Enhancing Homework Compliance in Correctional Psychotherapy

Abstract

This study investigated the effects of three homework compliance enhancement strategies (task option, task modeling, and public commitment) on a sample of probationers’ compliance with therapeutic homework tasks during the course of a multiphasic correctional treatment program. The study featured a within-subjects, counterbalanced, experimental design. Homework compliance was measured on the basis of therapists’ record of probationers’ homework completion (i.e., “yes/no” tally), as well as probationers’ scores on the Homework Rating Scale–II Client and Therapist rater versions. Results were mixed but suggested that public commitment and task modeling are potentially useful strategies in enhancing probationers’ beliefs about, expectations of, and compliance with therapeutic homework tasks. Furthermore, results provided preliminary support for the reliability of the Homework Rating Scale–II within correctional populations. Implications for correctional service delivery, treatment programming, and treatment outcome are discussed, as is the need for further research in this area.

Keywords

psychotherapy Homework Rating Scale–II homework enhancement homework compliance correctional rehabilitation

Cognitive-behavioral therapy is an efficacious and widely used treatment modality for reducing criminal behavior (Andrews & Bonta, 2010; Landenberger & Lipsey, 2005; Smith & Lombardo, 1995). One of the fundamental ingredients in cognitive-behavioral therapy is between-sessions homework (HW) tasks (Beck, Rush, Shaw, & Emery, 1979; Kazantzis, Lampropoulos, & Deane, 2005). HW is operationally defined as “any out-of-office activity directed by a therapist and intended to have a therapeutic effect if undertaken during the course of therapy” (Neimeyer, Kazantzis, Kassler, Baker, & Fletcher, 2008, p. 199). The relationship between HW and improved clinical outcomes has been well established in the treatment outcome literature (Burns & Nolen-Hoeksema, 1991; Kazantzis, Deane, & Ronan, 2000, 2004; Kazantzis & Lampropoulos, 2002). Consequently, it comes as no surprise that HW is common in the practice of correctional psychotherapy (Morgan et al., 2012).

The mounting literature in correctional psychotherapy suggests that HW is a critical factor in deriving optimal therapeutic gain (Morgan, Kroner, & Mills, 2006). Correctional interventions that include a HW component have been found to produce more favorable mental health (e.g., symptom severity, coping, behavioral functioning, psychiatric recidivism) and correctional (e.g., criminal recidivism) outcomes than those that do not (Morgan & Flora, 2002; Morgan, Kroner, Mills, & Bauer, 2011). This finding is consistent with outcome research conducted in other clinical populations (Burns & Nolen-Hoeksema, 1991; Kazantzis et al., 2000, 2004; Kazantzis & Lampropoulos, 2002). Decidedly, there is compelling evidence in support of HW’s utility in correctional treatment.

The caveat inherent in therapeutic HW exercises, however, is that the efficacy of such tasks, as well as any resulting improvement in outcome, is contingent on compliance (Kazantzis & Lampropoulos, 2002). For the purposes of this study, HW compliance has been operationally defined as completion of the HW assignment in the manner agreed on by the therapist and client (Tompkins, 2002). Empirical research has consistently demonstrated that HW compliance is significantly related to improved treatment outcomes (Burns & Spangler, 2000; Kazantzis et al., 2000, 2004; Kazantzis & Shinkfield, 2007). Therefore, practitioners’ ability to maximize clients’ compliance with HW assignments appears to be critical in determining treatment success (Tompkins, 2002). In recent years, researchers in the field of clinical psychology have sought to identify strategies for enhancing HW compliance (Freeman & Rosenfield, 2002; Kazantzis & Shinkfield, 2007; Tompkins, 2002). Such strategies, however, have yet to be tested specifically in correctional populations. It stands to reason that such strategies should have a similarly positive impact in correctional settings as they do elsewhere. Because HW is an important component to correctional psychotherapy (Morgan et al., 2006) that ultimately affects treatment outcomes (Morgan et al., 2011; Morgan & Flora, 2002), it follows that enhancement of HW compliance in the correctional setting is an area that warrants investigation.

Benefits of HW in Therapy

HW assignments often add significant value to psychotherapeutic interventions. From a process standpoint, HW tasks serve to extend the duration of therapy sessions and increase the amount of time during which clients directly address their presenting problems (Leucht & Tan, 1996). HW is also useful in providing continuity between sessions and enhancing the clinical work of each session (Hay & Kinnier, 1998). Furthermore, HW tasks allow practitioners to evaluate clients’ grasp of session content (Kazantzis & Lampropoulos, 2002), thereby enabling them to modify treatment plans or alter the course of therapy accordingly (Hay & Kinnier, 1998). From a treatment standpoint, clients benefit from numerous gains by engaging in HW activities. Such activities provide clients with opportunities to generalize skills and insights learned during the course of therapy (Leucht & Tan, 1996). Finally, HW assignments instill a sense of empowerment and promote self-efficacy and autonomy as clients learn they are capable of making changes independently of their therapists (Hay & Kinnier, 1998).

