Occupational therapy metacognitive intervention for adolescents with ADHD: Teen Cognitive-Functional (Cog-Fun) feasibility study

Abstract

Introduction

Adolescents with attention deficit hyperactivity disorder face neurocognitive impairments that impede their occupational functioning. The Cognitive-Functional model is a metacognitive occupational therapy intervention for individuals with attention deficit hyperactivity disorder that harnesses self-awareness and strategy behavior to support participation in an individualized occupational context. This study explored preliminary feasibility and efficacy of the Cognitive Functional model adapted for adolescents with attention deficit hyperactivity disorder, the Teen Cognitive-Functional intervention.

Method

A mixed method feasibility study including 22 adolescents with attention deficit hyperactivity disorder and their parents was conducted. Pre–post assessments included: occupational performance (Canadian Occupational Performance Measure); executive functioning (Behavior Rating Inventory of Executive Function); self-awareness and strategy behavior (Self-Regulation Skills Interview).

Results

Modest attrition and high satisfaction from Teen Cognitive-Functional intervention were found. Significant improvements were reported in adolescents’ occupational performance, executive functioning and strategy behavior. No significant gains were found in adolescents’ self-awareness. Adolescents’ strategy behavior was correlated with parent-rated occupational performance. Qualitative analysis of the strategies reported by the adolescents after intervention revealed three categories: “self-determined choices”; “plan and organize” and “adaptations.”

Conclusion

This study provides initial support for feasibility of the Teen Cognitive-Functional intervention and its potential efficacy in promoting occupational performance, executive functioning and strategy behavior. Controlled studies are needed to further validate these findings.

Keywords

ADHD adolescents occupational therapy metacognitive intervention executive function self-awareness

Introduction

Attention deficit hyperactivity disorder (ADHD) in adolescence is associated with many functional impairments, including various difficulties in everyday activities and social interactions and higher rates of academic underachievement (Cermak, 2018; Frazier et al., 2007; Gardner and Gerdes, 2015; Hareendran et al., 2015). The wide-ranging impact of ADHD in adolescence calls for the development of intervention programs in order to minimize functional disability and promote self-management of challenges over time. Existing interventions for adolescents with ADHD target specific skills and behaviors, and result in limited effects on functional outcomes (Chan et al., 2016). The Cognitive-Functional (Cog-Fun) intervention model in occupational therapy for individuals with ADHD (Maeir et al., 2018) may enable self-management for adolescents with ADHD. The Cog-Fun targets metacognitive components of self-awareness and strategy behavior in order to support participation. The Cog-Fun has been validated for children with ADHD (Hahn-Markowitz et al., 2016, 2018). This study explored the preliminary feasibility and efficacy of the Cog-Fun adapted for adolescents with ADHD: the Teen Cog-Fun.

Literature review

ADHD is a chronic health condition with a wide, impairing impact on daily life (American Psychiatric Association (APA), 2013). Executive function (EF) deficits are considered a central mechanism underlying functional disability in ADHD (Barkley, 2012). Executive functions are defined as self-regulatory processes that enable self-serving goal-directed behavior, including behavioral, emotional and cognitive regulation (Barkley, 2012). In adolescence, the ADHD neurocognitive profile, involving EF deficits, may impair abilities to cope with developmental challenges and threaten future adult functioning. Furthermore, impaired self-awareness and diminished self-efficacy among adolescents with ADHD (Mazzone et al., 2013; Owens et al., 2007) may pose additional barriers for adaptive functioning.

The gold standard for ADHD intervention involves the combination of pharmacological and psychosocial treatments (National Institute for Health and Care Excellence (NICE), 2018). Psychosocial treatments offered for adolescents with ADHD typically combine skill training, behavioral or cognitive-behavioral techniques (see Chan et al., 2016 for review). Intervention protocols incorporating behavioral techniques include defining and selectively reinforcing desired behaviors. Results of these interventions are mixed, for example no gains were found in risky driving behaviors (Fabiano et al., 2016); however, significant improvements were found in organization and planning of academic tasks (Langberg et al., 2018; Sibley et al., 2016). Limitations of behavioral management include targeting specific behaviors and contexts with lack of generalization; moreover, behavioral techniques rely heavily on external control and do not prepare the adolescent for self-management and coping with ADHD over time.

Cognitive behavior therapy (CBT) protocols for adolescents with ADHD combine skill training with cognitive restructuring aimed at modifying maladaptive thoughts and beliefs. Results of CBT studies demonstrate improvements in ADHD symptomatology (Boyer et al., 2015; Sprich et al., 2016; Vidal et al., 2015). Vidal and colleagues (2015) also found a reduction in functional impairment according to parents but not according to adolescents’ self-reports. Boyer and colleagues (2015) report improvement in overall level of functioning (as measured by the Impairment Rating Scale question: “the overall severity of this child’s problem in functioning and overall need for treatment”). In sum, the interventions reviewed above utilize a prescribed approach to skill and behavior acquisition. Evidence suggests that symptomatology and specific skills and behaviors can be improved, yet there is limited evidence of efficacy regarding functional outcomes (Chan et al., 2016). This review suggests that there may be a need for a more individualized approach in order to promote self-management for current and future functional challenges among adolescents with ADHD.

