" and "introverted" tendencies as determined by the Bernreuter Personality Inventory scales. In addition, the accident cases displayed a greater degree of self-confidence (65:498). These findings, in essence, agreed with the Fine study previously cited. Supporting the concept of accident-proneness as a realistic feature of the personality pattern of certain individuals were the series of five investigations of Kunce and others during the years 1966-67: Kunce and Worley, 1966; Kunce and Brewer, 1966; Kunce, Sturman, Longhofer, and Castor, 1966; Kunce, 1967; and Kunce and Worley, 1967. Kunce and Worley (1966) identified the Strong Vocational Interest Blank as an effective measurement for determining behavioral attributes in areas other than interest. Furthermore, they used the SVIB because of its excellent stability and reliability (47:352). They analyzed the SVIB scales for conceivable correlations to the accident- 48 prone pattern and hypothesized that: (1) high aviator scores reflect attitudes of daringness and adventurousness increasing the probabil ities of physical injury; (2) high banker scores are related to cautious, calculated behavior and hence negatively related to accidents, and (3) high masculinity-feminity scores indicated greater participation in sports and physical activity leading to greater exposure to possible injuries. (41:105) In this investigation Kunce and Worley studied the medical records of eighty-four injury and rehabilitation patients in an effort to ascertain if a significant correlation existed between severity of injury and the score on the SVIB aviator scale, the banker scale, and the M-F scale. The study results indicated that patients with severe injuries achieved a significantly higher score on the aviator scale and M-F scale than did the less severe injured patients. In addition, the severely injured patients scored significantly lower on the SVIB banker scales than did the less severe injured patients (41:107). Kunce and Worley alleged that the results of this investiga tion are compatible with the investigational hypothesis stated above. Hence, they suggested that interest patterns on the SVIB reflect personality characteristics predisposing one to accidents (41:106). However, they cautioned that it would be unwise to assume that the characteristic of adventurousness, as associated with the aviator's scale and accident-proneness can be considered tantamount to one 49 another because a high aviator score might imply a successful experience in high adventure occupations (41:107). The Kunce and Brewer (1966) study reinforced the author's belief that "accident-proneness" could be predicted. Further, they contended that accident involvement was more related to a pattern of life than to mental or emotional conditions. Hence, they alleged that the excessive w orrier may be less inclined to accidents than the general populace (39:287). This study investigated the records of 189 chronic neuropsychiatric male patients in Veteran's Hospital Jefferson Barracks, Missouri. Each of the subjects involved in the study had taken the Strong Vocational Interest Blank and each was assigned an accident-proneness index (AP) which was calculated by determining the mathematical difference between the scores of the Banker scale (SVIB) and the Aviator scale (SVIB). These scales were used because of their successful application in earlier accident- prone studies by Kunce. Members of the hospital psychological staff were asked to rate the subjects on accident tendency patterns. In essence, the staff members were identifying, through observational techniques, the subjects they discerned as accident-prone (39:288). The associ ation between AP scores and perceived accident behavior was compatible with earlier research by Kunce which established a 50 connection between stated intersts and patterns of accident- proneness (39:289). However, in the previous studies by Kunce and others involving physically disabled subjects, high school students, and university students a significantly higher percentage of the subjects had maximum AP scores as compared to the scores of the chronic neuropsychiatric subjects. Consequently, the authors suggested that neuropsychiatric conditions and the accident-proneness concept may not be in meaningful harmony (39:289). Manheimer and Mellinger (1967) were in general agreement with the findings of Kunce, et al. , when they described the accident liable boy as one who preferred participation in contact sports and games and who displayed traits of extroversion and adventurousness. Furthermore, the accident liable boy was inquisitive and independent in nature, choosing those activities that would lead to greater accident hazard and exposure (45:483). In review. - -While personality traits were identified in many early investigations as being related to the accident habit, the classical study of Dunbar which developed a personality profile for the accident-prone individual warrants special recognition. In the late fifties, the investigation of Conger, et al. (1957), revealed that certain categories of the Allport-Vernon Study of Values Survey were 51 meaningful discriminators in identifying the accident-prone person. In this study the no-accident subjects scored high in the religious category, whereas the high accident group scored high in the aesthetic and theoretical categories. Furthermore, Jenkins' study (1956) strengthened the belief that certain personality characteristics were allied to the accident habit. Also, Fine's study of the extrovert and introvert individual in relation to accident-prone ness revealed significant results. However, of special importance to this study were the various investigations of Kunce, et al. Kunce first identified a positive relationship between accident-proneness and a high aviator score on the Strong Vocational Interest Blank. In addition, Kunce observed that a high Banker score on the SVIB was associated with the low or no-accident individual. Consequently, these studies with their emphasis on individ ual traits of adventurousness versus cautiousness became the basic framework upon which the measuring instrument for this study was constructed. The reviewed literature revealed three distinct periods in the developmental concept of accident proneness; (1) identification of the accident-proneness phenomenon and the resulting period of experimentation; (2) the exploration of psychological testing; and (3) the investigation of personality characteristics and the relevance 52 of these traits to accident-proneness. Moreover, the literature in the area of accident-proneness has emphasized the importance that this subject has been accorded in the field of safety research during the past fifty years. However, this investigator soon discovered contradiction and disagreement among the research contributions. There are writings that disavowed any credibility to the phenomenon of accident-proneness and those which recognized its existence and offered solutions for its control and abatement. In addition, some investigators isolated a single causation factor whereas others believed in the multi-causational factor theory of accident-proneness. Furthermore, certain investigators stressed the psychologi cal testing route to identify the accident repeater while others isolated various personality characteristics in the psychological profile of man that were associated with the accident-proneness theory. Recent research into the area of accident-proneness has been directed toward the humanistic factors involved and their importance to the individual and his total environment. CHAPTER III PROCEDURE AND METHODOLOGY Introduction The investigational structure and organization of the study is presented in this chapter. Described in detail are the (1) procedures of sampling and the experimental sample; (2) research instrument and its relevance to the problem under investigation; (3) SAS scoring procedure; and (4) study data treatment. Sampling Procedure Because the study design required samples from both the school and industrial population, contacts were arranged with officials from both segments in the Long Beach community. A research project proposal was submitted to a southern California community college for consideration. The school's subsequent approval made available for testing all students enrolled in the following vocational areas: (1) aeronautics—airfram e, (2) aeronautics--powerplant, (3) architectural drafting, (4) automotive body repair, (5) automotive 53 mechanics, (6) carpentry, (7) diesel mechanics, (8) electronics, (9) electromechanical, (10) industrial electricity, (11) machine tool, (12) mill cabinet, (13) refrigeration, (14) sheet metal, (15) tool design, and (16) welding. The students who participated in the study were those in class attendance on the scheduled days of testing. There was a total school sample of 383 students, obtained from the following subject areas: Area Student Count Aeronautics 57 Architectural Drafting 25 Automotives 47 Carpentry and Mill Cabinet 22 Diesel Mechanics 22 Electronics 60 Electromechanical 19 Industrial Electricity 22 Machine Tool 15 Refrigeration 41 Sheetmetal 6 Tool Design 23 Welding 24 Instructor approval. —Prior to testing each of the sixteen 55 instructors was contacted personally regarding the purpose of the study, the proposed date for class testing, and the approval for class participation in the study. Each instructor cooperated in full measure with the project during the complete cycle of the testing procedure. In addition, a second student sample of twenty-six junior college students who had taken the Strong Vocational Interest Battery was compiled from the vocational planning classes at the participating college. The male members of two vocational planning classes (Spring, 1969; Fall, 1969) were contacted by phone and asked to participate in the study test session. Twenty-six students were able to participate in one of three scheduled testing sessions. In order to accommodate a majority of the student's schedules one morning, one afternoon, and one evening testing group was planned. Of the total accident population, twelve were students at the participating college who had experienced accidents from January, 1969, to January, 1970. Industrial contacts. —Arrangements were completed with the safety departments of two large southern California industrial corporations to test various members of their work force. Company approval was granted only after the Safety Alertness Survey was presented to and evaluated by the company safety experts. The participation in the study by the industrial segment represented a 56 financial commitment as workers were released from their respective assignments for a two-hour period to participate in the testing. Excellent testing facilities were provided at each plant and employees responded to the testing session with a very cooperative attitude. Furthermore, at each of the two industrial plants, the test groups were composed of both accident and non-accident employees. However, one company withheld the safety records of the employees until they (company safety officials) were provided with a projected accident potential index for each employee based on the results of his experience with the Safety Alertness Survey. Population samples. - -Three distinct sample groups were administered the Safety Alertness Survey: (1) junior college voca tional students, (2) junior college students who had previously taken the Strong Vocational Interest Battery, and (3) industrial employees and junior college vocational students who had records of accident involvement during the twelve-month period from January, 1969, to January, 1970. Junior college vocational students. - -The students that comprised the general junior college vocational group were admin istered the Safety Alertness Survey in the Fall, 1969, school sem ester. In addition, each class instructor was asked to identify the five students in his class that (through classroom observation and student 57 activity) he considered the most "unsafe" in the classroom environ ment. Furthermore, the instructor was asked to identify the five students that he considered the most "safe" in the classroom. The instructor's selections served to classify their class group into three categories: (1) the unsafe, (2) the safe, and (3) the neutrals. Thus, the instructor's ratings were compared with the student's Safety Alertness Survey index for significant relationships. Junior college students (Strong Vocational Interest Battery Group).