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Clinical decision analysis for effective supervision: a review of the supervisor-supervisee relationship

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Clinical decision analysis for effective supervision: a review of the supervisor-supervisee relationship

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Clinical Decision Analysis for Effective Supervision:
A Review of the Supervisor-Supervisee Relationship

by

Julie L. Melendez

A Thesis Presented to the
FACULTY OF THE USC DANA AND DAVID DORNSIFE
COLLEGE OF LETTERS, ARTS AND SCIENCES
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(APPLIED BEHAVIOR ANALYSIS)

May 2020

Copyright 2020 Julie L. Melendez

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Table of Contents
Abstract .......................................................................................................................................... iii
1.0 Introduction .............................................................................................................................. 1
1.1 Decision Models in the Medical Field .............................................................................. 2
1.2 Decision Models in Applied Behavior Analysis .............................................................. 6
1.3 Ethical Considerations of Decision Making .................................................................... 8
1.4 Supervision Practices in Behavior Analysis .................................................................... 9
2.0 Proposed Methods .................................................................................................................. 15
2.1 Participants and Setting .................................................................................................. 15
2.2 Experimental Design ....................................................................................................... 15
2.3 Procedures ........................................................................................................................ 15
2.3.1 Response Measurement and Interobserver Agreement ........................................... 15
2.3.2 Knowledge Surveys and Preference Assessment .................................................... 16
2.3.3 Baseline ................................................................................................................... 27
2.3.4 Utilization of the Decision Model ........................................................................... 17
2.3.5 Social Validity ......................................................................................................... 18
3.0 Discussion ............................................................................................................................... 19
References ..................................................................................................................................... 26

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Abstract

Clinical decision analysis assists practitioners across fields of study in determining the best
course of action given the specified circumstances. Clinicians are able to utilize decision models
to identify a problem and guide them to suggestions for a potential next step that is based on the
scientific literature of their discipline. Within the field of behavior analysis, decision models
have thus far demonstrated effectiveness for aiding the visual inspection of client progress
graphs, identifying appropriate measurement procedures for a behavior, and suggestions for
working in an interdisciplinary treatment team. However, given the importance of the
supervision of mentees, a clinical decision support system would be beneficial for evaluating the
quality of supervision. Behavior analysts often have the additional responsibility of providing
supervision to Registered Behavior Technicians (RBT). At present, there are limited supports
that aim to provide supervisors with evidence-based tools to assist them in expanding their
problem-solving repertoire. In the present review, the authors propose a decision model that will
recommend areas of focus to improve supervision procedures in regard to mentoring a
supervisee. The present review suggests evaluating supervisor/supervisee dyads to determine the
effectiveness of a decision model. It is hypothesized that after the use of the decision model,
supervisors will provide higher quality supervision, as determined by a supervision assessment.
This may demonstrate the utilization of the decision model as a tool for a complex, but valuable,
system that will create a higher standard of practice among BCBAs.

Keywords: clinical decision analysis, supervision standards, mentorship, ethics

1
Clinical Decision Analysis for Effective Supervision:
A Review of the Supervisor-Supervisee Relationship
There are various fields of study that require a mentor to make a decision on behalf of a
mentee. Moreover, the quality of the choices made by a mentor will ultimately impact the life of
a mentee. In clinical practice, when making a decision that will guide the treatment of an
individual, there should be a method of analysis that can be found at the root of that decision.
Optimal decision making should be based on the individual’s needs, learning history, and
environment. Clinical Decision Support Systems (CDSS) have been created with that standard of
care in mind. The purpose of decision models is to be utilized by clinicians as a tool to help
guide their clinical decision making. Moreover, decision models can be applied to fields that
require methodological decision making under complex circumstances.
Decision theory is the study of the types of decisions individuals, or groups, make and
how they make them (Hansson, 1994). Decisions range from simple, “Should I wear a thick coat
today?”, to complex, “What policy should be implemented to reduce nationwide
homelessness?”. Furthermore, an evaluation of options is conducted in order to determine what
pathways are available and how one will respond when faced with different options. The
distinction must be made between normative, rational, and descriptive decision theories.
Normative decision theory encompasses those decisions that should be made, given the
circumstances (Hansson, 1994). As an example, normative decisions would focus on fixed
normative issues. Normative issues remain consistent and often refer to situations in which there
is limited information about the context (Hansson, 1994). Within normative decision theory,
there is also a distinction between rational decision making. Rational decision making follows a
rational pathway that would most likely lead to success (Hansson, 1994). In other words, there is