Self-management requires metacognitive skills of awareness to challenges and effective use of strategies that can bridge the gap between neurocognitive executive impairment and the demands of daily occupations (Toglia, 2018). Occupational therapy models for cognitive rehabilitation can be utilized to address the cognitive barriers and limit the impact of ADHD on participation (Cermak, 2018). The Multicontext Treatment Approach (Toglia, 2018) targets metacognitive skills of self-management, promoting (a) awareness to self, task characteristics and context, and (b) the acquisition of effective compensatory strategies. Online awareness is emphasized, which refers to the skills needed to support effective strategic behavior during task performance (Toglia, 2018). The Bio–Psycho–Social theory of awareness in neurocognitive rehabilitation (Ownsworth et al., 2006) delineates the neurocognitive, psychological and social barriers to awareness, and specifically informs interventions that target awareness deficiencies.

The Cog-Fun intervention model (Maeir et al., 2018) is based on the above models of cognitive rehabilitation, and adapted specifically for individuals with ADHD. The Cog-Fun focuses on the development of metacognitive skills including adaptive self-awareness and strategic behavior in daily functioning. Adaptive self-awareness is defined as the awareness of strengths and resources in one’s daily life, and the recognition of ADHD symptoms and their functional implications, together with a sense of self-efficacy (Levanon-Erez and Maeir, 2014). The Cog-Fun systematically targets the Bio–Psycho–Social barriers to awareness (Ownsworth et al., 2006). In order to address the biological neurocognitive barriers (attention and EF deficits), the intervention facilitates learning via the use of structured templates (for example a monitoring template and session summary) and hierarchical cueing procedures. In order to address psychological defense mechanisms, the Cog-Fun uses a client-centered, strength-based approach and intentional therapeutic relationship techniques (Taylor, 2008). The social barriers to awareness, mainly stigma and lack of knowledge regarding ADHD, are addressed through psychoeducation. Importantly, the metacognitive learning process, whereby the client develops adaptive self-awareness, sets the stage for setting personally meaningful occupational goals. Within the context of each client’s occupational preferences, strategies that support occupational performance are acquired. Strategies include general problem-solving strategies, which are explicitly taught and repeatedly practiced (for example goal-setting, planning and monitoring), and specific strategies that target the client’s personal EF profile and his occupational requirements (for example use of reminders, regulating self-talk, breaking down tasks). In addition, environmental and/or task adaptations are incorporated, either by client or significant other (for example parent). Research on the Cog-Fun for children demonstrates a positive treatment effect on children’s ADHD symptomatology, EF, quality of life (QoL) and occupational performance, and on parental self-efficacy (Hahn-Markowitz et al., 2016, 2018). The Teen Cog-Fun protocol has been developed to meet the unique needs of adolescents with ADHD. The Teen Cog-Fun emphasizes the exploration of occupational identity and the reinforcement of autonomy by setting occupational goals in line with the adolescent’s volition and by supporting maximal independence in decision-making and in self-management (Levanon-Erez and Maeir, 2014). The purpose of this study is to examine the preliminary feasibility and efficacy of the Teen Cog-Fun intervention. The objectives of this study ware to (a) examine the intervention’s feasibility by evaluating compliance and the parent’s and adolescent’s satisfaction; (b) examine preliminary efficacy of the Teen Cog-Fun intervention on adolescents’ occupational performance, executive functioning in daily life and metacognition (awareness to difficulties and strategy behavior), and (c) explore the potential metacognitive change mechanism by testing the relation between metacognition and occupational performance gains, and by studying the types of strategies reported by participants to support their occupational performance following intervention.

Method

Study design

A mixed-methods feasibility study with a one-group pretest–posttest design was conducted. The quantitative methods of the study were used to explore Cog-Fun’s feasibility and initial efficacy for adolescents with ADHD. Qualitative content analysis was used to gain insight into the nature of the strategies reported by the participants after intervention to support their occupational performance.

Participants

Convenience sampling of adolescents aged 12–17 years with ADHD was used. Participants were referred by neuropsychologists and pediatric neurologists to an occupational therapy intervention between 2012 and 2014, within a neurocognitive health center. The neurocognitive health center also offered medical treatments. See Table 1 for inclusion and exclusion criteria.

Table 1.

Inclusion and exclusion criteria.

Inclusion criteria	Exclusion criteria
Valid ADHD diagnosis by neurologist or psychiatrist No change in pharmacological status during last 3 months Executive dysfunction: clinical impairment (score above cutoff T > 65) on at least one scale of the Behavior Rating Inventory of Executive Function (BRIEF) (Gioia et al., 2000a) Attendance in a regular educational framework	Other neurological disorders diagnosed by neurologist or psychiatrist Psychopathological comorbidity: scores above cutoff for clinical impairment in total problem, internalizing broad band score or anxious/depressed or withdrawn/depressed subscales (T > 63) in parent’s report on Child Behavior Checklist (CBCL) (Achenbach, 1991) Sub-threshold ADHD symptomatology: scores below cutoff for clinical impairment in both hyperactivity-impulsivity and inattentiveness DSM-IV symptoms subscales (<65) in Conners’ Parent Rating Scales – Revised (CPRS-R) (Conners et al., 1998) An estimated IQ below 85: lower than 1 standard score on Block Design and Vocabulary subtests of Wechsler Intelligence Scale for Children IV (Wechsler, 2003)