--The second testing sample of twenty-six vocational junior college students were those currently enrolled in school who had previously taken the Strong Interest Inventory Battery. Because of the established relationship between the aviator and banker scores of this test and accident-proneness (Kunce, et al. , investigations 38, 39, 40, 41, 42), the scores of these scales were compared with the subject's Safety Alertness Survey Index. Consequently, this test group provided a means to test the m erits of the Safety Alertness Survey as a predictor of accident potential. Industrial and junior college accident sample. --The third test group was composed of industrial employees and vocational students who had been involved in accidents during the year 1969. By compar ing the accident histories of this sample group with their score on the 58 Safety Alertness Survey, additional validation data became available for the evaluation of the survey instrument. In summary, then, the following groups were tested: (1) 383 junior college students from various vocational areas, (2) twenty-six junior college students who had taken the Strong Vocational Interest Battery, and (3) thirty-seven industrial accident-nonaccident employees and twelve junior college accident students. The Research Instrument Background. - -For a number of years the author has been interested in aspects of the safety educational program in industrial arts and vocational classes. First, it became evident that a m easur ing device to determine degrees of safety awareness within students would be of value in the industrial and vocational instructional area. However, little research is available to school officials (administra tion, counseling, and instruction) for the identification of the potential student accident risk. Thus, it was reasoned that to have such information would be of value to the instructor of industrial education in his total class planning. This is not to imply that the student identified as a poor safety risk would be denied enrollment in any class; rather, the instructor would be provided with information that would allow him to provide greater individualized safety education at 59 the time it is most pertinent--prior to the accident incident. Evidence is ample to identify the accident problem as being one that involves both the individual and his environment. However, in the industrial education classes it has long been traditional to treat the instruction of safety in the "equipment oriented context. " Yet, it would be most meaningful for the instructor to be able to reliably identify differences in the accident potential of the class population. Thus, the research instrument used in this study has been hopefully designed to reveal such student data. A second concern deals with the written safety examination that is administered to industrial arts and vocational students. T ra ditionally the safety examination is administered during the first weeks of the sem ester, before the student has the opportunity to physically engage in the operation of the various pieces of equipment. Understandably, the instructor, the school, and the district would surely be adjudged negligent if the students were not subjected to complete safety instruction covering all segments and equipment within any specific educational program. The written safety test as used in the school situation con tributes to the district's commitments to the safety program. However, because many instructors feel that the written test fulfills their responsibility in the field of safety education, many programs 60 are conducted with little or no continuity during the sem ester. After the administration of the written safety test, the only apparent stimulant to renewed safety instruction becomes the accident incident itself; consequently, the importance of accident education becomes reemphasized. However, the value of this type of a safety program is dearly priced. Hence, the need for continual safety instruction is evident and overdue. The written safety test is ineffectual in many instances because: (1) its technical terminology prevents adequate comprehen sion by the student, (2) it is administered by an instructor who reflects the philosophy that the examination is something to be covered before the student can begin the sem ester's work, and (3) is taken by a student who only wants to successfully hurdle the obstacle that is preventing him from the "doing" experiences that are related to the vocational instructional program. Consequently, thought was directed toward the development of a general safety alertness survey that would provide the instructor with a reliable index of each student's accident potential and, thus, provide the foundation for a more improved and meaningftil safety educational program. The Safety Alertness Survey This experimental study was designed to investigate the 61 feasibility of utilizing a photographic safety alertness survey to identify degrees of accident-proneness in junior college vocational students and industrial workers. However, as no commercial measuring device existed in this area, it became necessary to design such a device. The general assumption was established that a visual (photographic) safety survey would be more descriptive and therefore more meaningful to the examinee than the written type safety exami nation. In addition, it was assumed that the use of photographs would be an appropriate device to identify degrees of adventurousness or cautiousness within the examinee, traits that had been related to the accident-proneness phenomenon. The Safety Alertness Survey constructed for this study was designed to investigate three distinct facets of the safety problem. First, it was considered essential to investigate the possibility of developing an instrument that would allow the identification of various degrees of accident potential in students and industrial workers prior to an accident incident. Second, the examination was designed to investigate the importance that general safety knowledge (informa tional facts) had on the total safety alertness index of the individual. Thirdly, the test attempted to determine if there is a factor of "safety insight" within individuals that provided proper judgment in avoiding accident involvement. Thus, the Safety Alertness Survey 62 was compartmentalized into three separate question groupings: (1) visual questions concerning the personal choice of occupations and activities, (2) visual questions concerning general safety knowl edge, and (3) visual questions on general industrial safety. Group I, Questions regarding occupation and activity choice. —As previously indicated, this group of ten photographic questions was based on the findings of various investigations into the subject of accident-proneness. In each of the ten questions a deter mination was made to reveal certain personality characteristics that are related to the phenomenon of accident-proneness. Consequently, questions 1, 2, 3, 4, and 5 are occupational choice questions designed to reveal degrees of adventurousness or cautiousness within the examinee. In each grouping of four photographs that comprise each question, one photograph depicted a high adventurous occupation and another a high cautious (conservative) occupation. The relation ship of these two traits to accident-proneness has been previously cited. The remaining filler photographs in questions 1 to 5 contained subjects that depicted the above two traits but in lesser degree. Question 6 and 7 called for the examinee to indicate an activity preference from the four photographs that made up each of the two questions. The examinee was verbally instructed to answer questions 1 through 7 according to the following: 63 Assuming that you have all of the qualifications to engage in the occupations or activities shown,select the one that you would most prefer to participate in and record its identify ing letter in the first square after the question number. Then select your second choice record its identifying letter in the second square after the question number. Now, do the same for your third choice. In the last square after the question number, record the identifying letter of the occupa tion or activity that you would least like to engage in. Remember each of the four answer spaces for each question must be filled in with the identifying letter of a photograph depending upon your choice of most preferred to least preferred. Question 8 depicted four types of buildings: (1) sports center, (2) theatre, (3) bank, and (4) church. The photographic composition of this question was based on investigations by Dunbar (3), Conger, et al. (17), and Kunce, et al. (38, 39, 40, 41, 42). Dunbar's profile of the accident-prone individual indicated that this person had a strong association with sports. Moreover, the Conger study revealed that the no-accident group in their investigation were those who rated high in the religious value choices of the Allport- Vernon Study of Values Survey. In addition, the findings of Kunce, et al. , were incorporated within this test question with the inclusion of the bank photograph. The examinee was verbally directed to select the building you would most like to be associated with. Mark the identifying letter of this choice in the first square after the question number. Then select your second choice, record its identifying letter in the second square after the question number. Now do the same for your third preference. Inlhe last square after the question number, record the identifying letter of the building you would least like to be associated with. 64 Question 9, by selecting a preference of magazine reading, again served to identify the extent of an individual's adventurous or cautious personality characteristics. Once again, the examinee was verbally instructed as follows: Select the magazine that you would most prefer to read. Mark the identifying letter for this choice in the first square after the question number. Then select your second choice, record its identifying letter in the second square after the question number. Now do the same for your third choice. In the last square after the question number record the identifying letter of the magazine you would least like to read. The final question in Group I depicted four different wage earning patterns. According to the Dunbar investigations, the accident-prone individual displayed a pattern of frequent change of employment and many ups and downs in income. The verbal instruc tions to the examinee for this question were: Select the chart that most nearly represents the pattern of your income for your total wage earning period. Mark the identifying letter for this choice in the first square after the question number. Then select the chart that is the second most like your earning pattern and record its identifying letter in the second square after the question number. Now do the same for the chart that is third most like your wage earning pattern. In the last square after the question number, record the identifying letter of the chart that is the least representative of your wage earning pattern. Group I, In review. - -The majority of recent studies in the area of accident-proneness are concerned in varying degrees with the relationship of personality characteristics to accident-proneness. 65 The first ten questions of the Safety Alertness Survey attempted to identify degrees of various personality traits that have been signifi cantly related to the accident repeater. Furthermore, the survey endeavored to assign each subject with an accident potential index as a result of his survey rating. It should be emphasized that the examinee was not aware that he was taking a safety test during his participation in answering the questions of Group I. Conceivably, this unawareness allowed the subject to honestly commit himself to a certain personality profile which in turn provided key evidence for evaluating the subject's total safety potential. Group II, Photographic questions concerning general safety knowledge. —The photographic questions depicted in Group II of the Safety Alertness Survey were designed to reveal the subject's aware ness of safety knowledge as it concerned areas and activities involv ing the home, common transportation systems, freeways, water activities, and playground equipment. Consequently, it is at this stage of the survey that the subject first realized that he was participating in a "safety test. " The verbal instructions for Group II were as follows: In each of the ten questions in Group II you are to select the photograph that you consider represents the most unsafe situation, location, or activity. Mark the identifying letter ,of this choice in the first square after the appropriate 66 question number. Then record the identifying number of the photograph that you consider represents the second most unsafe scene in the second square after the question number. Now do the same for the photograph that represents the third most unsafe scene. Now record the identifying letter of the photograph that represents the safest scene, object or location in the last square after the question number. Research data from the National Safety Council and consulta tion with authorities established the ratings of the photographs in Group II from most unsafe to most safe (12). It was hypothesized that an understanding of the accident risk inherent in certain activities, commodities, and locations was valuable and positively related to one’s pattern of safe living. Con sequently, the first question of Group II depicted areas of safety concern around the home--garage, yard, rooftop, and stairway. This question determined whether a knowledge of the relative degrees of accident risk represented by these common home locations reflected respectful and cautious attitudes on the part of the individual involved in an activity located in these areas. In question two various home activities were depicted—use of power mower, home painting, garden spraying, and the use of the power edger. Once again the subject tried to attach degrees of accident risk to common home activities in which he periodically performs. In question 3, the subject was asked to record his aware ness of accident risks as they concerned various areas inside the 67 home. In addition, question 4 depicted four common household items which were rated by the subject for degrees of unsafeness. Questions 5, 6, 7, and 8 were concerned with transportation and freeway usage. Furthermore, the subject in answering question 8 was asked to consider the possibility of being forced into each of the four types of freeway dividers while traveling at a speed of sixty miles per hour. Under the above stated conditions, the examinee was asked to indicate his selection of the photograph that depicted the most dangerous situation to the photograph that depicted the least dangerous situation. Question 9 involved the dangers connected with various water activities while question 10 concerned itself with the area of play ground equipment. It was recognized that the ten questions compris ing Group II of the Safety Alertness Survey were in no way represent ative of all the situations one might encounter. However, it was concluded that the diversity incorporated into these ten questions was sufficient to test the stated criteria for Group II of the Safety A lert ness Survey. Group III—Photographic questions on general industrial safety. --The questions in Group III involved the use of tools, equip ment, and machinery common to the industrial environment. In each question, the four photographs depicted an unsafe situation. However, 68 these questions attempted to determine if certain individuals were endowed with a safety alertness that would allow a sound judgment of potential hazard in situations and with equipment that are not neces sarily totally familiar to them. The verbal instructions for this set of ten questions were as follows: In each of the ten photographic questions in this group you are to select the photograph that you consider represents the most unsafe situation or activity. Mark the identifying letter of this choice in the first square after the appropriate question number. Then record the identifying number of the photograph that you consider represents the second most unsafe scene in the second square after the question number. Now do the same for the photograph that represents the third most unsafe scene. Now record the identifying letter of the photograph that represents the safest scene of the four in the last square after the question number. Test photographs. --Each photograph was originally shot with a Kodak Instamatic 414 camera which produced a color print. The four color prints that completed the composition of each question were secured to a white mounting board which identified the question group and number. In addition, each mounted photographic question was re photographed with a Pentex Single Reflex 35 mm camera producing a color slide of each question. The test was administered to groups of various sizes through the use of the color slides. A slide reproduction of the survey answer sheet was also provided, permitting a thorough explanation of answer recording precedures prior to viewing the first test question. 