Within the scope of correctional psychotherapy, HW assignments offer additional benefits. HW is an effective supplement to group psychotherapy, and it facilitates the transfer of learning outside of individual sessions (Morgan et al., 2006). Furthermore, HW is useful in reinforcing the traditional aims of correctional psychotherapy, including personality restructuring, prosocial reintegration, addressing criminogenic (i.e., antisocial) thoughts and behaviors, and reduction of criminal recidivism (Morgan et al., 2006). Last, HW is consistent with the Risk-Need-Responsivity model (see Andrews, Bonta, & Hoge, 1990), which has demonstrated robust empirical support as an efficacious treatment paradigm for the treatment of criminal behavior (Andrews & Bonta, 2010; Andrews et al., 1990). According to Risk-Need-Responsivity, correctional services should be matched according to offenders’ level of risk, should target criminogenic needs, and should be delivered in a manner that is consistent with offenders’ learning styles (i.e., grounded in behavioral and/or social learning principles; Andrews et al., 1990). HW tasks in correctional psychotherapy commonly adhere to these guidelines because they target behavior modification and skill development and consist of group-oriented, cognitive, and behaviorally based tasks (see Morgan et al., 2006). For these reasons, HW offers significant benefits for offenders.

Barriers to HW Compliance

As previously discussed, the efficacy of therapeutic HW tasks is contingent on the extent to which clients comply with HW assignments (Kazantzis & Lampropoulos, 2002). Researchers have identified various factors that can impede task completion, known as barriers to HW compliance (Kazantzis & Shinkfield, 2007). Such barriers include task variables such as nature of the task (e.g., thought records, behavioral tasks, written assignments), difficulty level, and relevance to session content and treatment goals (Coon & Thompson, 2003; Fehm & Mrose, 2008; Freeman & Rosenfield, 2002; Tompkins, 2002); client variables, including participatory status (i.e., voluntary vs. involuntary), functional level, motivation, and symptom-related noncompliance (Hay & Kinnier, 1998; Kazantzis & Lampropoulos, 2002; Kazantzis & Shinkfield, 2007); therapist variables, such as competence, professionalism, working alliance, and degree of collaboration with clients (Coon & Thompson, 2003; Hay & Kinnier, 1998; Kazantzis & Shinkfield, 2007); and process variables, which include task delivery, review of HW assignments (i.e., consistent vs. inconsistent), and prioritization of tasks (Gaynor, Lawrence, & Nelson-Gray, 2006; Hay & Kinnier, 1998; Kazantzis & Lampropoulos, 2002).

In correctional settings, there are additional barriers to HW compliance that are unique to offenders. An offender may be reluctant to engage in treatment for self-preservation reasons, such as avoiding being perceived as weak or colluding with staff (Morgan, Steffan, Shaw, & Wilson, 2007). Offenders’ concerns about the consequences of therapy may also hinder their compliance. For example, they may fear that disclosures in session could be used against them (e.g., competency, conditions of sentence, seclusion/isolation; Morgan et al., 2007). Factors such as confidentiality and stigma associated with mental health services are also concerns for clients in correctional settings (Morgan et al., 2007). Each of these variables can hinder offenders’ compliance with HW tasks.

Enhancement and Proper Measurement of HW Compliance

Researchers have proposed general strategies for enhancing clients’ compliance with therapeutic HW tasks, which involve both task and process variables. With regard to task variables, it is recommended that tasks be on theme with session content and treatment goals, appropriately matched to client skill level, and accompanied by written instructions (Tompkins, 2002). With regard to process variables, it is recommended that therapists collaborate with clients in generating HW tasks (Freeman & Rosenfield, 2002), assign and review HW in a consistent manner (Kazantzis & Shinkfield, 2007), and maintain a strong working alliance throughout the course of treatment (Gaynor et al., 2006). Specific therapeutic strategies for enhancing HW compliance have been proposed, including presenting clients with options in selecting HW tasks (Hay & Kinnier, 1998), providing in-session rehearsal or modeling of proper task completion (Kazantzis & Lampropoulos, 2002), and encouraging clients to commit publicly to complying with HW assignments (Freeman & Rosenfield, 2002).

