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Articulated thoughts regarding cognitions toward older adults

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Articulated thoughts regarding cognitions toward older adults

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ARTICULATED THOUGHTS REGARDING COGNITIONS
TOWARD OLDER ADULTS
Copyright 2001
by
Wendy Wing-Han Fung
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF ARTS
(PSYCHOLOGY)
August 2001
Wendy Wing-Han Fung
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UNIVERSITY OF SOUTHERN CALIFORNIA
The G raduate School
U niversity Park
LOS ANGELES, CALIFORNIA 90089'1695
This thesis, w ritten b y
UZn7>Y folrtCi'/Mrf forlC __________
Under the direction o f h£.£. Thesis
Com m ittee, and approved b y a ll its members,
has been presen ted to and accepted b y The
Graduate School, in p a rtia l fulfillm ent o f
requirem ents fo r th e degree o f
Master o f Arts
Dean o f Graduate Studies
D ate August 7 , 2001_______
THESI S COMMITTEE
r .
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ii
Acknowledgments
The author of this study would like to sincerely thank Drs. Gerald C.
Davison, John Horn, and Margaret Gatz for their continuous support, advice, and
help throughout this project. I would also like to thank the research assistants who
helped with many aspects o f the study: Yezzennya Castro, Stephanie Cory, Julia
Mack, Elissa Jessica Shane, and Janet Whang. Finally, I would like to extend my
gratitude to Jennifer Best, Nadine Recker, M.A., Krista Barbour, M.A., and Archana
Jajodia for giving me wonderful advice and emotional support.
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Table of Contents
Acknowledgments............................................................................................................ii
List of Tables................................................................................................................... iv
List of Figures...................................................................................................................v
Abstract............................................................................................................................ vi
Introduction....................................................................................................................... I
Method.............................................................................................................................14
Results............................................................................................................................. 23
Discussion....................................................................................................................... 58
References.......................................................................................................................67
Appendix A..................................................................................................................... 73
Appendix B..................................................................................................................... 79
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iv
List of Tables
Table Page
1 Illustration of Interrater Reliability Data..................................................... 23-24
2 Initial Interrater Reliability Coefficients for All
Coding Dimensions............................................................................................25
3 Midpoint Interrater Reliability Coefficients
for All Coding Dimensions............................................................................... 26
4 Internal Consistency o f Coding Categories...................................................... 27
5 Means and Standard Deviations of Coding Categories................................... 29
6 Correlations between Coding Categories......................................................... 30
7 Factors computed for the 25 items in FAQ according to
the hypothesized 3 factors.................................................................................34
8 Correlations of the 3 Factors in FAQ................................................................35
9 Unrotated Principal Component Factor Matrix for KAE
for the first factor................................................................................................36
10 Correlation Matrix of the 17 items on the KAE scale.....................................37
1 1 Correlation Matrix o f KAE and FAQ items................................................38-41
12 Correlation Matrix o f the 16 items on the FP scale.........................................43
13 Table of Scores for Overall Effects.............................................................45-46
14 Table of Scores for Attitudinal Biases........................................................ 47-48
15 Table of Scores for Filial Piety......................................................................... 50
16 Mean Filial Piety Scores for Ethnic Groups.................................................... 52
17 Mean Scores for Participants who have or have not
lived/worked with older adults......................................................................... 53
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List of Figures
Figure Page
1 Structural Model of FAQ with 3 Factors........................................................ 33
2 Encountering OA versus Encountering YA conditions................................. 46
3 High/Low Attitudinal Biases toward OA........................................................48
4 High versus Low Filial Piety........................................................................... 51
5 Mean Filial Piety Scores for Ethnic groups.................................................... 52
6 Mean Anger Intensity for Encountering OA condition only......................... 54
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vi
Abstract
In a between-subject design, 102 college students were exposed to audiotaped
simulated scenarios encountering either older adults or younger adults. Participants’
articulated thoughts were content-analyzed using 11 categories. Participants were
more likely to identify the negative attributes and age of older adults than younger
adults. However, participants were more likely to give excuses to older adults and
more likely to be annoyed by younger adults. Further, participants who had more
ageist biases were more likely to be annoyed with, and gave fewer excuses, to older
adults. Those who were more respectful toward older adults were less verbally
aggressive toward them. Finally, those who have lived or worked with older adults in
real life expressed more anger toward them. Future studies should investigate how
the context of interactions as well as the type, length, and quality of previous
experiences affect the way young people think about older adults.
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Introduction
It has been projected by the U.S. Bureau of the Census (2000) that older
adults continue to be one of the fastest growing demographic groups in United
States. Today, approximately 12.4% of the U.S. population is composed of persons
who are 65 years or older. By 2030, this group is projected to increase to more than
20.2% of the population (U.S. Census Bureau, 2000). As a result, more and more
younger adults will encounter and work closely with older adults in many settings,
such as in retail and health service provision, in the coming decades. Due to this
continuous change in population demographics, there is a pressing need for younger
adults to be made aware of, and educated about, how best to serve this population by
being age-sensitive and age-competent.
General attitudes toward older adults
In America, attitudes toward older adults have generally been thought to be
negative (e.g. Allen, 1981; Hummert, 1990; Kite, Deaux, & Miele, 1991; Kite &
Johnson, 1998). The commonly accepted stereotypes of older adults include a
marked deterioration of intellectual abilities (Cornelius & Caspi, 1986, Ryan, 1992),
unattractiveness (Janelli, 1986), and diminished ability to participate in physical
activities (Ostrow, Keener, & Perry, 1987). Jensen and Oakley (1982-83)
summarized stereotypes of older adults and concluded that, “American ageist
attitudes portray older people as, and expect them to be, impotent, asexual, senile,
confused, forgetful, frail, useless, unproductive, helpless, childlike, unattractive,
smelly, unhappy, inactive, unemployable, uncreative, unable, perverted, unathletic,
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2
stooped, and slow.” (p. 20). This dated summary may not necessarily reflect the
current ways of thinking, but it is conceivable that some of these stereotypes still
exist in our society today.
A number of studies have found attitudes toward older adults to be neutral
(Knox, Gekoski, & Johnson, 1986), both positive and negative (Braithwaite, 1986),
or even slightly positive (see Crockett & Hummer, 1987; Kite & Johnson, 1988;
Kogan, 1979, for reviews). However, if the above-mentioned negative attitudes hold
true for even some young adults, they can translate to actual behaviors and lead to
ageism (Butler, 1969) that can foster discrimination toward older adults (Butler,
1980). Given the lack of consensus about whether ageism exists in our society, it is
necessary to understand how individual differences can correlate with attitudes
toward the elderly. Three factors that have been suggested to influence attitudes
toward older adults are filial piety, knowledge of aging, and experience with older
adults.
Ethnicity and the concept o f Filial Piety toward older adults
Asian cultures are often characterized in America as having more positive
attitudes toward older adults and aging than other ethnic groups (Tobin, 1987). This
stereotype is grounded in the Confucian ideals of filial piety (Cheung, 1989; Ho,
1994; Sung, 1995). Increased age is associated with increased respect and wisdom,
which carries tremendous social power in certain Asian cultures, such as Japan
(Koyano, 1989), China (Levy & Langer, 1994), and Korea (Park & Kim, 1992;
Sung, 1995). The urbanization hypothesis of aging, however, suggests that the
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traditional values of filial piety have been eroded by industrialization,
individualization, and liberalism since World War II (Bengtson & Smith, 1968).
Alternatively, the “erosion” of filial piety found in some parts of Asia through cross-
cultural research (see Amoff, Leon, & Lorge, 1964; Bengtson & Smith, 1968;
Bennett & Eckman, 1973; McTavish, 1971) can be attributed to the explanation that
“public avowal of filial piety belie[s] private ascriptions to a negative view of aging
and older adults” (Harwood et al., 1996, p. 308). One study showed that there was
little evidence to support the notion that contemporary Asian cultures (Hong Kong,
Korea, Philippines) evaluate their older adults in a more positive way compared with
Western cultures (Australia, New Zealand, USA) (Harwood et al., 1996). On the
other hand, studies in Australia and in the U.S. have found positive evaluations of
older adults, relative to younger adults, on traits such as wisdom and generosity
(Braithwaite, Lynd-Stevenson, & Pigram, 1993; Branco & Williamson, 1982).
Research seems to be inconclusive as to whether being Asian or coming from an
Asian culture is associated with more positive attitudes toward older adults.
Perhaps the problem with this line of research is that it is often assumed that
Asian ethnicity and values are one and the same. Research on ethnicity often does
not examine the strength of Asian (Confucian) values, and vice versa. It is possible
that a person who self-identifies as Asian or Asian American may not carry Asian
values, so an examination of his or her attitudes toward older adults is confounded.
On the other hand, it can also be conceived that a non-Asian person may carry these
“Asian” values of respect, duty, and reverence toward older adults.
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Knowledge o f aging and previous experiences with the elderly
In addition to ethnicity and filial piety, a small number of previous studies
have found that greater knowledge of older adults and the aging process is associated
with a more positive attitude toward that population (e.g. Block, 1982; Holtzman,
Toewe, & Beck, 1979; Warren, Painter, & Rudisiil, 1983). These studies, however,
were mostly based on responses from medical or mental health students and
personnel in classroom settings. Little research has been conducted on what non-
paraprofessional young adults know about aging and how this knowledge (or lack
thereof) affects the way they treat the elderly in situations that simulate real life
experiences.
Another variable, previous experience with older adults, has also been
posited as important in understanding attitudes toward the elderly (Mosher-Ashley &
Ball, 1999). Meyer, Hassanein, and Bahr (1980) reported that those who have
worked with older adults tend to have slightly less negative attitudes toward this
population than those who have not engaged in such activities. However, Riddick
(1985) failed to find a significant difference in the attitudes held toward older adults
between students who have had a lot of contact and those who had little. On the other
hand, Shoemaker and Rowland (1993) found that the students who held somewhat
positive attitudes toward older adults at pretest were those who had prior substantial
positive contact with older adults (over 90% rated contacts favorably). This body of
research is mostly based on self-report and is therefore prone to self-presentation
biases. Perhaps, an “on-line” assessment task (i.e. asking participants to simulate
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interaction, rather than answer close-ended questions about how they think they
would interact with the elderly) is needed in order to understand how previous
experience is associated with attitudes toward older adults in situations that simulate
real life.
The need o f a different method o f assessment
As with the example above, a serious issue with the available literature
assessing attitudes toward older adults is that the vast majority of studies conducted
have relied on self-report questionnaires (e.g. Facts of Aging Quiz (Palmore, 1977);
Attitudes Toward Old People scale (Kogan, 1961)). While these studies can provide
useful information about aging stereotypes, the self-report method can elicit subject
response apprehensions and impression management biases. In addition,
endorsement/forced-choice methods such as self-report questionnaires (i.e.
participants are asked to select one of several possible close-ended responses) may
not be able to tap into what participants would do in real life situations when they
encounter older adults (Chamberlain & Haaga, 1999) because they often include
very few possible responses. It seems necessary, therefore, to utilize an open-ended
method that can complement self-report measures by eliciting the cognitions of
younger adults in an experimentally controlled, yet on-line and non-retrospective
