Pilot Study of the Cognitive–Functional Intervention for Adults (Cog-Fun A): A Metacognitive–Functional Tool for Adults With Attention Deficit Hyperactivity Disorder

Abstract

Importance: Adults with attention deficit hyperactivity disorder (ADHD) often experience chronic challenges in their life roles. There is a need for evidence-based occupational therapy interventions to help enhance their functioning.

Objective: To determine the preliminary effectiveness of the Cognitive–Functional Intervention for Adults (Cog–Fun A), a metacognitive–functional occupational therapy tool for the improvement of occupational performance (OP) and quality of life (QoL) in adults with ADHD.

Design: One-group pretest–posttest design with a 3-mo follow-up.

Setting: Community setting in Jerusalem, Israel.

Participants: Fourteen adults, ages 18–60 yr, with a valid diagnosis of ADHD and an indication of executive function (EF) impairment.

Intervention: Participants received 15 1-hr weekly sessions that addressed self-awareness of strengths and challenges through education and guided discovery as well as strategy acquisition and implementation within a context of occupational goal attainment.

Outcomes and Measures: The Behavioral Rating Inventory of Executive Function–Adult version, an adult ADHD QoL measure, the Canadian Occupational Performance Measure, and the Self-Regulation Skills Interview were administered.

Results: Twelve participants completed the intervention. Posttreatment scores revealed statistically significant improvements in EF, awareness, OP, and QoL. Gains in QoL showed a modest reduction at the 3-mo follow-up.

Conclusions and Relevance: The Cog–Fun A is a promising intervention for improving OP and QoL among adults with ADHD and should be investigated further.

What This Article Adds: The Cog–Fun A offers an effective nonpharmacological, metacognitive–functional, occupation-centered treatment option for adults with ADHD.

The findings presented here lend preliminary support to the effectiveness of the Cognitive–Functional Intervention for Adults, an intervention based on a metacognitive–functional treatment model for adults with ADHD.

Attention deficit hyperactivity disorder (ADHD) is a widespread neurodevelopmental condition involving difficulties with inattention, impulsivity, and hyperactivity (American Psychiatric Association, 2013) that in 57% of cases persists into adulthood (Fayyad et al., 2017). The symptoms are typically attributed to executive dysfunction (Barkley, 2015) and stem from core neurological deficits in the prefrontal cortical networks that are responsible for self-regulation, directly impeding goal-directed behavior (Cortese et al., 2012; Munro et al., 2018). Studies have consistently found decreased quality of life (QoL) in adults with ADHD compared with peers without ADHD (Brod et al., 2015). ADHD is thus deemed a chronic neuropsychiatric health condition that requires intentional, lifelong management (Asherson et al., 2016; Turgay et al., 2012).

Self-awareness (SA) of personal strengths, challenges, and strategies is central to adaptive self-management of chronic health conditions such as ADHD (Ford, 2020; Hourzad et al., 2018). SA comprises two central components: (1) online awareness, defined as within-task self-regulation skills, and (2) metacognitive knowledge, which refers to off-task general knowledge (Toglia & Kirk, 2000). Studies of adults with ADHD have described deficits in both of these SA domains (Chen et al., 2015; Manor et al., 2012; Sibley et al., 2012). Impairments in SA limit adaptive coping and pervasively feed into the negative self– other belief system commonly mentioned in the adult ADHD literature (Ramsay, 2017; Torrente et al., 2014). Self-defeating thought patterns alongside the ever-increasing demands of adult life roles negatively affect an already-limited knowledge base and self-regulatory skill capacity, further hindering successful role participation.

Effective management of ADHD calls for an intervention framework that increases treatment adherence, proactively plans for continuity of treatment throughout the person’s lifetime, and effectively integrates pharmacological and nonpharmacological interventions (Dalrymple et al., 2019; Faraone et al., 2015). Targeting broader patterns of self-regulation and psychosocial impairment, nonpharmacological interventions such as cognitive–behavioral and other skills-based approaches offer valuable treatment options for adults with ADHD (Gallagher & Feder, 2018). In light of the negative effects on occupational performance (OP) of deficits in executive function (EF) and SA, adults with ADHD may also gain from treatment modalities that directly target SA and EF within occupational contexts. Although these treatment modalities have produced favorable results when implemented with adults with acquired brain injury (Dawson et al., 2009; Toglia et al., 2011) and youth with ADHD (Hahn-Markowitz et al., 2017; Levanon-Erez et al., 2019), they have not yet been applied within the context of adult ADHD. Thus, in this study we set out to examine the initial effectiveness of the Cognitive– Functional Intervention for Adults (Cog–Fun A) (Maeir et al., 2018), a metacognitive–functional intervention for adults with ADHD that targets SA and EF in occupational contexts.

