Deochand et al. (2020) Toward the development of a functional analysis risk assessment decision tool (1).pdf

Behavior Analysis in Practice (2020) 13:978–990 https://doi.org/10.1007/s40617-020-00433-y DISCUSSION AND REVIEW PAPER Toward the Development of a Functional Analysis Risk Assessment Decision Tool Neil Deochand 1 & Rebecca R. Eldridge 2 & Stephanie M. Peterson 2 Published online: 20 July 2020...

Behavior Analysis in Practice https://doi.org/10.1007/s40617-020-00433-y DISCUSSION AND REVIEW PAPER Toward the Development of a Functional Analysis Risk Decision Tool Neil Deochand 1 & Rebecca R. Eldridge 2 & Stephanie Published online: 20 July 2020 # Association for Behavior Analysis International 2020, Abstract Risk-benefit analyses are essential in the decision-making ment and treatment options for our clients. Clinical needed in order to weigh the potential detrimental recommendations pertaining to functional analyses (FAs) lead some practitioners to misjudge the risks of FA. assessment tool to evaluate risks prior to conducting doctoral-level Board Certified Behavior Analysts (BCBA-Ds), with an FA would be useful for the professional practice assess risk, which provides suggestions to mitigate panel of 10 BCBA-Ds reviewed the tool. Experts suggested about the FA process and as a supporting resource for Keywords Clinical decision making. Ethical practice. Demand continues to grow for Board Certified Behavior Analysts (BCBAs) and their expertise (Behavior Analyst Certification Board [BACB], 2018; Deochand & Fuqua, 2016). This demand has created a “supply” issue, in that there is a shortage of BCBAs. The BACB reports that a vast major- ity of individuals certified as behavior analysts have been certified for 5 years or less (BACB, n.d.). This heightened demand, coupled with the junior status of many practicing behavior analysts, creates a need for tools that will continue This article was updated to correct the spelling of name in the author listing. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s40617-020-00433-y) contains material, which is available to authorized users. * Neil Deochand [email protected] ported that 61.9% of certified behavior analysts surveyed (N = 205) had entire client caseloads where none or almost none had received an FA to inform treatment. The participants in University the Oliver et al. (2015) survey reported insufficient time (57.4%), lack of space/materials (51.8%), lack of trained sup- port staff (26.7%), and lack of administrative policies (24.9%) as the primary barriers to implementing FAs in practice. 979 train staff, minimize the time required to conduct their assessment, or embed their assessment into the client’s ongoing routine (and, hence, natural environment) to ame- liorate the need for a separate space for the FA. For the FA to gain social acceptance, it must be used in practice when it is the best suited assessment procedure. Administrative support for conducting FAs might increase if administrators had more knowledge of the risks and benefits of the procedure. Recently, Wiskirchen, Deochand, and Peterson (2017) concluded that safety rec- ommendations for FAs were not easily accessible to behav- ior analysts, which may make it difficult for behavior ana- lysts to effectively judge whether it is safe to conduct an FA or even what factors they should consider in making this judgment. Researchers have found that safety recommen- dations are often not consistently reported (Weeden, Mahoney, & Poling, 2010) or they are scattered in the be- havioral literature across numerous journals and books (Wiskirchen et al., 2017). Wiskirchen et al. (2017) advocat- ed for a formalized risk assessment prior to conducting an FA and suggested four domains (clinical experience, be- havior intensity, support staff, and environmental setting) that could be included in such a risk assessment. This “call to action” is timely given that clinical decision making sur- rounding FA safety precautions appears not to be transpar- ent to those in and outside the field. In recent years, Behavior Analysis in Practice has pub- lished decision trees to help guide behavior analysts, cov- ering topics ranging from selecting measurement systems (LeBlanc, Raetz, Sellers, & Carr, 2016) and treatments for escape-maintained behavior (Geiger, Carr, & LeBlanc, 2010), to considering the ethical implications of interdisci- plinary partnerships (Newhouse-Oisten, Peck, Conway, & Frieder, 2017). Such tools offer guidance and resources to support the growing number of behavior analysts in the field. A similar tool for evaluating the risk of FA and for pointing practitioners to helpful literature for decreasing risk could be helpful to the field. However, prior to devel- oping the FA risk assessment tool, we first surveyed BCBAs to ascertain if they reported a need for such a tool. Based on those results, we developed a beta version of a comprehensive risk assessment tool for evaluating risk pri- or to conducting an FA. The tool suggested strategies for ameliorating risks, provided references to peer-reviewed literature on how to implement such risk-reduction strate- gies, and provided considerations to increase the validity of FAs in practice. Ten BCBA-Ds