To date, methods of assessing HW compliance have been diverse and contradictory (Kazantzis et al., 2004). Inconsistency of measurement not only leads to findings that can be misleading but precludes meaningful interpretation of global compliance rates (Kazantzis et al., 2004). Researchers have offered various suggestions for accurate and reliable measurement of HW compliance. First, compliance should be measured objectively and with multiple sources (e.g., client and therapist) rather than subjectively by a single source to avoid reporting biases (Kazantzis et al., 2004). Second, compliance should be assessed session by session, rather than retrospectively, to maximize the accuracy of results (Gaynor et al., 2006). Third, compliance should be assessed stage by stage (e.g., beginning of treatment, midway point, end of treatment) rather than in the aggregate to maximize comprehensiveness (Gaynor et al., 2006). Finally, both quality (i.e., how well task was completed) and quantity (i.e., how much of the task was completed) of HW completion should be assessed rather than measuring one or the other (Kazantzis et al., 2004).

The Present Study

Despite strong theoretical support, HW compliance enhancement strategies (HCESs) have yet to be empirically tested with correctional populations. The current study examined the effects of three HCESs (task option, task modeling, and encouragement of public commitment) on a sample of probationers’ compliance with therapeutic HW tasks. Investigators measured probationers’ HW compliance during the course of their participation in a manualized correctional treatment program. HW compliance rates in each of the three enhancement conditions were compared with those in the HW as usual (HAU) condition. Investigators predicted that probationers in the enhancement conditions (receiving one of the three HCESs) would exhibit higher rates of HW compliance during the experimental phase of the treatment program than those in the HAU condition.

Method

Participants

An a priori power analysis was performed using G*Power 3.1.2—a statistical power software program. Using a critical α level of .05 and a medium effect size, it was determined that approximately 76 cases (i.e., 19 participants per condition) were needed to test the hypothesis using the intended analyses. The sample consisted of 28 adult male probationers receiving mental health, substance abuse, and criminal rehabilitation services through a dual-diagnosis program housed in a court residential treatment facility located in west Texas. Seven participants withdrew from services for a variety of reasons (e.g., disciplinary infractions, voluntarily withdrew, withdrew due to conflicts with employment schedule) prior to or during the experimental phase. Consequently, these cases were excluded from data analysis, leaving 21 remaining participants. The sample was limited to men because the facility houses only male probationers.

All participants were voluntarily enrolled in a correctional treatment program titled Changing Lives and Changing Outcomes: A Treatment Program for Justice Involved Persons With Mental Illness (Morgan et al., 2011). Participants were ineligible for enrollment in the treatment program if they declined to provide written informed consent, if they lacked the capacity to consent, if they were younger than 18 years of age, or if they were unable to read or write in the English language. Participation in the treatment program was not required by the treatment facility, and there were no sanctions for voluntary withdrawal from the program.

Participants’ ages ranged from 18 to 55 years, with a mean age of 29 years and 6 months (SD = 9.26). The sample was predominantly Caucasian (n = 19, 95.5%), with 9.5% (n = 2) identifying as Hispanic. Eight participants (38.1%) reported being single, whereas 5 (23.8%) reported being married, 3 (14.3%) reported being partnered, 3 (14.3%) reported being separated, and 2 (9.5%) reported being divorced. Years of formal education ranged from 8 to 16 years, with a mean of 10.95 years (SD = 2.09); 36% (n = 7) of participants earned a General Equivalency Diploma. With regard to time served, 15% (n = 3) of participants reported having served time in a state or federal correctional institution. Index offenses included assault and aggravated assault, burglary, theft, fraud, forgery, criminal trespassing, criminal mischief, driving while intoxicated, possession of illicit substances, and unauthorized use of a motor vehicle. Length of probated sentence ranged from 12 to 120 months, with a mean sentence of 55.19 months (SD = 26.13). The majority of participants (n = 18, 90%) reported being diagnosed with a mental illness, and such disorders included schizophrenia, schizoaffective disorder, bipolar disorder, major depressive disorder, generalized anxiety disorder, obsessive compulsive disorder, impulse control disorder, attention-deficit/hyperactivity disorder, and various substance use disorders. Most participants (n = 15, 71.4%) reported the current use of psychotropic medication.

Materials

Demographic questionnaire

A researcher-developed, self-report demographic questionnaire was used to obtain relevant demographic, legal, and mental health information from each participant. Items on this measure addressed participants’ age, race/ethnicity, education level, relationship status, probationary status, index offense, length of sentence, time served, current psychiatric diagnoses, current psychotropic medications, and current utilization of psychological services.

