Predictors and outcomes associated with therapeutic alliance in cognitive behaviour therapy for children with autism

Abstract

Therapeutic alliance is often an important aspect of psychotherapy, though it is rarely examined in clients with autism. This study aims to determine the child pre-treatment variables and treatment outcomes associated with early and late alliance in cognitive behaviour therapy targeting emotion regulation for children with autism. Data were collected from 48 children with autism who participated in a larger randomized-controlled trial. Pre-treatment child characteristics included child, parent, and clinician report of child emotional and behavioural functioning. Primary outcome measures included child and parent-reported emotion regulation. Therapeutic alliance (bond and task-collaboration) was measured using observational coding of early and late therapy sessions. Pre-treatment levels of child-reported emotion inhibition were associated with subsequent early and late bond. Pre-treatment levels of parent and child-reported emotion regulation were related to early and late task-collaboration. Late task-collaboration was also associated with pre-treatment levels of behavioural and emotional symptom severity. Task-collaboration in later sessions predicted improvements in parent-reported emotion regulation from pre- to post-therapy. Future research is needed to further examine the role of task-collaboration as a mechanism of treatment change in therapies for children with autism.

Keywords

autism children cognitive behavioural therapy therapeutic alliance

Children with autism often exhibit mental health and behavioural challenges, including high rates of anxiety, depression or aggressive behaviour. Cognitive behaviour therapy (CBT), if adapted, has been shown to be efficacious in reducing mental health problems and improving emotion regulation in verbally able children with autism, with small to moderate treatment effects (Weston, Hodgekins, & Langdon, 2016). Only a portion of individuals with autism who take part in therapeutic interventions demonstrate significant gains, with approximately 30% showing no improvement following CBT (Vasa et al., 2014). To refine and maximize treatment effects, focus needs to be directed towards examining the therapeutic factors that function as mechanisms of change (Lerner, White, & McPartland, 2012).

Therapeutic alliance is a recognized contributor to treatment outcome. Therapeutic alliance is conceptualized as the working relationship between therapist and client based on treatment goals central to both the client and therapist, collaboration on therapeutic tasks and a positive bond (Bordin, 1979). This relationship is dynamic and transactional in nature, influenced by both therapist and client attributes and varying in quality over the course of treatment (Bordin, 1994). In treatment for children without autism, alliance is thought to account for a significant portion of therapeutic outcomes (Karver, Handelsman, Fields, & Bickman, 2005). Recent meta-analyses suggest that alliance is associated with small to moderate effects (McLeod, 2011; Murphy & Hutton, 2018) and is related to improvements in both internalizing (Chiu, McLeod, Har, & Wood, 2009) and externalizing symptoms (Kazdin, Marciano, & Whitley, 2005) following CBT.

The quality of therapeutic alliance appears to be influenced in part by child pre-treatment factors. For example, children who are more motivated and prepared to change (Christensen & Skogstad, 2009), and who have better social competence and securer social relationships (Levin, Henderson, & Ehrenreich-May, 2012) tend to have a stronger alliance with their therapist based on ratings from multiple informants. Results from the adult literature indicate a relation between emotion regulation, client-reported alliance and treatment outcome (Owens, Haddock, & Berry, 2013), with at least one study reporting a link for children with anxiety (Chu, Skriner, & Zandberg, 2014). Results are more mixed around how pre-treatment internalizing and externalizing symptom severity is associated with the formation of bond and task-collaboration (Shirk & Karver, 2011).

Beyond child and treatment-specific factors, researchers have examined differences in the alliance-outcome association as a function of reporting source. Although the therapeutic alliance is undoubtedly a subjective experience for both client and therapist, objective techniques for assessing this relationship, such as through independent observer reports, may serve to be a more equitable methodological approach. In their meta-analysis, Shirk and Karver (2003) note that children may not be equipped with the social and cognitive skills needed to assess their own therapeutic alliance. Ceiling effects may also be observed in child reports of alliance because ratings are only provided by a subgroup of children who remain in treatment (Accurso & Garland, 2015). It has been argued that reports on process and outcome variables from the same source may potentially bias results by inflating effect sizes (Horvath & Symonds, 1991; McLeod, 2011). In addition, parent report of the therapist–child alliance may be biased (either positively or negatively) by the parent’s own perceptions and attitudes towards the therapist and the context of the assessment (e.g. providing ratings while the therapist is present; McLeod & Weisz, 2005). Few studies have looked at alliance in children with autism receiving psychotherapy. Kerns, Collier, Lewin, and Storch (2018) examined the relation between child- and therapist-reported alliance and treatment response in CBT designed to address anxiety in children and adolescents. Treatment responsive children were found to have greater post-treatment, retrospective therapist-rated (but not child-rated) levels of alliance than non-responsive children, with no link to child age or the severity of autism or internalizing and externalizing symptoms. Results from the grey literature support the link between therapist reports of alliance in therapy and anxiety symptom reduction (Klebanoff, 2015), and according to parent interviews, specific therapist qualities (i.e. collaborating, being fun, giving praise, being patient) are important for a strong therapist-child alliance (Houlding, 2014).

