Attention deficit hyperactivity disorder (ADHD) is a neurobiological disorder that affects 7%–10% of school-age children (Larson, Russ, Kahn, & Halfon, 2011; Spencer, Biederman, & Mick, 2007) and 2%–6% of preschool children (Greenhill, Posner, Vaughan, & Kratochvil, 2008). This disorder is the most prevalent chronic neurodevelopmental disorder of childhood and the number-one reason for referral to mental health treatment (American Academy of Pediatrics [AAP], 2011; American Psychiatric Association [APA], 2013). ADHD is a lifelong neurocognitive disorder involving impaired executive functions (EF) with broad implications that impede participation and quality of life in the present and future (Barkley, 2006; Brown, 2013; Turgay et al., 2012). The growing understanding of the early onset of ADHD among preschoolers, as well as the persistence and long-term implications of the disorder, provides the rationale for early diagnosis and intervention.

Intervention at a young age is of vital importance to improve current occupational functioning and lower the risks for future disabilities (Antshel & Barkley, 2008; Young & Amarasinghe, 2010). Increased understanding of the complex biopsychosocial mechanisms that influence the well-being of children with ADHD and their families guides the current trends in comprehensive health care for this population (AAP, 2011; National Institute of Mental Health and Clinical Excellence, 2009). The following text provides a brief account of these mechanisms and the rationale for the Cognitive–Functional (Cog–Fun) occupational therapy intervention for children with ADHD (Maeir, Hahn-Markowitz, Fisher, & Traub Bar-Ilan, 2012).

The biological basis of ADHD is well established, and the disorder is increasingly recognized as a developmental impairment that involves deficient EF (Barkley, 2006; Brown, 2009, 2013, Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). Brown’s model of ADHD (Brown, 2009, 2013) includes six clusters of neurocognitive EF that tend to be chronically compromised in people with ADHD: activation, focus, effort, emotion, memory, and action. These biological mechanisms control and regulate cognition, emotion, and behavior to effectively guide one’s actions toward future self-serving goals and occupational functioning, particularly in the more complex and dynamic activities of daily living (ADLs). Strong evidence supports the high prevalence of executive dysfunction in ADHD, which has a negative impact on widespread functional outcomes beyond symptom ratings (Stern, Pollack, Bonne, Malik, & Maeir, 2013; Willcutt et al., 2005). Therefore, impaired EF have been identified as important targets for intervention in the ADHD population (Cermak & Maeir, 2011).

Intervention models for people with neurocognitive deficits (e.g., EF impairment) in occupational therapy emphasize that these cognitive deficits do not occur in isolation. Accordingly, neurocognitive deficits need to be understood in the context of the whole person as he or she engages in meaningful occupations in his or her environment (Connor & Maeir, 2011; Katz, Baum, & Maeir, 2011). When considering the impact of executive dysfunction, it is imperative to take into account the psychosocial context of children with ADHD. These children are lacking in experiences that foster the development of a positive and cohesive sense of self in action (Polombo, 2001). Their core executive deficits hinder successful participation in age-appropriate tasks, leading to frequent frustration and reduced self-efficacy and enjoyment in their occupational engagements (Shimoni, Engel-Yeger, & Tirosh, 2010; Tabassam & Grainger, 2002). The parent–child dyad is constantly challenged. On the one hand, the child’s executive dysfunction impedes his or her internalization of parental representation to cope with daily challenges, resulting in increased demands for parental monitoring and involvement; on the other hand, the parent facing the child’s accumulating difficulties experiences reduced parental efficacy, frustration, and shame (Al-Yagon, 2007). The family system is often trapped in a negative interpersonal cycle characterized by high levels of stress and difficulty coping with daily demands, necessitating a family-centered treatment approach (Davis, Claudius, Palinkas, Wong, & Leslie, 2012; Whalen, Odgers, Reed, & Henker, 2011).

Existing pharmacological and psychosocial interventions have been shown to be effective in improving ADHD symptoms and behavioral outcomes of children (AAP, 2011). However, little evidence is available for family-centered and occupation-based interventions that address executive dysfunction in an occupational context among children with ADHD.

