Psychotherapy Research
ISSN: 1050-3307 (Print) 1468-4381 (Online) Journal homepage: http://www.tandfonline.com/loi/tpsr20
Youth self-efficacy domains as predictors of change in routine community mental health services Jared S. Warren & Benjamin C. Salazar To cite this article: Jared S. Warren & Benjamin C. Salazar (2015) Youth self-efficacy domains as predictors of change in routine community mental health services, Psychotherapy Research, 25:5, 583-594, DOI: 10.1080/10503307.2014.932464 To link to this article: http://dx.doi.org/10.1080/10503307.2014.932464
Published online: 22 Jul 2014.
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Date: 07 November 2015, At: 03:42
Psychotherapy Research, 2015 Vol. 25, No. 5, 583–594, http://dx.doi.org/10.1080/10503307.2014.932464
EMPIRICAL PAPER
Youth self-efficacy domains as predictors of change in routine community mental health services
JARED S. WARREN1 & BENJAMIN C. SALAZAR2 1
Department of Psychology, Brigham Young University, Provo, Utah, USA & 2Counseling and Psychological Service, Brigham Young University, Provo, Utah, USA
Downloaded by [Universite Laval] at 03:42 07 November 2015
(Received 10 January 2013; revised 7 May 2014; accepted 3 June 2014)
Abstract Objective: This study examined how youth self-efficacy in four domains—Social, Academic Diligence, Academic Proficiency, and Behavioral Regulation—was associated with youth symptoms and psychotherapy outcomes. Method: Participants were 104 youth (aged 12–17, mean age 14.6) and their parents/guardians. Youth completed a measure of perceived self-efficacy and the Youth Outcome Questionnaire–Self-Report (YOQ-SR) regularly over the course of treatment; parents/guardians also completed the Youth Outcome Questionnaire. Results: Although none of the selfefficacy domains significantly predicted changes in parent reports of symptoms, individual growth curve models indicated that increases in three of the four self-efficacy domains (Social, Academic Diligence, and Behavioral Regulation) over the course of treatment were associated with concurrent improvements in youth-reported symptoms. Conclusions: Results suggest that youth self-efficacy warrants further study in relation to change processes in youth mental health services. Keywords: child psychotherapy; mental health services research; outcome research; process research
Meta-analyses of child and adolescent psychotherapy interventions show mental health treatment as more effective in improving mental health problems than the passage of time alone (Kazdin & Weisz, 1998; Weisz & Jensen, 2001). Yet, while the efficacy of youth psychotherapy is well established, very little is known regarding the underlying mechanisms of therapeutic change (Kazdin & Nock, 2003; Weersing & Weisz, 2002). A better knowledge of predictors and processes of change can lead to a more parsimonious, effective approach to psychotherapy (Kazdin & Nock, 2003). More specifically, knowledge of the effects of mediating variables could lead to therapy tailored toward promoting more change in those factors which have been shown to produce the best therapeutic outcomes. Also, identifying moderators of change can lead to improved provision of treatment services to different kinds of clients. One socio-cognitive factor that may be an important predictor and/or mechanism of therapeutic change in
youth mental health services is self-efficacy. Youth selfefficacy—a youth’s beliefs and judgments of his/her ability to be successful in a given context—is related to a number of important social, behavioral, and academic outcomes. For example, high self-efficacy beliefs in youth are related to higher academic achievement, lower rates of conduct problems, and better social relationships (Caprara, Barbaranelli, Pastorelli, & Cervone, 2004; Caprara et al., 2008). In contrast, low youth self-efficacy has been linked to depression and behavior problems (Bandura, Caprara, Barbaranelli, Pastorelli, & Regalia, 2001; Kim & Cicchetti, 2003; Matsushima & Shiomi, 2003). According to Bandura and colleagues, psychotherapeutic interventions have their effects through the mediation of self-efficacy (Bandura, 1977; Bandura & Adams, 1977; Cervone & Scott, 1995). However, most of the research on selfefficacy has been conducted in nonclinical settings, with subjects not receiving mental health treatment (e.g., Bandura et al., 2001).