Although therapeutic alliance is a subjective experience, independent observation has emerged as a useful way to gauge quality, addressing concerns around validity of child reports (McLeod, Southam-Gerow, & Kendall, 2017). Only one intervention study has used independent observer ratings of alliance with participants with autism. As part of a pilot randomized-controlled trial (RCT) comparing CBT to non-directive, supportive counselling for adolescents with autism, Murphy and colleagues (2017) used the Therapy Process Observational Coding Scheme–Alliance Scale (TPOCS-A; McLeod & Weisz, 2005) as an index of treatment fidelity. Results indicated good interrater agreement among coders, and independent observer ratings of alliance were comparable to those given in previous therapy studies involving youth without autism (Brown et al., 2015). It is yet to be determined whether pre-treatment child characteristics are associated with observer ratings of alliance or whether such ratings are predictive of treatment change.

Current study

This study stems from a larger RCT evaluating an emotion regulation focused CBT intervention for children with autism (Weiss et al., 2018). Using independent observer ratings of early and late therapeutic alliance (operationalized as task-collaboration and therapeutic bond), the following research questions and hypotheses were addressed:

Do pre-treatment child characteristics, including emotional and behavioural symptoms, emotion regulation and readiness for therapy, predict the quality of therapeutic alliance? Based on previous research, it was expected that emotional and behavioural symptoms and emotion regulation challenges would negatively predict therapeutic alliance in early and in late sessions, whereas readiness for treatment would be a positive predictor.

Is therapeutic alliance in early and in late sessions a significant predictor of change in the CBT intervention’s primary outcome variable: emotion regulation? It was hypothesized that therapeutic alliance would account for a moderate portion of the variance in changes of emotion regulation, as reported by children and parents.

Methods

Participants

Participants included 48 children (91.7% male) between the ages of 8 and 12 years (M = 9.60, SD = 1.25), who took part in a RCT of an emotion regulation focused CBT intervention (Weiss et al., 2018). All children (1) demonstrated at least average intellectual functioning (IQ ⩾ 79) based on the Wechsler Abbreviated Scale of Intelligence–Second Edition (WASI-II; Wechsler, 2011); (2) exhibited some degree of willingness to participate in therapy; (3) had a documented autism diagnosis from a qualified healthcare professional; and (4) met cut-offs on either the parent-report versions of the Social Communication Questionnaire (SCQ cut-off > 14; Rutter & Bailey, 2003) or the Social Responsiveness Scale–Second Edition (SRS-2 Total T score cut-off > 59, Constantino, 2012). For children whose parent could not provide documentation and did not meet cut-off scores for either screening tool (n = 2), the Autism Diagnostic Observation Schedule–Second Edition (ADOS-2; Lord et al., 2012) Module 3 was administered. Children were not eligible to participate in the study if they had a recent history of aggressive behaviour towards others or self-injurious behaviours that could potentially be a serious safety concern, or if they were currently receiving CBT or another therapy targeting emotion regulation.

For the current sample, child Full-Scale IQ–2 (FSIQ-2) scores ranged from 79 to 140 (M = 105.00, SD = 14.64). Children varied in autism symptom severity both on the SRS-2 total T scores (M = 74.40, SD = 9.33) and SCQ total scores (M = 21.62, SD = 4.45). The majority of parents identified their children as White/Caucasian (78.6%) and reported themselves as being married (91.5%), having post-secondary education (90.7%), and having an annual family income of at least CAD$100,000 before taxes (65.1%; 18.6% preferred not to disclose).