with several years of expe- rience conducting FAs and who had contributed to the knowledge base on this topic reviewed the tool. Their feed- back was used to develop a refined version of the tool. In this article, we describe the outcomes of the survey, de- scribe the process for evaluation of the tool, and provide Behav Analysis Practice (2020) 13:978–990 in the first round. The survey was not searchable through search engine queries, so only those with an invite from the BACB® e-mail could participate. Additionally, to prevent multiple user responses generated from the same IP address, prevent “ballot box stuffing” was selected in the Qualtrics™ options. Survey data were separated by participants who com- pleted the first half of the survey and participants who com- pleted the entire survey (defined as having no more than two unanswered responses). tool. Survey Results and Discussion Practitioner Demographics Participants’ mean age was 39.2 years (range 24–78 years). Table 1 depicts participant demographic characteristics such as gender, certification type, age ranges, and years of experience in the field. There was a higher proportion of female participants, which comprised 81.2% (n = 539) of the sample. Of those, 450 identified as BCBAs, and 89 identified as BCBA-Ds. Male participants represented 18.7% (n = 124) of the sample, with 84 identify- ing as BCBAs and 40 as BCBA-Ds. One participant did not identify with the binary gender options. A large portion (31%) belonged to the 30- to 35-year-old age range. Approximately, 75% of the participants had fewer than 15 years of experience working in the field, which reflects the recent exponential growth of newly certified behavior analysts. assessment Table 1 Participant demographic data (N = Characteristic N Percentage 664) Gender Female 539 81.17 Male 124 18.67 Other 1 0.15 Certification BCBA 534 80.42 BCBA-D 130 19.58 Age range 24–29 100 15.13 30–35 207 31.32 36–40 131 19.82 41–45 70 10.59 46–50 53 8.02 >50 100 15.13 Years of experience in the field 0–5 175 26.36 6–10 195 29.37 11–15 126 18.98 16–20 76 11.45 21–25 40 6.02 >25 52 7.83 981 Yes No N (%) N (%) 631 (95.0) 33 (5.0) treatment based on the results of an FA? 610 (91.9) 54 (8.1) with or observed an FA? 602 (90.7) 62 (9.3) 543 (81.8) 121 (28.2) 461 (69.4) 203 (30.6) you were unsure whether it was appropriate to 519 (78.2) 145 (21.8) conduct an FA, would you be concerned about the 534 (80.4) 130 (19.6) the results? of the term “risk assessment” in relation to 550 (82.8) 114 (17.2) there is a need for a risk assessment tool that 629 (94.7) 35 (5.3) the risk of conducting an FA and offers ways to posed in an FA? that helps evaluate when it would be safe to 639 (96.2) 25 (3.8) FA be useful for the field of applied behavior more likely to conduct an FA if a tool existed that 546 (82.2) 118 (17.8) safety precautions, validity recommendations, ions? a formalized (standard decision-making tool) 35 (5.8) 563 (94.2) before conducting an FA? some behavior analysts do not conduct an FA 559 (93.5) 39 (6.5)v actually the best option to guide treatment? than agreement would shift the bar to the right and away from the statement on the left, and vice versa). Roughly 596 partic- ipants of the original 664 completed the entire survey includ- ing the Likert questions. Participants could leave two re- sponses unfilled and still meet inclusion criteria. Statements in Figure 1 are organized by the total responses for each state- ment, as some participants did not provide an endorsement to the provided 5-point Likert scale by leaving an unfilled response. Most participants (99.2%) agreed or strongly agreed that the FA helps guide future treatment when other methods have failed. Also, a majority of the sample (78.4%) agreed or strongly agreed that FAs are the gold standard functional as- sessment. Interestingly, 88.4% of participants disagreed or strongly disagreed with the statement “I do not generally con- duct FAs because when I do the results are usually wrong.” Most (90.8%) disagreed or strongly disagreed that an FA could only be used with individuals with developmental dis- abilities, and 88.3% disagreed that FAs could not be used with behaviors that were multiply controlled. Just under 73% disagreed or strongly disagreed that FAs were more of a re- search tool than something to be used in practice. In summary, there seemed to be strong agreement that FAs are robust and should be relied upon when needed to inform treatment. disagreement Behav Analysis Practice (2020) 13:978–990 Percentage of agreement or disagreement regarding FA related statements 9.2% 43.6% 44.8% 0.7% 1.3% 45.2% 15.9% 31.9% 6.4% 0.3% 14.0% 47.3% 16.4% 18.9% 3.0% n = 596 42.5% 46.3% 8.7% 0.3% 2.0% 13.0% 36.0% 48.0% 0.3% 2.5% 19.1% 50.8% 15.9% 12.7% 1.3% 45.7% 41.5% 9.9% 0.3% 2.5% 50.2% 37.1% 10.2% 0.3% 2.0% 4.3% 13.5% 9.2% 46.8% 25.9% 44.3% 34.1% 13.4% 7.2% 0.8% n = 597 54.7% 41.8% 3.3% 0.0% 0.2% 46.8% 29.9% 11.0% 10.2% 2.0% 7.5% 46.5% 41.8% 1.5% 2.7% 5.7% 43.0% 47.8% 1.8% 1.7% 5.5% 36.0% 25.1% 28.1% 5.4% n = 598 Strongly Agree Agree Neutral Disagree Strongly Disagree ABA-related statements at the conclusion of the survey, which allowed participants to provide textual information if they wanted to