69 In addition, a negative print was made of each mounted photographic question. This print produced the offset printing plate that was used for reproducing the black and white SAS questions that appear in the appendix. Safety Alertness Survey scoring procedures. —All answers recorded by the examinee to questions in Groups I through III were key-punched into IBM cards for processing by a Systems 360 IBM computer. Each question answer in Group I provided the possibility of twelve numerical values ranging from a minus eight to a plus eight depending on the examinee's selections and age. Consequently, those subjects from sixteen to forty-five were given a minus two value for each "most preferred" choice rated highly adventurous and a plus four for a "most preferred" choice rated highly cautious. However, subjects from forty-six to seventy- five were awarded a plus two for a "most preferred" choice rated highly cautious and a minus four for a "most preferred" choice rated highly adventurous. This method of reverse scoring based upon the age factor was utilized in an attempt to compensate for the effects of living in an adventurous oriented society whose advertising thrusts were designed to provide all with the sports car, the ski slope, or scubba gear, and to compensate for the natural adventurousness associated with the 70 lower age brackets and the natural cautiousness associated with the more advanced age brackets in the study sample. It will no noted that only the most adventurous and most cautious occupations or activities in each question carry numerical value, with the remaining two photographs acting as fillers with zero numerical value. The intent of this scoring procedure was to more nearly parallel the comparing of interest extremes (aviator versus banker) by Kunce. The possible numerical values of most and least preferred photograph combinations and their identifying letter combinations for Group I are listed in Appendix B . In addition, the charts contain the response frequency count for each question and the percentage the count represented of the total response. The scoring of responses to questions in Group II was based on a plus two for the correct identification of the most unsafe situa tion and a plus two for the correct identification of the most safe situation for any one question. Thus, each of the ten questions in Group II provided the possibility of twelve numerical values ranging from a plus four for correct selections of most unsafe and most safe situations to a minus four for incorrect selections of most unsafe and safe situations. The identical scoring procedure was applied to the responses 71 in Group III as was used in scoring the questions in Group II. In addition, the possible numerical values of most unsafe and most safe photographic combinations and their identifying letter combinations for questions in Groups II and III are listed in Appendix B. In addition, the charts contain the response frequency count and the percentage that count represented of the total response. Of the 360 possible photographic combinations in the thirty questions, 357 were selected at least once by the examinees. The only three photographic answer combinations that were rejected by all subjects were: (1) photograph "A" as most unsafe and photograph "B" as most safe in question 3 of Group II, (2) photograph "A" as most unsafe and photograph "D" as most safe in the same question, and (3) photo graph "B" as most unsafe and photograph "D" as most safe in question 5 of Group III. Treatment of Data The major problem of this investigation was to determine if accident potential can be identified by means of a photographic examination within a reasonable level of prediction. To test this hypothesis the SAS Group I mean scores were computed for the industrial accident and non-accident samples and a t-test for a significant difference between the means was calculated using the 72 formula: M , — M* + = i//&<‘, + E*'*\ ( N, +N4\ V \ N , + N i - a / In addition, the above statistical tool was used to determine the significant difference between the means of the SAS Group I scores of the age groups 16-45 and 46-75 (hypothesis number 4). Pearson product moment correlation coefficients were established for a relationship between (1) the SAS scores and the intelligence factor--hypothesis number 3, (2) the SAS scores and the instructor's safety rating of the "unsafe" and "safe" student— hypothesis number 5, and (3) the SAS scores and the subject's SV scores—hypothesis number 6. Comparisons of the mean and standard deviation of the SAS responses in Groups I, II, and III were shown with (1) the assigned risk levels of the vocational instructional areas—hypothesis number 7, and (2) the school and industrial sample—hypothesis number 2. CHAPTER IV FINDINGS AND ANALYSIS Introduction The fundamental purpose of this experimental study was to develop a photographic safety survey capable of measuring the accident potential of junior college vocational students and members of the industrial community. The measuring instrument originated with this investigation and was composed of three question groupings: (1) personal attitudes toward activities and occupational choice, (2) general safety knowledge, and (3) general industrial safety knowl edge. Chapter III described the construction and function of the vis ual Safety Alertness Survey as used in this study. The 459 subjects and their survey responses provided the research data necessary to evaluate the Safety Alertness Survey. The study involved three sample groupings: (1) vocational junior college students, (2) industrial accident and non-accident employees, and (3) junior college students who had taken the SVIB. Statistical data were processed on the Systems 360 IBM Computer complex. 73 74 The findings in this study were reviewed through an analysis of the data in relationship to the study hypotheses. Further more, the hypotheses were restated, followed by an explanation of the statistical treatment of the data and the interpreted results. Hypothesis 1. - -Accident potential can be identified by means of a photographic examination with a reasonable level of prediction. Since the major hypothesis was to determine the capabilities of a photographic safety survey to predict degrees of accident potential in junior college vocational students and industrial em ployees, it was essential to test subjects who had been involved in accidents and compare their SAS scores with non-accident employees. The industrial sample consisted of thirty-seven subjects, fourteen male employees from one industrial plant and twenty-three employees (sixteen male and seven female) from the second industrial plant. Both companies randomly selected accident and non-accident subjects. At the time of the industrial testing sessions, employee accident and non-accident classification was not known by the invest igator. In addition, one company (twenty-three employee sample) withheld worker accident information until after the SAS index for each employee was made available. The employee classification for the total industrial sample 75 was as follows: Of the thirty-seven workers, nineteen were classified as accident employees by the company safety department and eighteen were classified as non-accident employees. Of the nineteen indus trial accident employees, fourteen scored a negative SAS index in the Group I questioning. These findings indicated a 73 per cent accuracy in establishing the adventurous characteristic as a realistic element in the accident problem. a positive Group I SAS index—providing an 83 per cent accuracy factor in relating the cautious characteristic as a realistic person ality trait of the non-accident employee. (Note: Subject number 254SI was a company safety engineer who knew of the test composition prior to testing. Consequently, his test results have not been incor porated into the statistical analysis.) Table 1 lists the non-accident industrial employee sample with their resulting SAS scores, and Table 2 records the SAS scores of the employee accident group. Table 3 records the SAS scores of the student accident group. determine a significant difference between the means was employed and the following formula was used: Of the eighteen non-accident employee group, fifteen scored To test the first research hypothesis, Fisher's t-test to Mi — Mz Zxlt + N, + Na- 2 \ I N,+N t\ ) \ n , nl) 76 TABLE 1 TABULATION OF SAS SCORES, NON-ACCIDENT INDUSTRIAL GROUP Number Group I Group II Group III Total 254SI 14 20 16 50 420SI 4 -4 -6 -6 421SI -16 6 18 8 422SI 2 10 16 28 423SI 2 -12 16 6 424SI 0 12 26 38 425SI 4 12 22 38 427SI 10 16 16 42 428SI 10 12 0 22 431S1 20 2 16 38 436S1 30 10 8 48 437SI -26 14 10 -2 441SI -12 10 22 20 443SI 32 14 14 60 444SI 28 14 2 44 445SI 8 10 6 24 446SI 26 6 0 32 447SI 20 8 14 42 449SI 32 14 8 54 Mean Scores 9. 67 8.56 11.56 29.78 Standard Deviation 16.51 17.89 19.78 26.99 77 TABLE 2 TABULATION OF SAS SCORES, ACCIDENT INDUSTRIAL GROUP Number Group I Group II Group III Total 426AI -18 4 0 -14 432AI 22 10 4 36 433AI -10 14 10 14 434AI -22 18 -8 -12 435AI 10 18 8 36 439AI 8 20 16 44 440AI -10 8 -2 -4 442AI -8 12 18 22 448AI -2 8 -6 0 450AI 24 10 10 44 451AI -16 14 2 0 452AI -2 10 2 10 453AI -2 8 8 14 454AI -26 12 12 -2 455AI -18 4 10 -4 456AI 26 18 12 56 457AI -8 0 0 -8 429AI -10 6 22 18 430AI -12 16 22 26 Mean Scores -3.89 11.05 7.37 14.53 Standard Deviation 14.97 15.91 18.02 27.31 78 TABLE 3 TABULATION OF SAS SCORES STUDENT ACCIDENT GROUP Number Group I Group II Group III Total 4 HAS 2 12 10 24 412AS -6 8 2 4 413AS -8 8 12 12 414AS -16 10 18 12 415AS -16 10 20 14 416AS -2 20 8 26 417 AS -12 22 4 14 418AS -2 16 -12 2 419AS -20 22 14 16 438AS 12 14 10 36 458AS 16 16 14 46 4 59AS -12 6 18 12 Mean Scores -5.33 13.67 9.83 1 8.17 Standard Deviation 10.69 11.95 14.62 19.08 79 The results of comparing the two industrial groups are recorded in Table 4. The resulting t-value for Group I (adventurous vs. cautious choices) was 2. 396 which identified the findings as being significant beyond the . 05 level. However, the Group II (general safety knowledge) and Group III (general industrial safety knowledge) t-values were not significant. Figure 1 graphically depicts a greater incidence of adventure in the accident employee and accident student as opposed to the higher cautious level of the non-accident employee. These findings supported the various Kunce investigations which related adventurous and cautious personality traits with the accident problem (38, 39, 40, 41, 42). Additional support for hypothesis 1 was revealed by the findings that nine of the twelve accident subjects in the student sample recorded a negative SAS index for the Group I responses. The SAS scores of the student accident sample are recorded in Table 3 and graphically plotted in Figures 1, 2, 3, and 4. Female sample. --Of the seven female industrial subjects who took the SAS survey, six were identified by the company as non accident employees and one was identified as an accident employee. The study findings revealed that all six female non-accident employees received a positive SAS index for Group I question responses; whereas, the one accident female employee received a TABLE 4 INDUSTRIAL SAMPLE, ACCIDENT vs. NON-ACCIDENT DATA Accident Employees Non-Accident Employees SAS Number Mean S. D. Absolute Value Number Mean S. D. Diff. t Group I 19 -3. 89 14.97 18 9.67 16. 51 13. 56 2. 396* Group 1 1 19 11.05 15.91 18 8.56 17.89 2.49 .475** Group III 19 7.37 18.02 18 11.56 19.78 4.19 1.027** Comb. Totals 19 14.53 27.31 18 29.78 26.99 15.25 ♦Significant beyond the . 05 level. **Not significant. Industrial Accident Sample Industrial Non-accident Sample Student Accident Sample 40 35 30 25 20 15 10 5 0 5 -10 -15 -20 -25 -30 -35 -40 Sample Participants Fig. 1. - -Group I SAS Scores (Adventurous vs. Cautious C hoices),Industrial and Student Accident Sample. Adventurous Range Cautious Range 82 Industrial Accident Sample Industrial Non-Accident Sample Student Accident Sample 40 35 30 25 20 15 10 / 7 5 0 -10 -15 -20 -25 -30 -35 -40 1 2 3 4 5 6 7 8 9 10 1 1 12 13 14 15 16 17 18 19 20 Sample Participants Fig. 2. --G roup II SAS Scores (G eneral Safety Knowledge), Industrial and Student Accident Sample. Industrial Accident Sample Industrial Non-Accident Sample Student Accident Sample " 7 -10 -15 -20 -25 -30 -35 -40 Sample Participants Fig. 3. --G roup III SAS Scores (G eneral Industrial Safety Knowledge), Industrial and Student Accident Sample. Industrial Accident Sample Industrial Non-Accident Sample Student Accident Sample 64 56 48 40 32 24 16 8 0 8 -16 -24 -32 -40 -48 -56 -64 1 2 3 4 5 6 7 8 9 10 1 1 12 13 14 15 16 1 7 18 19 20 Sample Participants Fig. 4. --Com bined Total SAS Scores (Groups I, II, and III), Industrial and Student Accident Scores. 