way, which approximates real-life situations when they encounter older adults.
The Articulated Thoughts in Simulated Situations (ATSS) Paradigm
The Articulated Thoughts in Simulated Situations (ATSS) Paradigm
(Davison, Robins & Johnson, 1983) is a way of getting at moment-to-moment
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cognitions and emotions of an interpersonal nature under experimenter-controlled
circumstances. Research on ATSS suggests that one can detect complex cognitions
such as hostility, aggression, defensiveness and guilt as they occur in real-life
situations with a minimum of self-censoring and response apprehension.
ATSS was created by Davison twenty-three years ago and has been used by
him and a growing number of researchers to study adults and children under a wide
range of emotional states (e.g. depression, anxiety, aggression) and complex
situations (e.g. criticism, challenge, threat, interpersonal violence) (see Davison,
Navarre, & Vogel, 1995; and Davison, Vogel, & Coffman, 1997 for review). ATSS
is a think-aloud approach that has a subject participate in an audiotaped role-play
situation, such as being the object of someone’s criticism. At predetermined points in
the taped scenario, there is a tone and a pause, usually for 30 seconds, during which
the subject is instructed to verbalize whatever is on his or her mind in reaction to the
brief segment that has just been described on the stimulus tape. After this response
interval, a tone sounds, and the scenario continues for another 15 to 20 seconds, after
which there is another pause for the subject to express what is going through his or
her mind. The participant’s tape-recorded statements are later transcribed for content
analysis. The nature of the content analytic categories, as well as the nature of the
stimulus scenario that gives rise to the data, are dependent on the purpose of the
particular experiment. Two recent reviews of studies conducted using the ATSS
paradigm have confirmed the utility of this paradigm for eliciting people’s
phenomenological experiences in a wide range of emotionally important
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circumstances (Davison et al., 1995; Davison et al., 1997). These reviews also
demonstrate the reliability and validity (face, concurrent, predictive, and construct)
of the ATSS approach with many different subject populations, such as men with
borderline hypertension, college students with social anxiety, martially violent men,
mothers and sons in marital/family conflicts, and ex-smokers (e.g. Davison, Robins,
& Johnson, 1983; Davison & Zighelboim, 1987; Haaga, 1989; Bates, Campbell, &
Burgess, 1990; Kashima & Davison, 1990; Davison, Haaga, Rosenbaum, Dolezal, &
Weinstein, 1991; O ’Brien, Margolin, John, & Krueger, 1991; Davison, Williams,
Nezami, Bice, & DeQuattro, 1991; Warren & Smith, 1997; Eckhardt, Barbour, &
Davison, 1998).
There are many advantages of the ATSS approach vis-a-vis other cognitive
assessment approaches such as paper-and-pencil questionnaires and checklists: a)
unstructured and open-ended response format; b) on-line, rather than retrospective
assessment; c) situational specificity (not often found in questionnaires); and d)
flexibility and versatility, such that the method can be adapted to study virtually any
phenomenological cognition. Given the advantages and strengths of this paradigm, it
seems ideal to use the ATSS procedure to complement and contrast with self-
reported measures to study young adults’ attitudes toward the elderly. That is, the
ATSS method can provide a different kind of data that may or may not reflect the
same answers endorsed on self-report questionnaires.
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The Present Study
The present study investigates college students’ cognitions about older adults.
In particular, it examines the thoughts people have while they encounter either
younger or older adults in several simulated everyday situations. The use of the
ATSS paradigm examines not only the cognitions of younger adults toward older
adults without limiting their responses, but is also able to elicit articulated references
to specific behavioral responses toward older adults in an experimentally-controlled
environment. Participants’ verbalized thoughts in response to the ATSS audiotaped
scenarios were first transcribed, then content-analyzed according to the dependent
variables of interest, which include the specific dimensions below.
Specific dimensions assessed by ATSS
Due to previous research findings of both negative and positive attitudes
toward older adults, it is therefore of interest to investigate both sets of attitudes in
the present study. The coding categories were established post hoc by informal
content analysis of the ATSS data collected (types of responses were determined and
tallied), as well as based on the hypotheses of this study and on previous ATSS
research (e.g. Eckhardt et al., 1998; Recker, 2001). The negative dimensions
assessed include annoyance, verbal aggression, physical aggression,
sadness/pity/guilt, identification of negative attributes, identification of age, and
anger intensity. Positive dimensions assessed include verbal
respect/compassion/empathy, physical respect/ compassion/empathy, identification
of positive attributes, and giving of non-personal excuse.
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Annoyance. This dimension assesses the frequency of the participants’
annoyance directed at the simulated persons depicted in the audiotaped scenarios on
the ATSS procedure. The dimension of annoyance is viewed as a milder form of
anger in the sense that it relates more to feelings of irritability rather than feelings of
hostility.
Verbal Aggression. This coding dimension assesses the frequency of the
participants’ verbal insults, name-calling, or non-action-related aggression. This
dimension can be seen as synonymous with anger but without the explicit intention
to harm. It is posited that this dimension is a more severe form of annoyance.
Physical Aggression. This dimension assesses the frequency of the
participants’ action-related aggressive cognitions and intentions to physically harm
the simulated persons in the scenarios. This dimension can be seen as a more severe
form of anger than verbal aggression since the verbalizations can provide possible
insights into the actual intentions to harm.
Sadness/Pitv/Guilt. This dimension assesses the frequency of the participants’
verbalizations concerning how sorry they feel toward the persons on the tape. These
utterances exemplify feelings of sadness, pity, or guilt toward the persons on the
tape.
Identification of Negative Attributes. This dimension assesses the frequency
of the participants’ use of pejorative statements in association with the simulated
person’s age. These cognitions, when directed at an older adult on the tapes, can be
seen as overgeneralizations that exemplify ageism.
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Identification of Age. This dimension assesses the frequency of the
participants’ identification of the simulated persons’ age or age group. It is
hypothesized that participants are more likely to mention the age of the persons when
they encounter older adults as opposed to when they encounter younger adults in
parallel scenarios. It is presumed that a high frequency of responses on this
dimension is an indirect indication of ageism because the target persons differ from
the participant. That is, participant’s age identifications would indicate
generalizations based on one aspect of the targets, namely their age.
Anger Intensity. This final negative dimension is rated based on the tone of
voice of the participants as well as the actual words used. It is an intensity rating that
puts annoyance, verbal aggression, and physical aggression on a continuum of anger.
The tone of voice and the amount of cursing also factor into this dimension.
Verbal Respect/Compassion/Empathv. The first of the 4 positive coding
dimensions refers to the frequency of the participants’ use of statements indicating
that they care about, and feel respect, compassion, or empathy for, the persons on the
tapes. This dimension only includes those compassionate verbalizations that do not
indicate the intention to help.
Physical Respect/Compassion/Empathv. This dimension assesses the
frequency of the participants’ statements indicating what they would actually do to
show respect or compassion toward the persons on the tapes. This dimension can be
seen as a higher level of positive cognition than verbal respect/compassion/empathy.
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Identification of Positive Attributes. This dimension assesses the frequency
of the participants’ statements identifying positive attributes of the simulated
persons’ age group. This dimension can be seen as the opposite of ageism if
verbalized toward an older adult.
Giving of Non-Personal Excuse. This last dimension is the opposite of
fundamental attributional error (Ross, 1997), i.e. it assesses the frequency that the
participants articulate statements referring to situational (non-personal) variables as
an explanation for the behavior of the persons on the tapes. This dimension is
considered positive because it negates the idea that the persons on the tapes are
intrinsically bad.
In addition to the think-aloud procedure, the present study examines the
participants’ individual variables such as ethnicity, previous experience with older
adults, attitudinal biases, knowledge about aging and the elderly, and the concept of
filial piety using self-report measures.
A demographics questionnaire was given to each participant to collect data
on age, gender, and ethnicity, as well as asking them whether or not they have ever
worked or lived with older adults. In addition, three paper-and-pencil instruments
that have been used in other studies are employed here.
The Facts of Aging Quiz (FAQ; Palmore, 1977) assesses the self-reported
positive and negative attitudinal biases toward older adults. This questionnaire has
been used to examine both attitudes toward and knowledge about older adults
(Palmore, 1988). However, Kline, Scialfa, Stier, & Babbitt (1990) stated that the
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FAQ is greatly affected by both positive and negative biases toward the elderly and
is therefore a better measure of attitudes toward older adults than it is a measure of
knowledge of aging. In fact, Klemmack (1978) argues that individuals who give the
correct response to the negative bias items are more likely to give the incorrect
response to the positive bias items than those who give the incorrect response. This
methodological issue, however, makes the FAQ an ideal paper-and-pencil
assessment of attitudes toward older adults. Thus, even though the FAQ has been
used in the past as a test of knowledge, it is now more often seen as an attitudinal
measure.
The Knowledge of Aging and the Elderly (KAE) questionnaire (Kline et al.,
1990) is used to measure the extent of knowledge about older adults. It is patterned
after the FAQ but has been shown to be relatively immune to positive or negative
biases toward older adults when compared with the FAQ (Kline et al., 1990). The
KAE was also found to be slightly more sensitive to education-based differences in
knowledge regarding aging and the elderly as compared with the FAQ in its
normative sample.
The Filial Piety (FP) scale (Ho & Lee, 1974) has not been used with non-
Asian populations, but has been widely used in Chinese societies of Hong Kong and
Taiwan to examine relationships between filial piety and various other psychological
phenomena (Zhang & Bond, 1998). For example, studies have been conducted to
investigate the relationships between parents’ endorsement of filial piety and their
children’s cognitive performance (Boey, 1976), the changes in the strength of filial
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13
attitudes across generations (Ho & Kang, 1984), and the way in which filial piety
affects how older adults are cared for in their family (Yeung, 1989). This
questionnaire was used in this study with participants of both Asian and non-Asian
descent to measure the participants’ self-reported strength of respect and reverence
toward older adults.
Hypotheses o f the present study
Given findings in previous research, the following are hypothesized in this
study:
1) Overall, participants who encounter older adults on the ATSS tapes would
express more negative cognitions than those who encounter younger adults on
the tapes.
2) For the participants who encounter older adults on the tapes, those who have a
higher level of filial piety would express less negative cognitions toward the
targets than those with less filial piety.
3) Participants who have less attitudinal biases and higher levels of knowledge
toward the elderly on the self-report questionnaires would have less negative
cognitions toward the older adults on the ATSS than those who have more
attitudinal biases and lower levels of knowledge.
4) And finally, it is hypothesized that participants who have lived or worked with
older adults would express less negative cognitions toward the older adults they
encounter on the tapes than those who have not.
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14
Method
Participants
A total of 120 University of Southern California (USC) undergraduate
students participated in this study. However, 18 participants’ responses were used to
establish interrater reliability. Therefore, results were based on 102 participants (13
men and 89 women). The mean age of these 102 participants was 19.9 years
(SD=1.72). Thirty-nine (38%) were White/Caucasian, 27 (26%) were Asian
American, 20 (20%) were Latino/a, and 16 (16%) were of other ethnic groups
(African American=4, mixed races=3, other=7, unknown=2). Participants were
recruited with the assistance of the USC psychology department human subject pool
and received partial class credit for their participation.
Measures
In order to avoid priming to ageism issues and to decrease potential social
desirability bias on the ATSS think-aloud procedure, the questionnaires were
administered after the experimental manipulation.
Demographics Questionnaire. Participants were asked to provide personal
information on gender, ethnicity, age, year in college, and answer whether or not
they have ever lived or worked with the elderly and if so, in what capacity (See
Appendix Bl).
Facts of Aging Quiz (FAQ). In order to assess positive and negative
attitudinal biases toward the elderly, participants were asked to complete this short
(25-items) true-false questionnaire that covers the basic physical, mental, and social
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15
facts and the most common misconceptions about aging (Palmore, 1977) (see
Appendix B2). This scale has been widely used as an assessment of knowledge and
attitudinal biases toward the elderly and aging over the past two decades. Between-
group reliability is high (.86) as shown by the consistency with which comparable
educational groups have similar mean scores and by similar scores on test and retest