Inclusion criteria

Exclusion criteria

Valid ADHD diagnosis by neurologist or psychiatrist

No change in pharmacological status during last 3 months

Executive dysfunction: clinical impairment (score above cutoff T > 65) on at least one scale of the Behavior Rating Inventory of Executive Function (BRIEF) (Gioia et al., 2000a)

Attendance in a regular educational framework

Other neurological disorders diagnosed by neurologist or psychiatrist

Psychopathological comorbidity: scores above cutoff for clinical impairment in total problem, internalizing broad band score or anxious/depressed or withdrawn/depressed subscales (T > 63) in parent’s report on Child Behavior Checklist (CBCL) (Achenbach, 1991)

Sub-threshold ADHD symptomatology: scores below cutoff for clinical impairment in both hyperactivity-impulsivity and inattentiveness DSM-IV symptoms subscales (<65) in Conners’ Parent Rating Scales – Revised (CPRS-R) (Conners et al., 1998)

An estimated IQ below 85: lower than 1 standard score on Block Design and Vocabulary subtests of Wechsler Intelligence Scale for Children IV (Wechsler, 2003)

Note: Hebrew versions of all measures were adapted and published by PsychTech, Ltd.

ADHD: attention deficit hyperactivity disorder.

Twenty-seven adolescents and their parents participated in the study. Participants included six girls and 21 boys between the ages of 12 and 17 years (mean: 14.22±1.45), between the seventh and twelfth grade (mean: 8.67±1.52). Their mean Conners’ Parent Rating Scales – Revised (CPRS-R) (Conners et al., 1998) total score was 74.78±9.49. Eighteen of the participants (66.7%) were medicated. Medication status was stable for at least 3 months before the intervention, and remained so during the intervention according to adolescent and parent report.

Procedure

This study was approved by the Institutional Review Board (Reference ID: 04122011). No payment was received in return for participation in the study. Six qualified occupational therapists delivered the intervention protocol. All sessions took place in a designated clinic on the university campus. Sessions were documented by video recordings and by a written log. Treating therapists underwent regular reviews to verify treatment fidelity. See Figure 1 for study process chart.

Figure 1.

Study process chart.

Intervention

Participants in Teen Cog-Fun received 17, 1-hour, weekly sessions. Of those, 13 sessions were conducted with the adolescent, three sessions were conducted with the parents, and one final session included the adolescent and parents together. The protocol includes four modular units (see Table 2 for a description of the Teen Cog-Fun intervention protocol content).

Table 2.

Description of Teen Cog-Fun intervention protocol content.

Session	Content
1	Evaluation. Parent interview, reviewing the occupational profile of their child, discussing parents’ concerns and goals.
2	Evaluation. Teenager occupational and awareness interview.
3–6	Unit A. Adaptive self-awareness. Exploring occupational identity and promoting awareness of strengths, values, ADHD and EF challenges.Methods: Guided reflection on occupational experiences; online monitoring of task experiences; questionnaires probing interests and values; psychoeducation about ADHD.
8–13	Unit B. Strategy acquisition. Developing self-management in the context of occupational goal-attainment. Methods: Teaching general problem-solving strategies: goal-setting, planning and monitoring. Structured reflection on occupational experiences in order to discover specific strategies and identify environmental resources to bridge the gap between occupational demands and individual EF deficits.
7, 14	Unit C. Parent guidance. Collaborating with parents in order to design supports tailored to their teenager’s needs.
15–17	Unit D. Consolidation. Summarizing metacognitive learning and presenting it to parents in order to promote transfer and generalization. Methods: Teenager prepares a project that summarizes his/her individual profile, goals and strategies, and presents it to his/her parents at the final session.

ADHD: attention deficit hyperactivity disorder; EF: executive function.

Measures

Screening measures

Conners’ Parent Rating Scales-Revised (CPRS-R) (Conners et al., 1998). The CPRS-R is a parent rating scale of ADHD-related behaviors. Items are based on the American Psychiatric Association’s Diagnostic and Statistical Manual (DSM-IV) diagnostic criteria of ADHD and common comorbid problems/disorders. There are 80 items, rated from 0 (not at all) to 3 (very much). Raw scores are converted to T scores, with 65 or above considered clinically impaired. The scales include seven subscales, four indices and three DSM-IV subscales. The scales are valid and reliable, with test–retest reliability over 6–8 weeks ranging from .47–.85 (Angello et al., 2003). For the purpose of this study, the DSM-IV subscales of hyperactivity-impulsivity and inattentiveness symptoms were used.

Achenbach System of Empirically Based Assessment (ASEBA) Child Behavior Checklist 6-18 (parent version) (CBCL) (Achenbach, 1991). The ASEBA is a system of questionnaires designed to empirically identify psychopathological symptoms. The questionnaires contain ∼100 statements, and the informant rates how true each statement is on a 0 (never true) to 2 (always true) scale. Items are summed and converted into a standardized T-score based on age and gender norms (M = 50, SD = 10). Its reliability and validity have been documented in many populations and cultures (Achenbach et al., 2008). For the purpose of this study, the total problem, internalizing broad band score, anxious/depressed and withdrawn/depressed subscales were used.