Homework Rating Scale–II (HRS-II)

The HRS-II Client and Therapist versions (Kazantzis, Deane, Ronan, & L’Abate, 2005) were used as measures of probationers’ compliance with HW assignments. The HRS-II is a 12-item, self-report measure designed to assess numerous dimensions of HW-related feedback including, but not limited to, quality and quantity of HW completion, difficulty and comprehension of the task, amount of pleasure and mastery experienced, and match with therapy goals. Responses are scored on a 5-point ordinal scale. The HRS-II yields scores on three subscales: Beliefs—ideas related to the design, rationale, purpose, and assignment of the HW task (e.g., the reason for doing the activity was clear to me; the activity matched with my goals for therapy); Consequences—expectations regarding potential outcomes of completing the HW task (e.g., I gained a sense of control over my problems; the activity helped with my progress in therapy); and Engagement—the extent to which the individual participated in the HW activity (e.g., I was able to do the activity well; the activity was difficult for me). Higher scores on each of the subscales represent positive performance in each respective domain. In a validation study, the HRS-II Therapist and Client versions demonstrated good internal consistency reliability (α = .86 and .83, respectively) and excellent interrater reliability (overall intraclass correlation coefficient [ICC] = .83; Kazantzis et al., 2010). Furthermore, findings lent preliminary support for the factorial validity of the instrument, as three clearly defined, theoretically meaningful factors were identified (Kazantzis et al., 2010).

Procedure

Probationers housed in the residential treatment facility were referred by facility staff to participate in the Changing Lives and Changing Outcomes treatment program, within which data collection for this study occurred. Referral decisions were made according to length of sentence, as participants had to have at least 9 months remaining on their sentences to complete the program. Informed consent was obtained from each probationer during the enrollment period. Participants were not informed about the purpose or design of the study; they were merely informed about the opportunity to participate in a correctional treatment program designed to address mental health, substance abuse, and criminal reoffending. Participants also completed the demographic questionnaire on enrollment. Participants were instructed to return all forms to staff on completion. To ensure confidentiality, all data were stored in secure filing cabinets behind two locked doors in the psychology department at Texas Tech University.

The treatment program in which participants were enrolled targeted topics such as mental illness awareness, medication adherence, coping strategies, skill development, criminal thinking, emotion management, criminal associates, and substance abuse (Morgan et al., 2011). Sessions featured psychoeducation, group activities (e.g., handouts, worksheets, videos), and between-sessions HW tasks. The program consisted of group psychotherapy sessions, and participants met three times a week for approximately 6 months. For this study, however, data were gathered during a 6-week experimental phase occurring at the midpoint of the treatment program, with treatment as usual preceding and immediately following the experimental phase. Psychotherapy groups were facilitated by two male, 3rd-year doctoral students in an American Psychological Association–accredited counseling psychology program with one facilitator assigned to each group. The therapists were informed that the purpose of the study was to test the efficacy of three HCESs, but they were not informed of the study’s hypothesis. In total, results from three separate psychotherapy groups were included in the sample.

The treatment program was manualized and was strictly adhered to by the therapists, who made only slight modifications to the delivery of HW assignments during the experimental phase of the program. For each of the three psychotherapy groups, the experimental phase occurred at an identical point in the program and spanned exactly 18 sessions. The study consisted of four HW conditions in total—three enhancement conditions and the HAU condition. During the experimental phase, HCESs were systematically implemented during the delivery of various prescheduled HW assignments. Each condition featured the use of a separate HCES. The first enhancement condition featured task option, wherein group members were permitted to choose—between three equivalent HW tasks—the assignment in which they engaged. Group members made this decision by a majority vote. The second enhancement condition featured task modeling, wherein the therapist provided an in-session demonstration of how to properly complete the HW task. The third enhancement condition featured public commitment, wherein the therapist verbally encouraged the group members to comply with the HW assignment and obtained a tally of those who publicly agreed to comply. Finally, during the HAU condition, the HW assignment was delivered in a neutral manner as dictated by treatment manual (i.e., the participants were assigned the task and given brief instructions, but no choices, encouragement, or demonstrations were provided). Aside from these slight modifications to the delivery of the HW tasks, session content and structure was consistent across groups.

The study featured a within-subjects, counterbalanced, experimental design. The four HW conditions were implemented in a set of three iterations, in partial counterbalanced order, within each of the three psychotherapy groups. The design was such that each HW condition was delivered in conjunction with four predetermined HW tasks (i.e., the same four HW tasks were used with all participants). Each condition was implemented exactly once for each of the four HW tasks during the experimental phase of the study. HW was consistently assigned at the end of each session. Following the implementation of each HW condition, exactly four sessions elapsed before the implementation of the next, with treatment as usual occurring in the meantime. See Table 1 for a depiction of the HW schedule.

Table 1.

Homework Schedule

Group	Week	Day 1	Day 2	Day 3
A	1	Task option	—	—
	2	—	—	Task modeling
	3	—	—	—
	4	—	Public commitment	—
	5	—	—	—
	6	HAU	—	—
B	1	Task modeling	—	—
	2	—	—	HAU
	3	—	—	—
	4	—	Task option	—
	5	—	—	—
	6	Public commitment	—	—
C	1	HAU	—	—
	2	—	—	Public commitment
	3	—	—	—
	4	—	Task modeling	—
	5	—	—	—
	6	Task option	—	—

Note. Dashes indicate treatment as usual (i.e., no homework condition was implemented). HAU = homework as usual.