85 negative SAS index for Group I responses. The results provided a 100 per cent accuracy in identifying caution as a characteristic related to the non-accident female employee. However, one test factor which involved the female sample needs to be emphasized. It should be noted that the Safety Alertness Survey was originally designed for use with an all-m ale sample. Therefore, most of the occupations and activities depicted in Group 1 were oriented toward the male population. One company official dismissed this concern with the comment that a large segment of the company's work force were females engaged in the mechanical and technical work units at the plant. The mean scores of the women industrial workers were compared with the total sample survey in Table 5. The findings are TABLE 5 COMPARISON OF MEAN SAS SCORES OF WOMEN INDUSTRIAL WORKERS TO MEAN SCORES OF TOTAL SAMPLE Responses Group I Responses Group II Responses Group III Combined Group Totals Women Industrial Employees' Mean Scores 20.50 10.50 5.40 36.50 Total Survey Sample Mean Scores -4.63 11.20 10. 35 16.93 86 statistically interesting. It will be noted that the women industrial employees recorded a large positive Group I SAS mean index, which implied a high cautious level. Of equal interest was the low Group 1 1 1 mean index which reflected the lack of industrial experience and training that is characteristically associated with a woman's life style. However, the combined mean score for Groups I, II, and III as recorded by the women industrial sample is significantly higher than comparable scores for all other survey samples. The data obtained from the female sample (recognizing an inadequate numerical sample) offered support for the accepted assumption that women are naturally more conservative than men. They do not, as a rule, favor the more adventurous activities and therefore would not become exposed to the accident environment as frequently as men. The findings of the industrial sample revealed a positive relationship with the findings of the Kunce investigations. In general, the assumption that the more adventurous person would record a greater negative SAS Group I index and the more cautious person would record a greater positive SAS Group I index was substantially upheld. Hypothesis 2. --There is a difference in the accident potential recorded among the groups of students a id among the groups of 87 industrial employees. Statistically a comparison was made between the mean and standard deviation of the total school sample and the total industrial sample. The findings are reported in Table 6. TABLE 6 COMPARISON OF MEANS AND STANDARD DEVIATIONS OF TOTAL INDUSTRIAL AND TOTAL STUDENT SAMPLES Responses Group I Responses Group II Responses Group III Combined Group Totals Total Industrial (M) 2.70 9. 84 9.41 21.95 Sample (SD) 17.14 18. 25 20. 22 29.11 Total Student (M) -5.27 11. 32 10.44 16. 49 Sample ' (SD) 12.41 14.02 15.69 22.25 The evidence supported hypothesis number 2. It should be noted that the Group I mean score of the total student sample was a negative value (-5. 27). Whereas, the Group I mean score of the industrial sample was one of positive value (2.70). These results can be explained, in part, by the fact that the student population had a younger average age (23.98 years vs. 39. 34 years) than the industrial sample. In addition, the student sample was an all-male population engaged in mechanical and technical occupational training. 88 Conversely, the industrial group was a mixed sample, with a female population which contributed a high conservative-cautious element to the findings. Moreover, the findings corresponded favor ably with previous research studies that related the young, the male sex and the mechanically oriented to the accident problem (8, 11, 23, 29, 36). In addition, the student sample had a higher mean score for Groups II and III (general safety knowledge and general industrial safety knowledge) than did the industrial sample. The findings are understandable when one considers the type of educational emphasis placed upon the safety program in the school environment. Neverthe less, the combined mean score for the industrial sample was significantly higher than the combined mean score for the total school sample. Hypothesis 3. - -There is a positive correlation between accident potential and aptitude as determined by school intelligence testing. A Pearson product moment correlation coefficient was calculated between the SAS scores and the Henmon-Nelson intelligence test scores. The school records of 112 students who had taken the Henmon-Nelson revealed an average IQ index of 97.90. The calculations produced a negative Pearson r value of -.472 for Group I responses. Thus, the relationship between the 89 Group I responses (adventure vs. caution) and intelligence was negatively correlated and rejected the hypothesis. The findings are in agreement with Ghiselli and Brown (5:347-48) who reported a non significant relationship between the variables of intelligence vs. accident-proneness. However, the Pearson r of . 885 for Group II responses showed a significant positive relationship between intelligence and general safety knowledge. Furthermore, the Pearson r of . 863 for Group III responses revealed a strong positive correlation between intelligence and general industrial safety knowledge. Since Groups II and III were concerned with acquired knowledge, the resulting high positive correlation was anticipated. In addition, a Pearson product moment correlation coeffici ent was calculated for twenty-seven students with Otis IQ scores. The results were as follows: Group I, -.367; Group II, .843; and Group III, . 880. These findings were in complete accord with the Henmon-Nelson sample. Hypothesis 4. —Greater numbers of accidents are associated with the age group 16-45 than with the age group 46-75. To test this hypothesis the Fisher t-test for a significant difference between the means was used. Age has consistently been associated with the acci dent incident (138:12, 176). Numerous experiments have reported 90 sound statistics which confirm the high positive correlation between youth and the accident problem. The t-test was calculated for Group I, 1 1 , and III, using the difference of the SAS means (for these categories) between the age spans 16-45 and 46-75. The findings for these calculations are reported in Table 7. SAS Group 1 as related to age. - -The photographic questions in Group I determined the extent of the adventurous-cautious index basic to the personality of the examinee. It will be recalled that the photographic questions in Group I depicted activity and occupational choices which were numerically rated. Moreover, this rating produced a scored index from a positive (cautious) range to a negative (adventurous) range. Consequently, it was assumed that the younger age sample (16-45) would score a higher negative SAS score in Group I responses than would the age group 46-75. However, this was not the case as can be seen in Table 7. The Group I mean score for the age group 16-45 was -4.20 with a standard deviation of 12. 96, whereas, the Group I mean score for the age group 46-75 was -9.94 with a standard deviation of 12.78. The t-test to determine a significance of difference between the means of the two age groups and their SAS Group 1 scores TABLE 7 SAS INDEX AS RELATED TO AGE 16-45 Age Range 46-75 Age Range SAS Number Mean S. D. Number Mean Absolute Value S. D. Diff. t Group I 425 -4.20 12.96 34 -9.94 12.78 5.74 2. 323* Group II 425 11.15 14.49 34 11.82 14.54 .67 .290** Group III 425 10.48 16.11 34 8.71 17.05 1.77 .789** ♦Significant beyond the . 05 level. **Not significant. 92 produced a value of 2. 323 which was beyond the . 05 level of signifi cance. However, the t score for Group I must be interpreted as reflecting, in part, an older industrial employee group who were classified as accident subjects (10 of 34 in the 46-75 age group). Consequently, the small older age sample was considered atypical in composition (high accident record) and therefore statistically influenced the findings contrary to the majority of research. SAS Group II as related to age. --The t score for Group 1 1 (general safety knowledge) was not significant at the . 05 level. Table 7 shows a mean SAS score of almost equal value between the age groups--11.15 to 11. 82. The apparent lack of difference between the tested variables (t value of . 290) indicated that the area of general safety knowledge was not the property of any one age group in the sample and was equally acquired by all age levels in the survey. SAS Group III as related to age. - -The SAS Group III mean score of age group 16-45 was slightly higher than the comparable mean for the 46-75 age group and can be explained by the large number of school subjects in this age range, who have undoubtedly influenced the mean score by their recent participation in a safety educational program. The t sco re for Group III (general industrial safety knowl edge) was not significant at the . 05 level. Since the m ajority of the 93 total population was composed either from the vocational student sample or the industrial sample, one would expect the lack of differ ence reached between the two age variables regarding general industrial safety information. Hypothesis 4 was rejected, and the findings of this investiga tion regarding the influence of age in relation to accident potential produced a negative relationship to the majority of past research. Nevertheless, it would be advisable to retest age samples of a more typical composition before the findings regarding hypothesis 4 are considered without qualifications. Hypothesis 5. - -There is a significant relationship between the SAS index and the instructor's rating of student accident potential. A total of 156 students were identified by instructors to be either "unsafe" or "safe" in the classroom environment (78 "unsafe" and 78 "safe"). The breakdown by course area is shown in Table 8. The Pearson product moment correlation coefficient was calculated for the SAS responses of instructor rated "unsafe” and "safe" sample. The resulting Pearson r of -.409 for the tested variables in Group I revealed a strong negative correlation and rejected the stated hypothesis. However, the calculated r value for Group II was . 821 and indicated a high positive relationship between instructor ratings and general safety knowledge. Identical results TABLE 8 94 INSTRUCTOR RATED "UNSAFE"~"SAFE" STUDENTS IN DIFFERENT VOCATIONAL COURSES Course Unsafe Safe Aeronautics 10 10 Architectural Drafting 5 5 Auto Body 3 3 Carpentry—Mill Cabinet 5 5 Diesel 5 5 Electronics* 11 11 Electromechanical 4 4 Industrial Electricity 5 5 Machine Tool 2 2 Refrigeration 10 10 Sheet Metal** 1 1 Tool Design 4 4 Welding 4 4 *One electronics instructor identified all students in his class as being safe. **Only five sheet metal students were tested--the instructor selected one of the five to be unsafe and one to be safe. were obtained from Group III with a calculated r value of . 799. In addition, the comparison of the mean SAS scores of "unsafe" and "safe" students with the SAS mean score of the total survey sample is shown in Table 9. The findings indicate strong 95 support for the assumption that instructor ratings of the "unsafe" and "safe" student were directly related to the student's ability to acquire knowledge. TABLE 9 COMPARISON OF MEAN SAS SCORES AND STANDARD DEVIATIONS OF RATED UNSAFE AND SAFE STUDENTS WITH SAS MEAN SCORE AND STANDARD DEVIATIONS OF TOTAL SAMPLE Responses Group I Responses Group II Responses Group III Combined Group Totals Unsafe (M) -5.69 10. 29 9.57 14. 17 Unsafe (SD) 11.34 13.18 15.17 21. 58 Safe (M) -7.50 10.96 11.21 14.67 Safe (SD) 12. 53 14.01 15.60 21.63 Total (M) -4.63 11.20 10.35 16.93 Sample (SD) 13.03 14.57 16.26 23.03 These data reveal that students rated "unsafe" by instructors did show higher negative mean scores for Group I responses than did the total sample. This finding would imply a higher adventurous selection of activity and occupational choices by the "unsafe" students than the mean Group I score for the total sample. In addition, the "unsafe" students recorded a slightly lower m ean sc o re for the questions in Group II—general safety knowledge. 96 A sim ilar finding was indicated for the mean score in Group III responses--general industrial safety knowledge. Likewise, the combined mean score for the three groupings revealed a score lower than the comparable score for the total sample. For the subjects identified as "safe" by instructor rating, the findings are not positively related to the "unsafe" sample. Table 9 indicates a mean score for Group I of the "safe" sample at -7. 50. This can be interpreted as representing a greater choice of adventur ous activities and occupations by the "safe" student than both the "unsafe" student and the total survey sample. This evidence would indicate that the instructor criteria for identifying the "safe" student was not based on the adventurous- caution theory of accident potential but rather on student acquisition of safety knowledge. Consequently, the mean score of the "safe" student in Group II and III was higher than the mean score of the "unsafe" student. Therefore, it would be reasonable to report that the instruc tor's rating was more significant in relation to the identification of the "unsafe" student than to the identification of the "safe" student. The evidence revealed that the Group 1 responses rejected the stated hypothesis, while Groups II and III supported the fifth hypothesis. Hypothesis 6. --The student's SV score (difference of aviator 97 and banker score), as determined by the Strong Vocational Interest Blank, shows a significant relationship with the student's SAS score. A Pearson product moment correlation coefficient was used to show the relationship between the student's SAS scores and his SVIB calculated SV score. The calculated Pearson r value for Group I (adventurous vs. cautious choices) of . 