Screening and pre–post measure

Executive functioning

The Behavior Rating Inventory of Executive Function (BRIEF) (Gioia et al., 2000a) is an ecological rating scale designed to reflect the neuropsychological constructs of EF in everyday situations. The BRIEF is designed for parents of children and adolescents aged 5–18 years, and comprises 86 items. Each item is a short statement that reflects a behavioral manifestation of EF deficit in daily life. The informant marks “never,” “sometimes” or “always” based on their children’s behavior, over the past 6 months. Items form eight clinical scales. Scales are combined to form two indices – the Behavioral Regulation Index (BRI) and the Metacognition Index (MI) – as well as an overall Global Executive Composite (GEC). Raw scale scores are transformed into T scores, with 65 or above considered clinically impaired (SD = 10). Internal consistency, test–retest reliability, and discriminant and convergent validity have been established in individuals with ADHD (Gioia et al., 2000b; McCandless and O’Laughlin, 2007).

Pre–post measures

Occupational performance

The Canadian Occupational Performance Measure (COPM) (Law et al., 2005) is a standardized client-centered measure designed to identify client-specific occupational issues in daily functioning and measure change in a client’s self-perception of occupational performance over time. A 10-point scale is used to measure self-rated levels of performance and satisfaction with performance, with a higher score indicating better performance. A change score of two or more is considered clinically significant (Law et al., 2005). The reliability, validity and responsiveness of the COPM are satisfactory to excellent (Carswell et al., 2004; Law et al., 2005). Both adolescents and parents completed the COPM separately.

Metacognition

The Self-Regulation Skills Interview (SRSI) (Ownsworth et al., 2000) is a semi-structured interview that assesses metacognition related to difficulties in life. The SRSI is composed of six items that assess the following skills: emergent awareness, anticipatory awareness, self-rated readiness to change, strategy awareness, strategy use and strategy effectiveness. Each question is scored on a 10-point rating scale. Scores are summed and averaged within two subscales: awareness of difficulties (emergent and anticipatory) and strategy behavior (strategy awareness, use and effectiveness) ranging from 0 to 10, with lower scores indicating better awareness. The readiness to change domain was not used in this study. The measure has good inter-rater (r = 0.81–0.92) and test–retest (r = 0.69–0.91) reliability (Ownsworth et al., 2000). The interview was translated into Hebrew with permission from the authors, and internal reliability Cronbach’s alpha in our study was .89 and .88 (pre- and post-intervention). The interviews were videotaped and transcribed. All identifying information was removed to enable rating that is blinded to time of evaluation (pre–post) by an independent rater not involved in the intervention. In addition, post-intervention interviews were qualitatively analyzed by the authors (see statistical analyses section).

Post-intervention measure

Patient satisfaction

Parents and adolescents provided ratings of satisfaction at post-intervention using a questionnaire developed for this study. Respondents indicated their degree of satisfaction regarding relations with therapist, the impact of the intervention on adolescent's awareness of strengths and difficulties, knowledge of strategies and their use in daily life. Parents also rated their satisfaction regarding the impact of intervention on their own knowledge, skills and parental efficacy. The questionnaires consisted of 10 (parent version) or six (adolescent version) items that were scored on a 10-point Likert scale (1 = not at all satisfied to 10 = highly satisfied). The internal reliability Cronbach’s alpha for this scale was .82 for the parent version and .80 for the adolescent version.

Statistical analyses

Quantitative analysis

Baseline sociodemographic (age, grade, gender) and clinical characteristics (CPRS-R and medication status) were compered between completers and non-completers using chi-square (for gender and medication status) and Mann–Whitney (age, grade and CPRS-R) tests. All outcome variables met Kolmogorov–Smirnov test criteria for normal distribution >.05 except for the SRSI strategy score at time 1, therefore paired t-test analyses were computed between pre and post measures for all variables except for strategy score, for which the non-parametric Wilcoxon sign rank was computed. Effect sizes (ES) Cohen’s d were calculated. Bonferroni correction for multiple comparisons was performed. Spearman correlation analysis was computed to examine correlations between SRSI and COPM improvement.

Qualitative analysis

The SRSI interviews were video recorded and transcribed. In addition to the standard quantitative scoring, participants’ post-intervention interviews were analyzed using a directed approach to content analysis (Hsieh and Shannon, 2005). In the directed approach, existing theoretical concepts guide the coding process (Hsieh and Shannon, 2005). Strategy behavior (Ownsworth et al., 2000) was the speculated enabler of occupational performance in this study, thus this construct was explored. The authors read each interview, highlighted by hand all statements representing strategy behavior, extracted codes and assigned descriptive labels. Labels were consolidated into categories, and then re-examined and revised several times through discussion, until a consensus was reached.