offer additional context surrounding their responses. In the first question, about 94.2% of participants reported never using a formalized process to determine risk before conducting an FA. The re- sponses to the second question indicated that roughly 93.5% of the sample believed some behavior analysts do not conduct FAs even when they may be the best option to guide treatment. These data suggest there is a need for a structured support tool to help evaluate the risks of conducting an FA. They also support the potential utility of including with the tool recom- mendations to improve the validity of the FA procedure by designing FAs to meet the diverse needs of the clients for whom an FA is warranted, as well as cater to the settings and contexts in which FAs are conducted. In order of priority based on the perceived needs of the sample, our tool should (a) provide the various safety precautions for implementing an FA found in the literature, (b), offer a way to assess the risk of implementing an FA, (c) provide options to reduce risk, and (d) offer considerations regarding how to conduct a valid FA. the reason 983 the client or others at risk, appropriateness of the setting, clini- cian expertise, sufficiently trained personnel, buy-in from stakeholders, and other liabilities to the analyst. These sugges- tions correspond with Wiskirchen et al.’s (2017) four domains—clinical experience, behavioral intensity, FA envi- ronment, and support staff (see Figure 2)—which served as our primary categories of risk for the tool. We attempted to quan- tify these four domains as objectively as possible. Within each of these four domains, we created six levels from which the practitioner could select. Six levels were selected as they con- veniently helped categorize meaningful contextual differences that could impact risk. We used an aesthetic graduated blue-to- red color scale to denote low risk (blue) to high risk (red). For the clinical experience domain, we initially envisioned using a set number of FAs completed, but heuristically, behavior ana- lysts might more easily remember the number of years they have been conducting FAs. Thus, we used time-based criteria for experience. The levels for experience ranged from 5 or more years of experience conducting FAs with different inten- sities and topographies to no experience conducting FAs. For FA environment, conceivably the safest environment in which References Learning and Behavioral Disabilities 1 Intervention in Developmental Disabilities 1 4 Research and Practice 1 3 Principles, Models, and Practices 1 3 1 Training in Developmental Disabilities 2 Treatment of Children 4 of Behavior Analysis 1 Behavior Analysis 42 and Developmental Disorders 1 1 and Physical Disabilities 2 and Intensive Behavioral Intervention 1 Behavior Interventions 1 Association for Persons With Severe Handicaps 1 of North America 1 Developmental Disabilities 3 1 and Ethical Compliance Code for Behavior Analysts / 3 Edition Task Lists (BACB, 2012, 2017) (Ed.). (2012). Functional assessment for challenging 4 chapters York, NY: Springer. Behav Analysis Practice (2020) 13:978–990 are challenging to block regardless of whether the topography is self-injurious behavior, aggression, pica, elopement, or in- appropriate sexual behavior. Next, we attempted to develop a way for these six domains to be evaluated in an interactive fashion. Specifically, it was our opinion that risk could not be determined by simply con- sidering these four domains in a linear fashion. Rather, risk was either heightened or lessened based on how the four do- mains interacted with each other. For example, the risk of conducting an FA with a very intense, self-injurious behavior (e.g., severe head-banging) might be lowered by conducting the evaluation in the safest environment with highly experi- enced behavior analysts, medical oversight, and trained staff to assist in the evaluation. Conversely, risk is increased when attempting to conduct an analysis of severe self-injury with poorly trained staff and a BCBA with limited experience. We needed a mechanism to allow for these kinds of interactions. We determined this could be accomplished through Microsoft Excel®. This software allows for the use and integration of Visual Basic coding, as well as macros to create dynamic interactive programs. We programmed the domains to be dy- namically interactive, whereby a higher risk in the experience domain or in the behavioral intensity domain inflates the over- all risk to a greater extent than the other domains. This effect is magnified further if there is a higher risk in both of those 985 Overall risk can range from slight, moderate, substantial, to high risk (see Figure 3). The third tab, “Risk Assessment,” contains suggestions for lowering risk specific to given concerns selected by the user, as well as a published reference the user can refer to for more information. If any of the user’s clicks on the risk buttons on the second tab (Risk Evaluation) result in higher risk (i.e., within the 4–6 range for a given domain), matching sugges- tions for lowering risk and references in the third tab turn red to highlight for the user what the suggestions for lowering risk are. The fourth and