The Cog–Fun model incorporates neurocognitive and psychiatric rehabilitation principles within an occupational therapy intervention framework. It has four central change components: (1) metacognitive learning, (2) occupation centeredness, (3) environmental support, and (4) positive engagement. By addressing the chronic and pervasive effects of ADHD, the Cog–Fun A places increased emphasis on adaptive self-awareness, a unique construct defined as a combination of compassionate appreciation of self and acquisition of effective coping strategies linked to multiple occupational contexts (Levanon-Erez & Maeir, 2014).

In this study, we aimed to examine the preliminary effectiveness of the Cog–Fun A in improving OP and QoL of adults with ADHD. We hypothesized that the Cog–Fun A would be a feasible, effective intervention for adults with ADHD and that notable improvements would be found in OP, EF, SA, and QoL at treatment completion and at 3-mo follow-up. In addition, we explored effectiveness on EF and SA.

Method

Research Design

This intervention study had a pretest–posttest design with 3-mo follow-up.

Participants

Inclusion criteria were adult (age 18–60 yr), sufficient reading skills, valid diagnosis of ADHD, >5 symptoms on the Adult ADHD Self-Report Scale (Adler et al., 2003), score >64 on one or more scales of the Behavior Rating Inventory of Executive Function–Adult Version (BRIEF–A; Roth et al., 2005), and no change in pharmacological and nonpharmacological treatments within the past 3 mo. The exclusion criterion was acute psychiatric distress, defined as ≥2 SDs above the mean Global Severity Index of the Brief Symptom Inventory (Derogatis & Melisaratos, 1983).

Procedure

The study was approved by an institutional ethics committee and prospectively registered at ClinicalTrials.gov. Participants were recruited through advertisements on a university research website. A team member conducted a brief telephone call with all potential participants to explain the conditions of the study (e.g., length of intervention, inclusion and exclusion criteria). An assessment session was scheduled at which informed consent was obtained and the inclusion and exclusion measures were administered. Study participants were not offered reimbursement.

Two qualified occupational therapists delivered the intervention protocol. Treatment sessions began 1 to 2 wk after recruitment. All sessions took place in a designated clinic on the campus of the Hebrew University of Jerusalem. The treating therapist collected QoL and SA data at the first session. Baseline OP data were collected at Sessions 4 and 5. All sessions were documented via a written log, and video and audio recordings were used for participants who provided consent to do so. Treating therapists underwent regular reviews to verify treatment fidelity. An assessor blind to participants’ identity administered the postintervention measures 1 to 2 wk after treatment completion. A follow-up measure was electronically administered at 3 mo postintervention.

Intervention

The participants attended 15 1-hr weekly sessions. The protocol included four modular units, with each unit spanning approximately three to four sessions, applied in an iterative and incremental process comprising the following: SA promotion through education or guided discovery, between-session experience of strategy implementation in the context of occupational goal attainment, in-session mediated processing of occupational experience, and further SA enhancement (see Table 1 for a description of the treatment structure).

Table 1.

Description of the Cog–Fun A Treatment Units and Content

Unit No. and Description	Content
Unit 1: Promote awareness of chronic ADHD, EFD, and implications	• Engage in process-oriented assessment: understand functional implications of ADHD and EFD through joint review and psychoeducation • Set preliminary occupational goals
Unit 2: Acquire strategies in occupational contexts	• Discover strategies through structured activity monitoring (OPEA) • Link strategy to specific occupational goals (“mini-goals”) • Monitor strategy efficacy • Identify barriers to implementation • Modify or replace strategy as needed
Unit 3: Enable adaptive occupational identity	• Monitor goal attainment on an ongoing basis to reveal the tension between occupational demands and the limitations of effortful strategies • Explore volition and prioritize occupational goals • Introduce and practice self-compassion • Recruit external resources and promote self-advocacy • Promote awareness and acceptance of strengths and limitations in context
Unit 4: Prepare for long-term self-management	• Engage in reassessment • Practice self-advocacy • Consolidate optimal strategies • Develop a maintenance plan: identify ongoing occupational concerns, schedule follow-up, and explore group therapy for continued support

Note. The session structure includes a short check-in (“How was your week?”), an OPEA, education about and/or discovery of strategies, linking of a strategy to mini-goals, and completion of a structured summary. ADHD = attention deficit hyperactivity disorder; Cog–Fun A = Cognitive Functional Intervention for Adults; EFD = executive function dysfunction; OPEA = occupational performance experience analysis. From “An Integrative Cognitive Functional (Cog–Fun) Intervention Model for Children and Adolescents With ADHD,” by A. Maeir, R. Traub Bar-Ilan, L. Kastner, O. Fisher, N. Levanon-Erez, and J. Hahn-Markowitz, in N. Katz and J. Toglia (Eds.), Cognition, Occupation, and Participation Across the Lifespan: Neuroscience, Neurorehabilitation, and Models of Intervention (p. 342). Copyright ©2018 by AOTA Press. Adapted with permission.