Results

Study population and feasibility

Forty-four adolescents were recruited to the study. Parents provided oral consent and completed the screening measures. Eleven applicants were excluded due to scores above/below cutoffs on the CBCL (n = 6), CPRS-R (n = 4) and BRIEF (n = 1). Six participants did not show up for the initial evaluation session. The final sample comprised 27 participants who enrolled in the Teen Cog-Fun intervention (see Table 3 for demographic characteristics in enrolled group, completers and non-completers). Twenty-two (81%) participants completed the intervention. Three participants withdrew due to technical reasons (moved away, therapist childbirth) and two participants had difficulty with compliance. There were no significant differences between completers and non-completers in all demographic and clinical variables (p>.05).

Table 3.

Demographic characteristics in enrolled group, completers and non-completers.

	Enrolled (n = 27)	Completers (n = 22)	Non-completers (n = 5)	p
	M (SD)	M (SD)	M (SD)
Age (years)	14.22 (1.45)	14 (1.38)	15.2 (1.48)	.093^a
Grade (years)	8.67 (1.52)	8.45 (1.44)	9.6 (1.67)	.141^a
CPRS-R total	74.78 (9.49)	74.45 (9.2)	76.2 (11.76)	1.00^a
	n (%)	n (%)	n (%)
Female	6 (22.2)	4 (18.2)	2 (40)	.303^b
ADHD medication	18 (66.7)	15 (68.2)	3 (60)	.553^b

Data are M (SD), CPRS-R total: Conners’ Parent Rating Scales – Revised (CPRS-R) total score.

Mann–Whitney test

Chi-square test

The mean overall satisfaction rate from the intervention was high for both parents (M = 9.08, SD = 1.25) and adolescents (M = 8.58, SD = 1.18). The highest satisfaction for both parents and adolescents was reported on “relationship with therapist” (parent: M = 9.6, SD = 0.63; adolescent: M = 9.17, SD = 0.88). The lowest reported mean satisfaction was found for parent ratings of the impact of the intervention on parental self-efficacy (M = 6.87, SD = 2.27). Parents’ and adolescents’ mean ratings of satisfaction with the impact of the intervention on adolescents’ awareness, strategy acquisition and strategy effectiveness in daily life were all high ranging, from M = 7.71 (SD = 2.03) to M = 9.17 (SD = 0.94).

Preliminary efficacy of the Teen Cog-Fun intervention

Participants of the study set on average 2.5 occupational goals each, with 55 goals set overall. Goals represented a variety of occupational categories (instrumental activities of daily living, education, leisure, social participation and family participation). The category with the highest number of goals (47%) was education (school) functioning (see Table 4).

Table 4.

Number (n) of goals per occupation category and examples of the goals set (total goals: n = 55).

Occupation category	Goals, n (%)^a	Examples of occupational goals
IADL	16 (29)
Medication management		Remember to take ADHD medication
Time management		Get up on time in the morning on my own Be on time (to school/to leisure activity)
Material organization		Tidy my roomOrganize my travel pack
Task organization		Remember to do my chores
Education (school)	26 (47)
Tasks		Study for tests on my ownDo my homework
Behavior		Listen and participate in science classStop disrupting the class
Leisure	5 (9)	Participate in leisure activities other than TVGo to the gym twice a week
Social participation	2 (4)	Meet more friendsMeet friends more often
Family participation	6 (11)	Make a joint decision with my parentsInteract respectfully with my family during dinner

^an = goals (%) of total goals per category

IADL: instrumental activities of daily living.

Teen Cog-Fun intervention outcomes are presented in Table 5. Comparison of baseline to post-treatment scores revealed significant improvements in adolescent and parent ratings on the COPM (p<.001) with very large ES (d >1.0), in parent ratings on the BRIEF (p< .001) with large ES (d>.7) and in adolescents’ strategy behavior (p<.001) with very large ES (d = 1.24). No significant improvement was found in the awareness to difficulties subscale of the SRSI (see Table 5). Regarding the BRIEF clinical categories, 67% of the participants were in the clinically impaired category (GEC T-score > 65) pre-intervention and 32% post-intervention.

Table 5.

Teen Cog-Fun intervention outcomes (n = 22).

	Pre M (SD)	Post M (SD)	t _(1,21)	p	ES
COPM performance
Parent	2.56 (1.34)	5.33 (2.11)	–5.50	.000	1.57
Adolescent	4.29 (1.97)	8.19 (1.12)	–10.95	.000	2.43
COPM satisfaction
Parent	2.70 (1.58)	5.57 (2.24)	–5.86	.000	1.50
Adolescent	4.99 (1.92)	7.94 (1.22)	–6.85	.000	1.83
BRIEF (parent)
Global executive composite	68.91 (6.8)	60.41 (8.13)	4.43	.000	1.13
Behavioral regulation index	63.91 (11.3)	55.82 (9.89)	3.90	.001	0.76
Metacognitive index	69.36 (6.43)	61.32 (7.91)	4.14	.000	1.12
SRSI
Awareness of difficulties	6.47 (2.18)	5.78 (1.96)	1.60	.126	0.12
Strategy behavior	7.08 (1.98)	4.70 (1.87)	–3.73*	.000*	1.24

COPM: Canadian Occupational Performance Measure; BRIEF: Behavior Rating Inventory of Executive Function (T scores); SRSI: Self-Regulation Skills Interview; ES: Cohen’s d effect size.

Wilcoxon signed rank Z statistic, since variable did not meet criteria for normal distribution.

Bonferroni correction for multiple comparisons p = 0.05/9 = .005.