301 revealed a correlation coefficient that was compatible and in general support of the Kunce investigations (38, 39, 40, 41, 42). However, Groups II and III revealed negligible relation ships. Nevertheless, since the SV score is directly related to the Group I type question, it can be assumed that this hypothesis was supported by the study findings. Hypothesis 7. - -The student's SAS score (Group I) is positively related to the risk level assigned to their vocational choice. The findings to support this hypothesis are presented in Tables 10 through 24. The tables reveal the mean and standard deviations in relationship to the assigned risk level for the various vocational areas. The areas of vocational study were identified according to potential risk hazard as follows: high risk, medium risk, and low risk. Observation of the facilities and machinery in each course 98 area provided the assigned risk classification for the vocational program. Aeronautics- -Airframe High Risk Aeronautics - -Powerplant High Risk Architectural Drawing Low Risk Auto Mechanics High Risk Carpentry Medium Risk Diesel Medium Risk Electronics Low Risk Electromechanical Medium Risk Industrial Electricity Medium Risk Machine Tool High Risk Mill--Cabinet High Risk Refrigeration Medium Risk Sheet Metal Medium Risk Tool Design Low Risk Welding High Risk The findings that follow (Tables 10 through 24) provide meaningful information relating the Group I SAS index to the assigned risk level of the various vocational groupings. 99 TABLE 10 AERONAUTICS—AIR FRAME--HIGH RISK Responses Group 1 Responses Group II Responses Group 1 1 1 Combined Group Totals Mean Score -7.13 12.25 10.13 15.25 Standard Deviation 9.30 10.61 11. 84 16. 80 Note: The -7.13 mean score of Group 1 responses for this high risk vocational area was significant to the extent that it identified the class members as being at a high level of adventure orientation. TABLE 11 AERONAUTICS POWERPLANT--HIGH RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -9. 84 13.12 9.76 13.04 Standard Deviation 9.43 11.20 13.72 18.43 Note: The Aeronautics Powerplant sample with a mean SAS score of -9. 84 Group I was significantly related to the high risk classifica tion assigned. 100 TABLE 12 ARCHITECTURAL DRAWING-LOW RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -5. 84 10. 64 6. 56 11.36 Standard Deviation 13. 58 15.43 16. 58 23.74 Note: Although the Group I mean score was -5. 84 for this low risk vocational area, it should be noted that it was lower than the two previously listed high risk area scores. However, this score was not compatible with the anticipated score for a low risk vocational area. Note that the Group III score (general industrial safety knowl edge) was significantly lower than the previous two vocational areas. This can be interpreted as a reflection of the architectural drawing student's lack of contact with industrial tools and equipment. TABLE 13 AUTO MECHANICS—HIGH RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -9.49 11.95 9.69 12.15 Standard Deviation 16. 23 17.72 18.73 27.83 Note: The Group I mean score of -9.49 for a vocational area identified as high risk was statistically significant and further estab lished a relationship between adventure interest and vocational choice. 101 TABLE 14 CARPENTRY—MEDIUM RISK Responses Group I Responses Group 1 1 Responses Group III Combined Group Totals Mean Score -2.71 14.00 15.43 26.71 Standard Deviation 14.84 16.03 18.44 25.76 Note: The Group I mean score of -2.71 was below the anticipated mean score of a medium risk vocational area and therefore cannot be considered positively related to the adventure oriented level expected of members of this vocational area. TABLE 15 DIESEL--MEDIUM RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -4.27 11.18 10. 82 17.73 Standard Deviation 12.02 13. 87 15. 32 20.85 Note: The Group I mean score of -4.27 was compatible with the anticipated score for a medium risk vocational area. Hence, these findings can be considered statistically significant. 102 TABLE 16 ELECTRONICS—LOW RISK Responses Group I Responses Group 1 1 Responses Group III Combined Group Totals Mean Score -4.67 10.00 12. 90 18. 23 Standard Deviation 11.60 13.49 15.41 21.91 Note: The -4. 67 Group I mean score for a low risk area did not suggest a compatible relationship to the anticipated findings. How ever, it may be that this area was improperly assigned to the low risk level as it is the only shop type activity so classified—the other two low risk classifications were assigned to classroom drawing programs where the contact with industrial tools and equipment was non-existing. TABLE 17 ELECTROMECHANICAL—MEDIUM RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -5. 37 11.05 12. 84 18. 53 Standard Deviation 11. 52 13.43 15. 06 21.70 Note: The Group I mean score of -5.37 for a medium risk voca tional area was positively related to the expected adventure interest vs. vocational choice pattern. 103 TABLE 18 INDUSTRIAL ELECTRICITY—MEDIUM RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -5.45 13.00 12.45 20.00 Standard Deviation 11.11 12.40 13.44 18. 27 Note: For a medium risk vocational area the Group I mean scores of -5. 45 was positively significant. TABLE 19 MACHINE TOOL--HIGH RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -8.27 10. 53 10. 27 12. 53 Standard Deviation 11.82 12.40 14.79 21.59 Note: The Group I -8.27 mean score for a high risk vocational area was significantly related to the adventure interest factor reflected in this student sample. 104 TABLE 20 MILL CABINET--HIGH RISK Responses Group I Responses Group II Responses Group UI Combined Group Totals Mean Score -13.25 13.50 12.50 12.75 Standard Deviation 11.22 12.11 13.94 16.04 Note: The Group I mean score of -13. 25 was significant at a high level of relationship in establishing adventure interest to vocational choice. TABLE 21 REFRIGERATION—MEDIUM RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -2. 59 11.95 9. 32 18. 68 Standard Deviation 12. 20 13.34 14.96 22.99 Note: The Group I mean score of -2. 59 was not statistically significant for a medium risk vocational area classification. 105 TABLE 22 SHEET METAL—MEDIUM RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -5.67 9.00 10.67 14.00 Standard Deviation 10.92 12.97 15. 53 23.00 Note: The Group I mean score of -5. 67 for a medium risk voca tional area was positively related to the adventure oriented level expected. TABLE 23 TOOL DESIGN—LOW RISK Responses Group I Responses Group II Responses Group III Combined Group Totals Mean Score -3. 65 10.52 11.39 18.26 Standard Deviation 8.50 11.17 12.88 19.24 Note: The Group I mean score of -3. 65 for a low risk vocational area was statistically significant and supported the relationship of adventure interest to vocational choice. 106 TABLE 24 WELDING--HIGH RISK Responses Responses Responses Combined Group I Group II Group III Group Totals Mean Score -0.75 9.33 8.00 16.58 Standard Deviation 14.02 15.86 16.44 22.37 Note: The Group I mean score of -0.75 for a high risk vocational area was not related to the stated hypothesis and, at this time, no explanation can be offered for this wide departure from the other high risk vocational area scores. Of additional interest in the findings relating vocational risk levels to adventure orientation were the statistics of the Strong Vocational Interest Battery college sample. This group was composed of students from the college vocational planning class who represented a typical cross-section of the campus population. However, as suggested by the course title, these students were basically undecided about the choice of a vocational career. As shown in Table 25, this sample had a Group I mean score of -1.46 which became statistically significant when the Group I mean scores for all vocational areas were considered. It can be reported that the SAS Group I mean scores 107 TABLE 25 SVIB--COLLEGE SAMPLE Responses Group I Responses Group 1 1 Responses Group III Combined Group Totals Mean Score -1.46 10.77 9.15 18.46 Standard Deviation 11.35 12.84 14.19 18.07 achieved a 68 per cent accuracy rate in identifying the risk hazard assigned to various vocational groups. These findings are significant and indicate that the more adventurous orientated students tend to select vocational areas of study that show compatible levels of risk. Whereas, the cautious student selected a vocational area of study compatible with this personality characteristic. Summary of Findings The findings of the interpreted data were as follows: 1. A significant relationship (beyond the .05 level) existed between the SAS Group I scores of the industrial accident-nonaccident sample and their accident or non-accident work record. The results were significant beyond the . 05 level for predictive purposes and provided sufficient evidence to use the SAS Group I index for continued research in this experimental endeavor. An important difference between the SAS Group I scores of the total student sample and the total industrial sample was revealed. The data supported the stated hypothesis and indicated that the school sample composed of the youthful male vocational student would reflect a higher adventurous SAS Group I score than would the older mixed-sex sample of the industrial group. A negative relationship existed between the intelli gence factor and the SAS Group I scores. This evidence is in general agreement with the research of Ghiselli and Brown (5:347-48). However, the evidence did not support the research hypothesis. There was a higher adventurous index reported for the age group 46-75 than for the group 15-45. This evidence did not support the stated hypothesis and therefore was in disagreement with most of the existing research. However, the younger age group numbered 425; whereas, the older group numbered thirty-four. The older group contained a proportion ally large percentage of older industrial accident employees whose Group I scores would reflect an adverse influence to the anticipated results. Evidence was produced to question the use of super visory ratings as a means of predicting accident potential. The Pearson r of -.409 for the Group I responses revealed a negative relationship between the two means and therefore rejected the stated hypothesis. However, the Group II and III r values were of a high positive relationship. There was a significant relationship between the student's SV score and his SAS score. This evidence supported the investigations of Kunce, et al. (38, 39, 40, 41, 42) and further strengthened the evidence for a positive relationship between the adventure vs. cautious characteristics of personality and the accident potential. There was a significant relationship (beyond the . 10 level) between an individual's SAS Group I score and his choice of vocational training. Evi dence indicated that the high negative SAS Group I 110 score was associated with the high vocational risk subject. While the low SAS Group I score was associated with the medium or low risk vocational areas. Moreover, the SAS Group I score for the undecided major students (vocational planning class) revealed a low SAS Group 1 mean score. 8. The data indicated that the SAS as an instrument to determine accident potential in individuals was statistically more reliable when only the Group I scores were considered. The Group II scores were not significantly related to the accident employee, as indicated in Figure 2. However, Figures 3 and 4 do indicate a positive relationship between SAS scores in Group III and Combined Group Total and the industrial accident-nonaccident sample. Chapter Summary Chapter IV analyzed the statistical data obtained from the study samples, which consisted of junior college students and industrial employees. Included in this analysis was the initial task of establishing a reasonable predictive value for the SAS measuring instrument. Consequently, this was accomplished by comparing the I l l SAS scores of the industrial accident and non-accident population. With a significant relationship established between the SAS score (Group 1) and accident potential various relationships were tested for degrees of significance. These included relationships between (1) the SAS scores and the intelligence factor, (2) the SAS scores and instructor safety ratings, and (3) the SAS scores and the student's SV score. In addition, a comparison of the mean and standard deviation of the SAS scores with (1) the assigned risk levels of the various vocational areas, and (2) school and industrial sample were shown. CHAPTER V SUMMARY, CONCLUSIONS, AND R ECOMMENDATIONS Summary The problem. —The problem of this study was to develop and test a visual safety alertness survey which could be used to identify degrees of accident-proneness in junior college vocational students and industrial employees. The accident problem is one of the great concerns for the highly industrial society. Its effects are costly and reverberate throughout the community, touching a multitude of people far from the initial scene of the incident. In an attempt to combat the accident problem, safety programs have been formulated by both industrial and educational segments in our society; nevertheless, the accident is still a very frequent reality and one that millions of people will sadly experience in the coming years. Thus, it became apparent that innovative 112 113 direction must guide the attempts to lessen accidents in schools and industry. One such effort is presented within this dissertation in the form of a visual safety alertness survey (SAS). Research hypotheses. - -This investigation was done in terms of the following hypotheses: 1. Accident potential can be identified by means of a photographic examination with a reasonable level of prediction. 2. There is a difference in the accident potential recorded among the groups of students and also among the groups of industrial employees. 3. There is a positive correlation between accident potential and aptitude as determined by school intelligence testing. 4. Greater numbers of accidents are associated with the age group 16-45 than with the age group 46-75. 5. There is a significant relationship between the SAS index and the instructor's rating of student accident potential. 6. The student's SV score (difference of aviator and 114 banker score) as determined by the Strong Vocational Interest Battery shows a significant relationship with the student's SAS score. 