At the beginning of each session following the delivery of each HW condition, participants were asked to rate their HW compliance by completing the HRS-II Client version. Additionally, therapists rated participants’ HW compliance by completing the HRS-II Therapist version (Kazantzis et al., 2005). In total, for each participant, an HRS-II Client version and an HRS-II Therapist version was completed following the delivery of each of the four HW conditions. As an additional measure of HW compliance, therapists maintained a record of participants’ HW completion (i.e., “yes/no” tally) following the delivery of each HW condition. HW tasks were scored as complete if participants demonstrated a good faith effort in attempting to complete the tasks as assigned. Mental health outcomes were not measured because it was assumed that outcomes assessed during the experimental phase would be confounded by prior involvement in the treatment program (i.e., preexperimental phase). On conclusion of the experimental phase, each psychotherapy group continued as usual for the duration of the treatment program, and no further data were collected.

Data Analytic Strategy

For all analyses, cases containing missing data were excluded using a casewise deletion procedure to maintain unbiased parameter estimates (Howell, 2007). To determine significant (p < .05) within-group differences in HW completion, a related-samples Cochran’s Q test was conducted on the categorical dependent variable (i.e., therapists’ “yes/no” tally). The procedure for assessing HW compliance involved several steps. First, Cronbach’s alpha coefficients were calculated to evaluate the internal consistency reliability of the HRS-II Client and Therapist total scales and subscales. A series of Pearson’s correlation analyses were then employed to assess the relationship between HRS-II subscales. Next, separate one-way doubly multivariate analyses of variance (i.e., repeated-measures analysis of variance with multiple dependent variables; Tabachnick & Fidell, 2007) were conducted on the HRS-II Client and Therapist subscales to determine significant (p < .05) within-group differences in HW compliance. Post hoc pairwise comparisons were examined using Tukey’s honestly significant difference (HSD) tests to compare mean differences while controlling for experiment-wise error rate (Stevens, 1996). Finally, effect sizes were computed where appropriate.

Results

HW Completion

Results of the related-samples Cochran’s Q test indicated no significant differences in rates of HW completion within HW conditions, Q(3) = 3.800, p = .284. Task modeling yielded the highest HW completion rate (94.4%), followed by HAU (88.9%), public commitment (88.9%), and task option (77.8%). See Table 2 for a depiction of HW completion rates by condition.

Table 2.

Rates of Homework Completion by Homework Condition

Condition	No (%)	Yes (%)	N
Homework as usual	2 (11.1)	16 (88.9)	18
Task modeling	1 (5.6)	17 (94.4)	18
Public commitment	2 (11.1)	16 (88.9)	18
Task option	4 (22.2)	14 (77.8)	18
Total	9 (12.5)	63 (87.5)	72

Note. Cochran’s Q test frequency table, p = .284.

HW Compliance

Reliability of HRS-II subscales

Cronbach’s alpha (α) coefficients were calculated to examine the internal consistency reliability of the HRS-II subscales. Total scale Cronbach’s alphas were excellent for both Client and Therapist rater versions (α = .89 for both forms). The Beliefs subscale demonstrated acceptable internal consistency reliability on the Client and Therapist forms (α = .75 and .62, respectively). The Consequences subscale demonstrated good internal consistency reliability on the Client and Therapist forms (α = .80 and .90, respectively). Finally, the Engagement subscale demonstrated good internal consistency reliability on both forms (α = .81 and .88, respectively). Given the overall performance of the HRS-II subscales, all subscales were determined to be reliable constructs and were included in subsequent analyses.

HRS-II subscale intercorrelations

A series of Pearson’s correlation analyses were conducted to assess the relationship between Beliefs, Consequences, and Engagement on each rater version of the HRS-II. The analyses revealed strong positive intercorrelations between all subscales for both Client and Therapist versions (see Table 3 for a depiction of HRS-II scale intercorrelations). Beliefs was strongly related to Consequences for Client and Therapist forms (r = .70 and .57, respectively). These results suggested that the more positive participants’ beliefs were regarding the design, rationale, purpose, and assignment of the HW tasks, the more positively they viewed the potential outcomes of completing the tasks. Beliefs was also strongly related to Engagement for both forms (r = .57 and .47, respectively). These results suggested that the more positive participants’ beliefs were regarding the design, rationale, purpose, and assignment of the HW tasks, the more likely they were to engage in the HW tasks. Finally, Consequences was found to be strongly related to Engagement for both rater versions (r = .58 and .71, respectively). These results suggested that the more positive participants’ expectations were regarding perceived outcomes of completing the HW tasks, the more likely they were to engage in the HW tasks.