in control groups (Palmore, 1980). However, item-to-total (within scale) reliability is
low (alpha= .47) because several items have a low item-to-total correlation
(Klemmack, 1978), i.e. most people get one set of items wrong and another set right.
A Structural Equation Model (SEM) was designed to examine whether the FAQ can
successfully tap into both positive and negative ageist biases (see Results section).
The FAQ was found to be able to discriminate between the two types of biases
according to Palmore’s (1977) model.
Knowledge of Aging and the Elderly (KAE) Questionnaire. This 25-item
true-false questionnaire is based on the format of the FAQ but was developed to
improve over the FAQ as a measure of knowledge of aging (Kline et al., 1990) (see
Appendix B3). A factor analysis was conducted to determine the structure and utility
of this scale as a measure of knowledge of aging unadulterated by attitudinal biases
for the present sample (see Results section).
Filial Piety (FP) Scale. This 22-item measure presents statements concerning
familial respect and duties. Participants respond on a scale from 1 to 6, where 1
means Strongly Disagree and 6 means Strongly Agree (see Appendix B4). A split-
half reliability coefficient of .81 was obtained for this scale. The mean and standard
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16
deviations of the scores per item were 3.66 and .37, respectively based on a
normative sample of 135 Taiwanese primary school teachers (Ho & Lee, 1974). A
factor analysis was conducted to determine the structure and utility of this scale as a
measure of the concept of filial piety for the present sample (see Results section).
Procedure
The experimental ATSS procedure was administered in the ATSS laboratory
at USC by either the author or one of 4 trained undergraduate research assistants.
Upon arrival in the ATSS laboratory, participants were asked to read and sign an
informed consent form. At this time the experimenter also provided a brief overview
of the ATSS procedure and answered any questions or concerns. The participants
were then introduced to the ATSS procedure via tape-recorded instructions. The
participants were told that the researchers were interested in people’s thoughts. They
were asked to listen to several scenarios and to imagine themselves actually being
involved in the situations. In particular, they were asked to “tune into what is going
through your mind” as they listened to the scenarios.
Following the instructions, the participants listened to a brief sample scenario
consisting of a situation where they were at the garage waiting for their car to be
fixed by the mechanic. Then, the participants were asked to practice the procedure by
listening to a scenario where they imagined themselves overhearing two
acquaintances talking negatively about them. After ensuring that the participants
understood the procedure, the experimental ATSS procedure began. The
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17
experimenter left the room to ensure privacy and minimize the likelihood of subject
response apprehension and censoring.
ATSS Scenarios
The present study employed a between-subject design. Each participant was
randomly assigned into one of two experimental conditions: alternate participants
either listened and responded to two scenarios encountering older adults, or to two
scenarios encountering younger adults, both written by the author (See Appendix A).
Fifty of the 102 participants (49%) listened to the Encountering Older Adults
scenarios, while 52 participants (51%) listened to the Encountering Younger Adults
scenarios. The order of the experimental scenarios was counterbalanced to minimize
order effects. Each scenario included seven segments or “mini-scenes” that served to
elicit responses from the participants. The young adult scenarios was parallel to that
of the older adults scenario, that is, the two sets of scenarios were identical except for
the slight changes in content that reflected the age difference o f the persons
encountered. Prior to the experimental tapes, each subject listened and responded to
a thematically unrelated scenario that served as control.
Control scenario. In the control tape, the participants were asked to imagine
that they overhear a discussion between two fellow students about a boring
professor. This scenario was administered before the actual experimental tapes to all
participants in order to ascertain the absence of non-random group differences
between the participants who were in the Encountering Older Adults condition
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18
versus those who were in the Encountering Younger Adults condition (see Results
section).
Experimental scenario 1. Half of the participants listened to this scenario first.
The participants were exposed to several everyday situations where they encounter
people (either old or young depending on the condition they were randomly assigned
to) who were getting in their way. First, they were driving on the freeway in a hurry
but another car was in front of them going slowly. Then, they were at the ATM
machine waiting in line for a long time behind a person who was having trouble with
the machine. Next, a person tripped over himself in front of them while they were
heading to the library. And finally, they were in line at the grocery store checkout
counter and a person was arguing with the cashier, extending the time they had to
wait in line.
Experimental scenario 2. Half of the participants listened to this scenario
first. The participants were exposed to several situations where they were in a
position to be of help to several people (either old or young depending on the
condition they were randomly assigned to). First, they were working at a local
grocery store as a cashier when a person at the checkout counter did not have enough
money to pay for the items he wanted to buy. Second, they were volunteering at
either a physical or senior rehabilitation center where they worked with people who
have been in accidents.
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19
Debriefing.
After the ATSS procedure, each participant was given a questionnaire packet
(see Appendix B). At its conclusion, the participants were thoroughly debriefed by
the experimenter. It was emphasized that the scenarios they were asked to imagine
were fictional. The participants were encouraged to discuss any questions or
concerns they may have about the study with the experimenter.
ATSS Transcription and Coding of the Dependent Variables.
This study’s primary objective was to gain insight into the participants’
cognitions toward older adults, as compared to thoughts toward younger adults, in
several different situations as depicted in the ATSS scenarios. In particular, this
study focused on both negative and positive cognitions directed at the older adults in
those situations. As mentioned earlier, the negative coding categories include
annoyance, verbal aggression, physical aggression, sadness/pity/guilt, identification
of negative attributes, identification of age, and anger intensity. Positive coding
categories include verbal respect/compassion/empathy, physical
respect/compassion/empathy, identification of positive attributes, and giving of non
personal excuse.
Four undergraduate research assistants transcribed the ATSS tapes onto
computer files during the data collection phase of the study. At the conclusion of
data collection, two undergraduate research assistants received extensive training in
ATSS coding by the author. After the establishment of the coders’ interrater
reliability (see Results section), the tapes were divided between them for the purpose
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20
of content analysis. A mid-point reliability check was conducted to ensure that
interrater reliability had not drifted during the coding process.
Coding instructions on each dimension are provided below. With the
exception of the dimension o f Anger Intensity, all dimensions were frequency
counts. The frequency of each unit of analysis was summed across segments and
across scenarios for each participant. A unit of analysis consisted of a complete
utterance where a period (.) would usually be. Thus, the utterance of “he is old and
slow” would be considered one unit but “He is old. He shouldn’t be driving.” would
be considered two units. Utterances were coded if they fit into one of the categories
below. Each utterance could be coded on more than one dimension simultaneously
(see Results section for a more detailed description of the coding process).
Annoyance. This dimension assesses the frequency of the participants’
annoyance directed at the simulated persons depicted in the audiotaped scenarios.
Words used by participants, such as “irritated”, “annoyed”, and “frustrated” in their
statements are counted and summed across all segments.
Verbal Aggression. This coding dimension assesses the frequency of the
participants’ verbal insults (e.g. slow, dumb, crazy), name-calling (e.g. jerk, retard),
as well as any other instances where the participants verbalize non-action-related
aggression (e.g. “I hate this guy.”; “He should be put away.”)
Physical Aggression. This dimension assesses the frequency of the
participants’ action-related aggressive cognitions as well as intentions to physically
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21
harm the simulated persons in the scenarios (e.g. “I’m going kick his ass.”; “I’m
going to push him out of the way.”)
Sadness/Pitv/Guilt. This dimension assesses the frequency of the participants’
verbalizations concerning how sorry or sad they feel toward the persons on the tape,
as well as any expressions of pity or guilt (e.g. “Poor thing.”; “I shouldn’t rush
him.”; “I feel bad for him.”)
Identification of Negative Attributes. This dimension assesses the frequency
of the participants’ use of pejorative statements in association with the simulated
person's age only (e.g. “Old people are slow and retarded.”; ‘They should all be put
into a nursing home.”)
Identification of Age. This dimension assesses the frequency of the
participants’ identification of the simulated persons’ age or age group. For example,
the use of words such as “old”, “elderly”, “geezer”, and “young.”
Anger Intensity. This dimension is rated for each segment of the scenarios
and summed. The ratings range from 0 to 3 based on the tone of voice of the
participants as well as words used. A rating of 0 entails a neutral tone of voice with
no aggression or cursing. A rating of 1 indicates that the participant was slightly
angry where the voice was slightly raised, with mild sarcasm or mild verbal
aggression. A rating of 2 means that the participant was moderately angry where the
voice was raised and the participant cursed at the simulated persons on the tape. The
highest rating of 3 means that the participant’s voice was highly raised, and might
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22
have included either heavy cursing or severe verbal/physical aggression toward the
persons on the tapes.
Verbal Respect/Compassion/Empathv. This dimension refers to the
frequency of the participants’ use of statements indicating that they care about the
persons on the tapes but without the intention to help (e.g. “It’s okay, I’m not in a
hurry.”; “He can take as much time as he needs.”)
Physical Respect/Compassion/Empathv. This dimension assesses the
frequency of the participants’ statements indicating what they would actually do to
show respect or compassion toward the persons on the tapes (e.g. “I’ll go help him.”;
“I’ll slow down to let him pass.”)
Identification of Positive Attributes. This dimension assesses the frequency
of the participants’ statements identifying positive attributes of the simulated
persons’ age group (e.g. “Old people are nice to work with.”; “They should be
respected and cared for.”)
Giving of Non-Personal Excuse. This dimension assesses the frequency that
the participants articulate statements referring to situational (non-personal) variables
as an explanation for the behavior of the persons on the tapes (e.g. “He’s probably
lost.”; “He’s probably tired.”)
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Results
Interrater Reliability
To establish interrater reliability for the coding dimensions, two research
assistants were trained by the author using 7 actual participants’ responses (3
scenarios-one control and two experimental scenarios— from each participant=a total
of 21 scenarios) as well as a series of sample responses over the course of 4 weeks
(20+ hours of training in laboratory). The sum of utterances for each participant on
the 11 coding categories were calculated and the consistency intraclass correlation
coefficients (an index of interrater agreement) were calculated for the 11 actual
participants’ responses (a total of 33 scenarios) which were coded by both coders
(see illustration for one coding category in Table 1).
Table 1 . Illustration of Interrater Reliability Data
For each coding category:
Participant Rater 1 Rater 2
Control Scenario I 0 1
2 0 0
3 1 0
4 1 1
5 0 0
6 0 1
7 0 0
8 0 1
9 1 I
10 0 0
1 1 1 0
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Table 1. (continued)
Participant Rater 1 Rater 2
ExDerimental Scenario 1 1 2 3
2 2 2
3 0 1
4 1 1
5 0 0
6 2 1
7 1 0
8 1 I
9 0 1
10 2 3
11 2 2
Experimental Scenario2 1 3 4
2 2 1
3 3 3
4 2 1
5 2 2
6 1 2
7 3 3
8 4 3
9 1 2
10
2
2
11 1 0
Table 2 presents the interrater reliability for each of the 11 categories. The
correlation coefficients ranged from .70 to 1.0.
To ascertain that interrater reliability was maintained throughout the content
analysis process, a mid-point coding reliability check was conducted. Six
participants’ responses (18 scenarios) were content-analyzed by both coders about
halfway through the coding process. As shown in Table 3, interrater reliability was
maintained during the midpoint of coding. While 6 categories decreased slightly in
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25
reliability from the initial reliability coefficients, 4 categories improved and 1 stayed
the same. All intraclass correlation coefficients were above .73.
Table 2. Initial Interrater Reliability Coefficients for All Coding Dimensions
Intraclass Correlation Coefficients
Annoyance
.94
Verbal Aggression .91
Physical Aggression .98
Sadness/Pity/Guilt
1.0
Identification of Negative Attributes
.98
Identification of Age
.83
Anger Intensity
.90
Verbal Respect/Compassion/Empathy .99
Physical Respect/Compassion/Empathy
.70
Identification of Positive Attributes
1.0
Giving of Non-Personal Excuse
.94
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Table 3. Midpoint Interrater Reliability Coefficients for All Coding Dimensions
Intraclass Correlation Coefficients
Annoyance .9Ia
Verbal Aggression .93b
Physical Aggression .86a
Sadness/Pity/Guilt .79a
Identification of Negative Attributes .90“
Identification of Age 1.0b
Anger Intensity .84“
Verbal Respect/Compassion/Empathy .73“
Physical Respect/Compassion/Empathy ,74b
Identification of Positive Attributes 1.0C
Giving of Non-Personal Excuse 1.0b
a =decreased from initial reliability as shown on Table2; b =increased from initial
reliability as shown on Table 2; c=same as in Table 2.