7. The student's SAS score (Group I) is positively related to the risk level assigned to their vocational choice. Also, the study was directed by a series of questions listed on pages 5 and 6. The procedure. --O f major concern was the selection of a measuring instrument that would evaluate accident potential in individuals through visual questioning. However, a thorough search of the existing test materials failed to reveal such an evaluating device. Consequently, the development and testing of a visual safety alertness survey became the task of priority for this study. The measuring instrument was designed to investigate three areas of the safety problem. First, it was considered essential to investigate the possibility of developing an instrument that would allow the identification of various degrees of accident potential in students and industrial workers. Second, the examination was designed to investigate the importance that general safety knowledge (informational data) had on the total safety alertness index of the individual. Third, the test attempted to determine if there was a 115 factor of "safety insight" within individuals that provided proper judgment in avoiding accident involvement. The measuring instrument consisted of a group of thirty photographic questions. Each question was composed of four color photographs. The questions were equally grouped into three distinct areas: (1) personal attitudes toward activities and occupational choice--ten questions, (2) general safety knowledge--ten questions, and (3) general industrial safety knowledge--ten questions. Following the assembly of the photographic questions, the survey in its entirety was evaluated by qualified experts. The photographic questions were then processed as color slides for presentation to the examinees in group testing situations. The scoring of the SAS (Group I) responses was based on age as described in Chapter 1 1 1 and compensated for the natural adventure orientation associated with the lower age brackets and the natural cautious orientation associated with the more advanced age brackets in the study sample. Literature review. --Research into the literature revealed that the early investigation into the concept of accident-proneness directed its efforts toward the theme that a certain segment of the population was more prone to accidents. Moreover, this early investigational period saw the beginning of efforts to explore the 116 area of physio-psychological testing as a predictive measurement to identify accident-proneness. The results of these investigations reflected both positive and negative conclusions: both the proponents and opponents of such testing were provided with support for their beliefs regarding the value of testing as a tool to predict accident liability. Later investi gation was directed at the role human personality factors play in the accident incident. Consequently, the study of accident-proneness has under gone three distinct developmental phases: (1) the identification of the accident-proneness phenomenon and its accompanying period of experimentation; (2) the period of exploration into the area of psycho logical testing and related factors; and (3) the investigation of personality traits and characteristics and the relationships of these factors to accident-proneness. Study samples. - -Three sample groupings were administered the SAS: (1) 383 junior college students from various vocational programs, (2) twenty-six junior college students who had previously taken the Strong Vocational Interest Battery, and (3) an industrial sample of thirty-seven accident-nonaccident employees and twelve junior college students who had records of accident involvement during the twelve-month period, January, 1969, to January, 1970. 117 In each vocational class tested the instructor was asked to identify the five students he considered the most "unsafe" and the five students he considered the most "safe." These ratings were compared with the student's SAS index for significant relationships. Because of the established relationship between the aviator and banker scales of the Strong Vocational Interest Battery and accident-proneness, the SVIB scores of sample group two were compared with the subject's SAS score. In addition, the accident- nonaccident subject's SAS index was compared with their accident- nonaccident work records. The three sample groupings provided statistical data necessary for the evaluation of the SAS instrument. The findings. — 1. A significant relationship (beyond the .05 level) existed between the SAS scores (Group I) of the industrial accident-nonaccident sample and their accident or non-accident work record. 2. An important difference between the SAS scores of the total student sample and the total industrial sample was revealed, with the youthful male vocational student showing evidence of high adventure orientation. 3. A negative relationship between the intelligence factor and the SAS Group I scores was revealed. The data revealed that age was not directly related to the higher adventurous index. Hence, the mean Group I scores for the age group 46-75 was higher than the age group 16-45. However, these results can be partially explained by the high percentage of industrial accident employees in this age range. Instructor rating proved to be a poor means to predict accident potential. However, the data re vealed that instructor ratings for the "unsafe" students were more valid than instructor ratings for the "safe" student. The SV (SVIB) score was positively related to the SAS Group I score. In addition, a high SV score was associated with the high (adventurous) Group 1 SAS score. A significant relationship (beyond the . 10 level) existed between a student’s SAS score (Group I) and his choice of vocational training. Evidence indicated that the high negative SAS Group I score was associated with the high vocational risk subject. While the low SAS Group I score more frequently was associated with the medium or low risk vocational areas. 8. The SAS as an instrument to determine accident potential in individuals was statistically more reliable when only the Group I scores were con sidered. Group II (general safety information) responses did not reveal significant differences between the various sample groups in this question category. The responses to Group III (general industrial safety) also revealed little significant difference between the sample subjects. Conclusions This experimental investigation into the problem of identify ing degrees of accident potential within individuals seemed to justify the following four major conclusions: Visual Safety Alertness Survey. — 1. Accident-proneness can be predicted by the use of a visual (photograph) safety alertness test (SAS). The use of a photographic examination in the area of accident potential identification was novel in its approach and incorporated desirable advantages over the "written" safety examination. First, the descriptive qualities of the SAS were more meaningful to the vocational student or industrial employee. Second, the SAS utilized a non-verbal approach to the vocational and industrial safety programs. Third, the SAS provided a more meaningful method of indoctrinat ing the new or late school enrollee or the new hire in industry to the area of safety. Finally, it provided the basis for a continued educational safety program capable of reflecting individual safety needs. The SAS instrument provided authorities with an accident potential index for each examinee based upon the degree of adventurous-cautious orientation of the individual's personality. Since the SAS Group I responses for the industrial sample identified correctly twenty-nine of the thirty-seven employees (78 per cent) as having either accident or non-accident work records, evidence was in favor of continuing the investiga tion into the use of the photographic safety 121 examination. It was concluded that a negative 1 SAS index for Group I responses would be the minimum value for identifying the person with accident potential. It was further concluded that as the negative value increased so would the accident potential of the individual. Conversely, a positive 1 SAS index for Group I responses would be the minimum value for identifying the potenti ally safe student or employee. Furthermore, as this positive value increased so did the tendency for greater caution. The index score of the SAS was based on a continuum scale of from -80 (high adventure-high accident potential) to +80 (high caution-accident free). Student choice of vocational major. -- 2. A significant relationship exists between a student's vocational major and his Group I SAS index. The evidence from this investigation supported the conclusion that a student selects his vocational major, in part, on the basis of the degree of risk involved in the vocation and adventurous elements 122 in his personality. A substantial amount of the statistical data supported this conclusion as the majority of vocational students who had high (negative) adventurous SAS Group I responses were involved in the high risk vocational areas. Whereas, the high SAS Group 1 (cautious) responses were more generally associated with those students who had enrolled in the low risk vocational programs. Adventure-oriented school population. — 3. The school population is more adventure-oriented than the industrial population. Of the 383 vocational students in the school sample, 274 received a negative or adventurous score for the Group I responses. This would indicate that approximately 71 per cent of the vocational student population surveyed were adventure-oriented and, thus, have various degrees of accident susceptibility. How ever, the data for the industrial group showed twenty positive SAS scores as opposed to seventeen negative scores (54.1 per cent vs. 45.9 per cent) or slightly less than one-half of the industrial group identified as adventure-oriented. General safety information vs. industrial safety information. -- 4. General safety knowledge is not a significant factor in the identification of accident potential. However, industrial safety information did show a small positive relationship to the accident subject. Recommendations The following recommendations seem to be warranted by the findings of this study: 1. That a follow-up questionnaire be sent to the school and industrial sample of this study after a time lapse of two years to determine their actual accident records during this time period and the relationship to their SAS Group 1 index. 2. That the visual safety alertness survey Group I section (adventure vs. caution type photographic question) be enlarged to thirty questions, omitting sections II and III. The questions in this section should be oriented toward both sexes, depicting occupations and activities compatible to the interests of both men and women. Test instructions should be recorded allowing for greater consistency in verbal directions. That the examinee should be asked to list on the answer form accident involvement during the year preceding the test session. That the new visual survey should be given to a large accident sample (preferably in cooperation with a large municipal hospital) and a large randomly selected general population sample (mixed sexes). It is further suggested that this sample be asked to participate in a follow-up inquiry to determine their actual accident experiences during a two-year period after the administration of the survey. That an investigation into the relationship between vocational risk and the student's adventurous vs. cautious personality characteristics be conducted using evaluating devices of a different design. That the SAS index be used to foster the initiation of a continual safety awareness in the industrial educational program. It is further suggested that the SAS index be made available to interested school personnel, counselors, school nurses, 125 physical education instructors, e tc .. for appropriate consideration and application. 7. That industry experiment with the SAS type of examination to identify degrees of accident potential in employees. 8. That consideration be given to the development of a series of safety TV film clips regarding industrial and vocational safety practices and equipment usage. Furthermore, it is suggested that both school and industry consider the use of a closed circuit TV facility permitting the employee or student an immediate review of his safety concern through a visual replay of proper practices and procedures. APPENDIXES 126 APPENDIX A 128 October 27, 1969 From: Arthur F. Steiner To: Subject: Research Project Proposal 1 have entered the final stages in the program for the doctor's degree at the University of Southern California. A portion of my dissertational study involves administering a "safety alertness survey" to sixteen classes of junior college vocational students. The measuring instrument (self-designed) has been placed on slides, making it possible to administer the survey to large groups. I have included for your evaluation a basic outline of the survey and the extent of student and instructor involvement this study would require. This letter is requesting permission to utilize the listed vocational areas in the testing program. Aeronautics Architectural Drafting Automotives Carpentry--M ill Cabinet Diesel Mechanics Electronics Electromechanical Industrial Electricity Machine Tool Refrigeration Sheet Metal Tool Design Welding The survey would involve approximately 350 vocational students and each testing session would require from 45 to 55 minutes. 