Table 3.

Homework Rating Scale–II Client and Therapist Subscale Intercorrelations

Rater Version	Subscale	1	2	3
Client	1. Beliefs	—	.70*	.57*
	2. Consequences		—	.58*
	3. Engagement			—
Therapist	1. Beliefs	—	.57*	.47*
	2. Consequences		—	.71*
	3. Engagement			—

Note. *

p < .001.

Clients’ ratings of HW compliance

A one-way doubly multivariate analysis of variance was conducted to examine the within-subjects effects of HW condition on the HRS-II Client subscales. For this analysis, the total N of 21 was reduced to 17 as 4 cases were excluded due to missing data. The analysis yielded no significant multivariate main effect for HW condition, Wilks’s Λ = .602, F(9, 8) = .5587, p = .778. Given the result was not statistically significant, univariate main effects and pairwise comparisons were not examined. Descriptive statistics for the HRS-II Client subscales are presented in Table 4.

Table 4.

Means and Standard Deviations of Homework Rating Scale–II Client Subscales by Homework Condition

Subscale	Condition	M	SD	n
Beliefs	HAU	13.24	4.49	17
	Task modeling	13.29	4.12	17
	Public commitment	14.06	4.82	17
	Task option	12.77	4.72	17
Consequences	HAU	6.47	3.41	17
	Task modeling	6.94	2.66	17
	Public commitment	7.41	3.18	17
	Task option	6.53	3.81	17
Engagement	HAU	10.82	4.92	17
	Task modeling	12.35	3.97	17
	Public commitment	12.77	2.49	17
	Task option	11.88	4.12	17

Note. Cronbach’s α for Homework Rating Scale–II Client Total, Beliefs, Consequences, and Engagement scales = .89, .75, .80, and .81, respectively. HAU = homework as usual.

Therapists’ ratings of HW compliance

A one-way doubly multivariate analysis of variance was conducted to examine the within-subjects effects of HW condition on the HRS-II Therapist subscales. For this analysis, the total N of 21 was reduced to 18 as 3 cases were excluded due to missing data. The analysis revealed a significant multivariate main effect for HW condition, Wilks’s Λ = .171, F(9, 9) = 4.844, p = .014, η_p² = .829, observed power = .890. Given the significance of the overall test, the univariate main effects were examined for the HRS-II Therapist subscales. A significant univariate main effect was obtained for Beliefs, F(3, 51) = 3.80, p = .016, η_p² = .183, observed power = .785. Post hoc comparisons using Tukey’s HSD criterion (F_T = 4.076, α_FW = .05) revealed that, per the therapists’ ratings, participants displayed significantly more positive beliefs about the design, nature, purpose, and rationale for the HW task in response to public commitment than in response to task modeling, task option, or HAU, respectively, p < .05.

A significant univariate main effect was also obtained for Consequences, F(3, 51) = 2.83, p = .048, η_p² = .143, observed power = .646. Tukey’s HSD comparisons (F_T = 4.076, α_FW = .05) revealed that, per the therapists’ ratings, participants’ expectations regarding the outcomes of completing HW assignments were significantly more positive in response to public commitment than in response to task option, p < .05. In addition, participants’ expectations were judged to be significantly more positive in response to HAU than in response to task option, p < .05.

Finally, a significant univariate main effect was obtained for Engagement, F(3, 51) = 3.86, p = .014, η_p² = .185, observed power = .793. Tukey’s HSD comparisons (F_T = 4.076, α_FW = .05) revealed that therapists believed participants’ engagement in the HW tasks was significantly higher in response to public commitment than in response to task option or HAU, p < .05. In addition, therapists reported that participants’ engagement in HW tasks was significantly higher in response to task modeling than in response to task option, p < .05. Descriptive statistics for the HRS-II Therapist subscales are presented in Table 5.

Table 5.

Means and Standard Deviations of Homework Rating Scale–II Therapist Subscales by Homework Condition

Subscale	Condition	M	SD	n
Beliefs	HAU	11.06	3.80	18
	Task modeling	11.89	2.68	18
	Public commitment	14.78	3.93	18
	Task option	12.28	4.55	18
Consequences	HAU	6.28	3.46	18
	Task modeling	5.89	4.03	18
	Public commitment	6.72	3.69	18
	Task option	4.33	4.09	18
Engagement	HAU	9.00	4.68	18
	Task modeling	10.11	4.74	18
	Public commitment	11.22	4.67	18
	Task option	7.78	5.24	18

Note. Cronbach’s α for Homework Rating Scale–II Therapist Total, Beliefs, Consequences, and Engagement scales = .89, .62, .90, and .88, respectively. HAU = homework as usual.