The internal consistency of the coding categories was measured by
computing the correlation coefficients between the 2 experimental scenarios for each
of the 11 dimensions (see Table 4). This way of calculating internal consistency of
the coding categories examines whether (and how) stable each category is across
these scenarios. If the consistency is relatively high, then the category (made up of
the total number of utterances from both scenarios) can be seen as relatively stable
and therefore a good measure of that dimension. If the consistency is relatively low,
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then the category may be seen as relatively unstable and more prone to be affected
by the context of the scenario. Alternatively, low consistency can indicate the low
frequency of that category in one or both of the scenarios. Interpretations of these
low consistency categories must recognize that the measures may not exemplify
individual differences, but may be explained by contextual effects.
Table 4. Internal Consistency of Coding Categories
Category_________________ Correlation Coefficient Consistency Level
Annoyance .35 Medium
Verbal Aggression .29 Medium
Physical Aggression .12 Low
Sadness/Pity/Guilt .17 Low
Identification of Negative Attributes .39 Medium
Identification of Age .67 High
Anger Intensity .32 Medium
Verbal Respect/Compassion/Empathy .10 Low
Physical Respect/Compassion/Empathy .58 High
Identification of Positive Attributes -.08 Low-Negative
Giving of Non-Personal Excuse .11 Low
Traditionally, a large correlation is considered to be .50 or above, a moderate
correlation is considered to be about .30, and a small correlation is considered to be
about .10 (Cohen, 1988). Using this standard for the coefficients here, it can be seen
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that the categories of Identification of Age and Physical Respect have high internal
consistencies. Annoyance, Verbal Aggression, Identification of Negative Attributes,
and Anger Intensity have medium internal consistency. Physical Aggression,
Sadness/Pity/Guilt, Verbal Respect, and Giving of Non-Personal Excuse have low
internal consistency. Further, Identification of Positive Attributes has a negative and
low coefficient.
These results indicate that those 6 categories that have high or medium
internal consistencies are relatively stable and that the sum of the utterances from
both experimental scenarios is a relatively good measure of those constructs.
However, the 5 categories with low internal consistencies (ranging from -.08 to .17)
may be seen as less stable and reliable measures of those constructs. A closer
examination of the descriptive statistics of each category (see Table 5) reveals that 4
of these 5 low-consistency categories are low in frequency (Physical Aggression,
Sadness/Pity/Guilt, Identifications of Positive Attributes, and Giving of Non-
Personal Excuse) ranging from a mean o f .29 to 1.43 utterances per participant
across both experimental scenarios. This low frequency is likely to have contributed
to the low internal consistency of these categories. For Identification of Positive
Attributes, the internal consistency is not only low but also negative (-.08), indicating
that the frequency of utterances between the 2 scenarios is negatively correlated. A
closer examination of the raw data shows that almost all of these utterances (an
average of .29 per participant) were found in the second scenario. Given this
information, it seems appropriate to use only those utterances of Identification of
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Positive Attributes found in Scenario 2 (an average of .28 per participant) in later
analyses (see Table 5). The category of Verbal Respect (an average of 2.32
utterances per participant across both scenarios) was also found to occur almost
exclusively in Scenario 2, thus likely to have caused the low internal consistency.
Therefore, further analyses with this category will only use utterances found in
Scenario 2 (an average of 2.30 utterances per participant) (see Table 5).
Mean Mean
(Scenario 1 1 (Scenario 2)
Mean
(Both Scenario;
Annovance 2.17 1.58 3.75
Verbal Aggression 1.37 .77 2.14
Physical Aggression .92 .50 1.42
Sadness/Pitv/Guilt .73 .70 1.43
Identification of Negative
Attributes .44 .27 .71
Identification of Age 1.45 .93 2.38
Anger Intensity 2.36 1.25 3.61
Verbal Respect .02 2.30" 2.32
Physical Respect .84 1.41 2.25
Identifications of Positive
Attributes .01 .28" .29
Non-personal Excuses .19 .28 .47
aOnly Scenario 2 means were used in subsequent analyses due to proportionally
lower frequency in Scenario 1 .
Table 6 presents the correlations between the 11 coding categories for data
collected from the 102 participants. The higher correlations (above .60) between
Physical Aggression and Anger Intensity, Verbal Aggression and Anger Intensity,
and Identification of Negative Attributes and Identifications of Age, are likely to
have been artificially inflated because utterances were coded in two categories
simultaneously. For example, a statement such as “I am going to kick his ass!”
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30
would be coded in both Physical Aggression and Anger Intensity. And a statement of
“old people are so slow” would be coded in both Identification of Negative
Attributes and Identification of Age. Correlation between all of the categories is .51.
By its definition (see Introduction and Methods sections), the category of
Sadness/Pity/Guilt can be considered as a positive, negative, or neutral cognition.
The decision to include this category as a negative cognition in this study was based
upon its relatively higher correlation with the other negative categories (ranging from
.0242 to .3380) as well as its relatively low correlation with the positive categories
(ranging from -.0965 to .0833) (see italics in Table 6).
Table 6. Correlations between Coding Categories
Annoyance Verb.Agg. Phys.Agg. SPG Neg.Att.
Annoyance 1.0000
Verbal Aggression .3654 1.0000
Physical Aggression .0444 .1773 1.0000
Sadness/Pity/Guilt .1826 .0242 .1818 1.0000
Negative Attributes .1034 .2905 .0871 .2484 1.0000
Identification of Age -.0285 .0755 .1978 .3380 .6026
Anger Intensity .3867 .6229 .6839 .1835 .2294
Verbal Respect -.0015 -.1470 -.0991 .0067 -.0014
Physical Respect -.1417 -.2700 .1397 -.0965 -.0132
Positive Attributes .0527 .1552 .0679 .0513 .0086
Non-personal Excuse .1722 .0675 -.0744 .0833 -.0808
Age Anger V.Resp. P.Resp. Pos.Att.
Identify Age 1.0000
Anger Intensity .1551 1.0000
Verbal Respect -.0851 -.2426 1.0000
Physical Respect -.0464 -.1003 -.0308 1.0000
Positive Attributes .2126 .0888 .0376 -.0840 1.0000
Non-personal -.1398 -.0352 .2022 -.1289 .1172
Excuse
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A closer examination of the correlations in Table 6 reveals that there seem to
be two clusters of negative cognitions. Annoyance, Verbal Aggression, and Anger
Intensity seem to form a cluster of more severe negative cognitions (see bolded
correlations in Table 6) whereas Identification of Negative Attributes, Identification
of Age, and Sadness/Pity/Guilt seem to form another cluster of less negative
cognitions (see underlined correlations in Table 6). In fact, this latter cluster can also
be seen as more ambiguous because some utterances coded in these 3 categories may
be negative, but not all (e.g. calling someone a “geezer” has a negative connotation,
but calling someone “old” may be more descriptive than negative).
In order to confidently base the analyses on data collected, it was important
to ascertain the validity of the questionnaires used. Since the three questionnaires
(FAQ, KAE, and FP) do not have well-established reliability or norms, it was
necessary to explore the factor structure of these instruments based on the data
collected in this study (N=120).
Structural Equation Model (SEM) to estimate the factors in the FAQ
According to Palmore (1977), all the odd-numbered items of the FAQ (see
Appendix B2) are factually false and all the even items are factually true. It was
hypothesized that all 25 items related to an “accuracy” factor (Factor 1). Since the
correct responses have been coded +1, regardless of whether it was an odd or even
item, all the loadings on Factor 1 were hypothesized to be positive. This item coding
should be reflected by the factor correlations.
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32
Palmore (1977) classified items 2 ,4 ,6 , 12, and 14 as indicating positive bias
if the respondent indicates that they are incorrect, i.e. they indicate factually true
items that the respondent checks as untrue. This “positive bias toward the elderly”
factor was specified as Factor 2.
Palmore (1977) also argued that if items 1, 3,5, 7, 8,9, 10, 11, 13, 16, 17, 18,
21,22, 24, and 25 are marked incorrectly, a negative bias toward older adults is
indicated. On the basis of these assertions, it was hypothesized that these 15 items
measure a factor of “negative bias toward the elderly” (Factor 3).
A structural model with the 3 factors (Accuracy, Positive and Negative biases
toward the elderly) and the 25 items from the FAQ was created using the computer
program, Mx, and is represented in Figure 1. The factors computed in accordance
with the above hypotheses are listed in Table 7.
The structural model in Figure 1 was run using Mx assuming N=100. Results
indicated a good fit (Chi-squared fit of model=301.2; df=276, Akaike’s Information
Criteria= -250.8; Root Means Square Error Approximation (RMSEA)= .03). This
result, along with the fact that, with the exception of the last 2, all items on the FAQ
were found to be either in accordance with, or in the right direction of, the
hypotheses above, indicate that Palmore’s (1977) assertion of negative and positive
bias items was supported.
As listed in Table 7, Positive Bias was scored in the non-bias direction (i.e. a
positive score indicates correct knowledge), while Negative Bias was scored in the
bias direction (i.e. positive for odd items is negatively related to the factor, positive
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Figure 1. Structural Model of FAQ with 3 Factors
for even items is positively related to the factor). Therefore, the high negative
correlation of .89 between Factors 2 and 3 (see Table 8) indicates a negative
relationship between negative bias and positive bias, which confirms Palmore’s
(1977) assertions. In fact, this correlation is about equal to the internal consistency
reliability of the separate factors. Therefore, these factors likely do not have separate
validities. Thus, to create a one-dimension index of bias using both the Positive and
Negative Bias Factors, the total bias score for each participant was calculated as
+nepative bias items minus positive bias items. In subsequent analyses, this one-
dimension attitudinal bias score was used.
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34
factors
Accuracv Positive Bias Negative Bias
Ql
.3171 .0000 -.2322
Q2 .1361 .2086 .0000
Q3 .4300 .0000 -.3050
Q4
.1304 .4436 .0000
Q5 .4022 .0000 -.2296
Q6 .1246 .2245 .0000
Q7 -.0770 .0000 -.0951
Q8 .0653 .0000 .2449
Q9 .3635 .0000 -.1891
Q10 -.0527 .0000 .3746
Q ll .3296 .0000 -.3974
Q12 .2344 .4099 .0000
Q13 .3170 .0000 -.3085
Q14 .0252 .2862 .0000
Q15 .5093 .0000 .0000
Q16 -.0696 .0000 .2539
Q17 .4138 .0000 -.0632
Q18 .0089 .0000 .3750
Q19 .0995 .0000 .0000
Q20 -.0833 .0000 .0000
Q21 .0732 .0000 .2236
Q22 -.2318 .0000 .3249
Q23 .1064 .0000 .0000
Q24 .2075 .0000 .3025
Q25 -.1114 .0000 -.1986
Bold indicates “in accordance with hypothesis”
Underline indicates “in the right direction, but coefficient not likely different from
zero”
Italics indicates “in opposite direction of hypothesis and coefficient likely different
from zero”
All items assume that True are scored +1, and False are scored 0.
A value of .0000 means that no path was drawn between the item and the latent
variable (i.e. the path value was set to zero).
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Table 8. Correlations of the 3 Factors in FAQ
Accuracy
Positive Bias
Negative Bias
1.000
-.2203
.1273
1.000
-.8903 1.000
Factor Analysis of the KAE
To date, no data have been published on the validity and reliability of the
KAE. Kline et al. (1990) claimed that this scale is superior to the FAQ as a measure
of knowledge of aging, and is less affected by attitudinal biases. However, their
support for this claim is weak, citing only 1.16 score-point’s difference between
those in the normative sample who have taken a course in aging and those who have
taken a course in life-span personality, and only 1.62 points’ difference between the
aging course students and those who only took social science courses.
To investigate the authors’ claim, an unrotated Principal Component analysis
was conducted that yielded 9 principal factors with Eigenvalues above 1.0. Since the
intent was to find one valid and reliable factor to use as the construct of knowledge
of aging, the first factor (which accounted for 11.4% of the variance in the scale) was
examined more closely (see Table 9). All the items that were positively correlated
with each other were selected. This yielded a factor with 17 of the original 25 items
from the KAE scale. Another Principal Component analysis was conducted with
only those 17 items where it was found that these items accounted for 16% of the
variance of the scale (see Table 9). The reliability coefficient of these 17 items is .66
(see Table 10). Each of the 8 items that were left out of this factor was added and
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new reliability coefficients calculated. It was found that adding any of these 8 items
reduced the reliability of the 17-item scale. Therefore, subsequent analyses were
conducted with only those 17 items, leaving out items 6, 9, 10, 11, 15, 19, 20, and 22
from the original scale.
Table 9. Unrotated Principal Component Factor Matrix for KAE for the first factor
____________ Initial Factor 1 _______17 items only__________________________
Ql
.384 .425
Q2 .367 .408
Q3 .432 .393
Q4 .401 .365
Q5 .367 .366
Q6 -.255
Q7 .325 .306
Q8 .235 .291
Q9 -.165
Q10 .000
Q ll .000
Q12 .505 .511
Q13 .437 .494
Q14 .240 .279
Q15 -.130
Q16 .379 .401
Q17 .329 .362
Q18 .483 .392
Q19 -.213
Q20 -.234
Q21 .490 .526
Q22 -.110
Q23 .481 .410
Q24 .273 .327
025 .381 .415
Eigenvalue= 2.843 2.699
Variance accounted= 11.43% 16.4%
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Table 10. Correlation Matrix of the 17 items on the KAE scale
Q401 Q402 Q403 Q404 Q405
Q401 1.0000
Q402 .0508 1.0000
Q403 .1679 .0577 1.0000
Q404 .1446 .1233 .0657 1.0000
Q405 .1014 .0659 .0782 .0481 1.0000
Q407 .1106 .0367 .3057 .1543 .2191
Q408 .0728 .0993 .0291 .0725 .1019
Q412 .1003 .1326 .1538 .0260 .0985
Q413 .2160 .2972 .1215 .0975 .0578
Q414 .1059 .0805 -.0212 .0317 -.0092
Q416 .0499 .1570 -.0013 .0921 .0809
Q417 .1549 .1364 .1008 -.0205 .1014
Q418 .0387 .0516 .1979 .2746 .1639
Q421 .1540 .1323 .1901 .0473 .0386
Q423 .0728 -.0140 .1622 .2911 .1722
Q424 .0301 .1432 -.1018 .0044 .1180
Q425 .2178 .1416 .0920 .1034 .1653
Q407 Q408 Q412 Q413 Q414
Q407 1.0000
Q408 -.0639 1.0000
Q412 .0799 .0597 1.0000
Q413 .0993 .3065 .0994 1.0000