129 October 27, 1969 From: Arthur F. Steiner To: Subject: Research Project Proposal Safety Alertness Survey The student will view three groups of ten slides each. Each slide will be composed of four color photographs. The first group of ten slides covers the area of personal attitudes toward activity and occupational choice—attempting to relate the personality character istics of the individual either positively or negatively to the theme of accident liability. This group of photographic questions will allow the student to select between degrees of occupational risk and adven ture in relation to more conservative activities or occupations. For instance, a question in this category might depict the following activities: (1) gardening, (2) chess game, (3) flying, and (4) tennis. The examinee would select the activity that he would most enjoy (if he had the necessary qualifications) to the activity he would least enjoy. The second group of ten questions deals with the area of general safety knowledge, and is utilized to determine the extent of a person's awareness of safety during his everyday activities. Hence, this group depicts areas of safety regarding the home, the auto mobile, the playground, recreational activities, etc. Therefore, the basic intent of this group of slides is to determine if safety knowl edge (facts and information) affects one's attitude toward the total profile of his safety pattern. The final ten questions cover areas of general industrial safety such as industrial power tools, m aterial storage, construc tion work, etc. This group of questions attempts to determine if certain individuals are endowed with a safety alertness that would allow a sound judgment of potential hazard in situations and with equipment that are not necessarily totally familiar to them. 130 In addition, the study would require that each class instructor participating in the survey select the five students whom he has identified thru classroom observation to be the "safest” and the five students he has identified as the most "unsafe. ” This evaluation should require no more than five minutes of individual instructor time. 131 OBSERVATION OF STUDENT SAFETY INSTRUCTOR EVALUATION FORM INSTRUCTOR____________________ DATE_____________________ CLASS__________________________ SCHOOL__________________ Dear Instructor, I. Please identify below the five students in your _________________________________ class that (through classroom observation and student activity) you consider the most UNSAFE in the classroom environment. 1. ______________________________________ 2. ______________________________________ 3. ___________________________________ 4. ___________________________________ 5._____________________________________ II. Please identify below the five students in your _________________________________ class that (through classroom observation and student activity) you consider the most SAFE in the classroom environment. 1. ______________________________________ 2. ______________________________________ 3. ___________________________________ 4. ___________________________________ 5. III. Please return the completed form to Arthur Steiner, Long Beach City College, Liberal Arts Campus. Thank you for your considered cooperation. 132 Nam Addr City Com SURVEY INFORMATION FORM a Age 1A 688 Phoi Zone D ll oanv . - Positii Department Group I SLIDES Group 2 Group 3 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 133 134 135 136 137 Pf»(<X‘ Or Wafig P a t re a m f l £ # W O f £Af>H/M$S 141 Ml- ii ■ 6-2 142 6-3 145 APPENDIX B PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE A TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 1 Group 1 Question 2 Group 1 PVA PVA Per Cent PVA PVA Per Cent MR LP 16-45 46-75 RFC TR PR MP LP 16-45 46-75 RFC TR D B -4 -8 144 31.37 1 C D -4 -8 31 6.75 D C -2 -4 39 8.50 2 C A -2 -4 175 38.13 D A -2 -4 40 8.71 3 C B -2 -4 29 6. 32 A B -2 -4 59 12.85 4 B D -2 -4 42 9.15 A C 0 0 25 5.45 5 B A 0 0 93 20. 26 A D 44 4 -2 26 5. 66 6 B C 44 4 -2 5 1.09 B D +8 44 6 1.31 7 D C 48 44 5 1.09 B A 44 4 -2 21 4.58 8 D B 44 4 -2 17 3.70 B C 44 . 4 -2 13 2. 83 9 D A 44 4 -2 40 8.71 C D 44 +2 23 5.01 10 A C 44 4 -2 4 0.87 C A 0 0 26 5. 66 11 A B 0 0 7 1.53 C B -2 -4 37 8.06 12 A D -2 -4 9 1.96 PR = Possible Response; MP = Most P referred; LP = L east P referred; PVA = Point Value—Age; RFC = Response Frequency Count; Per Cent TR = Percentage of T otal Response. * > . v O PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE B TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 3 Group 1 PVA PVA MP LP 16-45 46-75 RFC B C -4 -8 58 B D -2 -4 20 B A -2 -4 38 A C -2 -4 35 A D 0 0 16 A B +4 +2 27 C B +8 44 19 C A 44 4 -2 24 C D +4 4 -2 18 D B 44 4 -2 58 D A 0 0 63 D C -2 -4 78 Question 4 Per Cent TR PR MP LP 12.64 1 C A 4.36 2 C B 8.28 3 C D 7.63 4 D A 3.49 5 D B 5. 88 6 D C 4.14 7 A C 5. 23 8 A D 3.92 9 A B 12.64 10 B C 13.73 11 B D 16.99 12 B A Group 1 PVA PVA Per Cent 16-45 46-75 RFC TR -4 -8 19 4.14 -2 -4 54 11.76 -2 -4 34 7.41 -2 -4 34 7.41 0 0 67 14.60 44 4 -2 40 8.71 4 -8 44 52 11.33 44 4 -2 43 9. 37 44 4 -2 74 16.12 44 4 -2 15 3.27 0 0 17 3.70 -2 -4 10 2.18 PR * Possible Response; MP = Most P referred; LP = L east P referred; PVA = Point Value—Age; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response. S PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE C TABULATION OF QUESTION PHOTOGRAPH1C-COMB1NATION RESPONSES Question 5 Group 1 Question 6 Group 1 PVA PVA Per Cent PVA PVA Per Cent MP LP 16-45 46-75 RFC TR PR MP LP 16-45 46-75 RFC TR B A -4 -8 122 26. 58 1 C B -4 -8 134 29.19 B D -2 -4 10 2.18 2 C A -2 -4 158 34.42 B C -2 -4 32 6.97 3 C D -2 -4 48 10.46 C A -2 -4 40 8.71 4 D B -2 -4 16 3.49 c D 0 0 8 1.74 5 D A 0 0 28 6.10 c B 44 4 -2 6 1.31 6 D C 44 4 -2 5 1.09 A B 46 44 7 1.53 7 B C 46 44 6 1.31 A C 44 4 -2 4 0. 87 8 B D 44 4 -2 6 1.31 A D 44 4 -2 9 1.96 9 B A 44 +2 14 3.05 D B 44 4 -2 28 6.10 10 A C 44 4 -2 10 2.18 D C 0 0 50 10. 89 11 A D 0 0 9 1.96 D A -2 -4 143 31.15 12 A B -2 - 4 25 5.45 PR = Possible Response; MP = Most P referred; LP = L east P referred; PVA = Point Value--Age; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response. PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE D TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 7 Group 1 Question 8 Group 1 MP LP PVA 16-45 PVA 46-75 RFC Per Cent TR PR MP LP PVA 16-45 PVA 46-75 RFC Per Cent TR D A -4 -8 103 22.44 1 A D -4 -8 117 25.49 D B -2 -4 14 3.05 2 A C -2 -4 49 10. 68 D C -2 -4 10 2.18 3 A B -2 -4 54 11.76 C A -2 -4 134 29.19 4 B D -2 -4 26 5. 66 C B 0 0 18 3.92 5 B C 0 0 15 3.27 C D +4 42 47 10. 24 6 B A 44 42 9 1.96 A D 4« 44 17 3.70 7 D A 48 44 20 4.36 A C 44 4 -2 2 0.44 8 D B 44 42 22 4.79 A B +4 4 -2 9 1.96 9 D C 44 42 28 6.10 B D +4 4 -2 16 3.49 10 C A 44 42 22 4.79 B C 0 0 13 2.83 11 C B 0 0 30 6.54 B A -2 -4 73 15.90 12 C D -2 -4 64 13.94 PR = Possible Response; MP = Most P referred; LP = L east P referred; PVA = Point Value—Age; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response. cn to PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE E TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 9 Group 1 Question 10 Group 1 PVA PVA Per Cent PVA PVA Per Cent MP LP 16-45 46-75 RFC TR PR MP LP 16-45 46-75 RFC TR A D -4 -8 49 10. 68 1 D A -4 -8 58 12.64 A B -2 -4 116 25. 27 2 D B -2 -4 3 0. 65 A C -2 -4 13 2. 83 3 D C -2 -4 33 7.19 C D -2 -4 59 12.85 4 C A -2 -4 21 4.58 C B 0 0 74 16.12 5 C B 0 0 1 0. 22 C A +4 4 -2 35 7.63 6 C D 44 4 -2 4 0.87 D A 44 19 4.14 7 A D 48 44 93 20. 26 D C +4 4 -2 8 1.74 8 A C 44 4 -2 102 22. 22 D B +4 4 -2 45 9. 80 9 A B 44 4 -2 3 0. 65 B A 44 4 -2 15 3. 27 10 B D 44 4 -2 52 11.33 B C 0 0 2 0.44 11 B C 0 0 53 11.55 B D -2 -4 17 3.70 12 B A -2 -4 35 7.63 PR = Possible Response; MP = M ost Preferred; LP = L east P referred; PVA = Point Value—Age; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response. TABLE F TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 1 Group 2 Question 2 Group 2 PR MU MS RFC Per Cent TR RPV PR MU MS RFC Per Cent TR RPV 1 B D 2 0.44 -4 1 C B 10 2.18 -4 2 B C 3 0. 65 -2 2 C A 28 6.10 -2 3 B A 1 0. 22 -2 3 C D 14 3.05 -2 4 A D 4 0. 87 -2 4 D B 24 5. 23 -2 5 A C 10 2.18 0 5 D A 27 5. 88 0 6 A B 32 6.97 +2 6 D C 80 17.43 +2 7 D B 75 16. 34 +1 7 B C 115 25.05 44 8 D A 32 6.97 + 2 8 B D 26 5. 66 +2 9 D C 5 1.09 +2 9 B A 63 13.73 +2 10 C B 242 52.72 +2 10 A C 42 9.15 +2 11 C A 45 9.80 0 11 A D 6 1.31 0 12 C D 8 1.74 -2 12 A B 21 4.58 -2 PR = Possible Response; MU = M ost Unsafe; MS = M ost Safe; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response; RPV = Response Point Value. H - £ TABLE G TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 3 Group 2 Question 4 Group 2 Per Cent Per Cent PR MU MS RFC TR RPV PR MU MS RFC TR RPV 1 B A 55 11.98 - 4 1 B A 27 5. 88 -4 2 B D 5 1.09 -2 2 B C 6 1.31 -2 3 B C 140 30.50 -2 3 B D 29 6. 32 -2 4 C A 5 1.09 -2 4 D A 62 13.51 -2 5 C D 3 0. 65 0 5 D C 7 1.53 0 6 C B 2 0.44 +2 6 D B 29 6. 32 +2 7 A B 0 0.0 44 7 A B 11 2.40 + 4 8 A C 3 0. 65 +2 8 A D 26 5. 66 +2 9 A D 0 0.0 +2 9 A C 4 0.87 +2 10 D B 7 1.53 +2 10 C B 40 8.71 +2 11 D C 178 38.78 0 11 C D 125 27.23 0 12 D A 59 12.85 -2 12 C A 89 19.39 -2 PR = Possible Response; MU = Most Unsafe; MS = Most Safe; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response; RPV = Response Point Value. PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE H TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 5 Group 2 Question 6 Group 2 Per Cent Per Cent MU MS RFC TR RPV PR MU MS RFC TR RPV c A 1 0. 22 -4 1 D A 12 2.61 -4 c B 2 0.44 -2 2 D B 16 3.49 -2 c D 2 0.44 -2 3 D C 4 0. 87 -2 D A 9 1.96 -2 4 C A 6 1.31 -2 D B 2 0. 44 0 5 C B 12 2.61 0 D C 11 2.40 +2 6 C D 40 8.71 +2 A C 155 33.77 +4 7 A D 302 65.80 44 A D 193 42.05 +2 8 A C 9 1.96 +2 A B 7 1.53 +2 9 A B 27 5. 88 +2 B C 27 5. 88 +2 10 B D 28 6.10 +2 B D 39 8.50 0 11 B C 1 0.22 0 B A 7 1.53 -2 12 B A 1 0.22 -2 PR = Possible Response; MU = Most Unsafe; MS = Most Safe; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response; RPV = Response Point Value. cn O PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE I TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 7 Group 2 Question 8 Group 2 Per Cent Per Cent MU MS RFC TR RPV PR MU MS RFC TR RPV B D 7 1.53 -4 1 D C 60 13.07 -4 B C 2 0.44 -2 2 D B 43 9.37 -2 B A 3 0. 65 -2 3 D A 84 18.30 -2 A D 10 2.18 -2 4 A C 39 8.50 -2 A C 14 3.05 0 5 A B 18 3.92 0 A B 29 6. 32 +2 6 A D 108 23.53 +2 D B 160 34.86 +4 7 C D 33 7.19 44 D A 49 10. 68 42 8 C A 20 4.36 4 -2 D C 124 27.02 +2 9 C B 11 2.40 4 -2 C B 42 9.15 +2 10 B D 27 5. 88 4 -2 C A 10 2.18 0 11 B A 7 1.53 0 C D 6 1.31 -2 12 B C 6 1.31 -2 PR = Possible Response; MU = M ost Unsafe; MS = Most Safe; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response; RPV = Response Point Value. TABLE J TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 9 Group 2 Question 10 Group 2 PR MU MS RFC Per Cent TR RPV PR MU MS RFC Per Cent TR RPV 1 C A 10 2.18 -4 1 D B 26 5. 66 -4 2 C B 2 0.44 -2 2 D C 24 5. 23 -2 3 C D 11 2.40 -2 3 D A 86 18.74 -2 4 D A 2 0.44 -2 4 A B 3 0. 65 -2 5 D B 8 1.74 0 5 A C 7 1.53 0 6 D C 65 14.16 + 2 6 A D 18 3.92 +2 7 A C 181 39.43 +4 7 B D 34 7.41 44 8 A D 27 5. 88 +2 8 B A 65 14.16 +2 9 A B 23 5.01 + 2 9 B C 15 3.27 + 2 10 B C 97 21.13 + 2 10 C D 59 12. 85 + 2 11 B D 27 5.88 0 11 C A 96 20.92 0 12 B A 5 1.09 -2 12 C B 24 5. 23 -2 PR = Possible Response; MU = Mos Unsafe; MS = Most Safe; RFC = Response Frequency Count; P er Cent TR = Percentage of Total Response; RPV = Response Point Value. cn o o PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE K TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 1 Group 3 Question 2 Group 3 Per Cent Per Cent MU MS RFC TR RPV PR MU MS RFC TR RPV A B 11 2.40 -4 1 B A 3 0. 65 -4 A C 14 3.05 -2 2 B D 2 0.44 -2 A D 28 6.10 -2 3 B C 9 1.96 -2 D B 6 1.31 -2 4 C A 14 3.05 -2 D C 6 1.31 0 5 C D 9 1.96 0 D A 32 6.97 +2 6 c B 57 12.42 +2 B A 46 10.02 +4 7 A B 119 25.93 44 B D 61 13.29 +2 8 A C 48 10.46 +2 B C 10 2.18 +2 9 A D 52 11.33 +2 C A 108 23.53 +2 10 D B 87 18.95 +2 C D 113 24.62 0 11 D C 41 8.93 0 C B 23 5.01 -2 12 D A 17 3.70 -2 PR = Possible Response; MU = M ost Unsafe; MS = Most Safe; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response; RPV = Response Point Value. TABLE L TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 3 Group 3 Question 4 Group 3 PR MU MS RFC Per Cent TR RPV PR MU MS RFC Per Cent TR RPV 1 A D 42 9.15 -4 1 C A 22 4.79 -4 2 A B 87 18.95 -2 2 C D 28 6.10 -2 3 A C 61 13.29 -2 3 C B 26 5. 66 -2 4 C D 17 3.70 -2 4 B A 16 3.49 -2 5 C B 40 8.71 0 5 B D 15 3.27 0 6 C A 31 6.75 +2 6 B C 32 6.97 +2 7 D A 60 13.07 44 7 A C 62 13. 51 44 8 D C 57 12.42 +2 8 A B 47 10.24 4 -2 9 D B 41 8.93 +2 9 A D 41 8.93 4 -2 10 B A 15 3. 27 +2 10 D C 80 17.43 4 -2 11 B C 3 0. 65 0 11 D B 26 5. 66 0 12 B D 4 0.87 -2 12 D A 62 13.51 -2 PR = Possible Response; MU = M ost Unsafe; MS = Most Safe; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response; RPV = Response Point Value. PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE M TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 5 Group 3 Per Cent MU MS RFC TR B C 1 0.22 B A 4 0. 87 B D 0 0.0 D C 4 0.87 D A 55 11.98 D B 20 4.36 C B 103 22.44 C D 51 11.11 C A 135 29.41 A B 38 8. 28 A D 40 8.71 A C 6 1.31 Question 6 RPV PR MU MS -4 1 D B -2 2 D A -2 3 D C -2 4 C B 0 5 C A +2 6 C D +4 7 B D +2 8 B C +2 9 B A +2 10 A D 0 11 A C -2 12 A B Group 3 Per Cent RFC TR RPV 15 3.27 -4 29 6. 32 -2 49 10. 68 -2 3 0. 65 -2 1 0.22 0 4 0.87 +2 31 6.75 44 65 14.16 +2 26 5. 66 +2 76 16. 56 +2 126 27.45 0 33 7.19 -2 PR = Possible Response; MU = Most Unsafe; MS = M ost Safe; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response; RPV = Response Point Value. O ' TABLE N TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 7 Group 3 Question 8 Group 3 PR MU MS RFC Per Cent TR RPV PR MU MS RFC Per Cent TR RPV 1 D A 9 1.96 -4 1 C B 2 0.44 -4 2 D C 28- 6.10 -2 2 C A 3 0. 65 -2 3 D B 42 9.15 -2 3 C D 16 3.49 -2 4 B A 3 0.65 -2 4 D B 2 0.44 -2 5 B C 6 1.31 0 5 D A 10 2.18 0 6 B D 8 1.74 +2 6 D C 3 0. 65 +2 7 A D 146 31.81 44 7 B C 75 16.34 44 8 A B 91 19.83 4 -2 8 B D 135 29.41 4 -2 9 A C 56 12.20 +2 9 B A 31 6.75 4 -2 10 C D 34 7.41 +2 10 A C 50 10. 89 4 -2 11 C B 31 6.75 0 11 A D 121 26. 36 0 12 C A 2 0.44 -2 12 A B 10 2.18 -2 PR = Possible Response; MU = M ost Unsafe; MS = M ost Safe; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response; RPV = Response Point Value. PR 1 2 3 4 5 6 7 8 9 10 11 12 TABLE O TABULATION OF QUESTION PHOTOGRAPHIC-COMBINATION RESPONSES Question 9 Group 3 Question 10 Group 3 Per Cent Per Cent MU MS RFC TR RPV PR MU MS RFC TR RPV A C 2 0.44 -4 1 A B 83 18.08 -4 A D 3 0. 65 -2 2 A D 64 13.94 -2 A B 6 1.31 -2 3 A C 90 19.61 -2 B C 8 1.74 -2 4 C B 7 1.53 -2 B D 22 4.79 0 5 C D 12 2.61 0 B A 31 6.75 +2 6 C A 22 4.79 +2 C A 166 36.17 44 7 B A 39 8.50 44 C B 30 6. 54 +2 8 B C 29 6. 32 4 -2 C D 39 8.50 +2 9 B D 22 4.79 4 -2 D A 99 21.57 +2 10 D A 36 7.84 4 -2 D B 28 6.10 0 11 D C 35 7.63 0 D C 24 5. 23 -2 12 D B 18 3.92 -2 PR = Possible Response; MU = M ost Unsafe; MS = Most Safe; RFC = Response Frequency Count; Per Cent TR = Percentage of Total Response; RPV = Response Point Value. 