Discussion

The purpose of this study was to examine whether particular HCESs (task option, task modeling, and public commitment) were effective in improving probationers’ compliance with therapeutic HW tasks during a group treatment program. HW compliance was measured using probationers’ overall HW completion rates as well as scores on the three subscales of the HRS-II (Beliefs, Consequences, and Engagement). Although results were mixed, in general, findings provided preliminary support for the utility of public commitment and task modeling as effective strategies for enhancing HW compliance in correctional psychotherapy. In terms of HW completion, the HCESs were found to have no statistically significant effect on probationers’ completion of therapeutic HW tasks. Despite this finding, task modeling did appear to produce a clinically significant effect on HW completion. Probationers receiving task modeling completed HW at a rate of 94.4%, which was more than 5% higher than HAU (88.9%) and more than 10% higher than the mean completion rate across the three other HW conditions combined (83.3%; see Table 2). Although these findings lacked statistical significance, they suggested that task modeling may be a potentially useful strategy for improving offenders’ completion of therapeutic HW tasks. Nonetheless, given the absence of a statistically significant effect, further research is needed to examine the efficacy of task modeling as a strategy for enhancing HW completion rates with offender populations.

Investigators also measured probationers’ and therapists’ responses on the HRS-II, which yielded various dimensions of HW-related feedback, namely, beliefs associated with the nature and purpose of the HW activities (Beliefs), expectations regarding the consequences of completing the HW activities (Consequences), and overall engagement in the HW activities (Engagement). First of all, the three HRS-II subscales demonstrated acceptable to excellent internal consistency reliability on both rater versions. This provided preliminary evidence that these constructs can be measured reliably in correctional samples. This finding is significant because, to date, the HRS-II has primarily been limited to mental health samples (Kazantzis et al., 2010). As expected, the HRS-II subscales were found to be strongly, positively intercorrelated (see Table 3). Strong positive correlations between Beliefs and Consequences indicated that beliefs about the design, nature, rationale, and assignment of HW tasks were consistent with expectations about potential outcomes resulting from HW completion. Furthermore, these results suggested that providing probationers with a clear understanding of the nature, rationale, and purpose of HW tasks is crucial in helping them understand the potential gains that may be reached by engaging in the tasks. Both subscales were also strongly related to probationers’ overall engagement in HW assignments. This result is consistent with research conducted elsewhere (Kazantzis et al., 2010). These findings are compelling, as they suggest that promoting positive beliefs about HW tasks and positive expectations about outcomes can lead to increased HW compliance in correctional samples, just as in clinical samples.

Examination of the HRS-II subscales also revealed positive findings. Although probationers did not report significant differences in HW compliance in response to the various HCESs, therapists’ ratings seemed to capture several significant effects of the HCESs. First, therapists reported that probationers’ beliefs about the nature, purpose, and rationale of HW tasks were significantly more positive when they were encouraged to publicly commit to their peers that they would complete the HW activities. By comparison, no other HCESs, including HAU, were as effective in eliciting this response. Second, therapists reported that probationers’ expectations regarding outcomes of completing HW tasks were significantly higher when they were encouraged to commit publicly to their peers than when they were given an option in choosing their HW tasks. Finally, therapists rated probationers’ engagement in HW activities as significantly higher in response to public commitment than in response to either HAU or task option. Task modeling was also reported to significantly improve probationers’ engagement in HW activity as compared to task option.

Overall, results provided preliminary evidence that public commitment and task modeling are potentially useful strategies in enhancing offenders’ completion of HW, beliefs about HW, perceived consequences of completing HW, and overall engagement in HW. This finding is generally consistent with the investigators’ predictions. When therapists encouraged group members to publicly commit to completing the HW activities, group members responded with more positive beliefs about the nature and assignment of the HW task. This result is important, as researchers have found that beliefs about HW tasks are predictive of HW compliance (Kazantzis et al., 2010). This finding could suggest that there is a relationship between increased accountability for HW completion and positive beliefs about the HW activity. It may also suggest that there is a motivational component that is activated as a result of public commitment. Results also indicated that when therapists encouraged public commitment, probationers’ expectations about completing HW were significantly improved. Finally, probationers receiving public commitment exhibited significant improvements in quality and quantity of HW compliance. This finding may indicate that public commitment elicits more positive appraisals of HW completion. It may also suggest that public commitment is associated with a certain degree of pride in one’s work.