Measures

Therapeutic alliance

Child and parent reports of therapeutic alliance were not included in the initial protocol for the larger RCT in which this study is embedded. Therapists did provide ratings of their perceived quality of the therapeutic alliance following each session. However, this was only measured using a single-item (‘How would you describe the quality of the therapeutic relationship during the session with the child?’ 1 = very poor; 7 = very good) and was collected for the purposes of assessing treatment fidelity. For these reasons, this study opted to focus on the use of retrospective independent observational ratings. Therapeutic alliance was measured using the TPOCS-A (McLeod & Weisz, 2005). The TPOCS-A is a nine-item observational measure evaluating two facets of the alliance: the therapeutic bond between therapist and client (bond; six items) and compliance and collaboration on therapeutic tasks (task-collaboration; three items). Items are rated by an independent observer on a 6-point Likert-type scale (0 = not at all; 5 = great deal), indicating the extent to which the client or therapist demonstrate given behaviours in session. Initial psychometric properties of the measure in children 8–14 years of age suggest acceptable interrater reliability (intraclass correlation coefficient (ICC) ⩾ 0.40) for all nine items and excellent internal consistency (α = 0.95). The measure also has convergent validity with therapist reports of alliance (McLeod et al., 2017). The TPOCS-A has been used in other studies of alliance in both individual and group CBT for children with acceptable reliability (Chiu et al., 2009; Liber et al., 2010). For this study, ratings ranged from 1.75 to 3.75 for early bond (M = 2.80, SD = 0.46), 1.17 to 5.00 for early task-collaboration (M = 4.04, SD = 0.76), 2.00 to 3.92 for late bond (M = 2.98, SD = 0.48) and 1.83 to 5.00 for late task-collaboration (M = 3.99, SD = 0.69). Interrater reliability is described below.

Primary treatment outcome

The primary treatment outcome of the intervention trial was emotion regulation, as reported by parent and child.

Children’s Emotion Management Scales (CEMS)

Child self-reported emotion regulation was measured using the CEMS (Zeman, Cassano, Suveg, & Shipman, 2010). The CEMS include three separate scales assessing self-regulation during feelings of Sadness (12 items), Anger (11 items) and Worry (10 items), each yielding three subscales: Inhibition (e.g. ‘I hide my sadness’), Dysregulation (e.g. ‘I do things like slam doors when I am mad’) and Coping (e.g. ‘I talk to someone until I feel better when I’m worried’). A research assistant read each statement aloud and confirmed the child understood each item. Children then rated how frequently they engage in each behaviour on a 3-point scale (1 = hardly ever; 3 = often). Items were averaged across emotion scales to provide overall scores for each subscale. Average pre-treatment scores in this study ranged from 1.00 to 3.00 for Inhibition (M = 1.74, SD = 0.47), 1.00 to 2.78 for Dysregulation (M = 1.73, SD = 0.41) and 1.17 to 2.75 for Coping (M = 1.96, SD = 0.42). The CEMS has demonstrated convergent and divergent validity (Zeman et al., 2010) and acceptable to good internal consistency for this sample (α = 0.71–0.85).

Emotion Regulation Checklist (ERC)

The ERC (Shields & Cicchetti, 1997) is a 24-item parent-report measure assessing emotion regulation processes. Each item is rated on a 4-point scale (1 = never; 4 = almost always). The ERC includes two subscales: Lability/Negativity (15 items), measuring mood swings, reactivity, emotional intensity, and dysregulated emotions (e.g. ‘Is prone to disruptive outbursts of energy and exuberance’), with higher scores indicating greater dysregulation, and Emotion Regulation (eight items; one item was not included), measuring adaptive regulation processes (e.g. ‘Responds positively to neutral or friendly overtures by adults’), with higher scores indicating better emotion regulation (Shields & Cicchetti, 1998). Pre-treatment scores in this study ranged from 1.67 to 3.53 for Lability/Negativity (M = 2.43, SD = 0.41) and 1.88 to 4.00 for Emotion Regulation (M = 2.87, SD = 0.49). The ERC has good to excellent internal consistency (Shields & Cicchetti, 1997, 1998) and acceptable to good internal consistency for this study (α = 0.75–0.80).

Predictors of therapeutic alliance

In addition to pre-treatment levels of emotion regulation, as assessed using the CEMS and ERC measures described above, the following pre-treatment child characteristics were included as predictors of therapeutic alliance.

Readiness to participate

Child readiness to participate in therapy was assessed at initial screening using three questions: (1) ‘How much do you want to be part of the program?’ (2) ‘How much do you want to change?’ and (3) ‘How hard you are willing to work?’ Children rated each question on 8-point Likert-type scale, ranging from 0 = not at all to 8 = very, very much, and an overall readiness score was calculated by averaging the three ratings. Pre-treatment mean readiness was 4.89 (SD = 2.00), ranging from 0.33 to 8.00.