2
criteria that leads to expected favorable outcomes (i.e., success). Decision models are created to
allow an individual to arrive to a decision in such a way that is based on literature and follows
rational decision theory to be successful (Van Houten & Axelrod, 1993). Descriptive decision
theory focuses on how decisions are made in reality (Hansson, 1994). For instance, although a
rational pathway may have been identified, a descriptive decision may be implemented through
the use of other variables, even if they do not follow rationality. It is important to point out that
the aforementioned concepts are blurred in the literature (Hansson, 1994). This may be due in
part to the complexity of decision analysis and the examples given in the literature. However,
decision models are useful tools created to assist with normative decisions by recommending
rational decision pathways.
Decision Models in the Medical Field
Creating a decision model consists of working through a multistep process that begins
with defining the decision problem (Van Houten & Axelrod, 1993; Watts, 1989). The following
steps consist of successful and unsuccessful outcomes: (1) describing alternative approaches and
their consequences, (2) estimating and analyzing probabilities of success, (3) estimating costs,
and (4) selecting a preferred strategy (Van Houten & Axelrod, 1993; Watts, 1989). One study
examined the effectiveness of a clinical decision model for determining preventive care for
individuals and found it to be effective in determining treatment of dyslipidemia (Souza et al.,
2011). In addition, there is evidence in support of decision models to increase practitioner
performance via knowledge comprehension (Haynes & Wilczynki, 2010).
As Haynes and Wilczynki (2010) mention in their review, the components of CDSS in
the medical field consist of: (1) manual entry of patient characteristics, (2) patient characteristics
matched to a computerized knowledge base, (3) the CDSS algorithm using the patient

3
information and knowledge-based system to generate patient specific assessments and/or
recommendations, and (4) recommendations being delivered to the healthcare provider. Through
this process, the CDSS is able to provide support to the medical professional that is based on the
patient’s characteristics and link it with the appropriate recommendations. The purpose of such a
review is to examine the effects of using a clinical decision support system across various health
professions. Some of the considerations that the reviewers are examining include the ease of
implementation of a CDSS in regard to fitting into an existing workflow, the necessary training
logistics (i.e., who will train others and how long this process will take), and how the evidence
base for the clinical decision support system will be maintained, among other factors (Haynes &
Wilczynki, 2010). All of the aforementioned considerations are valuable in determining the best
fit for such a tool.
Further evaluation of clinical decision support systems is emphasized in a white paper
that reviews the recommendations of the American Medical Informatics Association (AMIA)
Spring Symposium (Sim et al., 2001). The authors touch on the need to incorporate more
thorough CDSSs called “evidence-adaptive CDSSs” which are able to acclimate more efficiently
to up-to-date evidence from within the research literature and practice-based sources (Sim et al.,
2001). The authors bring a level of awareness to major considerations for CDSS researchers,
developers, evaluators, and implementers, along with policy makers and organizations. Such
recommendations include the need for automatic methods for updating CDSS knowledge bases,
developing more CDSSs for outpatient settings, conducting more evaluations in actual practice
settings, and the establishment of CDSS teams for collaboration and problem-solving (Sim et al.,
2001). Moreover, the authors discuss how patient-directed evidence should be incorporated; the
Internet, while it may provide misinformation to patients, has increased the need for patient

4
involvement. Implementers of CDSSs need to consider the growing involvement patients face in
regard to their treatment and should provide patients and healthcare professionals with systems
that may ultimately lead to better client outcomes (Sim et al., 2001; Alden, Friend, Schapira, &
Stiggelbout, 2014).
Within the medical field, there has been a greater emphasis on allowing for patient
decision-making (Will, 2011; Alden, Friend, Schapira, & Stiggelbout, 2014). This is clearly
portrayed in the requirement of informed consent when treatment is recommended, or patients
are undergoing a procedure. The medical patient has the ability to refuse the treatment and is
therefore an active participant in the medical decisions being made. While the idea of informed
consent has been prevalent for decades, it has recently fallen in line with the broader implications
of patient autonomy (Will, 2011). Patient autonomy encompasses the need for shared knowledge
in regard to medical treatment and respect for patient decision-making. By allowing patients to
have a stake in their own treatment, there may be overarching benefits across various domains.
Physicians would also benefit in understanding that there is a degree of variance among
their patients’ decision-making styles. By evaluating the General Decision-Making Style
Inventory, one could examine the core decision processes and decision regulatory processes of
individuals (Fischer, Soyez, & Gurtner, 2015; Scott & Bruce, 1995). Core dimensions of
decision processes consist of: (1) rational style, (2) intuitive style, and (3) spontaneous style
(Scott & Bruce, 1995). If physicians were to utilize the General Decision-Making Style
Inventory, they would have a clearer indication of what their client’s style is and how to best
approach them about their medical needs. The benefit for patients lies in discovering their own
decision-making style and providing them with a better resource for making informed decisions
about their medical treatments.

5
While some may argue that in a large scale medical environment, it is more cost-efficient
to allow physicians to make all treatment recommendations, this is not necessarily the case once
the data is examined. A study assessed the cost of physician referrals for physical therapy among
Blue Cross-Blue Shield members in Maryland (Mitchell & Lissovoy, 1997). This was compared
to the cost of direct access visits to physical therapists (i.e., without needing a referral from a
physician). This data spanned across four years and each visit was coded using a decision-
making algorithm to determine whether a visit was direct access or physician referral. The
decision-making algorithm facilitated the ability of the team to code the claims more efficiently
and in a systematic way. The results indicated the direct access visits were ultimately more cost-
efficient for the insurance carrier (Mitchell & Lissovoy, 1997). In addition to this, the results of
the study demonstrated that patient involvement in medical treatment will enable larger gains
overall for the patient and potentially for their insurance carrier.
Medical decision aids are similar to practitioner decision models in that they inform the
patient about clinical testing strategies, treatment options (along with potential risks and
benefits), and medication options, among other relevant information (Alden, Friend, Schapira, &
Stiggelbout, 2014; Stankus, 2018). These decision aids are meant to guide patients to allow them
to make informed decisions about their medical treatment, while having a deeper knowledge
base to discuss with their physician. This, in turn, has the ability to lead to better patient
outcomes because it encourages patients to make informed decisions that are more aligned with
their personal preferences (Joseph-Williams et al., 2013). There have been attempts to
incorporate more cultural awareness in the development of such decision aids to address
culturally diverse groups. Based on self-identification of cultural values, this decision aid will
target their presentation of the information to focus more on the patient values and, ultimately,