Correspondence concerning this article should be addressed to Jared S. Warren, Department of Psychology, Brigham Young University, 291 TLRB, Provo, Utah 84602-8626, USA. Email: [email protected] © 2014 Society for Psychotherapy Research
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A number of studies have examined the pathways through which self-efficacy may facilitate behavior change. First, people are more likely to engage in activities in which they judge themselves to be efficacious (Betz & Hackett, 1981). Second, people with higher perceived self-efficacy are also more likely to persevere during difficult tasks (Bandura & Cervone, 1983). Third, self-efficacy can also affect behavior through its affective consequences (Bandura, Cioffi, Taylor, & Brouillard, 1988). The affective outcomes of self-efficacy have especially important potential implications for psychotherapy because clients with high perceived self-efficacy will generally experience less stress and depression during treatment and will be able to cope better with traumatic life experiences (Major et al., 1990; Murphy, 1988). These affective and behavioral consequences of self-efficacy explain to some degree why children and adolescents with higher perceived self-efficacy would be expected to have more favorable treatment outcomes than those with a low perceived self-efficacy. The self-efficacy literature already provides support for the notion that a person’s perceived self-efficacy facilitates behavior change in a variety of situations. However, the majority of self-efficacy research has utilized adult subjects (e.g., Backenstrass et al., 2006; Naar-King et al., 2006), with few studies examining the relation between self-efficacy and mental health outcomes in children and adolescents (Connolly, 1989; Van Horn, 1997). The nascent child and adolescent literature on self-efficacy and psychosocial functioning reveals mixed results, with some studies failing to demonstrate a significant association (Connolly, 1989). One of the proposed criteria for establishing a mediated relationship is observing a strong association between the predictor and criterion variables (Kazdin, 2007); in this case, an association between increases in self-efficacy and improvements in symptoms. As this association has rarely been examined in the context of youth mental health services, addressing this question appears to be an important next step in elucidating underlying change processes. In addition, although self-efficacy is a multidimensional construct, relatively little is known regarding the specific domains of youth self-efficacy that may be most strongly related to psychosocial outcomes. Most child and adolescent self-efficacy research has focused on two domains: social and academic selfefficacy. Social self-efficacy has been defined as “the belief that one is capable of exercising control over the reactions and openness of other people” (Hagedoorn & Molleman, 2006, p. 643), while academic efficacy deals with a person’s beliefs about his/her ability to succeed in scholastic endeavors. Another potentially important domain of self-efficacy
for youth behavioral and emotional functioning is efficacy for behavioral regulation. Behavioral regulation efficacy deals with a person’s beliefs about his/her ability to manage negative emotions, resist negative peer pressure, and make progress toward meaningful goals (Bandura et al., 2001). Although less research has been performed on this domain of self-efficacy than the other domains, results from Bandura et al. (2001) suggest that self-regulation efficacy may be of particular significance to youth mental health treatment. Many adolescents in outpatient treatment present problems of conduct, attention, and depression. It is possible that these problems have origins in adolescents’ ability to regulate themselves appropriately. Thus, self-efficacy for behavioral regulation may be more strongly associated with psychosocial functioning than either social or academic efficacy. Additional research on the relation between specific domains of youth self-efficacy and psychosocial functioning could ultimately yield valuable insights into change processes in youth mental health services. Finally, although identifying potential predictors and processes of change is an important goal of psychotherapy research in any treatment context, this information may be most useful when derived from studies conducted in “real-world” clinical settings because of the differences typically observed between controlled clinical trials and actual practice settings (Weisz, Jensen, & McLeod, 2005). Child and adolescent psychotherapy conducted in controlled laboratory settings differs from mental health treatment in “usual care” settings when it comes to both the subjects and the treatment itself. For example, subjects recruited for research, as opposed to referred subjects in usual care, often present with less severe symptoms (Kazdin, 2003) and a lack of comorbid conditions (Weersing & Weisz, 2002). Parents and families may vary substantially across research and usual care settings, with youth recruited for research studies typically belonging to families experiencing less dysfunction and a more advantaged environment (Kazdin, 2003). In addition, the type of treatment provided, monitoring of therapist adherence to the treatment protocol, level of supervision, and average therapist caseload may differ significantly across traditional research and usual care settings. Consequently, some researchers note that the most externally valid answers to questions about outcomes and change processes may come from research conducted in routine clinical practice settings (Weisz et al., 2005). The purpose of the present study was to examine how four youth self-efficacy domains—Social, Academic Diligence, Academic Proficiency, and Behavioral Regulation—relate to youth symptoms and psychotherapy outcomes in routine outpatient
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Psychotherapy Research services delivered in a community mental health system. More specifically, four research questions were examined as part of this study: (i) How do youths’ reports of their self-efficacy in the four targeted domains change over the course of routine mental health services? (ii) Does youth self-efficacy at the beginning of treatment predict subsequent treatment outcomes (specifically, the rate of change over the course of treatment)? (iii) Are changes in youth self-efficacy over the course of treatment associated with changes in youth symptoms? (iv) Which specific domain of youth self-efficacy is most strongly associated with youth outcomes? We hypothesized that (i) youth self-efficacy would increase over the course of treatment for each of the domains; (ii) higher youth self-efficacy, in any domain, at the start of treatment would predict more rapid improvement in symptoms (steeper rate of change); (iii) increases in self-efficacy domains over the course of treatment would be associated with improvements in youth symptoms; and (iv) the Behavioral Regulation domain of youth self-efficacy would be most strongly related to youth outcomes. Method Data for this study were collected as part of a broader research program examining mental health treatment processes and outcomes of children and adolescents served in community mental health systems (Warren et al., 2008). Participant data for youth self-efficacy and treatment outcomes were reanalyzed in this study to evaluate the association of four specific domains of youth self-efficacy to initial symptoms and subsequent treatment outcomes. Participants This study sample included 104 adolescents aged 12–17 (mean age = 14.6 years; 46.2% female) who received outpatient treatment through a large community mental health system in the US Intermountain West. The sample was composed of participants from various ethnic groups, including 8 Mexican Americans (7.7%), 5 identified as Hispanic, not from Mexico (4.8%), 7 African-Americans (6.7%), 82 Caucasians (78.8%), 1 Native American/Alaska Native participant, and 1 Pacific Islander. Participants in the study typically came from lower to middle income households. Forty-four percent of participants’ parents reported no monthly income; while some of these participants may have declined to respond, it is believed that a substantial number of participants had no monthly income. The median monthly income for those who reported an income