Behavioural Assessment System for Children–Second Edition, Parent Rating Scale (BASC-2 PRS)

The BASC-2 PRS (Reynolds & Kamphaus, 2004) assesses behavioural and emotional problems and adaptive functioning. For children between 8 and 11 years of age, parents completed the PRS-Child form (160 items), while parents of children who were 12 years of age completed the PRS-Adolescent form (150 items). Three composites were included in this study: Externalizing Problems (M = 58.06, SD = 10.47, Range = 41–86), Internalizing Problems (M = 61.33, SD = 12.70, Range = 40–95) and Behavioural Symptoms Index (BSI; M = 69.25, SD = 10.05, Range = 53–95). The BASC-2 has strong internal consistency and concurrent validity with other child behaviour rating scales (Reynolds & Kamphaus, 2004) and has been used as an assessment tool in a number of studies that have included children with autism (Grondhuis & Aman, 2012; Volker et al., 2010).

Anxiety Disorder Interview Schedule–Parent Version (ADIS-P)

The ADIS-P (Silverman & Albano, 2004) is a semi-structured interview of both internalizing and externalizing disorders based on Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association 1994). Parents provide information regarding symptomology, age of onset and degree of interference in daily life for each disorder. Based on the information provided, the interviewer then gives an overall clinical severity rating ranging from 0 to 8, with higher ratings indicating greater severity. The overall severity rating for the current sample ranged from 0 to 7 (M = 4.04, SD = 1.66). The ADIS-P is recognized as the most commonly used outcome measure in CBT trials for children with autism (Sung et al., 2011; Walters, Loades, & Russell, 2016).

Procedures

The larger RCT from which this study was derived began in September 2013. This research has received ethics review and approval by the York University’s Ethics Review Board (#e2013-229). Thirty-two children were excluded for not meeting study inclusion criteria, and 11 declined to participate despite being eligible. Sixty-eight children were eligible to participate in the larger RCT. Once eligibility was determined, parents provided written informed consent and children provided either written or verbal informed assent. For the purposes of this study, all children who received the intervention in its entirety were combined to form one treatment group regardless of whether they were initially randomized to treatment immediate or waitlist. Measures were administered within the 2 weeks prior to treatment receipt (pre-treatment) and within 1 week of completing therapy (post-treatment).

Of the 68 eligible families, 13 withdrew from the study after confirming enrolment (nine children dropped out before beginning the intervention and four dropped out part way through the programme). Data were not available for an additional six children because parents did not consent to having session videos used for research purposes (n = 4) or technical issues caused session videos to be unusable (n = 2). Finally, data for one participant was excluded due to a change in therapist midway through treatment, leaving a final sample of n = 48.

Intervention

The Secret Agent Society: Operation Regulation (SAS:OR; Beaumont, 2013) is a manualized CBT programme targeting emotion regulation adapted for children with autism. The programme includes 10 individual therapy sessions that the therapist, child and primary caregiver attend. Over the course of the study trial, sessions were facilitated by three post-doctoral fellows and 19 trained graduate students (90.9% female; M_age = 26.95, SD = 3.05) enrolled in clinical or clinical-developmental psychology programmes, under the supervision of a registered clinical psychologist. Treatment integrity across sessions was acceptable (85% ± 11%, Range = 50%–100%). Additional details of the SAS:OR programme and therapist training procedures are provided elsewhere (Weiss et al., 2018).

Coding

TPOCS-A coding followed procedures outlined by McLeod and Weisz (2005). Training included in-depth review of the test development and scoring manual, coding practice sessions and weekly check-ins between coders to discuss any discrepancies or issues that arose during practice coding. The coders (C.A., P.T., and F.R.) worked in close proximity, allowing for regular meetings and brief check-ins. During the first week of training, coders met to code two therapy sessions together (for a pilot participant who was not included as part of the final study). This provided an opportunity to discuss coding as the session was being reviewed and make detailed notes on the coding system. Coders met in person for at least 2 h for the 5 weeks following (3 weeks of practice coding, followed by 2 weeks of study coding). During these meetings, discrepancies in ratings were thoroughly discussed and video content was reviewed to ensure all coders established a similar repertoire of examples that corresponded with particular ratings. Coders were trained over a 1-month period and reached excellent reliability (ICC = 0.92, p < 0.001). Once reliability was established, sessions were randomly assigned to coders. To avoid rater drift, coders continued to meet in person throughout the data collection phase (bi-weekly early on and then monthly once reliability was evidently stable) and regularly corresponded between meetings if any questions arose. Coders were not involved in therapy provision for sessions they were coding and were unaware of treatment outcome.