6
influence decision preparedness (Alden, Friend, Schapira, & Stiggelbout, 2014). In addition to
this, competent patient decision aids are updated as needed with the dissemination of relevant
clinical knowledge (Stankus, 2018). It has been recommended that patient decision aids should
undergo further evaluation to determine the quality of the aid and potentially even reach a
criterion to allow for certification of the decision aid (Joseph-Williams et al., 2013). This study
focused on a Delphi consensus process to determine quality indicators of patient decision aids.
127 professionals with experience in decision aid development and/or research participated in the
voting and collectively determined that there were three main categories of criteria to consider.
These categories included qualifying criteria, certification criteria, and quality criteria, which
would comprise the minimum standards for certifying patient decision aids that would lead to
“minimal risk of harmful bias on patients’ decisions” (Joseph-Williams et al., 2013). The authors
of this proposed criteria point out that there is further analysis of quality standards needed
moving forward.
Decision Models in Applied Behavior Analysis
Within the field of behavior analysis, decisions are made every day that influence the
course of a client’s treatment. Goals and procedures are individualized and require careful
consideration of the variables in the environment that will optimize a client’s development.
LeBlanc, Raetz, Sellers, and Carr (2015) created a decision model for the assessment and
treatment of problem behavior and found it to be a beneficial resource for recommendations for
selecting measurement procedures. Taking into consideration treatment efficacy, it is necessary
to determine appropriate data collection measures and intervention procedures in order for
behavior change to occur. In this instance, decision models are useful for guiding clinical

7
decision making while taking into consideration an individual’s circumstances and environment,
which is the hallmark of behavior analytic work.
Additionally, there have been proposed decision models found in the behavior analytic
literature to assist in problem solving when discrete trial training (DTT) is not demonstrating
effectiveness for a client (Ferraioli, Hughes, & Smith, 2005). The authors propose a model for
considerations when a program is not progressing, along with suggested solutions. The DTT
problem-solving model includes references to further developed decision diagrams. The
additional models are more specific in regard to potential areas for troubleshooting. Such areas
include the lack of skill acquisition, inconsistent progress, increase in problem behavior, and lack
of generalization (Ferraioli, Hughes, & Smith, 2005). The results of this application of clinical
decision analysis leads right back to the treatment evaluation behavior analysts are required to
continuously engage in for the benefit of their clients.
Behavior analysts often work within an interdisciplinary team and in such cases, it is
imperative that members of the team focus on the terminal goals of their clients and work in
unison, despite differing treatment recommendations. A study by Brodhead (2015) attempted to
use a decision model for problem solving through treatment options that may come from diverse
perspectives. With the use of the decision model, the clinicians would find an appropriate way of
discussing distinct opinions on treatment while maintaining professionalism. This would
ultimately lead to a more complete and diverse treatment recommendation for the client.
While proposed usage of decision models in the field of behavior analysis is well
underway, there are limitations as far as the assessment of such models. Two decision models
have been evaluated within Applied Behavior Analysis (ABA) agencies in the context of fading
and discharging services and incorporating adequate generalization practices within treatment

8
(Cameron, Leidt, & Gilliotte, 2019). The former decision model evaluated the recommendations
in regard to fading of services and attempted to improve the quality of the recommendations to
discharge clients. This decision model was successful in the improvement of discharge
recommendations across Board Certified Behavior Analysts (BCBAs; Cameron, Leidt, &
Gilliotte, 2019). The latter decision model was utilized to incorporate more technological
generalization procedures within clients’ treatment goals. Given the various generalization
procedures behavior analysts have available to them, it was identified that there was a lack of
programming for generalization from the onset of treatment. Therefore, this model had an
educational component surrounding the 12 generalization strategies and was effective in
improving the generalization procedures used by the clinicians (Cameron, Leidt, & Gilliotte,
2019; Stokes & Osnes, 1989; Osnes & Lieblein, 2003).
This is further exemplified in an additional study that utilized clinical decision analysis to
teach employees how to accurately conduct a visual analysis of graphed data. Accurate data
analysis is an important aspect of evaluating treatment effectiveness across the spectrum of
professionals working in behavior analysis. Employees in behavior analytic service settings
demonstrated an improvement in accuracy of interpreting graphic displays with the use of the
decision model (Kipfmiller et al., 2019). Beyond these exemplars, there is a limitation as far as
testing the efficiency and scope of a decision model within ABA agencies.
Ethical Considerations of Decision Making
According to Van Houten and Axelrod (1993), a decision model is proposed to guide
clinicians in determining how to select an optimal treatment procedure when faced between
restrictive or nonrestrictive approaches. This area of focus is especially useful considering the
ethical guidelines behavior analysts must uphold when referring to least restrictive treatment