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was $1070 per month. Sixty-three participants (60.6%) received medication management services as part of their treatment. The mean number of therapy sessions was 10.6 sessions per participant, including individual and family therapy, with a mean of 2.2 sessions per month. Participants presented with a wide range of mental health symptoms and diagnoses as assigned by the primary clinician. There was a high rate of comorbidity, with 80% of participants (n = 83) having multiple diagnoses. The most common primary diagnoses included depressive disorders (n = 35; 33.7%), followed by Attention-Deficit/Hyperactivity Disorder (ADHD) (n = 25; 24%), anxiety disorders (n = 15; 14.4%), adjustment disorders (n = 11; 10.6%), and conduct disorders (n = 8; 7.7%). The remaining 9.6% of participants exhibited a wide range of primary diagnoses, including bipolar disorder, bulimia nervosa, and cannabis abuse, among others. Clinician ratings on the Children’s Global Assessment Scale (CGAS) indicated a fairly broad range of functioning among participants. Scores ranged from 35 (major impairment of functioning in several areas) to 71 (no more than slight impairments in functioning). The median CGAS score was 55, indicating a variable level of functioning with sporadic difficulties, and most participants who had a CGAS score fell in the 51–60 range. As part of routine services, clients participated in individual and family therapy sessions that consisted of an eclectic range of therapeutic techniques and orientations. Therapists in this setting reported that they generally employed family therapy and cognitive strategies more often than psychodynamic or behavioral strategies. In general, the approach was consistent with the “clinically derived treatment” described by Weisz (2004, p. 12; i.e., common elements included talking or playing with the child, talking with parents about concerns, listening reflectively, showing empathy, and responding to the issues the child or parent brings to therapy). Measures Self-efficacy. Youth self-efficacy was measured using a 24-item questionnaire based on the test items developed by Bandura (2006). Items were selected following Bandura’s (2006) recommendations for constructing scales of self-efficacy. Specifically, items were identified that had reasonable face validity, were developmentally relevant to the target sample, had lower demand characteristics, and were not expected to have obvious floor or ceiling effects. Items were selected to incorporate a broad range of domains relevant to young adolescents, and to yield a generalized self-efficacy score as well as social,
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academic, and self-regulation subscales. A copy of the measure used along with scoring procedures can be obtained by contacting the primary author. A principal components analysis of the self-efficacy questionnaire revealed four main factors that significantly explained variability in the data and demonstrated adequate internal consistency (as determined by their eigenvalues having a value greater than 1.0 and internal consistency reliability values of .75 or greater; total variance explained was 56%). Factor loadings were rotated using oblique oblimin rotation. The four self-efficacy factors were named Social, Academic Diligence, Academic Proficiency, and Behavioral Regulation. The Social factor consisted of seven items assessing perceived ability to make and keep friends, recruit support from others, and use effective social skills (e.g., “How well can you get a friend to help you when you have social problems?” “How well can you work in a group?”). Item factor loadings for the Social domain ranged from .462 to .784. The Academic Diligence factor consisted of four items assessing perceived selfmotivation for completing schoolwork, ability to finish assignments on time, and to study when there are other interesting things to do (e.g., “How well can you motivate yourself to do schoolwork?” “How well can you study when there are other interesting things to do?”). Item factor loadings for the Academic Diligence domain ranged from .585 to .754. The Academic Proficiency domain consisted of five items assessing perceived ability to learn various academic subjects (e.g., “How well can you learn science?” “How well can you learn social studies?”). Item factor loadings for the Academic Proficiency domain ranged from .458 to .621. The Behavioral Regulation factor consisted of four items assessing perceived ability to control one’s temper and persist in goal-directed behavior (e.g., “How well can you control your temper?” “How well can you live up to what your parents expect of you?”). Item factor loadings for the Behavioral Regulation domain ranged from .391 to .804. Across the measure, item factor loading results generally followed a simple structure, with items loading strongly only their primary factor. One exception was the item “How well can you participate in classroom discussions.” This item loaded on both the Social (.465) and Academic Proficiency (.458) domains, and was included in the scoring of both domains due to its relevance to both areas. Four items remaining on the measure did not load sufficiently onto any of the four factors, and did not yield an internally consistent or interpretable factor on their own. Self-efficacy scores have a possible range from one to seven, with lower scores indicating lower perceived self-efficacy in a given domain. Psychometric
analyses indicated high internal consistency for the total measure (α = .91), and moderate-to-high internal consistency for the self-efficacy domains of Social (α = .87), Academic Diligence (α = .77), Academic Proficiency (α = .77), and Behavioral Regulation (α = .75). Test–retest reliability examined in the present sample over an approximately one-month period (Time 2 to Time 3) was .77 for the full measure. Treatment outcomes. The Youth Outcome Questionnaire (YOQ; Burlingame et al., 1996, 2005) and the Youth Outcome Questionnaire Self– Report (YOQ-SR; Wells, Burlingame, & Rose, 2003) were utilized to measure treatment outcomes. The YOQ (a parent-report questionnaire) and YOQSR (youth self-report questionnaire) were developed as measures of treatment progress for children and adolescents (aged 4–17) by assessing behavior change over the course of treatment. These questionnaires were designed for the specific purpose of being both relatively brief and sensitive to change over time (Burlingame et al., 2005). Both the YOQ and the YOQ-SR consist of 64 items that examine a variety of different domains pertinent to mental health treatment. These domains include intrapersonal distress (e.g., emotional distress), somatic problems (e.g., complaining of dizziness or headaches), interpersonal relations (e.g., problems with parents or peers), critical items (e.g., suicide, delusions, paranoia), social problems (e.g., cutting school or truancy), and behavior dysfunction (e.g., being inattentive, restless, or hyperactive). The items use a 5-point Likert-type scale and summative scoring to produce a total score for overall psychosocial distress. Total scores may range from −16 to 240 (eight reverse-scored items assessing adaptive behaviors can produce negative scores), with higher scores indicating greater psychosocial distress. Scores at or above the established clinical cutscore of 46 are considered in the clinical range for level of distress. The YOQ and YOQ-SR are administered at intake to establish a baseline level of youth symptoms, and are then administered periodically through the course of treatment to monitor progress (Burlingame et al., 2005). For this study, the total scores for the YOQ and YOQ-SR were used as an assessment of overall psychosocial distress. Studies on the psychometric properties of the YOQ indicate a high internal consistency for the total score (r = .97) and test–retest reliability scores over .70. Scores for the total YOQ measure correlate highly with total problems scores from the Child Behavior Checklist (r = .75), which is often used to assess treatment outcomes in youth (Burlingame et al., 1996, 2005).