The Cog–Fun intervention (Maeir et al., 2012) targets the cognitive, emotional, and environmental barriers to participation as they interact in an occupational context. This approach is in accord with the International Classification of Functioning, Disability and Health, which delineates the multidimensional biopsychosocial implications of health conditions (World Health Organization, 2001). The primary objective of the Cog–Fun intervention is to promote the acquisition of executive strategies and self-efficacy in occupational performance. For a child to internalize these strategies, they need to part of his or her occupational context and language, acquired in enjoyable and fun activities, and experienced as tools that are worth the effort. The effortful strategy learning is imparted within a positive, family-centered therapeutic setting and with environmental supports.

This integrative approach relies on established occupational therapy practice models and harnesses three key change mechanisms: (1) executive strategy acquisition, (2) an enabling therapeutic setting, and (3) use of environmental supports and procedural learning. Executive strategy acquisition is a metacognitive learning process based on the Multicontext Treatment Approach in cognitive rehabilitation (Toglia, 2011) and has several stages. At first, the child experiences the need for and use of an executive strategy in a variety of activities; for example, the need for inhibition—a “stop” strategy—is experienced in running and stopping in the game Red Light, Green Light, and the need for recruiting effort is experienced in playing tug-of-war or pushing against a large ball. The child then names the strategy and creates a tangible symbol of the strategy (e.g., stop-sign sticker, the word stop, “Mr. Effort,” “the Force,” or an action figure from the child’s play world) that he or she transfers to multiple activities and contexts in therapy and at home. The occupational therapy practitioner helps the child and parent select playful activities and occupational goals, practice the executive strategies, and transfer them to functional goals. Activities and goals are designed to be enjoyable and to harness motivational and cognitive resources toward goal-oriented behavior.

The second change mechanism, the enabling therapeutic setting, is a positive, safe, and enabling family-centered therapeutic environment. An enabling social context is achieved through therapeutic use of self, interpersonal reasoning, therapeutic communication, and family centeredness derived from the Intentional Relationship Model (Taylor, 2008).

The third change mechanism, use of environmental supports and procedural learning, is based on the neurofunctional approach to cognitive rehabilitation (Guiles, 2011), in which practitioners use behavioral learning and environmental resources and seek to minimize frustration during the child’s learning process. These principles are implemented to boost motivation and self-efficacy within a relatively short time and to supplement the more effortful metacognitive learning when necessary.

An initial pilot study found supporting evidence for the effectiveness of Cog–Fun with 17 children ages 7–9 diagnosed with ADHD (Hahn-Markowitz, Manor, & Maeir, 2011). Significant improvements were found after treatment on measures of EF and occupational performance. The purpose of the current study was to examine the effectiveness of Cog–Fun for young children with ADHD.

The study was a controlled experimental study with a crossover design to examine the effects of the Cog–Fun program on young children with ADHD. Ethical approval for the study was obtained from the Hadassah and Hebrew University of Jerusalem ethics committee. Parents provided informed consent, and children provided assent.

Twenty-seven parents of preschool children with ADHD applied to participate in the study in response to an advertisement distributed in three central neurodevelopmental clinics. Inclusion criteria were a medical ADHD diagnosis based on criteria for ADHD in the Diagnostic and Statistical Manual of Mental Disorders (4th edition, text revision; American Psychiatric Association, 2000) and confirmed by psychological interview and parent report of the child’s EF difficulties in daily life based on the Behavior Rating Inventory of Executive Function (BRIEF) cutoff score of ≥65 on at least one scale. Exclusion criteria were presence of other psychiatric or neurological disorders, specific language disorders, special education setting, and change in medication status in the previous 3 mo.