fifth tabs, “Validity” and “Considerations,” offer tips to the user for maintaining high levels of validity in the assessment. We used “if-then” scenar- ios to help guide the user in selecting appropriate consider- ations for the client. For example, after a high-risk scenario is detected, the tool might recommend selecting reinforcing pre- cursor behavior in an FA (Lalli, Mace, Wohn, & Livezey, 1995); using a structural analysis (Stichter & Conroy, 2005), modified choice assessment (Berg et al., 2007), or reinforcer or punisher assessments; or complimenting a descriptive as- sessment with a contingency space analysis (Martens, DiGennaro, Reed, Szczech, & Rosenthal, 2008). Additionally, in the Validity and Considerations tabs are ta- bles and figures from articles that offer guidance regarding scenario Behav Analysis Practice (2020) 13:978–990 domains and asked them to rate the appropriateness of the overall risk rating the tool produced for each specific scenario combination. Most of these combinations constituted more “middle-of-the-road” risk, as we assumed there would be higher agreement with recommendations at the extreme ends of the continuum. The “grayer” areas seemed to be those where the most feedback was warranted. We used a 3-point Likert scale that included It’s just right, Needs to be lower risk, and Needs to be higher risk. If the expert selected anything other than It’s just right, we asked the expert to comment on why/how the risk should be different. Finally, for each of the 12 combinations, we also asked the experts to rate the recom- mendations for reducing risk with a 5-point Likert scale that included not helpful, a little helpful, somewhat helpful, helpful, and very helpful. Following that question, the experts could type any additional comments for that scenario combination. After the initial assigned combinations, experts were asked to interact with the tool, choosing any combinations for the two domains clinical expertise and behavior intensity, while support staff and environment were fixed at the highest risk setting. We chose these two domains in particular to get expert feedback on, as these were the most commonly listed barriers to implementing FAs in the previously published survey re- search (Oliver et al., 2015). For these combinations, we asked the experts to rate the appropriateness of the level of risk identified, and if they would change it, to provide a rationale. Finally, experts selected additional combinations they wanted to try out, and again we only asked them to rate the appropri- ateness of the risk, and if they would change it, to provide a rationale. Finally, we asked open-ended questions about the four do- mains, if there were any risk factors they felt we missed, if the level of detail in the Risk Reduction tab was sufficient to carry out the suggested change, if the level of detail in the Risk Reduction tab and Considerations tab was appropriate, how accessible the tool was, whether the weighting we used for our risk scales was appropriate, if the tool was useful, and for whom the tool would be useful. We then took the ratings and commentary provided by the experts and analyzed what, if any, changes should be made to the tool. For most of the scenarios, at least 8 of 10 experts scored the risk rating as It’s just right. If more than one expert provided feedback that something needed to be changed, the authors discussed the expert’s rationale, compared it to the feedback given by the other experts, examined the literature, and made a determination whether to change the tool and, if so, how. Examples of changes made included the following. Originally, we had four overall risk ratings that included “min- imal,” “some,” “moderate,” and “high.” Many of the reviewers felt that “minimal” risk was too narrow and that there is always risk with an FA. This produced interesting and spirited discus- sion among the authors. Eventually, we decided to change the 987 decisions in an interactive decision-making process. In such cases, domains of consideration may interact with one another in unique ways. For instance, our four domains all potentially impact risk in an FA (clinical experience, behavior intensity, support staff, and environmental setting) but likely do so in an interactive fashion. High risk in one domain might interact with low or moderate risk in another domain to create unique risk situations. In this case, the four domains, each with six categories in the continuum, would lead to 1,296 different possible combinations of risk factors. Unfortunately, a deci- sion tree would not be a feasible format to display these op- tions, nor could it easily be presented on a journal page. Thus, we created this interactive tool so that all 1,296 possible com- binations could be taken into account in an efficient and useful manner. Code 4.05 of the BACB® Professional and Ethical Compliance Code for Behavior Analysts specifies, “to the extent possible, a risk-benefit analysis should be conducted on the procedures to be implemented to reach the objective” (BACB, 2014). Evaluating whether assessments or treatments could adversely impact a client can be done at any point throughout the therapeutic relationship and should