Psychotherapy Research Table I. Means and standard deviations for self-efficacy and outcome measures at participant intake to treatment.
YOQ Parent Report total YOQ-SR Youth Report total Social self-efficacy AD self-efficacy AP self-efficacy BR self-efficacy
Mean
SD
87.62 70.89 4.94 3.84 4.69 4.40
38.51 35.20 1.20 1.24 1.20 1.28
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AD, Academic Diligence; AP, Academic Proficiency; BR, Behavioral Regulation.
The YOQ-SR demonstrates high to moderately high internal consistency for each of the total scores (r = .95) across two samples, including a community youth group (N = 206) and a clinical youth group (N = 4037) (Ridge, Warren, Burlingame, Wells, & Tumblin, 2009). The YOQ-SR also demonstrates high temporal stability, with a test–retest reliability coefficient of .89 for the total score. As with the YOQ, the YOQ-SR correlates strongly with other commonly used measures of treatment outcomes in youth, such as the Child Behavior Checklist Youth Self-Report (r = .83) and the Behavior Assessment System for Children-2 Self-Report of Personality (r = .75). Table I provides means and standard deviations of youth self-efficacy and YOQ scores at intake.
Procedures Participants were recruited during their intake session at a large community mental health system in a metropolitan area in the Intermountain West. Of the clients invited to participate during initial intake procedures at the clinic, 62% participated in the study, resulting in our sample of 104 youth. Those who chose to participate were provided with a packet to complete for both the adolescent and the parent, which included a consent form and a variety of measures, including the YOQ in the parent packets and the self-efficacy measure and YOQ-SR in the youth packets. Research assistants administered these same measures to participants and their parents at the clinic at regular intervals immediately before or after the participants’ scheduled treatment sessions. The intervals included follow-ups at approximately three weeks, two months, four months, and six months after intake. Participants received a $10 gift certificate to a local store after completing the first set of measures and a $5 gift certificate for each set of measures completed during follow-up intervals.
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Analyses In examining the changes that occurred over the course of treatment in youth symptoms and youth self-efficacy domains, two components of change were of interest. First, the slope of change was examined to establish the direction and rate of change. Second, the shape of the change trajectory was examined to establish how change occurred at different time points in treatment. The treatment outcome variables were tested first, using linear, quadratic, logarithmic (natural log), and polynomial models for both parent report and youth report YOQ data. For parent report YOQ data, according to Schwarz’s Bayesian Criterion (BIC) for examining model fit, the logarithmic model provided the best fitting model of change. That is, according to parent reports, youth symptoms decreased over the course of treatment, with change occurring most rapidly at the start of treatment, then slowing down over subsequent treatment sessions. For youth report (YOQ-SR) data, the linear model of change provided the only significant fit to the data. As with the parent-report data, youth reports indicated a general decrease in symptoms over time, although change occurred at a more consistent pace over the course of treatment. Hierarchical linear modeling, also known as individual growth curve modeling or random effects regression analysis, was used to examine the changes that occurred in youth self-efficacy and in youth symptoms over the six-month data collection period for each participant. This type of analysis also revealed how changes in youth self-efficacy related to changes in youth symptomatology. The statistical analysis software SPSS 16.0 was utilized to analyze the data. Results Hypothesis 1: Patterns of Change in Youth Selfefficacy Self-efficacy domain change trajectories were also examined by testing linear, quadratic, and logarithmic models to see which model provided the best fit for the data. According to Schwarz’s BIC, the logarithmic model (natural log transformation) provided the best fit for all domains of self-efficacy. Table II provides data on the trajectories for each domain of self-efficacy. The fixed effects refer to the average change trajectory of the entire sample. Only the self-efficacy domain of Academic Proficiency exhibited a fixed pattern of change over time. In other words, the average change that occurred for the sample as a whole was only significant for Academic Proficiency self-efficacy, which demonstrated a
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Table II. Fixed and random effects for self-efficacy domain change trajectories. Domain Social
Fixed effects Random effects
AD
Fixed effects Random effects
AP
Fixed effects Random effects
BR
Fixed effects
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Random effects
Estimate
SE
p
4.907 0.002 1.230 0.061 3.827 0.039 1.004 0.064 4.639 0.092 1.130 0.018 4.383 0.046 1.219 0.074
0.122 0.046 0.214 0.025 0.120 0.054 0.224 0.036 0.122 0.042 0.222 0.024 0.127 0.053 0.241 0.034
ISSN: 1050-3307 (Print) 1468-4381 (Online) Journal homepage: http://www.tandfonline.com/loi/tpsr20
Youth self-efficacy domains as predictors of change in routine community mental health services Jared S. Warren & Benjamin C. Salazar To cite this article: Jared S. Warren & Benjamin C. Salazar (2015) Youth self-efficacy domains as predictors of change in routine community mental health services, Psychotherapy Research, 25:5, 583-594, DOI: 10.1080/10503307.2014.932464 To link to this article: http://dx.doi.org/10.1080/10503307.2014.932464
Published online: 22 Jul 2014.