Metacognitive change mechanism

Correlations between change scores (pre–post-intervention) of the SRSI and COPM scores revealed a positive moderate correlation between change in strategy behavior subscale of the SRSI and change in parent-rated COPM (r = .459, p<.05), whereas no significant correlation was found with change in adolescent-rated COPM (r = –.164). In addition, no significant correlations were found between the change in awareness to difficulties subscale of the SRSI and change in parent or adolescent-rated COPM scores (r = –.024, –.083).

Qualitative analysis of strategy types

Qualitative analysis of the strategies that were reported in the SRSI after intervention revealed three overarching strategy categories supporting occupational performance, which further divided into several subcategories (see Table 6). The first category, “self-determined choices,” includes statements reflecting the use of strategies that express the choice of occupational goals that stem from values, self-efficacy beliefs and interests. This category comprised two subcategories addressing strategies used for the initial choice to engage in an occupation and the subsequent choosing of a starting point, that is, where to begin the activity (for example components that require less effort). The second category, “plan and organize,” comprises statements reflecting a strategic approach to task performance: “analyze task requirements and barriers,” “prioritize,” “organize,” “sequence steps” and “time scheduling.” The third category, “Adaptations,” includes strategic self regulation and adapting task and environmental factors supporting occupational performance.

Table 6.

Qualitative analysis of the strategies reported after intervention in the SRSI.

Strategies category	Strategies sub-category	Examples
Self-determined choices	The initial choice of goals and sub-goals	“First, I have to think it’s important to me”“I decide, ‘this is what I want’”
Self-determined choices	Choosing to begin with task components that are most interesting/easiest	“[When I have to read a boring text] I look for something in that text that I can connect to [emotionally]” “I look for the easiest question [in the test] to start with”
Plan and organize	Analyze task requirements and barriers	“I write down what I need, physically and mentally, in order to begin” “I need to understand the obstacles, in order to minimize them”
	Prioritize	“[when] I have a 10-minute recess, I think of all the things I have to do… then I do the important things first”
	Organize	“I summarize the material [for exam], shorten it, divide it to subcategorize”
	Sequence steps	“In order to be on time to seminar, I need to go to sleep earlier and arrange my clothes and bag before I go to sleep”
	Time scheduling	“I have a weekly timetable, so I know what I should do every day”
Adaptations	Self:
	External actions (food; deep breathing; engage, slow down)	“If a eat before [I study] I’m more concentrated, less hyperactive” “I take a deep breath [to calm down]” “In order to stay focused [in class] I ask questions, answer questions” “When I don’t understand [what I read] I need to read it again, much slower”
	Internal self-talk: stop, motivate, calm down	“To stop [teasing] … I say things in my heart instead of saying out loud” “To go to the gym, I remind myself of its beneficial effect on my health” “To calm down I tell myself, ‘you don’t have to finish first [the exam]’… or ‘it’s all right not to get 100’”
	Task:
	Break it down to parts	“I break it down to small parts… for example I had an annual trip, one day I checked what I needed, the second I bought things, two days before the trip I packed”
	Change task demands	“In order to read a book, I’ll read a book with short stories” “I had to memorize a boring text, I turned it into a literary analysis which was interesting and fun and I remembered it better”
	Environment:
	Social: Asking for support	“I ask my parents to help me monitor task completion, they ask me, ‘did you do it?’… I won’t lie to my parents, I’ll do it… when I self-monitor, I may cheat” “I tell my teacher, ‘when you notice I start interrupting class, tell me to go out, wash my face and come back’”
	Physical: Adapting environmental features	“I prefer studying at the kitchen table, away from my computer, I also listen to music”
	Using adaptive aids	“I use reminders in my cell (phone)”

SRSI: Self-Regulation Skills Interview.

Discussion

This study sought to examine the feasibility of the Teen Cog-Fun intervention for adolescents with ADHD, and to test the potential effects of this metacognitive intervention embedded in daily occupations. The compliance rate was acceptable and participants that completed the intervention reported high rates of satisfaction (both teens and parents). Pre–post measures demonstrated significant gains in occupational performance, EF and strategy behavior. Moreover, a positive significant correlation was found between gains in occupational performance and strategy behavior. Qualitative findings point to participants’ use of three types of strategies to support their occupational performance: “self-determined choices,” “plan and organize” and “adaptations.” These positive preliminary findings provide a rationale for further controlled research on the Teen Cog-Fun intervention. The current study is unique in its focus on functional outcomes as represented by the individualized occupational goals as well as standardized metacognitive outcomes and ecological measures of EF in daily life.

Considering the low adherence of adolescents with ADHD to any treatment (Bussing et al., 2012), the attrition rate of this study was reasonable, with 81% of participants completing the intervention. Importantly, of the five adolescents that dropped out of treatment, two dropped out due to therapist childbirth, not willing to continue with another therapist. This may reflect the centrality of the therapeutic relationship as supported by the high satisfaction rates for relationship with therapist. The Cog-Fun protocols place an explicit emphasis on the therapeutic alliance, utilizing communication modes (Taylor, 2008) to create the accepting and empowering environment necessary for the development of adaptive self-awareness (Maeir et al., 2018). Further studies should examine the features of the therapeutic relationship in the Teen Cog-Fun and their influence on treatment gains.