9
(Behavior Analyst Certification Board, 2014). Since the Behavior Analyst Certification Board’s
Professional Code of Conduct has been implemented, it is often the case that behavior analysts
attempt the least restrictive procedures, while intermittently showing ineffective results. The time
consuming practice of only initially choosing least restrictive procedures allows for failed
attempts and stagnates potential effective procedures for a client. Time is one of the main factors
when determining treatment, especially if immediate behavior change is necessary to ensure the
safety of the client or others. It is important to consider the array of factors that contribute to
decision making in this context, such as the distress caused by the procedure, distress caused by
the behavior, and the probability of treatment success (Van Houten & Axelrod, 1993). The
implementation of a decision model in this context is a guide to more effective and consistent
treatment.
Supervision Practices in Behavior Analysis
With the introduction of the Behavior Analyst Certification Board (BACB) in 1998,
standards for clinical training have been established. These requirements comprise the BACB
Professional and Ethical Compliance Code for Behavior Analysts (hereafter referred to as the
BACB Guidelines or the Code; Behavior Analyst Certification Board, 2014). Within the last few
years, Bailey and Burch released the third edition of their book that encompasses the guidelines
and provides case examples as to how the guidelines should be upheld (see Ethics for Behavior
Analysts, 2016). Such requirements include the need for stringent supervision requirements. This
includes an emphasis on the accrual of supervised experience hours. While accumulating
experience hours to sit for the Board Certified Behavior Analyst (BCBA) exam, supervisees
must meet the requirements for appropriate supervised fieldwork.

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It is valuable to consider mentor models that are already standard practice within a well-
established field such as medicine. Recommendations have been made for qualities that
successful mentor-mentee relationships should comprise. As discussed in the medical literature,
supervision practices are key to the career development of an individual. It has been found that
frequency and volume of feedback play a role in the perceived satisfaction that a supervisee has
in regard to their mentoring relationship (Nguyen & Divino, 2007; Fraser, 2016). Furthermore, in
regard to gender of a mentor, the literature indicates that whether gender between the supervisor
and the supervisee is matched may lead to a higher perceived level of success in the relationship
(Levinson, Kaufman, Clark, & Tolle, 1991). With an increased focus on supervisory practices,
there is wider availability of the formation of long-term career relationships. It has been found
that valuable mentorship experiences are a fundamental factor in career specialty decisions
(Healy, Cantillon, Malone, & Kerin, 2012). The medical literature has indicated that a more
enriched supervision experience may result in the future success of the supervisee and further
their careers.
The BACB Fourth Edition Task List is a resource developed by the BACB to familiarize
candidates with items that fall under the umbrella of their scope of practice (Behavior Analyst
Certification Board, 2012a). The BACB Fourth Edition Task List, emphasizes that BACB
candidates must be able to identify contingencies influencing the behavior of supervisees (Item
K-02 of the Fourth Edition Task List, Behavior Analyst Certification Board, 2012a). In addition,
BCBA candidates must be able to conduct competency-based training while designing effective
performance monitoring systems (Items K-03 and K-04 of the Fourth Edition Task List,
Behavior Analyst Certification Board, 2012a). The greatest benefit for supervisees would come
from gaining supervision that shapes the supervisee’s behavior into a successful repertoire that

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will allow them to be effective in their careers. This is the responsibility of both the supervisor
and the supervisee. Therefore, the supervisor and supervisee relationship will bidirectionally be
affected by the quality of supervision experiences.
Once a candidate becomes a Board Certified Behavior Analyst, they are frequently in the
position of supervising direct service staff and individuals who are in the process of completing
requirements to become credentialed behavior analysts. As a BCBA, there are further
supervision ethical requirements that must be upheld. Section 5.0 of the Code, Behavior Analysts
as Supervisors, addresses seven sub codes BCBAs must abide by when functioning as
supervisors. The BACB Guidelines emphasize that behavior analysts only accept an amount of
supervisory activities that will allow them to operate effectively (Code 5.02 of the Compliance
Code, Behavior Analyst Certification Board, 2014). In addition, it is the responsibility of the
supervisor to design effective supervision and training (Code 5.04 of the Compliance Code,
Behavior Analyst Certification Board, 2014). Furthermore, behavior analysts must find a way to
assess their own supervisory activity, such as obtaining feedback from another BCBA or their
supervisee (Code 5.07 of the Compliance Code, Behavior Analyst Certification Board, 2014). As
demonstrated, the Code outlines various aspects of supervision that should be a focus but may be
lacking as far as supervisor adherence. This may in part be due to the lack of explicit supervision
training; supervision training in this sense refers to the training required to effectively mentor a
supervisee (Kazemi, Rice, & Adzhyan, 2019, p. 20).
Initial evidence that an issue has arisen within the supervisor-supervisee relationship is
that the supervisee is not successfully implementing the procedures that the supervisor has put in
place. This ultimately hinders the advancement of the client, and points to a performance
management problem of the RBT. Another underlying problem is whether the supervisee is able