The Behavior Rating Inventory of Executive Function–Preschool version (BRIEF–P; Gioia, Espy, & Isquith, 2003) is a 63-item ecological rating scale completed by a parent or teacher designed to reflect the neuropsychological constructs of EF in everyday situations of children ages 2 yr, 0 mo, to 5 yr, 11 mo. It comprises five executive scales—Inhibit, Shift, Emotional Control, Working Memory, and Plan—and a global executive composite (GEC). Raw scores are transformed into t scores, with 65 or above indicating clinical impairment. The subscales of BRIEF–P parent ratings show high internal consistency (Cronbach’s α rs = .80–.90), adequate to high test–retest reliability (Inhibit and GEC, r > .90; Shift, Emotional Control, Working Memory, r > .80; Plan, r > .70). Moreover, the assessment was shown to be applicable to diverse ethnic groups, with no significant impact of ethnicity on BRIEF ratings (Sherman & Brooks, 2010).

The BRIEF version for children (Gioia, Isquith, Guy, & Kenworthy, 2000) was used for the children already enrolled in first grade. It comprises 86 items divided into eight scales and a GEC. Internal consistency, test–retest reliability (rs = .72–.84 for parent form over 3 wk), and discriminant validity have been established for people with ADHD (Gioia et al., 2000; McCandless & O’Laughlin, 2007). In this study we used the standardized scale scores common to both BRIEF versions—Inhibit, Shift, Emotional Control, Working Memory, and Plan—and the GEC.

The Canadian Occupational Performance Measure (COPM; Law, Baptiste, et al., 2005) is a semistructured, client-centered instrument to help identify problems and detect change in the performance of daily occupations. It is well validated, reliable (test–retest reliability = .80 for Performance scale over 1–2 wk), and standardized (Law, Baptiste, et al., 2005). Law, Majnemer, et al. (2005)  used the COPM to measure occupational performance outcomes before and after an occupational therapy home care program for children, some of whom had ADHD. In the current study, we interviewed the parents using the COPM, and they rated their child’s performance and their own satisfaction on their identified occupational goals.

Parents who applied to participate in the study were invited to a meeting with a certified developmental psychologist to determine eligibility. The participants were consecutively assigned to the Cog–Fun intervention group or to a wait-list control group. After the 12-wk intervention, the control group received the Cog–Fun intervention. Three months after treatment, both groups were evaluated to determine the stability of the occupational gains. The Cog–Fun intervention was administered by three experienced occupational therapists (Authors Fisher, Boas, and Traub). Eighty percent of the treatment sessions were videotaped and reviewed by senior researchers (Authors Maeir and Landau) to verify fidelity to treatment principles. The COPM was administered to the intervention group at the beginning of treatment by the occupational therapists who also carried out the treatment and to the control group by the psychologist (Author Landau). At the end of intervention for both groups, a different occupational therapist (not involved in the treatment) readministered the measures to parents. The COPM was readministered by phone 3 mo after treatment by the psychologist.

The Cog–Fun intervention is a manualized approach (Maeir et al., 2012) that targets the cognitive, emotional, and environmental barriers to participation as they interact in the occupational context. It supports participation via the metacognitive learning of executive strategies (e.g., stop, recruit effort/persist, check, plan) within an enabling context. The program involves ten 1-hr weekly sessions with child and parent in which the occupational therapist introduces executive strategies one by one in a nonthreatening, playful atmosphere. The number of strategies completed in the course of treatment and the use of adaptations are tailored to the child’s cognitive and emotional profile and occupational goals. Parents identify occupational goals before and during the intervention, and the goals are gradually introduced in the therapy sessions as the ecological context for strategy transfer. For example, the child acquires the stop strategy and transfers the strategy in playful games and then further transfers it to his or her occupational context—for example, “stop and hold adult’s hand when crossing the street.”

The role of the parent in treatment is central. The parent attends each session to experience positive engagement with his or her child in playful activities and to learn the metacognitive language and supportive treatment principles in order to orchestrate transfer to the home context. A weekly communication session by phone or email with the parents is scheduled between sessions to support implementation of the program. In addition, one session is conducted in the home to help the practitioner further understand the child in his or her natural surroundings and facilitate transfer of learning.

The study hypotheses were as follows:

• A significant improvement will be found in the intervention group after treatment on all outcome measures.