Like public commitment, task modeling appeared to have a positive impact on HW completion. According to anecdotal accounts by the therapists involved in the study, the process of modeling the HW tasks during the sessions seemed to elucidate potential barriers to, or questions about, the HW tasks, which thereby enabled group members to complete the tasks effectively. Whatever the mechanism by which task modeling produced increased completion rates, the result is important as empirical research has consistently demonstrated that HW compliance is predictive of better general treatment outcomes (Burns & Spangler, 2000; Kazantzis et al., 2000, 2004; Kazantzis & Shinkfield, 2007). It appears that task modeling may be a useful method of increasing offenders’ initial engagement in HW activities, which may lead to better overall HW completion. Overall, these findings provide preliminary support for the use of public commitment and task modeling as strategies for enhancing HW compliance in correctional psychotherapy; however, the investigators acknowledge that further research in this area is needed.

By most accounts, task option performed most poorly in enhancing offenders’ compliance with HW activities. Task option produced the lowest HW completion rate (77.8%), and by therapists’ reports, it resulted in significantly poorer beliefs and expectations about HW tasks, as well as significantly lower engagement in HW activities. This result was contrary to predictions. Investigators expected probationers to gain a sense of ownership over their treatment and enjoy a degree of collaboration with the therapist as a result of selecting their HW activity. Although this occurred to some extent, it was also evident that task option appeared to generate some confusion or misunderstandings about the assignments. Anecdotal evidence indicated that other factors may have been at play. For example, according to anecdotal accounts by the therapists, group members often disagreed during the selection of the HW task. Although the selected task represented a majority vote, it is possible that group members whose selections were not chosen were less inclined to complete the activity due to lack of interest, spite, or other reasons. This could explain the low compliance rates in response to the task option strategy. It seems that providing probationers with an option in selecting their therapeutic HW tasks may create more barriers than benefits to HW compliance. Based on these findings, correctional service providers may consider refraining from offering offenders multiple options in selecting HW activities, at least in group modalities.

These findings should be considered within the context of the study’s various limitations. First of all, the sample was homogeneous with respect to race and ethnicity, gender, and geographic region, which presents potential threats to the external validity of the study. More than 95% of participants identified as Caucasian, which is not representative of larger correctional populations. The sample was also limited to adult male probationers. Other offender classifications (e.g., inmates, parolees, juveniles, females) were not represented in this study. These issues limit the generalizability of results to other correctional populations. Notably, the sample was also rather diverse with regard to age, index offense, and psychiatric diagnosis. The design of the study presented additional limitations. For example, due to the absence of a pretest measure of HW compliance, investigators were unable to determine whether HW compliance rates actually improved over time as a result of the HCESs, only that it differed within conditions. Furthermore, because participants received all HW conditions sequentially, it is possible that there were carryover effects; however, investigators took appropriate measures to minimize this (e.g., counterbalancing, scheduling ample time between each condition). These caveats are inherent in within-subjects designs. A final limitation of this study lies in the fact that overall HW completion rates during the experimental phase of the treatment program were unusually high (87.5%). Although the therapists were not informed about the study’s hypothesis, they were told that the purpose of the study was to test the efficacy of HCESs. Therefore, it is possible that extraneous error variance was introduced as a result of experimentation itself (i.e., Hawthorne effect). Regardless, these high overall HW completion rates may have compromised investigators’ ability to detect statistical effects of the HCESs with regard to completion of HW tasks.

In spite of these limitations, the results of this study are important, as they lend preliminary support to the efficacy of public commitment and task modeling as strategies for enhancing HW compliance in correctional psychotherapy. However, given this study’s limitations, it is important to note that further research is needed to better understand these effects. Given the current data, it appears that the public commitment and task modeling strategies may enhance the clinical value of between-sessions HW activities in correctional settings. Moreover, such value comes at minimal cost to practitioners, as these strategies require little effort and can be easily implemented in a brief amount of time. Positive clinical implications can be extrapolated from this research, as research conducted in the general clinical population shows a strong positive relationship between HW compliance and treatment outcomes (Burns & Spangler, 2000; Kazantzis et al., 2000, 2004; Kazantzis & Shinkfield, 2007). Although it was outside the scope of the present study, future research should examine the relationship between HW compliance and correctional outcomes. Future researchers may also consider examining the effects of combining the public commitment and task modeling strategies. Given the preliminary findings, it is plausible that a combination of the two may produce a positive synergistic effect (i.e., an effect that is greater than the sum of its parts) on HW compliance. Although the current research represents a positive first step, further research in the area of enhancing HW compliance in correctional psychotherapy is needed.

Footnotes

Brendan R. McDonald is a doctoral candidate in counseling psychology at Texas Tech University. His research interests include correctional mental health treatment, forensic issues, and the attorney-client working relationship.

Robert D. Morgan is the John G. Skelton, Jr. Regents Endowed Professor in Psychology at Texas Tech University. His research interests are in correctional mental health treatment, forensic mental health assessment, and professional development and training issues.

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