Sampling of therapy sessions for study coding mimicked methods employed by previous research examining early and late phases of therapy for children (Chiu et al., 2009; McLeod & Weisz, 2005). Sessions 2 and 3 (early) and sessions 8 and 9 (late) were coded, and ratings were averaged to produce early and late bond and task-collaboration scores. If video recordings were not available (e.g. technical issues with recording equipment), subsequent sessions for early alliance (i.e. session 4) and previous sessions for late alliance (i.e. session 7) were coded. This was the case for nine early sessions (session 2, n = 5; session 3, n = 4), and eight late sessions (session 8, n = 5; session 9, n = 3). Kruskal–Wallis analyses confirmed that ratings on TPOCS-A items did not significantly differ between cases where sessions 4 and 7 were coded as alternates.

Interrater reliability for the TPOCS-A was then calculated using ICCs for approximately 30% of available sessions (n = 60). Reliability coefficients were based on the one-way random effects ICC (1, 1) model. The overall interrater reliability for TPOCS-A was excellent (ICC = 0.95, p < 0.001). Interrater reliability for individual items was all within acceptable range (ICC ranging from 0.76 to 0.96).

Analysis plan

All analyses were conducted using IBM SPSS Statistics version 24. Spearman-rho correlations were calculated to test the hypothesis that pre-treatment characteristics would be associated with subsequent measures of early and late bond and task-collaboration at the bivariate level. Multiple regressions were then calculated to determine if pre-treatment child characteristics that were significant at the bivariate level predicted therapeutic alliance. If predictor variables were largely correlated with each other (i.e. r > 0.50), only the variable with the strongest association with bond and task-collaboration was included in the model to maintain power to detect moderate to large effects.

A series of hierarchical regression analyses were conducted to test the hypothesis that early and late alliance would predict treatment outcomes. The first step controlled for time in treatment, child IQ and baseline levels of an outcome measure (McLeod & Weisz, 2005). The second block consisted of either early or late bond and task-collaboration scores. Separate analyses were run for each outcome variable.

We recognize that conducting these analyses raises questions about issues related to multiplicity, including inflated Type I error rates. Scientific and clinical risk associated with Type I error within the context of this study include identifying and placing undue emphasis on pre-treatment factors that are not true predictors of the quality of alliance, and falsely predicting the extent to which therapeutic alliance predicts treatment change. While failing to correct for multiple comparisons may increase the likelihood of identifying false positive findings, the small sample size, limited research in the area and an interest in balancing the examination of significance in terms of the probability of identifying a true effect serve as rationale for no adjustments being made (Feise, 2002). All variables included in the analyses were selected on the basis of clinical relevance and previously derived empirical evidence. Power analyses using G*Power 3.1 (Faul, Erdfelder, Buchner, & Lang, 2009) indicated that moderate to large effects could be detected using multiple linear regression analyses with a sample of 48 children, depending on the number of predictors included.

Results

Pre-treatment child characteristics and therapeutic alliance

As shown in Table 1, several pre-treatment child characteristics were associated with TPOCS-A ratings, both early and late in treatment. Child age and autism symptom severity (SCQ and SRS) were not related to any early or late alliance measure. Child IQ was associated with late task-collaboration, but no other indicator of alliance. Early and late bond were both positively associated with child report of emotional inhibition (CEMS-Inhibition). Early task-collaboration was positively related to child-reported coping (CEMS-Coping) and negatively associated with child report of emotional dysregulation (CEMS-Dysregulation). Late task-collaboration was positively associated with child report of inhibition (CEMS-Inhibition) and negatively related to child report of emotional dysregulation (CEMS-Dysregulation), parent report of child emotional lability (ERC Lability/Negativity), child externalizing symptoms (BASC-2 Externalizing), child behavioural symptoms (BASC-2 BSI) and clinician rated overall severity of psychopathology (ADIS-P Overall Severity).

Table 1.

Spearman-rho correlations between pre-treatment child characteristics and TPOCS-A ratings (N = 48).