• Before crossover (Time 2), significant differences will be found between the intervention and wait-list control groups in change scores for all outcome measures.

• After crossover from wait list to treatment (Time 3), the control group will show no significant differences from the original treatment group in change scores (pre–post treatment) for all outcome measures.

• At 3-mo follow-up (Time 4), no significant changes will be found in COPM scores for all participants.

In addition, the study also explored the categories of occupational goals in relationship to the COPM domains and executive dysfunction among the young children with ADHD.

The data were analyzed with SPSS Version 19.0 (IBM Corporation, Armonk, NY). Nonparametric statistics were used because of the small sample size. The Wilcoxon signed rank test was used to examine within-group effects, and the Mann–Whitney U test was computed between the two groups on change scores to study Time × Group interaction. Significance level was set at .05 for two-tailed hypotheses. Effect size was computed using Hedge’s g because of the small sample size (Lion, 2008).

The final sample included 19 children with ADHD (mean age = 5.97 yr, SD = 0.66). Of the 27 children recruited for the study, 6 did not meet ADHD inclusion criteria, and two families declined to participate for scheduling reasons. No significant differences were found between the groups in age, years of parent education, or gender distribution (p > .01). Table 1 lists participant characteristics.

Participants set a total of 88 occupational goals on the COPM (4.6 goals per child on average) in the ADL (n = 34), social participation (n = 39), academic (n = 8), and leisure (n = 7) domains. EF deficits typical of ADHD were represented in the difficulties the parents identified in their child’s occupational performance. The majority of goals reflected difficulties in the EF area of inhibition (n = 47), followed by difficulties recruiting effort and persistence (n = 20), monitoring and checking performance (n = 16), and planning (n = 13). Examples of the occupational performance goals parents identified are provided in Table 2.

Within-group analysis revealed that the intervention group showed significant gains after treatment on all outcome measures (p < .05) except for the BRIEF Plan scale. All outcomes demonstrated improved median scores within the intervention group. As expected, the wait-list control group demonstrated no improvement and even a worsening of 3–10 points in median BRIEF scores. Between-group analyses comparing change scores on the outcome measures for the two groups revealed significant differences in COPM and BRIEF scores except for the Plan and Emotional Control scales (see Table 3).

After crossover to the treatment condition, the control group demonstrated gains similar to those of the intervention group, and no significant differences were found between the groups in change scores (pre–post treatment) for all outcome measures (p > .05). Therefore, we pooled the results for both groups to examine the effects of treatment on the entire group (see Table 4). The COPM findings pertaining to occupational performance demonstrated very large effect sizes for both the Performance and Satisfaction scales. Moreover, examining clinically significant change (2-point change on ratings of Performance and Satisfaction), participants showed significant improvement in 89% of the occupational goals. The effect sizes for the BRIEF were small to medium, with higher effect sizes in the Inhibit, Shift, and Working Memory scales.

The occupational treatment gains were maintained at follow-up. The median COPM change scores from the end of treatment to 3-mo follow-up were less than 1 point (Performance change score = 0.125, Satisfaction change score = 0.286). No significant changes were found in COPM scores from the end of treatment to 3-mo follow-up in the entire sample (COPM Performance z = −0.545, p = .586; COPM Satisfaction z = −0.758, p = .449).

The findings of this controlled study support the efficacy of the Cog–Fun occupational therapy intervention for young children with ADHD. The results demonstrate that Cog–Fun treatment resulted in improved outcomes, whereas wait-list control participants showed no improvement and even demonstrated a trend toward worsening. Moreover, treatment gains were replicated in the wait-list control group. These results support the assertion that Cog–Fun treatment gains are replicable and not incidental and may be attributed specifically to the treatment and not to maturation. The findings of the current study are in line with the previous pilot study on Cog–Fun effectiveness with older children (Hahn-Markowitz et al., 2011) and demonstrate that an integrative cognitive approach can be effective for younger as well as older children.