Q414 .1512 .1161 .0575 .1122 1.0000
Q416 -.0514 .1219 .2278 .1847 -.0720
Q417 -.0878 .0728 .2343 .0833 .1059
Q418 .0565 .0105 .1492 .0729 .0368
Q421 -.0603 .0131 .3384 .1887 .0352
Q423 .1331 -.0581 .1484 .0870 .0728
Q424 .0033 .1344 .1381 .0823 .1861
Q425 .2272 .1133 .0977 .0615 .2395
Q416 Q417 Q418 Q421 Q423
Q416 1.0000
Q417 .1859 1.0000
Q418 .0770 .0387 1.0000
Q421 .2249 .2220 .0739 1.0000
Q423 -.0131 -.0071 .3652 .1931 1.0000
Q424 .2326 .0955 .0039 .1723 .0911
0425 .0967 .0127 .0318 .1727 .0228
Alpha= .6560 Standardized Item Alpha= .6614
Q425
1.0000
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38
There has been much debate about whether the KAE is a better measure of
knowledge of aging than the FAQ (which has been used as both a knowledge and an
attitude scale, but is now mostly used as an attitude scale). However, there is no
published data on how the items on the 2 scales correlate. If an item on the KAE
correlates highly with items on the FAQ, i.e. above .50 according to Cohen (1988),
then that item may be asking about attitude toward older adults instead of knowledge
of aging. Since both of these measures were used in this study, it is important to
investigate their divergent validity. Table 1 1 displays the correlation matrix of all the
items of KAE and FAQ.
Table 11. Correlation Matrix of KAE and FAQ items
KAE 1 2 3 4 5 6 7
FAQ
1 -0.0025 0.2629 0.0069 -0.0335 0.1239 0.0352 0.1115
2 0.0825 0.0767 0.1182 0.1030 -0.1734 -0.0168 0.0064
3 0.1131 0.1436 -0.0425 0.0602 0.1666 0.0467 0.1455
4 -0.1045 0.0571 0.0530 0.0154 -0.1250 0.0856 0.0635
5 0.0949 -0.0309 0.0861 0.1905 0.0519 -0.0626 0.0420
6 0.0507 0.0247 0.0000 -0.1245 -0.1110 0.2293 0.0000
7 -0.0633 0.0452 0.0000 0.1376 0.0519 -0.0402 0.0000
8 0.0578 -0.0624 0.0648 0.0326 -0.0242 -0.0509 -0.0948
9 0.0949 -0.0919 0.0516 0.2329 0.1558 -0.0268 -0.0252
10 0.1653 -0.1426 0.0426 0.0330 0.1190 -0.1893 -0.0762
11 0.1421 0.0515 0.1017 -0.0818 0.0164 0.1247 -0.0298
12 -0.0337 0.0567 0.0530 -0.0320 0.1076 -0.0345 0.0071
13 0.0120 -0.0349 0.1236 -0.0560 0.1766 0.0507 0.1619
14 -0.0120 0.0346 -0.1757 0.0720 0.0589 0.0304 -0.0857
15 0.1157 -0.0368 0.2283 0.1057 0.2990 0.0122 0.2800
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39
Table 11 (continued)
KAE 1 2 3
FAQ
16 -0.1653 -0.0587 0.1562
17 0.0854 -0.0694 -0.0179
18 0.0245 -0.0713 -0.1378
19 0.0673 0.0506 0.0610
20 0.0913 -0.0530 -0.0099
21 0.2029 -0.0852 -0.0345
22 -0.0120 -0.2424 -0.0716
23 0.0671 -0.1294 0.0730
24 -0.0673 -0.0506 -0.0203
25 -0.0855 -0.0947 -0.1119
8 9 10
FAQ
1 0.1332 -0.0059 -0.0317
2 0.0822 -0.0259 -0.0831
3 0.1811 -0.0600 0.0961
4 -0.0257 0.0041 -0.2555
5 -0.0466 0.0364 0.0000
6 -0.0160 0.1895 0.1129
7 0.2195 -0.0091 0.0000
8 -0.1523 -0.1016 -0.0061
9 0.0200 0.0000 -0.1352
10 -0.0055 0.2200 0.0527
1 1 -0.0330 0.0258 -0.0133
12 0.1084 0.1670 -0.0284
13 -0.0226 0.0825 -0.0894
14 0.0830 -0.0825 -0.0128
15 0.0100 -0.0991 0.0525
16 0.1372 0.0600 0.0217
17 0.1698 -0.0679 0.0468
18 0.1597 -0.0563 -0.0087
4 5 6 7
0.1067 0.1095 0.0467 -0.1317
0.1567 0.1006 -0.0130 0.1307
-0.0711 0.0938 -0.1177 0.0195
0.0184 0.1678 -0.0021 -0.0298
-0.0367 0.1499 -0.1703 0.0145
-0.0736 0.0763 0.0573 0.0000
-0.1360 -0.0981 -0.0507 -0.0095
-0.0150 0.1468 -0.0758 0.0535
0.2319 -0.0164 -0.1247 -0.0894
-0.1222 -0.0641 0.0385 0.0630
1 1 12 13 14
0.0404 -0.0467 0.0343 -0.0310
0.0907 -0.1561 0.0262 0.1095
-0.0048 -0.0827 0.0228 -0.0576
0.0494 0.0806 -0.0490 -0.1486
0.1384 0.1736 0.0673 -0.0300
-0.1110 0.0345 0.1034 0.0245
-0.0130 0.0650 -0.0168 0.0450
-0.0242 -0.0885 -0.1277 -0.0615
-0.2077 0.1309 0.0673 -0.0913
-0.1095 0.0833 0.0308 0.0600
0.0777 0.0721 -0.0848 -0.1655
0.0494 0.0798 0.1394 -0.1483
-0.0589 -0.0492 0.1271 -0.0348
0.0589 0.0492 -0.0254 0.0346
0.0757 0.1340 0.0177 -0.0366
-0.0048 -0.0837 -0.1418 0.1432
0.0467 0.1716 0.0721 0.0112
0.0402 0.0334 0.0521 -0.0704
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40
Table 11 (continued)
KAE 8 9 10 1 1 12 13 14
FAQ
19 0.0330 -0.0172 0.0533 0.0777 0.0725 0.0345 0.0504
20 0.0576 -0.0840 0.0586 0.0300 0.0754 -0.1553 -0.0541
21 0.1760 0.0656 0.2823 0.2324 0.1389 0.1438 0.0978
22 0.0830 -0.0825 -0.0128 -0.0981 -0.1479 0.0768 0.0351
23 0.0423 -0.0772 0.0478 0.0367 -0.0459 -0.0832 -0.1300
24 0.0330 -0.1118 -0.0533 -0.0164 0.0826 -0.0345 -0.0498
25 0.0419 0.0218 -0.0395 -0.0121 -0.0049 0.0292 0.0882
15 16 17 18 19 20 21
FAQ
1 -0.1289 -0.0320 -0.0319 0.3719 -0.0316 -0.0644 -0.0313
2 -0.1029 0.7700 -0.1098 0.1021 -0.1102 -0.0541 -0.1088
3 -0.2240 0.0552 -0.0582 0.1635 0.0587 -0.0427 -0.0581
4 -0.1456 -0.1480 -0.1484 -0.0228 0.0560 -0.0622 -0.1484
5 0.0788 -0.0298 -0.0302 0.2226 0.2752 -0.0478 -0.0295
6 -0.1685 0.0152 0.0250 -0.2383 0.0241 0.1101 0.0249
7 -0.1182 0.0465 -0.1836 0.0019 0.0474 0.1523 0.0461
8 0.1327 -0.0623 -0.0626 0.0865 0.0619 -0.1168 -0.0627
9 -0.0394 0.0923 -0.0911 0.1386 0.0916 0.2150 -0.0896
10 0.0072 0.0588 0.0586 -0.1044 0.0591 -0.0361 0.0589
1 1 -0.0683 0.0515 -0.1656 -0.0686 0.0503 0.2598 -0.1646
12 0.0750 -0.1476 -0.1488 -0.0228 0.0568 -0.1825 -0.1482
13 -0.0298 -0.0339 -0.0346 0.0324 -0.0342 -0.1490 -0.0337
14 -0.0894 0.0353 0.0362 -0.1001 0.0350 -0.0135 0.0354
15 0.0584 -0.0374 -0.0369 0.1376 0.2256 -0.0711 -0.0368
16 0.2095 0.1422 -0.0588 0.0640 -0.0585 -0.0427 0.1435
17 -0.0109 -0.0691 -0.0696 -0.0184 0.1208 0.0025 0.1212
18 0.1017 0.1179 0.1183 0.0203 -0.0708 -0.0463 -0.0727
19 0.0248 -0.1653 -0.1660 -0.0686 0.0508 0.0791 0.0505
20 0.0455 0.1592 -0.0528 0.1531 -0.0532 -0.1034 -0.0532
21 0.0369 -0.0852 -0.0858 -0.1536 0.0982 -0.0263 0.0975
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41
Table 11 (continued)
KAE 15 16 17 18 19 20
FAQ
22 -0.0298 0.0342 0.0343 -0.1001 0.2427 -0.0677
23 -0.0697 0.0650 -0.1293 -0.0132 0.1292 -0.1727
24 0.0683 -0.0507 -0.0503 0.1321 0.1497 -0.0791
25 0.0210 0.0989 0.0883 -0.0563 0.0887 -0.0848
22 23 24 25
FAQ
I -0.2061 0.2072 0.0813 -0.0927
2 -0.1078 0.0254 0.1048 0.1258
3 -0.0261 0.1966 0.2691 -0.0589
4 -0.0337 0.1880 0.1204 -0.0457
5 -0.0105 0.3641 0.1167 -0.0174
6 0.3044 -0.0216 0.1292 -0.1486
7 -0.0633 0.0607 0.0333 0.1564
8 0.1258 -0.0101 0.1188 -0.0230
9 -0.0316 0.3236 0.2500 0.0174
10 -0.0435 -0.1521 -0.0657 0.0589
1 1 -0.0075 0.1945 0.3849 0.0835
12 -0.1045 0.0521 0.3071 0.1100
13 0.1076 0.1682 0.1323 0.0854
14 -0.0120 -0.1070 -0.0315 0.0723
15 0.0250 0.3084 0.0785 0.0951
16 0.0435 -0.0705 0.0290 -0.0589
17 -0.0460 0.1875 0.1165 0.2248
18 0.0899 -0.1149 -0.0043 0.1673
19 0.0673 0.0510 -0.1274 0.0425
20 -0.0548 -0.0701 0.0481 0.1706
21 -0.0507 -0.2081 0.0156 0.1022
22 -0.0120 -0.2294 0.0189 0.0197
23 0.0671 0.1573 0.0943 -0.0240
24 0.0075 0.0446 0.0092 -0.0425
25 -0.0222 -0.058 0.1507 0.0272
21
0.0334
-0.1289
-0.0503
0.0879
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42
As shown in Table 11, the inter-item correlations between the KAE and the
FAQ ranged from 0.000 to .3849. None of the correlations were considered high
(Cohen, 1988). Note that items 6,9, 10, 11, 15, 19,20, and 22 from the KAE were
excluded in subsequent analyses due to their negative correlation and low reliability
with the other items on the KAE. Also, items 15, 19,20, and 23 on the FAQ were
excluded from the calculation of attitudinal biases because these 4 items do not
correlate with either the positive or the negative bias factors according to Palmore
(1977). The correlation between the scores on the full scales (all 25-items of both
questionnaires) of the FAQ and KAE is .4181. However, the correlation between the
scores on the abbreviated scales—21 items on the FAQ and 17 items on the KAE—
is .3106. It is encouraging that the latter correlation is lower, i.e. the abbreviated
scales used in subsequent analyses have better divergent validity than the complete
scales. It can be concluded that the 2 measures do have divergent validity, i.e. the
KAE and the FAQ are measuring different constructs that do not overlap greatly (see
Table 3).
Factor Analysis for the FP Scale
No studies were found to have investigated the factor structure of the FP
scale. It was of interest to ascertain that the instrument is valid and adheres to a
factor that exemplifies the construct of filial piety. An unrotated Principal
Component analysis was conducted to reveal no clearly distinguishable factors
within the scale. However, the main factor accounted for 25% of the variance. Item
reliability analysis indicated that the highest alpha of .86 is obtained with 16 of the
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
22 items on the scale (see Table 12). Therefore, the items that decreased this
reliability (2,6, 10, 14, 15, and 21) were left out of the subsequent data analyses.
Table 12. Correlation Matrix of the 16 items on the FP scale tin descending order of factor
values)
Q311 Q322 Q312 Q313 Q319
Q3I1
Q322
Q312
Q313
1.0000
.4170
.4960
.3224
1.0000
.5695
.3685
1.0000
.4707 1.0000
Q319 .4781 .3342 .2846 .3720 1.0000
Q318 .3886 .3605 .3610 .3459 .3818
Q317 .4100 .2337 .2522 .3796 .3916
Q320 .3363 .2997 .2626 .3991 .2832
Q305 .2430 .3658 .4087 .3273 .2686
Q301 .3003 .4084 .3672 .2750 .3791
Q311 Q322 Q312 Q313 Q31S
Q309 .3992 .3124 .2011 .2261 .3321
Q307 .3113 .3225 .2380 .2945 .4051
Q303 .3571 .2770 .2733 .1818 .2049
Q308 .1703 .1601 .1416 .1773 .3209
Q316 .2348 .1597 .1594 .3251 .2760
Q304 .2125 .2202 .3016 .2613 .0479
Q318 Q317 Q320 Q305 Q301
Q318
Q3I7
Q320
Q305
1.0000
.3911
.2885
.3828
1.0000
.2445
.0695
1.0000
.2595 1.0000
Q301 .2670 .1932 .1699 .1664 1.0000
Q309 .1645 .2305 .3931 .2341 .1218
Q307 .2073 .1718 .2545 .3108 .2317
Q303 .2848 .2577 .3104 .2082 .1914
Q308 .3976 .1525 .1726 .3163 .3064
Q316 .1985 .2700 .1811 .2269 -.0146
Q304 .1069 .1089 .3102 .1757 .0824
Q309 Q307 Q303 Q308 Q316
Q309
Q307
Q303
Q308
1.0000
.3073
.3398
.0111
1.0000
.0267
.1101
1.0000
-.0199 1.0000
Q316 .2207 .0954 .1276 .1359 1.0000
0304 .0939 .0015 -.0240 .1769 .0097
Reliability Analysis: Alpha = .8550
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44
Analyses of Variance
An analysis of variance (ANOVA) was conducted with the dependent
variables of the ATSS coding dimensions (sum of utterances across the 7 segments
of the control scenario for each participant on each coding category) for the control
tape to examine whether the random assignment into the two experimental
conditions: Encountering Older Adults (OA) and Encountering Younger Adults
(YA) were truly random. No significant differences were found in the coding
categories on the control tape except for the dimension of Anger Intensity.
Participants who were assigned to the Encountering YA condition were more likely
to have higher anger intensity on the control tape than those who were assigned to
the Encountering OA condition (p=.OI). This result is difficult to interpret and is
likely to have happened by chance. It is therefore important to be cautious when
interpreting results comparing between the two groups on the dimension of Anger
Intensity in subsequent analyses.
Subsequent analyses were conducted for the two experimental scenarios only.
Scores were calculated as the sum of utterances across the 14 segments of the 2
scenarios for each participant on each coding category except for the categories of
Verbal Respect and Identification of Positive Attributes where only the 7 segments
from Scenario 2 were summed due to the low frequency of responses of these two
dimensions in Scenario 1 (see Table 5). Overall, participants were more likely to
identify negative attributes (e.g. “those people are so slow and retarded and should
be put away”) toward the people they encounter on the tape when they were in the
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45
Encountering OA condition (M=1.30, SD= 1.64) than when they were in the
Encountering YA condition (M=.13, SD=.49) (F=23.9, df=l, 100, p<.001).
Participants were also more likely to identify the age (e.g. “old”, “elderly”) of the
people they encounter on the OA tape (M=4.38, SD=3.04) than on the YA tape
(M=.46, SD=1.02) (F=77.5, df=l, 100, pc.001) (see Figure 2).
On a more positive note, participants were more likely to give non-personal
excuses (e.g. “he’s probably running late”) when they were encountering OA
(M=1.40, SD=.68) versus when they were encountering YA (M=.63, SD=.91)
(F=4.42, df=l, 100, p=.04). There is also a trend that subjects were more likely to
voice annoyance (e.g. “I’m so frustrated”) toward the young adults on the tape
(M=4.40, SD=3.79) versus the older adults (M=3.08, SD=3.70) (F=3.19, df=l, 100,
p=.08)(see Table 13 and Figure 2).
Table 13. Table of Scores for Overall Effects
Category_________________Condition__________ Mean_______ SD_____Sig.
Negative Attributes Older Adults 1.30 1.64
Younger Adults 0.13 0.49 <.001*
Identify Age Older Adults 4.38
3.04
Younger Adults 0.46 1.02 <.001*
Non-Personal Excuse Older Adults 1.40 0.68
Younger Adults 0.63 0.91 .04*
Annoyance Older Adults 3.08 3.70
Younger Adults 4.40 3.79 .08
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46
Table 13. (continued)
Category Condition Mean SD Sig.
Positive Attributes Older Adults .40 .76
Younger Adults .19 .66 .14
Sadness/Pity/Guilt Older Adults 1.60 1.86
Younger Adults 1.27 1.40 .31
Physical Respect Older Adults 2.44 1.95
Younger Adults 2.06 2.14 .35
Verbal Aggression Older Adults 1.96 1.87
Younger Adults 2.31 2.53 .43
Verbal Respect Older Adults 2.36 1.69
Younger Adults 2.38 1.50 .69
Anger Intensity Older Adults 3.52 2.05
Younger Adults 3.69 2.83 .73
Physical Aggression Older Adults 1.42 1.18
Younger Adults 1.42 1.78 .99
♦Statistically significant (p<.05)
Figure 2. Encountering OA versus Encountering YA conditions
Neg. A tt* Identify Non-pers Annoy-
Age* excuse* ance
♦Statistically significant (pc.05)
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47
As elaborated earlier, a one-dimension attitudinal bias score was computed
for each participant according to the scores on the FAQ following an SEM
procedure. High and Low attitudinal bias groups were formed for those who were in
the Encountering OA condition. Median split yielded N=21 in the High bias group
and N=29 in the Low bias group. ANOVA revealed that those participants who have
a High level of biased attitude toward older adults displayed significantly higher
amounts of annoyance (M=4.43, SD=4.84) (F=5.23, df=l, 48, p=.03) and gave lower
frequency of non-personal excuses (M=.92, SD=.22) (F=5.48, df=l, 48. p=.02)
toward older adults than those who have a Low level of biased attitudes (Annoyance:
M=2.10, SD=2.19; Non-personal Excuses: M=1.84, SD=.84) (see Table 14 and
Figure 3).
Table 14. Table of Scores for Attitudinal Biases (OA condition only)
Cateaorv Bias GrouD Mean SD Sig.
Annoyance High 4.43 4.84
Low 2.10 2.19 .03*
Non-Personal Excuse High 0.92 0.22
Low 1.84 .84 .02*
Identification of Age High 5.00 3.38
Low 3.93 2.74 .22
Negative Attributes High 1.62 1.77
Low 1.07 1.53 .25
Physical Respect High 2.10 1.87
Low 2.69 2.00 .29
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48
Table 14. (continued)
Category Bias Group Mean SD Sig.
Sadness/Pity/Guilt High 1.90 1.76
Low 1.38 1.93 .33
Verbal Respect High 2.00 1.52
Low 2.45 1.80 .36
Anger Intensity High 3.81 2.25
Low 3.31 1.91 .40
Verbal Aggression High 2.19 2.09
Low 1.79 1.72 .47
Positive Attributes High .48 .98
Low .34 .55 .55
Physical Aggression High 1.33 1.20
Low 1.48 1.18 .66
*Statistically significant (p<.05)