Characteristic	Early TPOCS-A		Late TPOCS-A
Characteristic	Bond	Task-collaboration	Bond	Task-collaboration
Age	−0.15	0.16	−0.04	0.04
FSIQ-2^a	0.20	0.07	0.29^†	0.34*
SRS-2	0.03	0.03	0.05	−0.25^†
SCQ	0.22	0.14	0.13	0.19
Readiness to participate^a	0.17	0.25^†	0.02	−0.05
CEMS^b
Inhibition	0.30*	0.27^†	0.36*	0.30*
Dysregulation	−0.24	−0.38*	−0.27^†	−0.32*
Coping	0.09	0.36*	0.24	0.28^†
ERC
Lability/negativity	−0.16	−0.27^†	−0.07	−0.39**
Emotion regulation	0.11	0.17	−0.02	0.14
BASC-2
Externalizing problems	−0.12	−0.22	−0.14	−0.37**
Internalizing problems	0.04	−0.09	0.05	−0.26^†
BSI	−0.06	−0.11	−0.02	−0.36*
ADIS-P overall severity	−0.17	−0.14	−0.04	−0.30*

TPOCS-A = Therapist Process Observational Coding System–Alliance Scale; FSIQ-2 = Full-Scale IQ–2 Subscales; SRS-2 = Social Responsiveness Scale–Second Edition, Total T Score; SCQ = Social Communication Questionnaire; CEMS = Children’s Emotion Management Scale; ERC = Emotion Regulation Checklist; BASC-2 = Behavioural Assessment System for Children–Second Edition; BSI = Behavioural Symptoms Index; ADIS-P = Anxiety Disorder Interview Schedule–Parent Version.

n = 47.

n = 45.

†

p < 0.10; *p < 0.05; **p < 0.01.

Multiple regression analyses were not calculated for early or late bond, as only a single bivariate correlate emerged as significant. Results of multiple regressions revealed that child pre-treatment characteristics did not account for a significant portion of the variance in early task-collaboration and no unique predictors emerged. Child pre-treatment characteristics accounted for a moderate portion of the variance in late task-collaboration, R² = 0.40, F(7, 34) = 3.20, p = 0.01; however, there were no significant unique predictors.

Therapeutic alliance and primary treatment outcome

A series of hierarchical linear regressions were conducted to determine if alliance variables predicted treatment outcomes. Early bond and task-collaboration were not predictive of treatment change for any outcome variables (Supplemental Table 1). In contrast, significant patterns emerged when measures of late alliance were included as predictors, as shown in Table 2. Specifically, late ratings of alliance accounted for a significant portion of variance in treatment change in parent reports of child emotional lability (ERC Lability/Negativity), ΔR² = 0.07, p = 0.02, with late task-collaboration emerging as a unique predictor (β = –0.36, p = 0.02). Late task-collaboration emerged as a unique predictor of improvements in child report of emotional dysregulation (CEMS-Dysregulation), β = –0.45, p = 0.04, even though late alliance as a whole was not a significant predictor (ΔR² = 0.12, p = 0.07). Late alliance ratings were not predictive of change in CEMS-Inhibition or Coping and ERC Emotion Regulation (all ps > 0.05).

Table 2.

Linear regression results for late therapeutic alliance predicting treatment outcome.

Variable	B	SE B	β
CEMS-inhibition^a
Baseline score	0.78	0.17	0.66**
Days in treatment	<0.01	<0.01	0.06
FSIQ-2	<–0.01	0.01	−0.07
TPOCS-A bond	0.03	0.19	0.02
TPOCS-A task	−0.15	0.13	−0.20
CEMS-dysregulation^a
Baseline score	0.15	0.12	0.19
Days in treatment	<–0.01	<0.01	−0.05
FSIQ-2	0.01	<0.01	0.27^†
TPOCS-A bond	0.05	0.13	−0.08
TPOCS-A task	−0.19	0.09	−0.45*
CEMS-coping^a
Baseline score	0.42	0.12	0.48**
Days in treatment	<0.01	<0.01	0.17
FSIQ-2	<–0.01	<0.01	<0.01
TPOCS-A bond	−0.07	0.13	−0.09
TPOCS-A task	0.17	0.09	0.34^†
ERC lability/negativity^a
Baseline score	0.72	0.11	0.68**
Days in treatment	<0.01	<0.01	−0.01
FSIQ-2	0.01	<0.01	0.16
TPOCS-A bond	0.10	0.12	0.11
TPOCS-A task	−0.22	0.09	−0.36*
ERC emotion regulation^a
Baseline score	0.57	0.08	0.75**
Days in treatment	<0.01	<0.01	0.03
FSIQ-2	<0.01	<0.01	0.02
TPOCS-A bond	−0.05	0.10	−0.07
TPOCS-A task	0.10	0.07	0.20

CEM = Children’s Emotion Management Scale; FSIQ-2 = Full-Scale IQ–2 Subscales; TPOCS-A = Therapist Process Observational Coding System–Alliance Scale; ERC = Emotion Regulation Checklist.

Outcome variable.

†

p < 0.10; *p < 0.05; **p < 0.01.