conclude with a course of action where the benefits outweigh the risks (BACB, 2014, p. 24). Unfortunately, the language surround- ing how to conduct a risk-benefit analysis or what form a risk- benefit analysis should take is rather vague in our literature. “some,” Each assessment or treatment procedure can produce different probabilities of success, different amounts of time to take ef- fect, different levels of restrictiveness, and different impacts on quality of life, which make the selection process for assess- ments and treatments a delicate tightrope on which to balance (Axelrod, Spreat, Berry, & Moyer, 1993). Code 3.01(a) spec- ifies that functional assessments are prerequisites to behavior change programs and the type of assessment depends upon the needs of our clients, as well as their “consent, environmental parameters, and other contextual variables” (BACB, 2014). Because the functional assessment process is one of the largest differentiating factors of behavior-analytic practice from other psychological professions, it is essential that the safest and most efficacious assessment be selected for our clients’ needs. Thirty-five of 598 participants reported using a formal pro- cess to assess risk, but when asked to type additional informa- tion, only 19 responded. Those who responded referenced using a standard assessment in their facility, the chapter on risk-benefit analysis in Bailey and Burch (2016), or the article “Functional Assessment of Problem Behavior: Dispelling Myths, Overcoming Implementation Obstacles, and Developing New Lore” by Hanley (2012). It is unknown what the remaining 579 participants use (if anything) to evaluate risk when implementing an FA. The majority of our survey sample endorsed FAs as powerful assessment tools capable of being used to evaluate cases where behavior is maintained by combined functions (Hanley et al., 2014). However, two prior Behav Analysis Practice (2020) 13:978–990 further insight as to whether this variable potentially influ- enced responding. Although data were gathered on years of experience in the field, it would have been beneficial to divide that question into two separate questions: one to ascertain a participant’s years of experience post-BACB® certification, and another related to working within clinical or special edu- cation settings. There are notable considerations that should be taken into account when using the tool. One of the experts evaluating our tool rightly noted that not all years of experience are equal. For example, even with 2 years of FA exposure, the skill set of a postdoctoral fellow with extensive experience conducting FAs with the most severe behaviors under the mentorship of leading experts in the field is very different from a master’s- level practitioner working with only a few children who dis- play mild problem behaviors. As a result, the level of risk for conducting an FA for each of these practitioners may be very different. Our tool does not account for this difference in train- ing. We tried to make this apparent in our tool by offering instructions to the user to account for this (e.g., “Note FA experience in the buttons below do not take into account in- tensive experience with the procedure e.g. postdoctoral train- ing, or an increased # FAs conducted within a time period. Thinking about these factors, which of the below best captures your experience?”). This is a clear example where clinical judgment must be used when completing and interpreting the ratings on the tool. Regardless, behavior analysts have a duty to promote an ethical culture. Offering this tool as an educational resource is our attempt to provide some guidance until further empirical support is generated for its application into behavior-analytic practice. snapshots of partic- Future Directions There is no guarantee that simply providing a tool to practic- ing behavior analysts will result in reducing the risks associ- ated with conducting an FA. Therefore, our next step is to evaluate whether practitioners’ use of the tool effectively im- pacts clinical decision making. Our expert panel anticipated the tool in its current stage may help safeguard the ethical practice of FAs for new practitioners or those in training. It is our hope that this tool will help narrow the research-to- practice gap and offer a structure for considering variables that may potentially contribute to risk in an FA. We do not pro- mote the use of FAs in all circumstances and contexts. In fact, there may be some cases where an FA is just not safe to conduct. We attempted to offer alternative forms of analyses (e.g., concurrent operants assessments, structural analysis) when the risk is just too great to make an FA appropriate or feasible, given the circumstances. It is our hope that this auto- mated, interactive tool will offer insights and feedback to practitioners across several domains and that it captures at 989 Behavior Analyst Certification Board. (2012). Task list (4th ed.). Littleton, CO: Author. Retrieved from http://www.bacb.com/ index.php?page=100165 Behavior Analyst Certification Board. (2014). Professional and ethical compliance code for behavior analysts. 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