The scope of occupational goals that parents determined reflects the broad impact of ADHD on the social participation, ADL, academic, and leisure domains in children’s life contexts. Moreover, the nature of the occupational difficulties parents reported demonstrates the functional implications of the core EF problems in ADHD primarily relating to inhibitory control. These findings are supported by the current understanding of ADHD as a disorder of executive functions (Barkley, 2006; Brown, 2009, 2013) and provide an ecological perspective on the neurocognitive deficits in ADHD.

The objective of Cog–Fun—to enhance participation of children with ADHD—was supported by large effect sizes for COPM scores and clinically significant change in the vast majority of goals. Regarding changes in EF in daily life, small to medium effects of treatment were found for BRIEF scores. The effect sizes on the Inhibit, Shift, and Working Memory scales were higher than those on the Plan and Emotional Control scales, which were small and not statistically significant. These findings may be attributable to the lesser focus of the treatment on these domains (the children acquired strategies mainly related to inhibition and recruiting effort and persistence) or to the centrality of inhibition and working memory at this young age (Welsh, 2001). Overall, the study hypotheses were confirmed for both occupational performance and executive functions.

The Cog–Fun treatment is an integrative approach; hence, the underlying change mechanisms are likely attributable to a synergistic effect of the treatment components. First, that parents generally recognized and appreciated the family-centered practice was depicted in the treatment logs. Most parents made a point of mentioning family centeredness in their feedback as a crucial aspect of the treatment. The parents also valued their role in determining the occupational goals and implementing the treatment principles both in sessions and at home. Anecdotal reports highlighted parents’ feelings of being heard and respected, often for the first time in their journey to address their child’s neurodevelopmental problems. This approach empowered parents as the central change agents in coping with their child’s ADHD.

The triadic, intentional therapeutic relationship among the occupational therapist, parent, and child in the clinical setting created a safe arena for amending the negative cycle of parent–child frustration typical of families with ADHD (Theule, Wiener, Tannock, & Jenkins, 2013). Furthermore, the treatment setting provided parents with an opportunity to discover the type and amount of supports that were beneficial or necessary for their child to participate successfully in occupations. This enabling context facilitated the effortful metacognitive strategy learning necessary to address the neurocognitive executive deficits in ADHD. Thus, a second hypothesized change mechanism was the formation of the child’s executive toolbox to include basic executive strategies such as how to stop, recruit effort, and monitor themselves and their surroundings. The children and parents had fun with strategies and then experienced the benefit of executive strategy implementation in their occupational goals while gradually acquiring the executive language. Goal achievement was supported with task-specific training and environmental supports as necessary. We hypothesize that self-efficacy was boosted through the accomplishment of personally significant occupational goals and that this achievement, in turn, heightened motivation for further transfer of executive strategies and language to other activities, occupations, and contexts. Consequently, the child’s executive toolbox was established within a favorable motivational context to enable both present and future use and development.

In sum, Cog–Fun is designed to harness multiple change mechanisms in line with the theoretical understanding of the biopsychosocial implications of ADHD in context. The treatment effects addressed the children’s current occupational barriers and provided the foundations for coping with ADHD challenges in the future.

The study was limited by a small sample size and lack of randomization of the study groups. In addition, the children’s educational context (kindergarten and school) was not included in the assessment or intervention process. Finally, the children’s perspective was not evaluated in the assessment protocol. Future studies are planned with larger, more representative samples in a randomized controlled design that will incorporate a child-centered pictorial rating of executive functions in daily life. Moreover, the application of the Cog–Fun protocol to the school setting will be explored.

The results of this study have the following implications for occupational therapy practice:

• The core executive dysfunction of children with ADHD affects many areas of their occupational performance. The Cog–Fun treatment program integrates established occupational therapy practice models from cognitive rehabilitation to target the impact of executive deficits in a holistic, family-centered approach.

• The Cog–Fun treatment program has initial evidence to support its efficacy in improving occupational performance and executive functioning in young children with ADHD.

• The COPM and BRIEF are occupation-based measures that are sensitive to treatment-induced changes.

The authors thank the Irving B. Harris Foundation Project on Professional Development and Social Policy for Children and Families for supporting this project.