Discussion

This study examined the role of therapeutic alliance in CBT for children with autism by evaluating the contribution of pre-treatment child characteristics to the quality of alliance and the contribution of alliance to change in emotion regulation following treatment. This was among the first study to explore predictors of alliance and consider how it relates to treatment outcome in therapy for children with autism. It is also the first to use a behavioural observation method that assesses alliance at multiple points in treatment.

Pre-treatment child characteristics and therapeutic alliance

Consistent with the initial hypothesis, emotion regulation was significantly related to the quality of therapeutic alliance at different points of treatment. In particular, child self-reported tendencies to inhibit emotional responses were associated with a stronger therapeutic bond and better task-collaboration both early and late in treatment. In the context of therapy with children with autism, emotional inhibition may benefit the therapeutic process, in contrast to the negative effects that suppressing one’s emotions may have in day-to-day life (Aldao, Nolen-Hoeksema, & Schweizer, 2010). In comparison to common overt emotional dysregulation that require significant management of behaviours from parents and individuals working with children with autism (Mazefsky, 2011), children who are better able to inhibit highly emotional displays may allow for therapists to more easily establish rapport. It is also likely that those children who are more emotionally inhibited are less likely to demonstrate negative behaviours and affect that would impede on the quality of the bond as operationalized on the TPOCS-A bond subscale. Several other pre-treatment indicators of emotion regulation were associated with better task-collaboration at early and late sessions. This included child report of greater coping skills and less emotional dysregulation and parent report of greater child emotion regulation. These findings suggest that both parent and child reports of emotional regulation ability and the presentation of emotional dysregulation are pertinent to consider when working to establish therapeutic rapport with children in treatment, especially since emotion regulation is a common challenge for children with autism (Mazefsky & White, 2014).

Parent reports of child externalizing problems, and clinician judgements of overall psychopathology, were associated with poorer task-collaboration in later sessions, but not to early therapeutic alliance or to late-session ratings of therapeutic bond. In the only other study of pre-treatment characteristics and alliance for children with autism, demographic factors and pre-treatment clinical levels of internalizing and externalizing symptoms were not related to post-treatment retrospective ratings of alliance, as reported by child, parent or therapist (Kerns et al., 2018). Beyond autism, associations of child factors and alliance are known to occur as a result of differences in source of reporting (e.g. child report vs therapist report vs independent observer) and the timing of reporting (e.g. at early or late sessions, or retrospectively following treatment completion; McLeod, 2011; McLeod et al., 2017), and thus may contribute to why our findings differed.

Contrary to expectations, child readiness to participate in therapy was not significantly related to the quality of therapeutic alliance, though there was a trending association with early task-collaboration. Although children varied in their degree of readiness to participate, treatment was sought by the child’s primary caregiver, and in this context, children may fail to recognize personal emotional and behavioural challenges (Shirk & Russell, 1998, as cited in Shirk & Karver, 2003). From a process and developmental perspective, this lack of insight may serve as a unique challenge when trying to establish alliance with younger clients (Shirk & Karver, 2003). An additional unexpected finding was that in this sample of children with at least average estimated intellectual functioning, IQ was related to late task-collaboration and had a trending association with bond. Given the heterogeneity in intellectual functioning for children with autism, future research should continue to examine the role of cognitive functioning and variable profiles within the context of CBT, as this treatment orientation is so focused on active task-collaboration.

Although not a focus of this study, exploratory analyses indicated no significant association between autism symptom severity and observer-rated therapeutic bond or task-collaboration. To our knowledge, only one study to date has compared therapeutic alliance in children with and without autism. Klebanoff (2015) found that in CBT targeting anxiety in children, therapist ratings of alliance were significantly lower for children with autism aged 10–11 years, compared with those without autism. However, there was no significant difference between ratings for children below 10 years of age. This age by group finding certainly warrants further study of potentially autism-specific dynamics, and the TPOCS may be a useful tool given its application in both clients with and without autism.

Child pre-treatment characteristics did not predict either aspect of the therapeutic alliance early in treatment, or the therapeutic bond later in treatment, when entered into regressions. Furthermore, only a moderate portion of variance of late task-collaboration was accounted for by the pre-treatment characteristic regression model, with no significant unique predictors. This lack of significant regression results may be a result of the low power to account for small to moderate effects in models where the predictor variables, though not at the level of multicollinearity, continue to show correlations with each other.