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to address known performance issues with their supervisor. It is often the case that the
supervisor-supervisee relationship is not based on a foundation of well-established rapport,
which is crucial to the development of increased employee performance (Lau & Cobb, 2010;
Sellers, LeBlanc, & Valentino, 2016; Sellers, Valentino, & and LeBlanc, 2016; Turner, Fischer,
& Luiselli, 2016). These circumstances do not allow for the performance improvement of the
supervisee, which in turn effects the ultimate supervisory responsibility of the BCBA. As
Brodhead and Higbee (2012) outline in their study analyzing the importance of ethical
management and supervision, there are overarching benefits to an in-depth analysis of the
organizational systems which contribute to employee performance. With an emphasis in training
and supervision, it is supported that there will be an increase in quality care, further relevant
training for employees, and the field of behavior analysis will be strengthened (Brodhead &
Higbee, 2012; Sellers, LeBlanc, & Valentino, 2016; Sellers, Valentino, & LeBlanc, 2016;
Turner, Fischer, & Luiselli, 2016).
There have been attempts made by the behavior analytic community to encourage the
implementation of effective supervisory practices. One such example can be found in Hartley,
Courtney, Rosswurm, and Lamarca (2016). The authors suggest an apprenticeship model meant
to provide BCBAs with a tool for fulfilling their duties as a supervisor. Hartley et al. (2016)
identified a key factor that may lead to ineffective supervision, that is, the increased supervision
requirements determined by the Behavior Analyst Certification Board (Behavior Analyst
Certification Board, 2012b). Hartley et al. developed an apprenticeship model for their specific
organization which allowed for more effective supervision, that still managed to fulfill the
requirements set forth by the BACB. The implementation of the apprenticeship model led to
more learning opportunities for supervisees, decrease in supervisory effort due to client

13
caseloads, increase in unrestricted experience hours, and a decrease in employee turnover rate
after the completion of experience hours (Hartley, Courtney, Rosswurm, & Lamarca, 2016).
As behavior analysts, supervisors orient their problem-solving skills in regard to function
of behavior, as they do with clients (Sellers, LeBlanc, & Valentino, 2016). Some supervisors fail
to apply this level of assessment of behavior when applied to their supervisory duties. In turn,
their role as a supervisor may be limited in terms of success. Resources and suggestions are
made available to supervisors to assist them in determining how to solve supervision problems
(see Behavior Analyst Certification Board, 2012b; Sellers, LeBlanc, & Valentino, 2016).
However, there is still a gap in research and practice that has not been addressed.
At present, there are limited techniques that aim to provide supervisors with evidence-
based tools to assist them in expanding their problem-solving repertoire. There is a currently a
point being made that suggests that behavior analysts should provide treatment that follows a
standard of care across the field (Van Houten & Axelrod, 1993). Steps should be taken to ensure
that behavior analysts are being trained to become competent clinicians. One example of an
attempt to analyze decision-making repertoires within the context of behavior analytic work, can
be found in Turner, Fischer, and Luiselli (2016). The authors discuss the necessary problem-
solving abilities for success, such as identification of a problem, forming potential solutions to
the problem, deciding to choose one solution over another, and evaluation of the chosen solution
(Turner, Fischer, & Luiselli, 2016). Another attempt to derive the most crucial aspects of
effective supervision can be found in Sellers, Valentino, and LeBlanc (2016). The authors
identify five essential requirements: (1) establishing an effective supervisor-supervisee
relationship, (2) establishing a structured competence evaluation plan, (3) evaluating the effects
of the supervision, (4) incorporating ethics into supervision, and (5) continuing the professional

14
relationship post certification (Sellers, Valentino, & LeBlanc, 2016). The present study aims to
continue to fill the gap with a clinical decision analysis to aid supervisors in analyzing problems
in their supervision and adjusting to the best of their ability.
Typically, clinical decision models utilized in human service settings are done via a series
of questions that lead the clinician to a recommended decision based on the needs of the
individual. In the present review, the author proposes a decision model that will recommend
areas of focus to improve supervision procedures in regard to mentoring a supervisee. The
proposed decision model will examine the supervisor’s and supervisee’s strengths and provide a
recommendation of how best to proceed with quality supervision that is based on the literature.
Given the emergence of training available to BCBAs centered around effective supervision
practices, a decision model can bridge the gap between unstructured and a more guided approach
to problem-solving. The purpose of the proposed study is to analyze if, after exposure to the
decision model, supervisors’ problem-solving repertoire changes. Moreover, by implementing a
decision model into a company’s system, a standard of quality decision making is imbedded into
the culture of that company. A major takeaway of decision modeling is that they are not
recommended for use for all clinical decisions. They are to be allocated towards complicated
decisions that require an in-depth analysis of what the literature recommends, such as
supervision. The purpose of this proposed study is twofold: (1) to evaluate the impact of a
Clinical Decision Support System (i.e., decision model) on a mentor’s ability to adhere to
standards of practice and provide high quality supervision, and (2) to assess a mentee’s
knowledge of required and effective supervision standards, and their ability to contribute to a
high quality mentor/mentee relationship. The present review offers a proposed course of study
for those interested in utilizing a supervision decision model.