164 TABLE P TABULATION OF SAS SCORES AERONAUTICS—AIRFRAME Number Group I Group II Group III Total 1AA -20 20 18 18 2AA -20 16 14 10 3AA -8 10 8 10 4AA -18 16 4 2 5AA 2 8 24 34 6AA -8 12 16 20 7AA -10 10 8 8 8AA 2 18 4 24 9AA -14 18 2 6 10AA -16 14 6 4 11AA 6 12 16 34 12AA -16 18 10 12 13AA -10 10 4 4 14AA -18 12 16 10 15AA -22 10 8 -4 16AA -8 8 14 14 17 A A 0 -2 12 10 18AA -8 14 4 10 19 AA -4 18 18 32 20AA -8 4 6 2 21AA -16 8 10 2 22AA 10 12 12 34 23AA 4 12 6 22 24AA 0 4 10 14 25AA -12 16 4 8 26AA 4 18 10 32 27 AA 10 16 14 40 28AA -2 16 8 22 29 AA -18 12 4 -2 30AA 4 14 14 32 31AA 0 2 6 8 32AA -14 16 14 16 Mean Score -7.13 12.25 10.13 15.25 Standard Deviation 9.30 10. 61 11.84 16.80 165 TABLE Q TABULATION OF SAS SCORES AERONAUTICS—FOWERPLANT Number Group 1 Group II Group III Total 33AP -2 20 10 28 34AP 6 20 -6 20 35AP -16 10 14 8 36AP -4 8 4 8 37 AP -20 22 14 16 38AP -14 4 -6 -16 39AP -14 8 22 16 40AP -12 6 6 0 41AP 0 22 6 28 42AP -8 8 12 12 43AP 2 16 16 34 44AP -14 8 10 4 45AP -22 22 6 6 46AP -14 22 24 32 47AP -10 6 14 10 48AP -6 18 10 22 49AP -14 6 16 8 50AP -20 14 14 8 51AP 14 10 0 24 52AP -2 20 16 34 53AP -16 12 2 -2 54AP -2 8 6 12 55AP -10 14 -2 2 56AP -26 8 16 -2 57 AP -22 16 20 14 Mean Score -9.84 13.12 9.76 13.04 Standard Deviation 9.43 11.20 13.72 18.43 166 TABLE R TABULATION OF SAS SCORES ARCHITECTURAL DRAFTING Number Group I Group II Group III Total 58AD 2 14 8 24 59AD 14 10 4 28 60AD -8 10 -2 0 61AD -20 4 -6 -22 62AD 2 24 14 40 63 AD -16 4 8 -4 64AD -16 14 4 2 65AD -8 4 22 18 66AD -24 10 12 -2 67AD -14 12 2 0 68AD -16 6 8 -2 69 AD 4 18 6 28 70AD -6 -2 6 -2 71 AD 4 0 6 10 7 2 AD -6 6 6 6 73AD 34 0 10 34 74AD -10 24 4 18 75AD 4 26 8 38 76AD -14 10 6 2 77AD 10 12 14 36 78AD -24 10 16 2 79AD -10 10 0 0 80 AD 10 6 8 24 81AD -16 18 4 6 82AD -22 16 -4 -10 Mean Score -5. 84 10. 64 6. 56 11.36 Standard Deviation 13.58 15.43 16.58 23.74 167 TABLE S TABULATION OF SAS SCORES AUTO BODY Number Group I Group II Group III Total 83AB -12 8 2 -2 84AB -8 6 -2 -4 85AB 10 -2 0 8 86AB 8 0 0 8 87 A B -10 12 0 2 88AB -6 0 -4 -10 89AB 0 10 10 20 90AB -22 14 16 8 Mean Score -5.00 6.00 2.75 3.75 Standard Deviation 9.95 11.45 13.07 15.70 168 Total 6 -8 -2 -10 10 2 8 36 22 14 6 60 12 8 6 16 24 -2 -18 -12 58 38 12 16 16 38 -6 8 24 -2 60 18 2 -18 -24 TABLE T TABULATION OF SAS SCORES AUTO MECHANICS Group I Group II Group III 0 8 -2 -22 4 10 -30 16 12 -36 14 12 -12 12 10 -20 8 14 -12 16 4 4 18 14 8 6 8 -8 10 12 -14 18 2 18 20 22 -6 10 8 -22 22 8 -26 16 16 4 8 4 -2 16 10 -10 -4 12 -22 -8 12 -14 2 0 40 16 2 12 18 8 -18 16 14 -14 16 14 -12 20 8 -6 26 18 -18 4 8 -12 8 12 -4 16 12 -22 4 16 36 20 4 -2 8 12 -26 12 16 -28 4 6 -28 10 -6 TABLE T--C ontinued 169 Number Group I Group II Group III Total 126AM -18 12 6 0 127 AM -12 10 4 2 128AM -18 12 12 6 129AM 2 22 24 48 Mean Score -9.49 11.95 9.69 12.15 Standard Deviation 16.23 17.72 18.73 27.83 TABLE U TABULATION OF SAS SCORES CARPENTRY Number Group I Group II Group III Total 130C 22 10 14 46 131C -2 0 14 12 132C 26 10 28 64 133C -4 14 26 36 134C 0 14 14 28 136C 10 6 8 24 137C 8 22 26 56 138C -10 18 20 28 139C -14 16 -6 -4 140C -18 20 18 20 141C 2 10 4 16 142C -20 18 24 22 143C -26 16 16 6 144C -12 22 10 20 Mean Score -2.71 14.00 15.43 26.71 Standard Deviation 14.84 16.03 18.44 25.76 170 TABLE V TABULATION OF SAS SCORES DIESEL Number Group I Group II Group III Total 135D 8 18 14 40 14 5D -6 2 6 2 146D -8 4 0 -4 147D -10 6 16 12 148D -24 18 8 2 149D 6 16 4 26 150D -14 14 16 16 151D 10 2 0 12 152D -34 14 10 -10 153D 0 12 10 22 154D 10 2 14 26 155D -6 14 12 20 156D 6 8 8 22 157D -6 8 12 14 158D 0 18 20 38 159D 6 -2 22 26 160D 12 8 14 34 161D -12 20 16 24 162D -6 8 -2 0 163D 2 20 18 40 164D -2 24 4 26 165D -26 12 16 2 Mean Score -4.27 11.18 10. 82 17.73 Standard Deviation 12.02 13.87 15.32 20.85 171 TABLE W TABULATION OF SAS SCORES ELECTRONICS Number Group I Group 1 1 Group III Total 166E -4 4 20 20 167 E -6 14 12 20 168E -20 14 18 12 169E -18 6 6 -6 170E -8 10 6 8 171E -10 8 4 2 172E 12 8 6 26 173E -6 8 18 20 174E -2 6 8 12 175E -4 2 6 4 176E -24 6 2 -16 177 E -4 8 4 8 178E -14 8 22 16 179E 10 6 6 22 180E -6 14 12 20 181E -12 22 28 38 182E -26 20 6 0 183E -4 10 18 24 184E -14 14 12 12 185E 0 -4 16 12 186E -10 0 6 -4 187E -20 14 24 18 188E -14 2 16 4 189E 16 -2 10 24 190E 18 20 26 64 191E -20 14 28 22 192E -14 8 10 4 193E -16 10 4 -2 194E 2 14 4 20 195E -4 -10 6 -8 196E -16 14 16 14 197 E -18 2 22 6 198E 2 6 14 22 199E -12 6 18 12 200E 0 22 -2 20 TABLE W --Continued 172 Number Group I Group 1 1 Group III Total 201E -10 12 0 2 202E 4 8 12 24 203E -10 12 6 8 204 E 8 4 20 32 205E 2 10 16 28 206E 16 24 10 50 207 E 2 4 8 14 208E 8 12 10 30 209E -8 14 16 22 210E -4 22 26 44 211E -8 10 18 20 212E 4 10 16 30 213E 4 18 18 40 214E -14 16 18 20 215E -2 -4 6 0 216E 20 10 12 42 217E -6 24 16 34 218E 8 8 -2 14 219E 8 10 18 36 220E -18 10 20 12 221E -12 18 14 20 222E -26 8 24 6 223E 24 16 18 58 224 E -10 10 6 6 225E 6 10 16 32 Mean Score -4.67 10.00 12.90 18. 23 Standard Deviation 11.60 13.49 15.41 21.91 173 TABLE X TABULATION OF SAS SCORES SVIB SAMPLE Number Group I Group II Group III Total 226SV 4 8 4 16 227SV -12 20 10 18 228SV 22 8 -4 26 229SV -8 22 18 32 230SV 4 8 6 18 231SV 2 20 10 32 232SV -4 14 6 16 233SV -2 0 10 8 234SV -24 22 18 16 235SV -6 12 10 16 236SV 2 12 10 24 237SV 26 12 6 44 238SV -4 12 8 16 239SV -8 12 12 16 240SV -2 14 4 16 241SV 16 8 4 28 242SV -4 6 20 22 243SV -8 8 10 10 244SV -10 6 8 4 245SV -12 12 20 20 246SV -4 14 16 26 247SV -2 -2 10 6 248SV -18 14 -4 -8 249SV 6 2 6 14 250SV 16 10 14 40 251SV -8 6 6 4 Mean Score Standard Deviation -1.46 10.77 9.15 18.46 11.35 12. 84 14.19 18.07 174 TABLE Y TABULATION OF SAS SCORES ELECTROMECHANICAL Number Group I Group II Group III Total 256EM -2 0 22 20 257 EM -8 20 6 18 258EM -16 2 14 0 259EM 6 16 18 40 260EM -20 4 14 -2 261 EM -6 20 6 20 262EM -24 2 18 -4 263EM -14 12 -8 -10 264 EM -16 14 6 4 265EM 8 28 10 46 266EM -26 10 20 4 267 EM 4 6 14 24 268 EM -6 8 18 20 269 EM -6 16 18 28 270EM 2 14 14 30 271 EM 18 12 8 38 272 EM -6 8 14 16 27 3EM 6 8 18 32 274EM 4 10 14 28 Mean Score -5.37 11.05 12. 84 18. 53 Standard Deviation 11.52 13.43 15.06 21.70 175 TABLE Z TABULATION OF SAS SCORES INDUSTRIAL ELECTRICITY Number Group I Group II Group III Total 2751E 0 10 8 18 2761E 2 10 16 28 277IE -22 20 14 12 278IE -6 18 2 14 279IE 0 20 14 34 280IE -22 2 14 -6 281IE 4 6 8 18 282IE 0 -2 8 6 283IE 2 14 18 34 284IE 14 16 14 44 285IE -6 20 10 24 286IE -18 18 14 14 287IE -14 12 16 14 288IE 8 12 2 22 289IE -22 16 4 -2 290IE -18 12 16 10 29IIE 0 10 10 20 292IE -24 16 18 10 293IE -6 16 22 32 294IE 0 16 16 32 295IE -2 12 16 26 296IE 10 12 14 36 Mean Score -5.45 13.00 12.45 20.00 Standard Deviation 11.11 12.00 13.44 18.27 176 TABLE AA TABULATION OF SAS SCORES MACHINE TOOL Number Group 1 Group II Group III Total 297MT 0 10 14 24 298MT -8 10 8 10 299MT -8 14 4 10 300MT -4 12 4 12 301MT -12 10 24 22 302MT -10 12 0 2 303MT -24 10 8 -6 304MT -8 14 16 22 305MT -28 4 6 -18 306MT -14 4 18 8 307MT 26 14 12 52 308MT 0 4 4 8 309MT -12 14 -4 -2 310MT -6 10 16 20 311MT -16 16 24 24 Mean Score -8.27 10. 53 10. 27 12. 53 Standard Deviation 11.82 12.40 14.79 21.59 177 TABLE B B TABULATION OF SAS SCORES MILL CABINET Number Group 1 Group 1 1 Group III Total 312MC -30 20 20 10 313MC -16 18 12 14 314MC 4 10 -4 10 315MC -14 6 10 2 316MC -20 12 14 6 317MC -22 14 18 10 318MC -12 18 16 22 319MC 4 10 14 28 Mean Score -13.25 13. 50 12.50 12.75 Standard Deviation 11.22 12.11 13.94 16.04 178 TABLE CC TABULATION OF SAS SCORES REFRIGERATION Number Group I Group 1 1 Group III Total 255R 4 20 14 38 320R -6 18 20 32 321R -18 16 8 6 322R -6 22 8 24 323R -10 10 8 8 324 R -4 10 20 26 325R -4 16 4 16 326R 12 10 12 34 327R -18 10 18 10 328R 4 14 -4 14 329R -22 14 16 8 330R -18 8 12 2 331R -6 10 8 12 332R -14 2 -2 -14 333R -6 14 20 28 334 R -16 6 10 0 335R 22 14 22 58 336R -20 -8 -4 -32 337R -6 8 4 6 338R -8 8 8 8 339R 6 8 12 26 340R -14 16 10 12 341R -8 10 10 12 34 2R 16 16 4 36 34 3R 22 16 12 50 344 R 14 16 6 36 34 5R 8 6 12 26 34 6R -12 10 4 2 347 R 0 14 4 18 34 8R 10 20 14 44 349R -16 12 4 0 350R 20 16 2 38 351R -10 6 10 6 352R -8 8 18 18 353R -20 18 2 0 TABLE CC--Continued 179 Number Group I Group 1 1 Group 1 1 1 Total 354R 8 12 22 42 355R 0 8 2 10 356R 14 16 2 32 357R 4 12 14 30 358R 0 14 4 18 359R 0 14 12 26 Mean Score -2.59 11.95 9. 32 18.68 Standard Deviation 12.20 13. 34 14.96 22.99 TABLE DD TABULATION OF SAS SCORES SHEET METAL Number Group I Group II Group 1 1 1 Total 253SM -2 4 20 22 360SM -26 8 8 -10 361SM 2 20 24 46 362SM -4 14 4 14 363SM 8 -2 0 6 364SM -12 10 8 6 Mean Score -5.67 9.00 10.67 14.00 Standard Deviation 10.92 12.97 15. 53 23.23 180 TABLE EE TABULATION OF SAS SCORES TOOL DESIGN Number Group I Group II Group III Total 365TD 6 26 12 44 366TD 4 14 6 24 367 TD -12 8 2 -2 368TD 8 8 10 26 369TD -6 16 8 18 370TD -10 6 0 -4 371TD -8 10 12 14 372TD -14 12 24 22 373TD -10 12 18 20 374TD 10 10 16 36 375TD 2 16 14 32 376TD -10 22 24 36 377 TD 2 12 10 24 378TD -12 0 2 -10 379TD -4 18 12 26 380TD -12 0 6 -6 381TD -14 -2 20 4 382TD 6 4 10 20 383TD -6 4 12 10 384TD -14 12 12 10 385TD 14 10 10 34 386TD 2 22 4 28 387TD -6 2 18 14 Mean Score -3.65 10. 52 11.39 18. 26 Standard Deviation 8.50 11.17 12.88 19.24 181 TABLE FF TABULATION OF SAS SCORES WELDING Number Group I Group II Group III Total 252W 22 6 2 30 388W 30 4 12 46 389W -4 12 8 16 390W -12 12 -2 -2 391W -4 12 4 12 392W 20 14 10 44 393W 8 -12 4 0 394W 2 4 8 14 395W -2 10 8 16 396W -8 18 0 10 397W -16 14 10 8 39 8W 4 14 12 30 399W -8 12 8 12 400W -6 18 6 18 401W -16 12 12 8 402W 10 10 6 26 403W -6 8 12 14 404W 16 6 8 30 405W -30 0 10 -20 406W 6 -6 8 8 407W 6 20 16 42 408W -22 18 4 0 409W -12 12 12 12 410W 4 6 14 24 Mean Score -0.75 9.33 8.00 16. 58 Standard Deviation 14.02 15. 86 16.44 22.37 182 TABLE GG TABULATION OF SAS SCORES STUDENT ACCIDENT GROUP Number Group I Group II Group III Total 411AS 2 12 10 24 412AS -6 8 2 4 413AS -8 8 12 12 414 AS -16 10 18 12 415AS -16 10 20 14 416AS -2 20 8 26 417AS -12 22 4 14 418AS -2 16 -12 2 419AS -20 22 14 16 438AS 12 14 10 36 458AS 16 16 14 46 4 59AS -12 6 18 12 Mean Score -5. 33 13.67 9.83 18.17 Standard Deviation 10.69 11.95 14.62 19.08 183 TABLE HH TABULATION OF SAS SCORES ACCIDENT INDUSTRIAL GROUP Number Group I Group II Group III Total 426AI -18 4 0 -14 432AI 22 10 4 36 433AI -10 14 10 14 434AI -22 18 -8 -12 435AI 10 18 8 36 439A1 8 20 16 44 440AI -10 8 -2 -4 442AI -8 12 18 22 448A1 -2 8 -6 0 450AI 24 10 10 44 451AI -16 14 2 0 452AI -2 10 2 10 453AI -2 8 8 14 454AI -26 12 12 -2 455AI -18 4 10 -4 456AI 26 18 12 56 457AI -8 0 0 -8 429AI -10 6 22 18 430AI -12 16 22 26 Mean Score -3.89 11.05 7.37 14.53 Standard Deviation 14.97 15.91 18.02 27.31 184 TABLE II TABULATION OF SAS SCORES NON-ACCIDENT INDUSTRIAL GROUP Number Group I Group II Group III Total 254SI 14 20 16 50 420S1 4 -4 -6 -6 421SI -16 6 18 8 422SI 2 10 16 28 423SI 2 -12 16 6 424SI 0 12 26 38 425SI 4 12 22 38 427SI 10 16 16 42 428SI 10 12 0 22 431SI 20 2 16 38 436SI 30 10 8 48 437SI -26 14 10 -2 441SI -12 10 22 20 443SI 32 14 14 60 444SI 28 14 2 44 445SI 8 10 6 24 446SI 26 6 0 32 447SI 20 8 14 42 449SI 32 14 8 54 Mean Score 9.67 8. 56 11.56 29.78 Standard Deviation 16.51 17.89 19.78 26.99 BIBLIOGRAPHY 185 BIBLIOGRAPHY Books 1. 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"Vocational Interests and Accident- Proneness." Journal of Applied Psychology, Vol. 51, 1967, pp. 223-72^ 39. ________, and Brewer, Blayne. "Neuropsychiatric Patients, Accident-Proneness, and Interest Patterns. " The Journal of Psychology, Vol. 63, 1966, pp. 287-290. 40. _____ ; Sturman, John; Longhofer, Paul; and Castor, Marvel. "Psychological Factors in High School Accidents. " The Personnel and Guidance Journal, Vol. 45, 1966, pp. 140-143. 41. ________ , and Worley, Bert H. "Interest Patterns, Accidents, Disability. " Journal of Clinical Psychology, Vol. 22, 1966, pp. 105-107^ 42. ________ . "Interest Scores and Accidents among Students. ” TEe Journal of College Student Personnel, Vol. 8, 1967, pp. 121-123. 190 43. LeShan, Lawrence L ., and Brame, Jim B . "A Note on Techniques in the Investigation of Accident-Prone Behavior." Journal of Applied Psychology, Vol. 37, 1953, pp. 79-81. 44. , and LeShan, Eda. "Is Your Child Accident-Prone?" 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"Reported Driving Speeds and Previous Accidents." Journal of Applied Psychology, Vol. 41, 1957, pp. 293^29^ 60. Stiles, Grace. "The Unmet Needs of Accident-Prone Children." Safety Education, Vol. 37, 1958, p. 19. 61. Teel, KennethS., and DuBois, Philip H. "Psychological Research on Accidents: Some Methodological Considera tions. " Journal of Applied Psychology, Vol. 38, 1954, pp. 397-400. 62. Tiffin, Joseph; Parker, B. T .; and Habersat, R. W. "Visual Performance and Accident Frequency. ” Journal of Applied Psychology, Vol. 33, 1949, pp. 499-502. 63. VanZelst, R. H. "The Effect of Age and Experience upon Accident Rate. " Journal of Applied Psychology, Vol. 38, 1954, pp. 313-317. 64. Webb, Wilse B., and Jones, Edward R. "Some Relations between Two Statistical Approaches to Accident- Proneness. ” Psychological Bulletin, Vol. 50, 1953, pp. 133-139. 192 65. Whitlock, John B., and Crannell, Clarke W. "An Analysis of Certain Factors in Serious Accidents in a Large Steel Plant. 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"An Investigation of Industrial Arts Teacher Liability and the Preparation of a Safety Guide for Laboratory Use. " Unpublished m aster's project, University of Southern, California, 1960. 72. Vilardo, Frank J. "Historical Development of the Concept of Accident-Proneness. " Unpublished paper, National Safety Council, Chicago, Illinois, n. d.

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Creator Steiner, Arthur Frederick (author)

Core Title The Identification Of Accident-Proneness In Junior College Vocational Students And Industrial Employees

Contributor Digitized by ProQuest (provenance)

Degree Doctor of Education

Degree Program Education

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag education, industrial,OAI-PMH Harvest

Language English

Advisor Pullias, Earl Vivon (committee chair), Olson, Myron S. (committee member), Wilbur, Leslie (committee member)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c18-431134

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