Figure 3. High/Low Attitudinal Biases toward OA (Encountering OA condition only)
Annoyance* Non-pers excuse*
*p<.03
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49
Based on the most reliable items on the FP scores (16 out of 22 items),
descriptive statistics revealed a bimodal distribution, which led to the decision to
divide the scores into High (N=24) and Low (N=26) groups. Subsequent analyses
were conducted comparing these two groups. When encountering older adults in the
ATSS scenarios, participants who were low in filial piety exhibited significantly
higher amounts of verbal aggression (M=2.50, SD=2.15) (F=4.08, df=l, 48, p=.05)
than those high in filial piety (M=1.28, SD=1.41). A trend was found for those low
in filial piety toward verbalizing more negative attributes (M=2.00, SD=2.43)
(F=3.77, df=l, 48, p=.06), age identifications (M=5.06, SD=3.70) (F=3.83, df=l, 48,
p=.06) and feelings of sadness/pity/guilt (M=2.22, SD=2.24) (F=3.72, df=l, 48,
p=.06) toward the older adults they encounter on the tapes than those high in filial
piety (Negative Attributes: M=.83, SD=.79; Identifications of Age: M=3.06, D=2.26;
Sadness/Pity/Guilt: M=1.06, SD=1.26). An unexpected finding in the Encountering
OA condition is that participants with low filial piety were found to provide more
non-personal excuses (M=.56, SD=.92) (F=4.97, df=l, 48, p=.03) toward the older
adults than those high in filial piety (M=.00, SD=.24)(see Table 15 and Figure 4).
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50
Table 15. Table of Scores for Filial Pietv (OA condition only)
Category FP Group Mean SD Sig,
Negative Attributes Low 2.00 2.43
High 0.83 0.79 .06
Identify Age Low 5.06 3.70
High 3.06 2.26 .06
Sadness/Pity/Guilt Low 2.22 2.24
High 1.06 1.26 .06
Verbal Aggression Low 2.50 2.15
High 1.28 1.41 .05*
Non-Personal Excuse Low 0.56 0.92
High 0.00 0.24 .03*
Anger Intensity Low 4.22 1.93
High 3.17 2.28 .14
Verbal Respect Low 1.72 1.36
High 2.28 1.49 .25
Physical Respect Low 2.28 1.74
High 3.06 2.48 .29
Annoyance Low 3.78 3.12
High 2.61 4.55 .38
Positive Attributes Low .28 .46
High .50 1.04 .41
Physical Aggression Low 1.50 1.04
High 1.28 1.18 .55
♦Statistically significant (p<.05)
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51
Figure 4. High versus Low Filial Pietv
4-'
■ Low FP
□ High FP
Neg. att Age SPG V. agg* Non-pers
excuse*
*p<=.05
An analysis was conducted to look at the possible association between
ethnicity and the subjects’ responses on the ATSS manipulation and on the Filial
Piety Scale. No significant differences were found between the 4 ethnic groups
(Whites/Caucasians, Asian Americans, Latino/a, Other) overall in their responses to
the experimental conditions in any of the coding categories. However, Asian
Americans (M=71.85, SD=12.27) scored significantly higher than
Whites/Caucasians (M=58.59, SD=11.95) on the Filial Piety Scale (F=5.16, df=3,
p=.001). No other differences were found between the other ethnic groups (see Table
16 and Figure 5).
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52
Table 16. Mean Filial Pietv Scores for Ethnic Groups
Ethnic group______________ Filial Pietv Score_____
Asian-American
White/Caucasian
Latino/a
Other
71.85*
58.59*
64.02
65.96
♦Significant at p=.00l.
Figure 5. Mean Filial Pietv Scores for Ethnic groups
■FP scores
5 5 -
n i k
i i i i
Asian- W hite* Latino/a Other
Am*
*p=.001.
On the demographics questionnaire, participants were asked if they have ever
lived or worked with the elderly. For those who were assigned to the Encountering
OA condition, 33 participants answered Yes, and 17 answered No. Unexpectedly,
ANOVA revealed that those subjects who have lived or worked with older adults
were significantly more likely to respond with higher levels of anger intensity
(M=4.00, SD=1.92)(F=5.83, df=l, 48, p=.02) toward the older adults in the ATSS
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53
scenarios than those who have never lived or worked with older adults (M=2.59,
SD=2.03) (see Table 17 and Figure 6). None of the other coding categories was
significant.
older adults
Cateeorv Lived/Worked w/OA? Mean SD Sig.
Anger Intensity Yes 4.00 1.92
No 2.59 2.03 .02*
Identification of Age Yes 4.79 2.86
No 3.59 3.30 .19
Non-Personal Excuse Yes .21 .55
No .47 .87 .21
Positive Attributes Yes .48 .87
No .24 .44 .27
Physical Respect Yes 2.24 1.80
No 2.82 2.21 .32
Sadness/Pity/Guilt Yes 1.79 1.88
No 1.24 1.82 .33
Verbal Aggression Yes 2.09 1.79
No 1.71 2.05 .50
Verbal Respect Yes 2.15 1.54
No 2.47 1.97 .53
Negative Attributes Yes 1.39 1.66
No 1.12 1.65 .58
Annoyance Yes 3.27 4.02
No 2.71 3.06 .61
Physical Aggression Yes 1.42 1.03
No 1.41 1.46 .97
♦Statistically significant (p<.05)
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54
Figure 6. Mean Anger Intensity for Encountering OA condition only
Lived/Worked w/OA
Yes No
Lived/Worked w/OA?
p<.05
As mentioned earlier, the construct of knowledge of aging and the elderly
was operationalized by 17 of the 25 items on the KAE questionnaire. ANOVAs were
conducted to compare the High (N=22) and Low (N=28) Knowledge groups in the
Encountering Older Adults condition. No significant differences were found in any
of the coding categories for the High and Low Knowledge groups. No significant
differences were found in attitudinal bias scores between the High (M=3.64,
SD=2.06) and Low (M=3.00, SD=2.37) Knowledge groups (F=.993, df=l, 48,
p=.324). Finally, no significant differences were found in filial piety scores between
the High (M=48.32, SD=15.15) and Low (M=45.14, SD=9.73) Knowledge groups
(F=.808, df=l, 48, p=.373).
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55
Summary of Results
To summarize the findings from this study, the hypothesis that participants
who encountered older adults on the ATSS tapes would have more negative
cognitions than those who encountered younger adults on the tapes was partially
supported. More specifically, participants were significantly more likely to invoke
negative attributions and identify the age group of the persons on the tapes if they
were encountering older adults as opposed to younger adults. However, on a more
positive note, participants were more likely to give non-personal excuses to the older
adults they encountered on the tapes than to the younger adults. Further, participants
were more likely to express annoyance toward younger adults on the tapes than
toward older adults. That is, despite the above more negative findings on the
Encountering OA tapes, participants seemed to express more tolerance toward older
adults than toward younger adults.
The hypothesis which stated that, for the participants who encountered older
adults on the tapes, those who have higher levels of filial piety would express fewer
negative cognitions than those who have less filial piety, was supported. Results
showed that participants who had lower level of filial piety were more likely to
verbalize higher amounts of verbal aggression, negative attributions, age
identifications, and sadness/pity/guilt toward the older adults they encountered on the
tapes than those who had higher level of filial piety. These results suggest that
participants who were low in filial piety were more likely to verbalize ageist,
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56
aggressive, or pitying statements toward the older adults on the tapes than those who
were high in filial piety.
Given that the construct of filial piety originated from Asian cultures, it was
of interest to examine whether ethnicity was associated with both the participants'
cognitions when they responded to the ATSS procedure and their levels of filial
piety. No significant difference was found on any of the ATSS coding dimensions
among the different ethnic groups. However, Asian Americans were found to have
significantly higher scores on the Filial Piety scale than Whites/Caucasians. This
result suggests that responses on the Filial Piety Scale did not influence the way they
responded when they encountered OA or YA in the ATSS scenarios.
The hypothesis that participants who have less attitudinal biases and higher
level of knowledge of aging on the self-report questionnaires would have less
negative cognitions toward the older adults on the ATSS procedure than those who
have more attitudinal biases and lower level of knowledge was partially supported.
Results indicated that participants who had higher amounts of attitudinal biases
against the elderly verbalized more annoyance toward, and gave fewer non-personal
excuses to, older adults they encountered on the tapes than those who were less
biased against the elderly. However, no significant differences were found in any of
the coding dimensions between those who had higher amounts of knowledge of
aging and those with lower amounts of knowledge. Further, no significant
differences were found in attitudinal biases or filial piety between those participants
with higher and lower amounts of knowledge of aging.
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57
Finally, it was hypothesized that participants who have lived or worked with
older adults would have less negative cognitions toward older adults they
encountered on the tapes than those who have not. This hypothesis was not
supported. In fact, participants who said they have lived or worked with older adults
were more likely to have higher amounts of anger toward the older adults they
encountered on the tapes than those who have never lived or worked with older
adults. This is an unexpected finding since it was hypothesized that familiarity with
older adults increases positive cognitions toward them. Maybe contact per se can
have negative effects on future interactions. However, this finding is difficult to
interpret in the absence of information on the type, length, and quality of interaction
between the participants and older adults in real life.
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58
Discussion
The current research study presents information on the way young adults
think about older adults by providing insight into people’s thoughts when they
encounter older adults in different everyday situations using the ATSS paradigm.
Scenarios ranged from having the participants be inconvenienced by the persons on
the tape, to having them help those they encounter.
Overall comparisons between the two experimental conditions
This study found that young adults’ cognitions toward older adults in
simulated situations could be seen as both negative and positive. Young adults were
more likely to identify the age of an older person and more likely to invoke negative
attributes of aging when they encountered older adults versus younger adults. This
result is in agreement with previous studies (e.g. Kite & Johnson, 1988; Slotterback
& Saamio, 1996) in that attitudes toward older adults are generally thought to be
more negative than attitudes toward younger adults.
According to Kite and Johnson’s (1988) meta-analysis of 43 previous studies,
older people were judged more negatively than younger people when individuating
information was not provided about the target person (i.e. a generalized persona of
an older adult was used). Results from the present study suggests that it is possible
the participants verbalized more negative attributes toward the older adults on the
tapes because these targets were “generic”, in the sense that these older adults were
presented without individuating information, so that the participants might have
responded in a generalized manner. That is, if the scenarios included targets such as
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59
“your grandfather” or “your elderly neighbor”, their responses may have been more
positive.
In addition, Slotterback and Saamio (1996) found that people were more
likely to reveal a more negative view of older adults when they were asked to
generate their own descriptors in an open-ended sentence completion task versus a
close-ended answering task. According to these authors, people have a tendency to
focus on common stereotypes of both older adults (which tend to be more negative)
and younger adults (which tended to be more positive). Perhaps the format of the
open-ended ATSS think-aloud procedure used in this study contributed to eliciting
more negative responses than if a more closed-ended procedure was used.
Alternatively, Kite and Johnson (1988) found that when participants
evaluated both the younger and the older adult targets, they were more likely to
evaluate the older adults more negatively. Since the present study was a between-
subject design (such that the participants were only asked to respond to either older
adults or young adults), it may have lessened the negative responses they would
otherwise have given if they were asked to respond to both conditions (within-
subject design). That is, if this study were to compare participants who only
responded to the Encountering Older Adults condition and those who responded to
both the Encountering Older Adults and Younger Adults condition, results may
reveal that those who responded to both conditions had more negative cognitions
toward the older adults than those who only responded to the older adults condition.
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60
A somewhat unexpected finding was that participants were more tolerant
toward older adults than younger adults on the tapes. This result suggests that the
contexts of the scenarios may have been responsible for eliciting such responses. As
Kite and Johnson (1988) suggested, the “question of whether older people are
evaluated more negatively than younger people... should be redefined to determine
the conditions under which differences in perceptions of younger and older people
occur” (p.242). For example, results in previous research have shown that in work-
related experiments, elderly and younger targets were not differentially evaluated.
However, in non-work-related experiments, elderly targets were viewed more
negatively than were younger targets (Kite & Johnson, 1988).
Findings for ATSS coding dimensions and participants’ personal variables
Previous research has not examined the relationship between attitudes toward
older adults and other personality variables of the participants who are making
evaluations or judgments about the elderly. In this study, several individual
difference variables were investigated: attitudinal biases, knowledge of aging and the
elderly, filial piety, ethnicity, and previous experience with older adults. These
personal variables were examined against the 11 cognitive dimensions assessed by
the ATSS procedure.
Annoyance. Participants who reported more attitudinal biases toward older
adults were more likely to express annoyance toward them on the ATSS procedure
than those who were less biased. This finding appears logical since biased attitudes
can suggest a negative feeling of irritability toward the target group of individuals.
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61
Verbal Aggression. Participants who had lower level of filial piety were more
likely to express higher amounts of verbal aggression toward older adults on the
ATSS procedure than those who had higher level of filial piety. This finding also
makes sense since people who are less respectful toward older adults may be less