15
Proposed Method

Participants and Setting
The proposed participants for an evaluation should be Board Certified Behavior Analysts
(BCBAs) employed at an agency that provides applied behavior analysis services to individuals
with developmental disabilities. All participants should meet criteria from the Behavior Analyst
Certification Board to provide supervision to BCBA candidates. All participants should have
experience supervising direct service staff (RBTs) for a minimum of 1 year and should currently
supervise candidates for Board certification.
It is logical that the setting for the proposed study should take place in a variety of
locations, given that the decision model is technology based and the software needed to utilize
the decision model could be accessed wherever the participants have access to a computer.
Specific areas of performance will be measured via clinical observations; therefore, observations
may occur during scheduled supervision meetings between the supervisor and the supervisee
dyad, in the client home or elsewhere. Clinical observations should be conducted in-vivo if
possible but may be conducted via audio/visual recordings.
Experimental Design
A multiple baseline design across participants is the selected design for this evaluation. A
supervisor/ supervisee dyad will be chosen for all participants, in which one supervisor would be
evaluated with one of their supervisees throughout the duration of the study. A multiple baseline
design will be used to evaluate the effectiveness of the decision-making model for determining
the most appropriate methods for providing quality supervision to the supervisee.
Procedure
Response Measurement and Interobserver Agreement

16
The independent variable of the proposed study consists of the use of the decision-
making model. The dependent variables include the frequency of supervision contacts and the
quality of supervision. Quality of supervision will be determined via a rubric. An increase in the
rubric score indicating quality of supervision will be specifically evaluated. Secondary measures,
such as social validity analyses completed by the supervisors and the supervisees will also be
collected.
Interobserver agreement for frequency of supervision contacts will be collected via the
self-report of the supervisor and the supervisee. Interobserver agreement will be collected using a
frequency ratio method. To calculate agreement ratio, the smaller bi-weekly total will be divided
by the larger bi-weekly total and multiplied by 100 to be converted to percentage of agreement.
A second observer should collect data during at least 30% of all supervision observations.
Interobserver agreement will be collected by using the rubric score. Each observer will total the
rubric score for each participant at the end of the observation period. Observation periods may
vary, depending on the dyad’s supervision meetings. To calculate agreement ratio, the smaller
total score will be divided by the larger total and multiplied by 100 to be converted to percentage
of agreement.
Knowledge Surveys and Preference Assessment
Prior to baseline, the BCBA participants will respond to a knowledge survey that consists
of fifteen questions relating to their supervisory duties. Knowledge surveys will be distributed
via Survey Monkey to facilitate the ease of use of the model. Since BCBAs and their supervisees
often have various clients to see within a day, it is imperative that the knowledge surveys require
little response effort. Three sample questions follow: (1) Is there a signed contractual agreement
between you and the supervisee?, (2) How many BCBA candidates are you currently

17
supervising?, and (3) Do you have knowledge of your supervisee’s previous supervision
experiences?. Supervisees should also compete a different 13 item questionnaire that is relating
to their supervision experience with their current supervisor. Supervisee questions will include
items such as: Does your supervisor provide frequent corrective feedback?, Are there consistent
meetings between you and your supervisor?, and Do you know if your supervisor is qualified to
supervise?. Baseline observations will be conducted to allow for the experimenter to determine a
baseline rubric score for each BCBA.
Preference assessments will be conducted for each RBT examined during the study; they
will be imbedded into the knowledge surveys. Choices will be given to the RBTs to create a
hierarchy of preferred supervision techniques. This hierarchy will contribute to the
individualized recommendation for best supervision practices for that specific supervisee.
Baseline
Baseline observations will be conducted to allow for the experimenter to determine a
baseline rubric score for each BCBA. Observations throughout this study may be gathered in-
vivo or via audio/visual recordings. The supervisee participants will be required to collect
recordings of their entire supervision meetings with their supervisor. Supervisee participants will
be told to submit a naturally-occurring meeting they had with their supervisor that was an
accurate representation of their supervision. The participants will not be allowed to edit or alter
the recordings. This recording will then be sent to the experimenter for analysis. Baseline rubric
scores will be determined via the submitted recordings and the information gathered in the
knowledge surveys.
Utilization of the Decision Model

18
After baseline data are collected, the supervisor participants will be sent a web link that
will allow them to work through the technology based decision model. The participants will go
through the model by answering questions within the model. Based on their answers, each
participant will be given a recommendation at the end of model. This recommendation will be
based on the current literature and will be individualized to problem solve the needs of their
specific circumstances.
After the completion of the decision model, the experimenter will evaluate new
supervision meeting recordings and determined the quality with the help of the rubric. A new
rubric scored will be obtained at the conclusion of each new observation. The new rubric scores
will determine if maintenance of problem-solving repertories were developed and observed.
Social Validity
A social validity measure will be given to both the BCBAs and to the supervisees that
were included in the study. The BCBAs and supervisees will be asked to complete a social
validity measure that consists of questionnaires with a Likert scale. They will both be asked to
rate statements from 1-5 that demonstrate level of agreement. A score of 1 would indicate
“strongly disagree” and a score of 5 would indicate “strongly agree.” The questionnaire for the
BCBAs and the supervisees differs in regard to the content of the statements. Both
questionnaires contain items that focus on the procedures, goals, outcomes, and satisfaction of
the intervention and its subsequent results. Higher scores would indicate higher acceptability.
The questionnaire for the BCBAs consists of 10 statements. Sample statements from the
questionnaire are as follows: I would recommend the use of the decision model to other
clinicians; I feel more confident in my supervisory abilities; I found the decision model to be
effective for increasing my skills. Scores for this measure can range from 10-50 points.