Therapeutic alliance and primary treatment outcome

The initial hypothesis around therapeutic alliance and treatment outcome was partially supported, in that only a particular aspect of late alliance was associated with child change in therapy. More specifically, late task-collaboration was predictive of improvements in child emotion dysregulation. Although this study was the first to examine alliance as it relates to emotion regulation as a treatment outcome, these findings align with those from studies involving children without autism, where alliance-outcome effect sizes tend to be greater when considering changes in externalized symptom presentation, compared with internalized presentations (McLeod, 2011). Whereas emotion regulation involves internalized processes (Mazefsky et al., 2013), the current results reflect changes in emotion dysregulation; the child’s negative externalized behavioural response. The measures of emotion regulation that were not significantly predicted by alliance (e.g. ERC Emotion Regulation subscale) focused more on the internalized aspects of emotion regulation. Considerable literature also favours late measures of alliance versus early ones in being related to treatment outcome in therapy for children (Karver, Handelsman, Fields, & Bickman, 2006; McLeod, 2011; Shirk & Karver, 2011). Although ratings of later alliance may be biased by symptom improvement when the reporter has been actively involved or invested in the treatment process (McLeod & Weisz, 2005; Shirk & Karver, 2011), this study used independent observational coding, which may have helped to reduce the perception of treatment progress as a confound.

Limitations

There are several limitations with this study that should be considered. First, results should be interpreted with the consideration that no alpha-level adjustments were made to correct for multiple comparisons. The sample only included participants who completed treatment, and for whom post-treatment data were available. Premature termination is recognized as an important methodological issue for intervention research because it limits generalizability of results, introduces sampling bias and, depending on sample size available, reduces statistical power (Nock & Ferriter, 2005). In addition, the sample included was predominately male, limiting how results generalize to females with autism. Although previous research has not demonstrated a gender-effect in the association between alliance-outcome (Kerns et al., 2018; McLeod, 2011), future studies should aim to include a larger proportion of females to determine if this finding holds within the autism population. Coders could also not be completely blind to session number. Although session order was randomized to reduce coding bias, the session content is manualized for each session and the client or therapist may also have mentioned the session number in video recordings, making it difficult for coders to be blind to the session. Notably, this study only assessed therapeutic alliance using independent observer ratings. Given that alliance-outcome associations tend to vary as a result of informant source, future research should consider assessing the convergence and predictive validity of multi-informant ratings in therapy for children with autism. Finally, this study was part of a larger efficacy trial that in part looked to evaluate therapist fidelity to a manualized protocol, potentially affecting the generalizability of findings to the real-world context.

Conclusion

Therapeutic alliance is an important process factor to consider when providing therapy to children with autism. Although this study could not determine whether the quality of alliance differs from children without autism, it appears that this relationship can still develop and is relevant to the benefit some children with autism experience from participating in CBT. Child pre-treatment characteristics, particularly intellectual functioning, emotion dysregulation and overall symptom severity, may influence aspects of alliance, most notably, the in-session task-collaboration between therapist and child. Task-collaboration was found to be a stronger predictor of treatment outcome and appears to be more heavily influenced by child characteristics prior to treatment than was the therapeutic bond. Since task-collaboration in later sessions was identified as an important predictor of treatment change, addressing challenges related to engagement throughout the treatment process and applying therapeutic skills that foster a collaborative relationship may be important aspects of therapy provision when working with children with autism. This active collaboration between therapist and child during session activities fits into the broader process-related factor of treatment adherence or engagement, which is known to be crucial for making treatment gains (Meichenbaum & Turk, 1987). Clinicians working with children with autism would benefit from skills training that specifically focuses on promoting and supporting child engagement and collaboration in therapy.

Supplemental Material

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Supplemental material, AUT849985_Lay_Abstract for Predictors and outcomes associated with therapeutic alliance in cognitive behaviour therapy for children with autism by Carly Albaum, Paula Tablon, Flora Roudbarani and Jonathan A Weiss in Autism

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Supplemental material, AUT849985_Supplemental_material for Predictors and outcomes associated with therapeutic alliance in cognitive behaviour therapy for children with autism by Carly Albaum, Paula Tablon, Flora Roudbarani and Jonathan A Weiss in Autism

Footnotes

Acknowledgements

The authors wish to thank the many families, graduate students and research assistants who participated in this research.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the Chair in Autism Spectrum Disorders Treatment and Care Research, the Canadian Institutes of Health Research in partnership with Autism Speaks Canada, the Canadian Autism Spectrum Disorders Alliance, Health Canada, Kids Brain Health Network (formerly NeuroDevNet) and the Sinneave Family Foundation.

Supplemental material

Supplemental material for this article is available online.

ORCID iDs

Carly Albaum

Jonathan A Weiss

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