Submit your article to this journal
Article views: 98
View related articles
View Crossmark data
Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=tpsr20 Download by: [Universite Laval]
Date: 07 November 2015, At: 03:42
Psychotherapy Research, 2015 Vol. 25, No. 5, 583–594, http://dx.doi.org/10.1080/10503307.2014.932464
EMPIRICAL PAPER
Youth self-efficacy domains as predictors of change in routine community mental health services
JARED S. WARREN1 & BENJAMIN C. SALAZAR2 1
Department of Psychology, Brigham Young University, Provo, Utah, USA & 2Counseling and Psychological Service, Brigham Young University, Provo, Utah, USA
Downloaded by [Universite Laval] at 03:42 07 November 2015
(Received 10 January 2013; revised 7 May 2014; accepted 3 June 2014)
Abstract Objective: This study examined how youth self-efficacy in four domains—Social, Academic Diligence, Academic Proficiency, and Behavioral Regulation—was associated with youth symptoms and psychotherapy outcomes. Method: Participants were 104 youth (aged 12–17, mean age 14.6) and their parents/guardians. Youth completed a measure of perceived self-efficacy and the Youth Outcome Questionnaire–Self-Report (YOQ-SR) regularly over the course of treatment; parents/guardians also completed the Youth Outcome Questionnaire. Results: Although none of the selfefficacy domains significantly predicted changes in parent reports of symptoms, individual growth curve models indicated that increases in three of the four self-efficacy domains (Social, Academic Diligence, and Behavioral Regulation) over the course of treatment were associated with concurrent improvements in youth-reported symptoms. Conclusions: Results suggest that youth self-efficacy warrants further study in relation to change processes in youth mental health services. Keywords: child psychotherapy; mental health services research; outcome research; process research
Meta-analyses of child and adolescent psychotherapy interventions show mental health treatment as more effective in improving mental health problems than the passage of time alone (Kazdin & Weisz, 1998; Weisz & Jensen, 2001). Yet, while the efficacy of youth psychotherapy is well established, very little is known regarding the underlying mechanisms of therapeutic change (Kazdin & Nock, 2003; Weersing & Weisz, 2002). A better knowledge of predictors and processes of change can lead to a more parsimonious, effective approach to psychotherapy (Kazdin & Nock, 2003). More specifically, knowledge of the effects of mediating variables could lead to therapy tailored toward promoting more change in those factors which have been shown to produce the best therapeutic outcomes. Also, identifying moderators of change can lead to improved provision of treatment services to different kinds of clients. One socio-cognitive factor that may be an important predictor and/or mechanism of therapeutic change in
youth mental health services is self-efficacy. Youth selfefficacy—a youth’s beliefs and judgments of his/her ability to be successful in a given context—is related to a number of important social, behavioral, and academic outcomes. For example, high self-efficacy beliefs in youth are related to higher academic achievement, lower rates of conduct problems, and better social relationships (Caprara, Barbaranelli, Pastorelli, & Cervone, 2004; Caprara et al., 2008). In contrast, low youth self-efficacy has been linked to depression and behavior problems (Bandura, Caprara, Barbaranelli, Pastorelli, & Regalia, 2001; Kim & Cicchetti, 2003; Matsushima & Shiomi, 2003). According to Bandura and colleagues, psychotherapeutic interventions have their effects through the mediation of self-efficacy (Bandura, 1977; Bandura & Adams, 1977; Cervone & Scott, 1995). However, most of the research on selfefficacy has been conducted in nonclinical settings, with subjects not receiving mental health treatment (e.g., Bandura et al., 2001).