Satisfaction rates regarding the impact of intervention on awareness, strategy acquisition and strategy effectiveness in daily life were high according to both parents and teens. This finding is encouraging, supporting feasibility of the intervention. On the other hand, lower satisfaction was reported regarding parents’ own gains in parental self-efficacy. It is reasonable to assume that the two sessions with the parents were not sufficient to address the substantial parental challenge of raising an adolescent with ADHD (Theule et al., 2013). This finding can be compared to the significant gains in parental self-efficacy that were found among the parents of young children that participated in a full dyadic Cog-Fun intervention, where parents attend all sessions (Hahn-Markowitz et al., 2018). Due to the unique autonomy issues of adolescents it was decided not to include parents in sessions with their teens; however, the results suggest that, in further development of the Teen Cog-Fun intervention, it might be advisable to consider offering parents additional guidance and support.

Participants of this study set goals concerning varied occupations, possibly reflecting the comprehensive effect of ADHD in adolescents’ lives (Cermak, 2018; Hareendran et al., 2015). The high number of goals related to school functioning may echo the struggle that adolescents with ADHD experience in this domain (Frazier et al., 2007), and the high value they attribute to school success (Levanon-Erez et al., 2017). In line with this, many interventions for adolescents with ADHD focus on school functioning (Langberg et al., 2018; Sibley et al., 2016). However, the substantial number of goals in non-academic domains calls for expanding the scope of interventions to meet the broad occupational needs and concerns of adolescents with ADHD. The significant improvement, with large effect sizes in the occupational performance of adolescents’ goals according to both parents and adolescents, provides initial support for intervention efficacy. Nevertheless, the gains in occupational functioning should be interpreted cautiously since the COPM measure used in this study does not represent overall functional impairment, but rather represents specific functioning in individually desired occupations. The positive findings may indicate that functional impairment is modifiable but the potential extent of this functional gain needs to be further examined.

The participants’ EF in daily life, as measured by BRIEF, demonstrated significant improvements following intervention, with the average score shifting from the clinical to non-clinical range. These positive findings replicate those found among children receiving the Cog-Fun intervention (Hahn-Markowitz et al., 2016), reflecting the potential for change among adolescents as well as children in this important area. However, caution is warranted considering that parent report may have been biased due to participation in the study. Future studies should add more objective informant reports or performance-based measures of EF in daily life.

To the best of our knowledge this is the first study of an occupation-based intervention for adolescents with ADHD that included a metacognitive measure of awareness of difficulties and strategy behavior. The strength of the study is that the SRSI interviews were rated by a blinded rater that did not participate in the intervention. Positive gains were found in strategy behavior but, contrary to our expectation, gains in awareness of deficits were not found. These findings can be compared to other metacognitive occupation-based interventions with adults with traumatic brain injury (Toglia et al., 2010), which found improvements in both awareness and strategy behavior on the SRSI. It is possible that awareness of deficits among adolescents with a neurodevelopmental disorder, as opposed to an acquired injury, is less modifiable. According to the Bio–Psycho–Social model of awareness, these factors may have prevented adolescents’ full recognition of their dysfunctions (Ownsworth et al., 2006). Adolescents evolving identity may be specifically vulnerable and thus psychogenic defense mechanisms may be highly influential, despite explicit therapeutic attempts to identify and capitalize on strengths in order to reduce the need for defensive denial.

In contrast to awareness of deficits, strategy behavior, comprising strategy awareness, use and effectiveness, was shown to be more responsive to intervention in our study. The differential effect of intervention on awareness of deficits and awareness of strategies can be understood by the multidimensional nature of awareness. According to the Dynamic Comprehensive Model of Awareness (DCMA) (Toglia and Kirk, 2000), awareness is a complex construct compromising several distinct components. The differential association found between awareness components and functioning, whereby awareness and use of strategies, and not awareness of deficits, correlated with occupational performance further validates this model.

The positive significant correlation that was found between occupational functioning gains and strategy behavior is encouraging. Correlation does not prove causality, yet this finding is in line with the assumption that utilization of strategies may be a key component of adaptive coping with neurocognitive challenges (Toglia, 2018). Our correlational findings support the recent findings of Kysow and colleagues (2017), whereby the use of strategies had a beneficial effect on functioning in employment, education and parenting of adults with ADHD. Interestingly, Kysow and colleagues (2017) also found a significant correlation between childhood and adulthood use of strategies. The long-term benefits of strategy behavior gains following Teen Cog-Fun should be further explored. Of note, the correlation between strategy behavior and occupational performance was found only with parent-rated occupational performance and not with adolescents’ ratings. The difference in correlations may reflect adolescents’ overestimation of performance, as demonstrated in other studies (Owens et al., 2007). However, comparing between self-report and informant report was not the focus of this study, therefore further inquiry is needed.