hesitant to verbalize their aggression toward the target group.
Sadness/Pitv/Guilt. Participants who had lower level of filial piety were more
likely to articulate statements of sadness, pity, or guilt toward the older adults on the
ATSS procedure. Perhaps people who are less respectful are more prone to feel sad,
pity, or guilt toward older adults.
Identification of Negative Attributes and Age. Participants who had lower
levels of filial piety were more likely to verbalize statements that included negative
attributes about old people as well as overtly identify these targets as “old”. Given
the above findings about people who were less respectful toward older adults, this
finding also seems logical.
Anger Intensity. Participants who have lived or worked with older adults
were more likely to have higher amounts of anger in their tone of voice as well as
more frequent use of cursing and/or aggressive language toward older adults on the
ATSS procedure. This result is surprising as well as troubling given the potential for
serious consequences such as elder physical and emotional abuse. Alternatively,
those participants who have lived or worked with older adults might have been more
honest in their expressions of anger toward the targets on the tape because they felt
more comfortable interacting with this population. Nevertheless, it is unclear from
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62
this study the conclusions that can be drawn. More research in this area is needed to
investigate the positive and negative aspects of living and working with the elderly
and to examine how the type, length, and quality of interactions with older adults can
impact the ways young people think about, and treat, older adults. The current
finding, however, highlights the point that familiarity and contact per se do not
necessary make for positive cognitions. It is possible that people can have extensive
contact with a group and come away feeling more, rather than, less negative toward
them.
Giving of Non-Personal Excuse. Participants who were more biased toward
older adults were less likely to give non-personal excuses to older adults on the
tapes when these targets were getting in the way. This result is logical given that
when a person is biased in his/her attitude toward older adults, he/she is more likely
to commit fundamental attributional error (Ross, 1977). That is, he/she is more likely
to see any shortcoming of the older adults as a personal flaw, and not because of
situational circumstances. Another finding is that participants who had lower level of
filial piety were more likely to give non-personal excuses. This finding is
encouraging because perhaps people who were less respectful were nonetheless able
to attribute the cause of older adults getting in their way to situational circumstances.
No significant findings were obtained for the dimensions of Physical
Aggression, Verbal Respect, Physical Respect, and Identification of Positive
Attributes. The null results of Physical Aggression and Identification of Positive
Attributes are likely to have been caused by the extreme quality of these categories.
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63
That is, Physical Aggression is the most extreme of all the negative cognitions, and
Identifications of Positive Attributes is the most extreme of all positive cognitions.
This is likely to have caused the low frequency of these utterances (as well as the
low internal consistency of these constructs). As mentioned in the Results section,
Physical Aggression was uttered, on average, 1.42 times per participant, and
Identification of Positive Attributes was uttered, on average, .29 times per participant
across both scenarios. If the scenarios had included more extreme contexts, such as,
“an older woman knits you a scarf’, or “an older man spits at your car’’, the above
categories may have been elicited more often.
As for the dimensions of Verbal and Physical Respect, one reason that no
significant differences were found may be due to the contexts of the scenarios.
Perhaps participants were prone to express respect based on the contexts of the
scenarios regardless of personal characteristics (such as the ones measured in this
study). For example, many of the participants felt sympathetic toward the older man
who tripped over himself and fell down in the middle of the street. In order to find
individual differences in the expressions of respect, perhaps more neutral contexts
are needed, such as the participant is riding a bus with an older adult and the
participant can choose whether or not to give up his or her seat to the older person.
It was surprising that no significant differences were found for the construct
of knowledge of aging. One interpretation is that knowledge about aging truly did
not correlate with the way participants think about older adults, nor was it associated
with whether or not the participants were respectful or have biased attitudes against
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64
them. Alternatively, the instrument used (KAE) may not have been sensitive enough
to detect individual differences of knowledge of aging. Perhaps it is necessary to
construct a better measure that can differentiate between different types of
knowledge of aging (e.g. physical, social, psychological) as well as differentiate to a
better degree the range of amounts of knowledge that people can have. In addition,
items on the KAE may be outdated as it was developed over ten years ago (1990).
Updated and more accurate items should be substituted to increase the validity of this
measure.
The finding that Asian Americans scored significantly higher than
Whites/Caucasians on the Filial Piety Scale seems to contradict the fact that no
significant differences were found between the ethnic groups on any of the coding
dimensions. It is interesting that Asian American were no less disrespectful in the
scenarios than other ethnic groups. It may be because respect and reverence for the
elderly (as expressed in the form of filial piety) is most notably an Asian concept,
and that the FP scale has high face validity, Asian Americans, who knew that they
were stereotyped to be more respectful toward the elderly, answered this
questionnaire in a more positive way (self-presentation bias) than
Whites/Caucasians.
Limitations and Recommendations for Future Research
The present study provides important insights regarding how young adults
perceive older adults in different situations. Even though these scenarios were
simulated, they were able to elicit a range of realistic verbal responses that may
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65
suggest possible intentions for actual behaviors. The advantage of being able to
expose the participants in a controlled, experimental setting also depended on the
ability of the participants to imagine themselves in those situations. Responses from
post-ATSS debriefing suggests that while most of the participants (N=99) were able
to visualize themselves actually in the scenarios, a small number (N=3) did not feel
that the laboratory setting provided sufficient stimuli to help them envision
themselves in those situations. This may have affected the quality of some of the
responses in the study.
Future research using the ATSS paradigm may be able to improve on its
realism by having video-projection or more realistically recorded audiotapes of the
scenarios. This would hopefully increase the external validity of the study without
compromising experimental control. In addition, future research with ATSS can
improve on its generalizability by including more scenarios of different contexts and
situational variables to elicit a wider range of responses. Better-researched coding
dimensions can also be used to capture more succinctly the way participants respond.
This study addressed mostly female USC undergraduate Psychology
students' perceptions about older adults. The scope and generalizability of research
can be improved by replicating the study with more male participants, and by
including people of different ages, ethnicity, and from different geographic areas.
In addition, future studies should focus on the type, length, and quality of
previous interactions between the participants and older adults in the community, as
well as the type and quality of knowledge the participants have about aging and the
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66
elderly. Other personal variables such as family composition, social values, strength
of ageist and other stereotypes, should be studied in conjunction with the ATSS
procedure.
In sum, the present study illustrated that young adults' perceptions about
older adults are complex and not well understood. The use of the ATSS paradigm
complemented self-report questionnaires in understanding this phenomenon. This
study helped to illustrate that more enriched data can be collected, and more complex
conclusions can be drawn, when we study the cognitions people have during
simulated situations in conjunction with the use of self-report questionnaires.
Subsequently, unexpected findings were revealed, such as previous contact do not
necessary correlate with more positive cognitions toward older adults. In addition to
advancing the research in attitudes toward older adults, this study adds to the body of
knowledge that has been accumulating using the ATSS paradigm (Davison et al.,
1997) by demonstrating that this paradigm is a useful tool in examining ageist
attitudes and cognitions of young adults. It is hoped that the results from this study
can spur researchers to think about the possible personal and situational variables in
which younger adults may have more negative (or positive) cognitions toward older
adults. Finally, these findings may help suggest ways in which young adults can be
made more aware of the importance of age-sensitivity in real life situations.
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67
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Appendix A
Content of ATSS Experimental Tapes
Encountering younger adults. Scenario 1
Segment 1
It’s Monday morning, and you wake up to the sound of the alarm clock next to your
bed. You look at the clock and it says 9 am. You get up and get ready to go to school
for a class at 10. It usually takes half an hour for you to drive to school. Then, as
you’re leaving home, you realize that you forgot about the meeting you scheduled
with your professor. You are supposed to meet with him at 9:45. You check your
watch and it’s already 9:30.
Segment 2
You figure you might just make it to the meeting. After all, when the traffic is good,
it is possible to drive to school in 15 minutes. You get into your car and begin
driving. You’re on the freeway now and the traffic seems relatively light. The
problem however, is the person driving in front of you. He is weaving left and right
in the lane and driving quite slowly considering there is no one in front of him. You
try to overtake him, but the cars next to you are going by too fast.
Segment 3
You’re finally able to pass this slow car, and in your rear view mirror, you’re able to
catch a glimpse of the person driving it. It looks like a guy you have seen in one of
your classes. He has on a baseball cap and a pair of thick glasses and he has both
hands on the steering wheel.
Segment 4
You get to school just in time for the meeting and you have just had your class. It’s
time for lunch. You’re really hungry and your stomach is growling, but you realize
that you only have a dollar in your wallet. You walk quickly to the ATM by the food
court. Luckily, you are the only person waiting in line. The girl at the machine
seems to be having trouble with using the ATM. She is punching the keypad and
trying to deposit a check. You have been waiting for 5 minutes.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
74
Segment 5
She finally leaves the ATM and you are able to get some money for lunch. You go
into the food court and buy some food that you finish quickly. It’s now time to go to
the library to study. As you walk across campus, you see a guy crossing the street in
front of you carrying a lot of books. He trips over himself and falls onto the ground.
Segment 6
You have been studying in the library for 2 hours and you’re ready to go home.
You’re making dinner tonight but there is nothing in your fridge. So you gather up
your stuff and drive to the grocery store. You pick up everything you need and line
up to pay. The young girl at the head of the line is arguing with the cashier about the
price of one of the items she bought.
Segment 7
It’s been a long day and you’re just glad to be home. You settle down on the couch
for some good TV and eat the dinner that you have just made. Let’s hope tomorrow
isn’t as crazy as today!
Encountering younger adults. Scenario 2
Segment 1
It’s 10 o’clock on Saturday morning- your day to earn some spending money and
volunteer for the community. You start the day by driving to Trader Joe’s two blocks
away. It’s a relaxing way to earn money, just punching in numbers and bagging
groceries.
Segment 2
You are now at your regular register. There is a steady flow of customers buying the
usual items: milk, juice, frozen dinners. Then a really tired looking guy comes up to
your register with a huge basket of food. You punch in the prices for all the items
and tell the guy that he owes $50.35. He gulps and says, “Wow! I don’t have that
much money with me. I only have a 20 and I don’t have my check book or credit
cards.”
Segment 3
You take out half of the food items and subtract almost $33 from his bags. You take
the guy’s $20 bill and gave him back some change...(pause). You’ve been working
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
75
for 4 hours and it’s now time to leave. You are a JEP volunteer this semester. You
figure it’s a good way to meet new people and give back to the community, plus it
looks good on your resume.
Segment 4
Originally, you wanted to work with the kids in the local schools, but the positions
were all filled. So you’ve taken a position at the local physical rehab center. You
are working with young and middle-aged adults who have been in accidents and
need someone to cheer them up while they do their daily exercise.
Segment 5
You arrive at the physical rehab center and are greeted by the receptionist. You
take the elevator to the second floor and enter into the physical therapy area. Today
your task is to help transport the clients in wheelchair to and from physical therapy.
Segment 6
It’s been a demanding 3 hours and you’re glad it’s time to go home. As you head
toward your car in the parking lot, you see one of the clients you worked with today.
He is being wheeled by his girlfriend. He waves at you, greets you warmly, and
thanks you for helping him today.
Segment 7
As you drive home, you think about all that you’ve done. You know some of your
friends are also volunteering for JEP today. You wonder how their day has been
compared to yours.
Encountering older adults. Scenario 1
Segment 1
It’s Monday morning, and you wake up to the sound of the alarm clock next to your
bed. You look at the clock and it says 9 am. You get up and get ready to go to school