Correspondence concerning this article should be addressed to Jared S. Warren, Department of Psychology, Brigham Young University, 291 TLRB, Provo, Utah 84602-8626, USA. Email: [email protected] © 2014 Society for Psychotherapy Research
Downloaded by [Universite Laval] at 03:42 07 November 2015
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A number of studies have examined the pathways through which self-efficacy may facilitate behavior change. First, people are more likely to engage in activities in which they judge themselves to be efficacious (Betz & Hackett, 1981). Second, people with higher perceived self-efficacy are also more likely to persevere during difficult tasks (Bandura & Cervone, 1983). Third, self-efficacy can also affect behavior through its affective consequences (Bandura, Cioffi, Taylor, & Brouillard, 1988). The affective outcomes of self-efficacy have especially important potential implications for psychotherapy because clients with high perceived self-efficacy will generally experience less stress and depression during treatment and will be able to cope better with traumatic life experiences (Major et al., 1990; Murphy, 1988). These affective and behavioral consequences of self-efficacy explain to some degree why children and adolescents with higher perceived self-efficacy would be expected to have more favorable treatment outcomes than those with a low perceived self-efficacy. The self-efficacy literature already provides support for the notion that a person’s perceived self-efficacy facilitates behavior change in a variety of situations. However, the majority of self-efficacy research has utilized adult subjects (e.g., Backenstrass et al., 2006; Naar-King et al., 2006), with few studies examining the relation between self-efficacy and mental health outcomes in children and adolescents (Connolly, 1989; Van Horn, 1997). The nascent child and adolescent literature on self-efficacy and psychosocial functioning reveals mixed results, with some studies failing to demonstrate a significant association (Connolly, 1989). One of the proposed criteria for establishing a mediated relationship is observing a strong association between the predictor and criterion variables (Kazdin, 2007); in this case, an association between increases in self-efficacy and improvements in symptoms. As this association has rarely been examined in the context of youth mental health services, addressing this question appears to be an important next step in elucidating underlying change processes. In addition, although self-efficacy is a multidimensional construct, relatively little is known regarding the specific domains of youth self-efficacy that may be most strongly related to psychosocial outcomes. Most child and adolescent self-efficacy research has focused on two domains: social and academic selfefficacy. Social self-efficacy has been defined as “the belief that one is capable of exercising control over the reactions and openness of other people” (Hagedoorn & Molleman, 2006, p. 643), while academic efficacy deals with a person’s beliefs about his/her ability to succeed in scholastic endeavors. Another potentially important domain of self-efficacy
for youth behavioral and emotional functioning is efficacy for behavioral regulation. Behavioral regulation efficacy deals with a person’s beliefs about his/her ability to manage negative emotions, resist negative peer pressure, and make progress toward meaningful goals (Bandura et al., 2001). Although less research has been performed on this domain of self-efficacy than the other domains, results from Bandura et al. (2001) suggest that self-regulation efficacy may be of particular significance to youth mental health treatment. Many adolescents in outpatient treatment present problems of conduct, attention, and depression. It is possible that these problems have origins in adolescents’ ability to regulate themselves appropriately. Thus, self-efficacy for behavioral regulation may be more strongly associated with psychosocial functioning than either social or academic efficacy. Additional research on the relation between specific domains of youth self-efficacy and psychosocial functioning could ultimately yield valuable insights into change processes in youth mental health services. Finally, although identifying potential predictors and processes of change is an important goal of psychotherapy research in any treatment context, this information may be most useful when derived from studies conducted in “real-world” clinical settings because of the differences typically observed between controlled clinical trials and actual practice settings (Weisz, Jensen, & McLeod, 2005). Child and adolescent psychotherapy conducted in controlled laboratory settings differs from mental health treatment in “usual care” settings when it comes to both the subjects and the treatment itself. For example, subjects recruited for research, as opposed to referred subjects in usual care, often present with less severe symptoms (Kazdin, 2003) and a lack of comorbid conditions (Weersing & Weisz, 2002). Parents and families may vary substantially across research and usual care settings, with youth recruited for research studies typically belonging to families experiencing less dysfunction and a more advantaged environment (Kazdin, 2003). In addition, the type of treatment provided, monitoring of therapist adherence to the treatment protocol, level of supervision, and average therapist caseload may differ significantly across traditional research and usual care settings. Consequently, some researchers note that the most externally valid answers to questions about outcomes and change processes may come from research conducted in routine clinical practice settings (Weisz et al., 2005). The purpose of the present study was to examine how four youth self-efficacy domains—Social, Academic Diligence, Academic Proficiency, and Behavioral Regulation—relate to youth symptoms and psychotherapy outcomes in routine outpatient
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Psychotherapy Research services delivered in a community mental health system. More specifically, four research questions were examined as part of this study: (i) How do youths’ reports of their self-efficacy in the four targeted domains change over the course of routine mental health services? (ii) Does youth self-efficacy at the beginning of treatment predict subsequent treatment outcomes (specifically, the rate of change over the course of treatment)? (iii) Are changes in youth self-efficacy over the course of treatment associated with changes in youth symptoms? (iv) Which specific domain of youth self-efficacy is most strongly associated with youth outcomes? We hypothesized that (i) youth self-efficacy would increase over the course of treatment for each of the domains; (ii) higher youth self-efficacy, in any domain, at the start of treatment would predict more rapid improvement in symptoms (steeper rate of change); (iii) increases in self-efficacy domains over the course of treatment would be associated with improvements in youth symptoms; and (iv) the Behavioral Regulation domain of youth self-efficacy would be most strongly related to youth outcomes. Method Data for this study were collected as part of a broader research program examining mental health treatment processes and outcomes of children and adolescents served in community mental health systems (Warren et al., 2008). Participant data for youth self-efficacy and treatment outcomes were reanalyzed in this study to evaluate the association of four specific domains of youth self-efficacy to initial symptoms and subsequent treatment outcomes. Participants This study sample included 104 adolescents aged 12–17 (mean age = 14.6 years; 46.2% female) who received outpatient treatment through a large community mental health system in the US Intermountain West. The sample was composed of participants from various ethnic groups, including 8 Mexican Americans (7.7%), 5 identified as Hispanic, not from Mexico (4.8%), 7 African-Americans (6.7%), 82 Caucasians (78.8%), 1 Native American/Alaska Native participant, and 1 Pacific Islander. Participants in the study typically came from lower to middle income households. Forty-four percent of participants’ parents reported no monthly income; while some of these participants may have declined to respond, it is believed that a substantial number of participants had no monthly income. The median monthly income for those who reported an income