Qualitative analysis of the types of strategies that adolescents reported in order to support their occupational performance provides a more in-depth account of the strategy change mechanism. Adolescents reported utilizing three types of strategies: “self-determined choices,” “plan and organize” and “adaptations.” Employing “self-determined choices” may reflect their recognition of the impact of internal motivation. Explicit linking of motivation to action is considered a powerful enabler for effort recruitment and regulation among individuals with ADHD (Barkley, 2015). The use of motivational techniques like motivational interviewing and self-chosen goals is reported in other psychosocial interventions for adolescents with ADHD (Boyer et al., 2015; Vidal et al., 2015). The Teen Cog-Fun emphasis on addressing adolescents’ volition, first by comprehensive exploration of occupational identity, discussing values, strengths and challenges in occupational contexts, and then by setting goals arising from adolescents’ self-determination, may have contributed to adolescents’ perception of motivation as a valuable enabler.

Adolescents reporting the use of “Plan and organize” strategies supports positive findings of other interventions targeting these skills (Langberg et al., 2018; Sibley et al., 2016), indicating that adolescents with ADHD are able to acquire them. Planning and organizing can be conceptualized as compensating for various EF dysfunctions, and is thus important for ADHD self-management. Other interventions have imparted planning and organizing skills in specific academic contexts (Langberg et al., 2018; Sibley et al., 2016) and the findings of this study suggest these skills can be acquired in other occupational contexts as well.

The varied adaptation strategies reported by adolescents may suggest that their challenges can be compensated for by using many different individualized strategies, as opposed to the “one size fits all” approach of other interventions (Langberg et al., 2018). The Teen Cog-Fun intervention is specifically designed to develop self-management skills. General problem-solving strategies of goal-setting, action planning and monitoring are explicitly taught and systematically practiced during the intervention. On the other hand, specific strategies and modifications are not given by the therapist, encouraging the adolescent to generate or discover his own (Maeir et al., 2018). It is hypothesized that strategy generation skills would promote adolescent ability to strategically approach future challenges, thus supporting self-management of ADHD over time. Of note, goal-setting and use of resources have been referred to as components of proactive coping that promote wellbeing in the face of upcoming stressors (Sohl and Moyer, 2009). Based on our findings, there is a possibility that the Teen Cog-Fun may enhance proactive coping.

Limitations

Participants who completed the intervention reported high satisfaction, yet the 19% dropout rate may reflect more variation in overall satisfaction than was measured. Regarding outcomes, the use of subjective outcome measures with a lack of performance-based measures may limit the validity of findings, since one cannot rule out the possibility of a placebo or therapeutic alliance effect. Finally, regarding the strategy categories found in the qualitative analysis, caution is required in attributing these strategies to the intervention since pre-intervention influences were not controlled for in this study (for example prior interventions, family practices).

Conclusion, clinical implications and future directions

The current study provides preliminary evidence regarding the feasibility and efficacy of Teen Cog-Fun within a clinical setting. Participants were satisfied with the intervention. The adolescents’ occupational performance, EF and strategic behavior improved. Following intervention, participants reported using a variety of self-determined, planning and specific adaptation strategies, suggesting that adolescents are able to acquire a self-management approach to their challenges. The correlation found between gains in adolescent-reported strategy behavior (awareness use and effectiveness of strategies) and parent-reported occupational functioning suggests that functioning can be improved by training metacognitive skills.

There is a need for future randomized controlled studies in order to validate these findings. Studies should include long-term follow-up in order to examine the speculated benefits of metacognitive abilities on managing ADHD over the lifespan.

Key findings

The Teen Cog-Fun intervention resulted in improvement in adolescents’ occupational performance, executive functioning and strategy behavior.

Following the intervention, adolescents’ strategy behavior was correlated with parent-rated occupational performance.

What the study has added

This study initially supports the feasibility and efficacy of the Teen Cog-Fun, an occupational therapy metacognitive intervention, for promoting the occupational performance, executive functioning and strategic behavior of adolescents with ADHD.

Footnotes

Acknowledgments

The authors deeply thank the parents and adolescents who participated in this study for their trust and for allowing us to learn from their experiences. We would also like to express our strong appreciation and thankfulness for the occupational therapists that implemented the intervention, Orit Fisher, Tamar Paley-Altit, Adi Caspi, Nufar Grinblat and Osnat Alon, for their professional and caring implementation, for precision in data collection and for sharing their constructive feedback. Special thanks to Ruthie Traub Bar-Ilan for her valuable contribution to the Teen Cog-Fun protocol and for helping in post-intervention data collection, to Shiri Davidovich, MA child clinical and school psychology student, for assisting with the screening phase of the study, and to Inbal Kelmm, graduate occupational therapy student, for her devoted attention to the trustworthiness rating of the SRSI data.

Research ethics

Ethical approval was obtained from the Institutional Review Board of the Hebrew University of Jerusalem in 2011 (Reference ID: 04122011).

Consent

All participants, parents and adolescents provided written informed consent for participation in Teen Cog-Fun intervention and research.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

Contributorship

Nirit Levanon-Erez and Adina Maeir researched literature, developed the intervention protocol and applied for ethical approval. Orli Kampf-Sherf contributed to subject recruitment and to screening for inclusion/exclusion criteria. Nirit Levanon-Erez and Adina Maeir supervised data collection and carried out the statistical analysis. All authors interpreted the data. Nirit Levanon-Erez and Adina Maeir wrote the first draft of the manuscript. All authors reviewed and edited the manuscript and approved the final version.

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