19
The questionnaire for supervisees consisted of 5 statements. Sample statements from the
supervisee social validity questionnaire are as follows: I agree with more emphasis on
supervisory practices; I have observed a change in the way my supervisor interacts with me; I am
more confident in seeking feedback from my supervisor. Scores for this measure can range from
5-25 points.
Discussion
Given the methodology of the proposed study, it is strongly suggested that through the
use of the decision model there will be an improvement in the quality of supervision of BCBAs.
Furthermore, the proposed decision making tool may demonstrate effectiveness for increasing a
mentor’s problem-solving repertoire in regard to their supervision practices. Given the emphasis
of the need for effective and ethical supervision practices, the proposed decision model can be a
useful tool to increase the competence of a supervising BCBA. In addition, this model will
encourage a focus on supervision training within organizations, which will increase the
professional development of competent supervisors.
There is currently a large gap in the number of new BCBAs and the number of competent
mentors available to them. In 1999, there were 28 Board Certified Behavior Analysts (BACB
Certificant Data). By January 2020, there were 37,859 BCBA certificants worldwide (BACB
Certificant Data). When looking at the number of BCBAs that have completed the 8-hour
training necessary to supervise BCBA candidates, the number was astonishing. As of March
2020, there were 28,821 BCBAs in the United States that have completed the supervisor training
(T. Sellers, personal communication, March 26, 2020). These numbers indicate that the
percentage of competent mentors available to BCBAs is inadequate. Although there are a
substantial percentage of competent and experienced mentors that offer effective supervision,

20
with the increasing presence of new BCBAs it is highly likely that there is variability in the
quality of supervision that BCBA candidates are receiving. For this reason, a tool such as a
decision model may help guide supervisors in their mentoring practices and give them
recommendations about how to become an effective supervisor.
Taking on the role of being a mentor is a purposeful action that one should be eager about
and committed to. A behavior analyst must meet and complete specific requirements in order to
become a supervisor for a BCBA candidate. Such requirements include the completion of an 8-
hour training, obtaining additional continuing education units, and following the supervisor
training curriculum outline. Per the BACB, the Supervision Training Curriculum Outline 2.0
took effect on November 1, 2019. This updated curriculum is more intensive and subsumes
various responsibilities a supervisor must maintain in order to encourage the professional clinical
development of their supervisee. Some new aspects of the updated Supervision Training
Curriculum Outline 2.0 include a focus on the supervisor to create a committed and positive
relationship with their supervisees, reviewing of the expectations for behavior when feedback is
being delivered, and a collaboration to establish training objectives, among others.
Unfortunately, beyond the aforementioned requirements, behavior analysts are not explicitly
taught effective methods for mentorship. Therefore, many BCBAs are not equipped with the
proper tools to help them in their role as mentors. This area should be a key focus to the
professional development of BCBAs and their supervisees. By using a decision making tool that
is rooted in the behavior analytic literature, ethical guidelines, supervision requirements, and
well-established mentoring models it will allow for a richer supervision experience.
In addition, the medical literature and behavior analytic literature, emphasizes an
encouragement of including the mentee in the supervision process. There are benefits to the

21
supervisory relationship when the supervisee is an active member in their supervision by creating
an agenda for the meeting, determining preferred methods of receiving feedback, cultural
competence training, and creating learning plans to reach their goals (Healy, Cantillon, Malone,
& Kerin, 2012; Fraser, 2016; Sellers, Valentino, and LeBlanc, 2016; Kazemi, Rice, & Adzhyan,
2019). Just as the interventions behavior analysts recommend to their clients is individualized,
supervision should also be conducted to fit the need of that specific supervisee. Since behavior
analysts adjust their treatment dependent on the learner and their learning history, there should
be an emphasis on the generalization of that skill to meet the needs of the BCBA candidate.
While creating a way for our ABA agencies to systematize supervision, it is crucial that
we examine the change management literature. Change management is a body of literature that
focuses on how best to implement changes within an organization to produce the most effective
results (Ebert & Freibichler, 2017; Maurer, 2015). One study examined change management
techniques and how they, in combination with small changes (i.e., nudges) can be used to
increase worker productivity and create more efficient execution of goals (Ebert & Freibichler,
2017). The reason why change management literature should be referenced is because
management teams need a guide as to how best to implement changes in a way that will not only
be successful for the organization, but also to set their employees up for success when facing
systematic changes to company processes.
One method of implementing change is via the Kaizen method. The Kaizen method has
been identified as a way of implementing changes by taking incremental steps towards a larger
change. The reason for this is that Kaizen attempts to use very small steps to improve a habit,
process, or product (Maurer, 2015). The Kaizen method may be applied to personal fitness goals,
physical and mental health goals, and even within large scale organizations, such as Toyota