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was $1070 per month. Sixty-three participants (60.6%) received medication management services as part of their treatment. The mean number of therapy sessions was 10.6 sessions per participant, including individual and family therapy, with a mean of 2.2 sessions per month. Participants presented with a wide range of mental health symptoms and diagnoses as assigned by the primary clinician. There was a high rate of comorbidity, with 80% of participants (n = 83) having multiple diagnoses. The most common primary diagnoses included depressive disorders (n = 35; 33.7%), followed by Attention-Deficit/Hyperactivity Disorder (ADHD) (n = 25; 24%), anxiety disorders (n = 15; 14.4%), adjustment disorders (n = 11; 10.6%), and conduct disorders (n = 8; 7.7%). The remaining 9.6% of participants exhibited a wide range of primary diagnoses, including bipolar disorder, bulimia nervosa, and cannabis abuse, among others. Clinician ratings on the Children’s Global Assessment Scale (CGAS) indicated a fairly broad range of functioning among participants. Scores ranged from 35 (major impairment of functioning in several areas) to 71 (no more than slight impairments in functioning). The median CGAS score was 55, indicating a variable level of functioning with sporadic difficulties, and most participants who had a CGAS score fell in the 51–60 range. As part of routine services, clients participated in individual and family therapy sessions that consisted of an eclectic range of therapeutic techniques and orientations. Therapists in this setting reported that they generally employed family therapy and cognitive strategies more often than psychodynamic or behavioral strategies. In general, the approach was consistent with the “clinically derived treatment” described by Weisz (2004, p. 12; i.e., common elements included talking or playing with the child, talking with parents about concerns, listening reflectively, showing empathy, and responding to the issues the child or parent brings to therapy). Measures Self-efficacy. Youth self-efficacy was measured using a 24-item questionnaire based on the test items developed by Bandura (2006). Items were selected following Bandura’s (2006) recommendations for constructing scales of self-efficacy. Specifically, items were identified that had reasonable face validity, were developmentally relevant to the target sample, had lower demand characteristics, and were not expected to have obvious floor or ceiling effects. Items were selected to incorporate a broad range of domains relevant to young adolescents, and to yield a generalized self-efficacy score as well as social,
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academic, and self-regulation subscales. A copy of the measure used along with scoring procedures can be obtained by contacting the primary author. A principal components analysis of the self-efficacy questionnaire revealed four main factors that significantly explained variability in the data and demonstrated adequate internal consistency (as determined by their eigenvalues having a value greater than 1.0 and internal consistency reliability values of .75 or greater; total variance explained was 56%). Factor loadings were rotated using oblique oblimin rotation. The four self-efficacy factors were named Social, Academic Diligence, Academic Proficiency, and Behavioral Regulation. The Social factor consisted of seven items assessing perceived ability to make and keep friends, recruit support from others, and use effective social skills (e.g., “How well can you get a friend to help you when you have social problems?” “How well can you work in a group?”). Item factor loadings for the Social domain ranged from .462 to .784. The Academic Diligence factor consisted of four items assessing perceived selfmotivation for completing schoolwork, ability to finish assignments on time, and to study when there are other interesting things to do (e.g., “How well can you motivate yourself to do schoolwork?” “How well can you study when there are other interesting things to do?”). Item factor loadings for the Academic Diligence domain ranged from .585 to .754. The Academic Proficiency domain consisted of five items assessing perceived ability to learn various academic subjects (e.g., “How well can you learn science?” “How well can you learn social studies?”). Item factor loadings for the Academic Proficiency domain ranged from .458 to .621. The Behavioral Regulation factor consisted of four items assessing perceived ability to control one’s temper and persist in goal-directed behavior (e.g., “How well can you control your temper?” “How well can you live up to what your parents expect of you?”). Item factor loadings for the Behavioral Regulation domain ranged from .391 to .804. Across the measure, item factor loading results generally followed a simple structure, with items loading strongly only their primary factor. One exception was the item “How well can you participate in classroom discussions.” This item loaded on both the Social (.465) and Academic Proficiency (.458) domains, and was included in the scoring of both domains due to its relevance to both areas. Four items remaining on the measure did not load sufficiently onto any of the four factors, and did not yield an internally consistent or interpretable factor on their own. Self-efficacy scores have a possible range from one to seven, with lower scores indicating lower perceived self-efficacy in a given domain. Psychometric
analyses indicated high internal consistency for the total measure (α = .91), and moderate-to-high internal consistency for the self-efficacy domains of Social (α = .87), Academic Diligence (α = .77), Academic Proficiency (α = .77), and Behavioral Regulation (α = .75). Test–retest reliability examined in the present sample over an approximately one-month period (Time 2 to Time 3) was .77 for the full measure. Treatment outcomes. The Youth Outcome Questionnaire (YOQ; Burlingame et al., 1996, 2005) and the Youth Outcome Questionnaire Self– Report (YOQ-SR; Wells, Burlingame, & Rose, 2003) were utilized to measure treatment outcomes. The YOQ (a parent-report questionnaire) and YOQSR (youth self-report questionnaire) were developed as measures of treatment progress for children and adolescents (aged 4–17) by assessing behavior change over the course of treatment. These questionnaires were designed for the specific purpose of being both relatively brief and sensitive to change over time (Burlingame et al., 2005). Both the YOQ and the YOQ-SR consist of 64 items that examine a variety of different domains pertinent to mental health treatment. These domains include intrapersonal distress (e.g., emotional distress), somatic problems (e.g., complaining of dizziness or headaches), interpersonal relations (e.g., problems with parents or peers), critical items (e.g., suicide, delusions, paranoia), social problems (e.g., cutting school or truancy), and behavior dysfunction (e.g., being inattentive, restless, or hyperactive). The items use a 5-point Likert-type scale and summative scoring to produce a total score for overall psychosocial distress. Total scores may range from −16 to 240 (eight reverse-scored items assessing adaptive behaviors can produce negative scores), with higher scores indicating greater psychosocial distress. Scores at or above the established clinical cutscore of 46 are considered in the clinical range for level of distress. The YOQ and YOQ-SR are administered at intake to establish a baseline level of youth symptoms, and are then administered periodically through the course of treatment to monitor progress (Burlingame et al., 2005). For this study, the total scores for the YOQ and YOQ-SR were used as an assessment of overall psychosocial distress. Studies on the psychometric properties of the YOQ indicate a high internal consistency for the total score (r = .97) and test–retest reliability scores over .70. Scores for the total YOQ measure correlate highly with total problems scores from the Child Behavior Checklist (r = .75), which is often used to assess treatment outcomes in youth (Burlingame et al., 1996, 2005).