for a class at 10. It usually takes half an hour for you to drive to school. Then, as
you’re leaving home, you realize that you forgot about the meeting you scheduled
with your professor. You are supposed to meet with him at 9:45. You check your
watch and it’s already 9:30.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
76
Segment 2
You figure you might just make it to the meeting. After all, when the traffic is good,
it is possible to drive to school in 15 minutes. You get into your car and begin
driving. You’re on the freeway now and the traffic seems relatively light. The
problem however, is the person driving in front of you. He is weaving left and right
in the lane and driving quite slowly considering there is no one in front of him. You
try to overtake him, but the cars next to you are going by too fast.
Segment 3
You’re finally able to pass this slow car, and in your rear view mirror, you’re able to
catch a glimpse of the person driving it. It’s an old man with lots of white hair and
a pair of thick glasses. He’s wearing a brown shirt and has both hands on the steering
wheel.
Segment 4
You get to school just in time for the meeting and you have just had your class. It’s
time for lunch. You’re really hungry and your stomach is growling, but you realize
that you only have a dollar in your wallet. You walk quickly to the ATM by the food
court. Luckily, you are the only person waiting in line. The elderly woman at the
machine seems to be having trouble with using the ATM. She is punching the
keypad and trying to deposit a check. You have been waiting for 5 minutes.
Segment 5
She finally leaves the ATM and you are able to get some money for lunch. You go
into the food court and buy some food that you finish quickly. It’s now time to go to
the library to study. As you walk across campus, you see an old man with a cane
crossing the street in front of you. He trips over himself and falls onto the ground.
Segment 6
You have been studying in the library for 2 hours and you’re ready to go home.
You’re making dinner tonight but there is nothing in your fridge. So you gather up
your stuff and drive to the grocery store. You pick up everything you need and line
up to pay. The silver-haired older woman at the head of the line is arguing with the
cashier about the price of one of the items she bought.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
77
Segment 7
It’s been a long day and you’re just glad to be home. You settle down on the couch
for some good TV and eat the dinner that you have just made. Let’s hope tomorrow
isn’t as crazy as today!
Encountering older adults. Scenario 2
Segment 1
It’s 10 o’clock on Saturday morning- your day to earn some spending money and
volunteer for the community. You start the day by driving to Trader Joe’s two blocks
away. It’s a relaxing way to earn money, just punching in numbers and bagging
groceries.
Segment 2
You are now at your regular register. There is a steady flow of customers buying the
usual items: milk, juice, frozen dinners. Then a really tired looking older man
comes up to your register with a huge basket of food. You punch in the prices for all
the items and tell the man that he owes $50.35. He gulps and says, “Wow! I don’t
have that much money with me. I only have a 20 and I don’t have my check book or
credit cards.”
Segment 3
You take out half of the food items and subtract almost $33 from his bags. You take
the man’s $20 bill and gave him back some change...(pause). You’ve been working
for 4 hours and it’s now time to leave. You are a JEP volunteer this semester. You
figure it’s a good way to meet new people and give back to the community, plus it
looks good on your resume.
Segment 4
Originally, you wanted to work with the kids in the local schools, but the positions
were all filled. So you’ve taken a position at the local senior rehab center. You are
working with older adults who have been in accidents and need someone to cheer
them up while they do their daily exercise.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
78
Segment 5
You arrive at the senior rehab center and are greeted by the receptionist. You take
the elevator to the second floor and enter into the physical therapy area. Today your
task is to help transport the clients in wheelchair to and from physical therapy.
Segment 6
It’s been a demanding 3 hours and you’re glad it’s time to go home. As you head
toward your car in the parking lot, you see one of the clients you worked with today.
He is being wheeled by his wife. He waves at you, greets you warmly, and thanks
you for helping him today.
Segment 7
As you drive home, you think about all that you’ve done. You know some of your
friends are also volunteering for JEP today. You wonder how their day has been
compared to yours.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
79
Appendix B 1
Demographics Questionnaire
Directions; Please fill out this short questionnaire. Please be advised that all the
information you provide is completely confidential and will not be used to
personally identify you. The last four digits of your Social Security number will
serve as your subject number. Do not write your name on this questionnaire.
Thank you.
1. Last four digits of your Social Security number:___________(subject number)
2. Gender: Male_____ Fem ale_____
3. Race/Ethnicity (please check one or more of the following categories):
African-American/Black _____
Asian-American/Pacific Islander _____
Caucasian/White _____
Latino/Latina _____
Middle Eastern _____
Native American _____
Other (please specify)_________________
3. Age:_____
4. Year in college: Freshman_________
Sophomore _____
Junior_______ _____
Senior____________
Other (please specify)__________________
5. Have you ever lived/worked with the elderly? Y es No_____
If so, in what capacity? (e.g. live with grandparents, volunteer in senior center,
participate in meals on wheels program)
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
80
Appendix B2
Facts of Aging Quiz (FAQ)
Directions; Listed below are a number of statements about which people often have
different opinions. You will discover that you agree with some, that you disagree with
others. Please read each statement carefully, then circle either “T” for True, or “F ’ for
False. Answer every statement even if you have to guess at some.
T F 1. The majority of old people (past age 65) are senile (i.e. defective memory,
disoriented, or demented).
T F 2. All five senses tend to decline in old age.
T F 3. Most old people have no interest in, or capacity for, sexual relations.
T F 4. Lung capacity tends to decline in old age.
T F 5. The majority of old people feel miserable most of the time.
T F 6. Physical strength tends to decline in old age.
T F 7. At least one-tenth of the aged are living in long-stay institutions
(i.e. nursing homes, mental hospitals, homes for the aged, etc.).
T F 8. Aged drivers have fewer accidents per person than drivers under age 65.
T F 9. Most older workers cannot work as effectively as younger workers.
T F 10. About 80% of the aged are healthy enough to carry out their normal
activities.
T F II. Most old people are set in their ways and unable to change.
T F 12. Old people usually take longer to learn something new.
T F 13. It is almost impossible for most old people to learn new things.
T F 14. The reaction time of most old people tends to be slower than reaction
time of younger people
T F 15. In general, most old people are pretty much alike.
T F 16. The majority of old people are seldom bored.
T F 17. The majority of old people are socially isolated and lonely.
T F 18. Older workers have fewer accidents than younger workers.
T F 19. Over 15% of the U.S. population are now age 65 or over.
T F 20. Most medical practitioners tend to give low priority to the aged.
T F 21. The majority of older people have incomes below the poverty level
(as defined by the Federal Government).
T F 22. The majority of old people are working or would like to have some kind of
work to do (including housework and volunteer work).
T F 23. Older people tend to become more religious as they age.
T F 24. The majority of old people are seldom irritated or angry.
T F 25. The health and socioeconomic status of older people (compared to
younger people) in the year 2000 will probably be about the same as now.
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81
Appendix B3
Knowledge of Aging and the Elderly questionnaire (KAE)
Directions: Listed below are a number of statements about which people often have
different opinions. You will discover that you agree with some, that you disagree with
others. Please read each statement carefully, then circle either “T” for True, or “F ’ for
False. Answer every statement, even if you have to guess at some.
T F 1. There are more old widowed women than old widowed men in the U.S.
T F 2. Lung diseases are the number one cause of death among the elderly.
T F 3. Of the elderly who live in the community, a majority of them live with one
of their children.
T F 4. Retirement is not a very difficult experience for almost all old people.
T F 5. Among young adults, you find a great many personality types, but there
are relatively few personality types among old people.
T F 6. The prevalence of vision and hearing impairments increases greatly with
age.
T F 7. An older person with a failing memory tends to forget long past events
more so than recent ones.
T F 8. Old individuals who are depressed and passive tend to live longer than
those who are grouchy and easily upset.
T F 9. Older adults tend to have fewer years of formal education than young
adults.
T F 10. Old people are more likely than young adults to have a low socioeconomic
status.
T F 11. Mental abilities decline steadily after age 20.
T F 12. There is a large decrease with age in the speed at which nerves in the body
conduct impulses.
T F 13. Older persons are more likely than younger ones to experience problems
with sleeping.
T F 14. Old people, especially old men, have a lower suicide rate than young
people.
T F 15. Old people are less alike than young people.
T F 16. Due to the effects of aging and illness, there is an irreplaceable decline in
the number of brain cells with age.
T F 17. Old people generally have slower reaction times (i.e. take longer to
respond to a stimulus) than younger people.
T F 18. For those receiving it, Social Security by itself provides an adequate
income for most older people.
T F 19. Over 10% of all aged persons live in long-term health care institutions
(i.e., nursing homes, homes for the aged, mental hospitals, etc.).
T F 20. People do not get more religious as they age.
T F 21. Older workers are less efficient and have more on-the-job accidents than
younger workers.
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82
T F 22.
T F 23.
T F 24.
T F 25.
number of years a person is likely to live, as well as the maximum upper
age limit of a human life.
Old people pay very little for health care since Medicare covers almost all
their medical expenses.
Studies indicate that with increasing adult age, there is a decline in sexual
interest and activity.
One of the leading causes for admission to state mental hospitals is menta
disorders associated with old age.
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83
Appendix B4
Filial Piety Scale (FP)
The following items ask you about opinions concerning family relationships. We would like
to know what your opinions are on these items. Please respond according to your own
personal opinion.
For each item, select only one of the following alternatives:
1= Strongly disagree
2= Disagree
3= Somewhat disagree
4= Somewhat agree
5= Agree
6= Strongly Agree
1) Sons and daughters may protest against I 2
being unreasonably scolded by their parents.
2) There is no place under the sun for both I 2
oneself and the enemy of one’s father.
3) If there is a reason for doing so, one may 1 2
rely on an old people’s home to provide
for one’s aged parents.
4) Any sacrifice is worthwhile for the sake 1 2
of filial piety.
5) Sons and daughters should not go to 1 2
faraway places while their parents are
still living.
6) In choosing a spouse, sons and daughters 1 2
need not follow “their parents’ command”.
7) The main reason for sons and daughters I 2
not to do dangerous things is to avoid
getting their parents worried.
8) Parents should not interfere with their 1 2
children’s freedom to choose a vocation.
9) The great debt that you have to repay 1 2
your parents is as boundless as the sky.
3 4
3 4
3 4
3 4
3 4
3 4
3 4
3 4
3 4
5 6
5 6
5 6
5 6
5 6
5 6
5 6
5 6
5 6
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84
10) “Rearing sons and daughters to provide 1 2 3 4 5
for oneself in one’s old age” should no
longer be the main purpose of raising children.
11) No matter how their parents conduct 1 2 3 4 5
themselves, sons and daughters must
respect them.
12) After the father has passed away, sons 1 2 3 4 5
and daughters must conduct themselves
according to the principles and attitudes
he followed while he was still living.
13) If there is a quarrel between one’s wife 1 2 3 4 5
and one’s mother, the husband should
advice his wife to listen to his mother.
14) After their parents have passed away, 1 2 3 4 5
sons and daughters do not necessarily
have to finish the business left unfinished
by their parents.
15) “Spreading one’s fame to glorify one’s 1 2 3 4 5
parents” should not be the most important
reason for getting ahead.
16) To worship their ancestors regularly on 1 2 3 4 5
the proper occasions is the primary duty
duty of sons and daughters.
17) To continue the family line is not the 1 2 3 4 5
primary purpose of marriage.
18) Sons and daughters do not necessarily 1 2 3 4 5
have to seek parental advice and may
make their own decisions.
19) Sons and daughters do not necessarily 1 2 3 4 5
have to respect the people respected and
loved by their parents.
20) After children have grown up, all the 1 2 3 4 5
money they earn through their own
labor belongs to themselves, even though
their parents are still living.
6
6
6
6
6
6
6
6
6
6
6
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21) “There is no crime worse than being 1 2 3 4
unfilial.”
22) As a son or daughter, one must obey 1 2 3 4
one’s parents no matter what.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

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Asset Metadata

Creator Fung, Wendy Wing-Han (author)

Core Title Articulated thoughts regarding cognitions toward older adults

School Graduate School

Degree Master of Arts

Degree Program Psychology

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

Tag Gerontology,OAI-PMH Harvest,psychology, cognitive,psychology, social

Language English

Contributor Digitized by ProQuest (provenance)

Advisor Davison, Gerald C. (committee chair), Gatz, Margaret (committee member), Horn, John (committee member)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c16-41694

Unique identifier UC11336777

Identifier 1409586.pdf (filename),usctheses-c16-41694 (legacy record id)

Legacy Identifier 1409586.pdf

Dmrecord 41694

Document Type Thesis

Rights Fung, Wendy Wing-Han

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus, Los Angeles, California 90089, USA