22
Motor Corporation (Maurer, 2015). The Kaizen method focuses on small, incremental changes
that will facilitate a larger change within an organization. By using the Kaizen method, a
manager is making such minor changes to processes, that it is not such a sudden change for the
company culture. While the overarching goals may be large, the manager knows how to
approach the change appropriately. The organization will begin to tackle small problems and
take small actions towards addressing a change. This will assist with dissipating the resistance
among employees and will ultimately yield better results. When employees, or anyone, hears the
word “change”, they often move into a state of fear and resistance (Maurer, 2015). By taking
small steps, steps so small that they require very little response effort, the individual begins to
bypass that stage of fear and move towards the change, rather than away from it.
Agencies that plan to make the necessary changes to their supervision practices as a
whole, should rely on the change management literature as a guide for facilitating such changes.
By introducing a decision model into an organization, this will make the change more systematic
because it is based on recommendations within the behavior analytic field. By utilizing a
technology-based decision model, the employer also makes it much easier for the supervisor to
access the tool within their already busy schedules. In addition to this, supervisors are already
having frequent meetings with their supervisees and evaluating their own behavior. The main
difference is that now they will have a tool that will bring the standards of practice to their level
of awareness. This falls in line with The Transtheoretical Model of Change and how it should be
approached via organizations. The Transtheoretical Model of Change refers to a framework of
progression that consists of five stages and which all people work through when attempting to
modify any behavior. These five stages consist of: (1) precontemplation, (2) contemplation, (3)
preparation, (4) action, and (5) maintenance/termination (Prochaska, Prochaska & Levesque,

23
2001). The Transtheoretical Model will allow for an organization to facilitate change by
matching their employees to what stage they are in. By doing this, the organization is able to
meet their employees in their respective stage and improve from that starting point.
A limitation of the proposed study is the setting, given that all participants will be part of
the same behavior analysis agency. There is a possibility that the effectiveness of the decision
model could be demonstrated due to another factor that is present within this agency. Moreover,
the supervision meetings may have been evaluated via audio/visual recordings. If the supervision
meeting evaluations would have been conducted in-vivo, there may have been clearer results.
However, the presence of an effect among such limited observation procedures could indicate
greater external validity. This effect could signify that there is no further intervention needed
besides the decision model, which can be distributed electronically. Therefore, there would be
greater access to individuals worldwide and the dissemination of this tool would be more
efficient.
Future studies could evaluate the use of the decision-making model across agencies. Due
to the individual structure of each organization, the use of this model in a large array of
environments would be useful to further establish external validity. It would be beneficial to also
examine the use of the model with supervisor’s that have been mentors for a longer period of
time (15+ years). As behavior analysts are aware of, it is more difficult to change an individual’s
behavior once an extensive learning history is present. It would be advantageous to evaluate if
BCBAs with more experience are able to adjust their supervisory practices based on the
recommendation of the decision model. This would allow for more salient results of the
effectiveness of the model. Furthermore, since the nature of the present proposed decision model
is specific to supervision practices within the field of behavior analysis, other decision models

24
that are specific to a variety of fields’ mentorship practices should be evaluated. If the use of
these models is effective, these respective fields would be preparing more competent and
effective professionals.
As a science, it is our responsibility to disseminate our findings to other areas that could
benefit from our knowledge. It is already common practice that behavior analysts are members
of interdisciplinary teams that contribute to treatment, interventions, and consultation. As
members of these interdisciplinary teams, behavior analysts should be learning from other fields,
imbedding that knowledge into our practice, and using our science to make these systems better.
The present review is an exemplar of how, as a field, we are able to do this. Decision models are
well-established in other fields and have recently entered the field of behavior analysis. By using
decision models in areas that allow for greater professional development, which will in turn
affect the standard of care provided by future professionals, a systematic way of evaluating a
problem in mentorship will be available. Future studies should attempt to utilize decision models
to focus on other areas of treatment or clinical practice. Additionally, decision models can be
used in other areas of behavior analysis, such as behavioral pediatrics, education, sports and
fitness, or delinquency.
The proposed decision model is an attempt to combat the effects of poor quality
supervision practices within the field of behavior analysis. There is a large emphasis on the need
for quality supervision per BACB standards, published articles, and practice recommendations
via published books. However, the field was lacking in a systematized method for increasing the
problem-solving repertoire of mentors when faced with an issue in their supervisory relationship.
The present decision model was created with the future of the field of behavior analysis in mind.
Our field is growing at an increasing rate and the number of candidates requiring supervision

25
will exceed the number of competent mentors. If solutions are not proposed, the efficacy of our
behavior analytic recommendations will be affected. Therefore, it would be in the field’s best
interest to combat those potential effects and remedy the root of the development of past,
present, and future behavior analysts by evaluating supervision and training.

26
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Asset Metadata

Creator Melendez, Julie L. (author)

Core Title Clinical decision analysis for effective supervision: a review of the supervisor-supervisee relationship

School College of Letters, Arts and Sciences

Degree Master of Science

Degree Program Applied Behavior Analysis

Publication Date 04/22/2020

Defense Date 03/24/2020

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

Tag clinical decision analysis,ethics,mentorship,OAI-PMH Harvest,supervision standards

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Cameron, Michael (committee chair), Harris, Jennifer (committee member), Manis, Frank (committee member)

Creator Email jlmelend@usc.edu,jlouisemel@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-288170

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Rights Melendez, Julie L.

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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 a...

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