Psychotherapy Research Table I. Means and standard deviations for self-efficacy and outcome measures at participant intake to treatment.
YOQ Parent Report total YOQ-SR Youth Report total Social self-efficacy AD self-efficacy AP self-efficacy BR self-efficacy
Mean
SD
87.62 70.89 4.94 3.84 4.69 4.40
38.51 35.20 1.20 1.24 1.20 1.28
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AD, Academic Diligence; AP, Academic Proficiency; BR, Behavioral Regulation.
The YOQ-SR demonstrates high to moderately high internal consistency for each of the total scores (r = .95) across two samples, including a community youth group (N = 206) and a clinical youth group (N = 4037) (Ridge, Warren, Burlingame, Wells, & Tumblin, 2009). The YOQ-SR also demonstrates high temporal stability, with a test–retest reliability coefficient of .89 for the total score. As with the YOQ, the YOQ-SR correlates strongly with other commonly used measures of treatment outcomes in youth, such as the Child Behavior Checklist Youth Self-Report (r = .83) and the Behavior Assessment System for Children-2 Self-Report of Personality (r = .75). Table I provides means and standard deviations of youth self-efficacy and YOQ scores at intake.
Procedures Participants were recruited during their intake session at a large community mental health system in a metropolitan area in the Intermountain West. Of the clients invited to participate during initial intake procedures at the clinic, 62% participated in the study, resulting in our sample of 104 youth. Those who chose to participate were provided with a packet to complete for both the adolescent and the parent, which included a consent form and a variety of measures, including the YOQ in the parent packets and the self-efficacy measure and YOQ-SR in the youth packets. Research assistants administered these same measures to participants and their parents at the clinic at regular intervals immediately before or after the participants’ scheduled treatment sessions. The intervals included follow-ups at approximately three weeks, two months, four months, and six months after intake. Participants received a $10 gift certificate to a local store after completing the first set of measures and a $5 gift certificate for each set of measures completed during follow-up intervals.
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Analyses In examining the changes that occurred over the course of treatment in youth symptoms and youth self-efficacy domains, two components of change were of interest. First, the slope of change was examined to establish the direction and rate of change. Second, the shape of the change trajectory was examined to establish how change occurred at different time points in treatment. The treatment outcome variables were tested first, using linear, quadratic, logarithmic (natural log), and polynomial models for both parent report and youth report YOQ data. For parent report YOQ data, according to Schwarz’s Bayesian Criterion (BIC) for examining model fit, the logarithmic model provided the best fitting model of change. That is, according to parent reports, youth symptoms decreased over the course of treatment, with change occurring most rapidly at the start of treatment, then slowing down over subsequent treatment sessions. For youth report (YOQ-SR) data, the linear model of change provided the only significant fit to the data. As with the parent-report data, youth reports indicated a general decrease in symptoms over time, although change occurred at a more consistent pace over the course of treatment. Hierarchical linear modeling, also known as individual growth curve modeling or random effects regression analysis, was used to examine the changes that occurred in youth self-efficacy and in youth symptoms over the six-month data collection period for each participant. This type of analysis also revealed how changes in youth self-efficacy related to changes in youth symptomatology. The statistical analysis software SPSS 16.0 was utilized to analyze the data. Results Hypothesis 1: Patterns of Change in Youth Selfefficacy Self-efficacy domain change trajectories were also examined by testing linear, quadratic, and logarithmic models to see which model provided the best fit for the data. According to Schwarz’s BIC, the logarithmic model (natural log transformation) provided the best fit for all domains of self-efficacy. Table II provides data on the trajectories for each domain of self-efficacy. The fixed effects refer to the average change trajectory of the entire sample. Only the self-efficacy domain of Academic Proficiency exhibited a fixed pattern of change over time. In other words, the average change that occurred for the sample as a whole was only significant for Academic Proficiency self-efficacy, which demonstrated a
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Table II. Fixed and random effects for self-efficacy domain change trajectories. Domain Social
Fixed effects Random effects
AD
Fixed effects Random effects
AP
Fixed effects Random effects
BR
Fixed effects
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Random effects
Estimate
SE
p
4.907 0.002 1.230 0.061 3.827 0.039 1.004 0.064 4.639 0.092 1.130 0.018 4.383 0.046 1.219 0.074
0.122 0.046 0.214 0.025 0.120 0.054 0.224 0.036 0.122 0.042 0.222 0.024 0.127 0.053 0.241 0.034