Instruments

Occupational Performance and Quality of Life

The Adult ADHD QoL measure (AAQoL) assesses QoL in adults with ADHD (Brod et al., 2005). The scale consists of 29 items rated on a 5-point scale relating to frequency of symptom occurrence, yielding a total average score and four subscale scores (Life Productivity, Life Outlook, Relationships, and Psychological Health). Raw scores are converted into a 0- to 100-point scale, with higher scores indicating better QoL. A clinically relevant improvement in QoL is indicated by a change score of 8 or more points (Tanaka et al., 2015). The scale has good internal consistency (α = .93) and test–retest reliability (intraclass correlation coefficient α = .86) and discriminates between groups with and without ADHD (Brod et al., 2005; Matza et al., 2011). To minimize participant burden, the AAQoL was the only primary outcome measure also administered at follow-up.

The Canadian Occupational Performance Measure (COPM; Law et al., 2019) is a standardized client-centered instrument that was designed to identify client-specific occupational issues and measure changes in OP. A 10-point scale is used to measure performance levels (Performance Level subscale) and satisfaction levels (Satisfaction Level subscale), with higher scores indicating better performance. A change score of 2 or more is considered clinically significant (Law et al., 2014). The reliability, validity, and responsiveness of the COPM are satisfactory to excellent (Carswell et al., 2004). The COPM has high test–retest reliability (rs = .84–.92) and good concurrent and content validity, and is responsive to changes in occupational performance (Carswell et al., 2004; Law et al., 2014).

Higher Level Cognitive Functions (Executive Function and Self-Awareness)

The BRIEF–A is a 75-item self-report questionnaire that yields an overall summary score (the Global Executive Composite score), which includes two index scores: (1) the Behavioral Regulation Index (BRI), consisting of four scales (Inhibit, Shift, Emotional Control, and Self-Monitor), and (2) the Metacognition Index (MI), which includes five scales (Initiate, Working Memory, Plan/Organize, Task Monitor, and Organization of Materials). Raw scores are converted into a 0- to 100-point scale, with lower scores indicating better EF. A t score of 65 or above indicates clinical impairment. The BRIEF–A has moderate to high internal consistency (αs = .73–.98), high test–retest stability (rs = .82–.94), and moderate interrater agreement between self- and informant reports (rs = .44–.68). Moreover, the BRIEF–A can significantly differentiate between adults with and without ADHD (Rotenberg-Shpigelman et al., 2008).

The Self-Regulation Skills Interview (SRSI; Ownsworth et al., 2000) is a semistructured instrument that assesses three awareness domains: (1) Awareness Level (AL: emergent and anticipatory awareness), (2) Strategy Behavior (SB: strategy generation, degree of strategy use, and strategy effectiveness), and (3) Readiness to Change. The Readiness to Change domain was not used in this study. Scores are summed within the AL and SB domains and can range from 0 to 10, with lower scores indicating better awareness. The test has good interrater (r = .81–.92) and test–retest reliability (r = .69–.91; Ownsworth et al., 2000).

Statistical Analysis

We analyzed baseline sociodemographic and clinical characteristics for participants who completed the study (called completers) and those who did not using means and standard deviations. All outcome variables met Kolmogorov–Smirnov test criteria for normal distribution. We used t tests to compare within-group differences from pre- to postintervention and postintervention to follow-up. Cohen’s d effect sizes were calculated. All change scores remained statistically significant after Bonferroni correction for multiple comparisons.

Results

Study Population

The sample consisted of 14 participants with an average age of 31 yr (see Table 2 for a summary of participant characteristics). Four participants (29%) reported having been diagnosed with comorbid psychiatric conditions. Ten (71%) took medication for their ADHD. Four participants (29%) were self-referred, with the remainder referred by a friend, parent, or spouse. Thirteen participants were gainfully employed or students. One participant had been receiving supportive therapy on a monthly basis and remained at this status throughout the study. The remaining 13 received no additional psychosocial support.

Table 2.

Baseline Participant Characteristics in the Enrolled Group, Completers, and Noncompleters

Characteristic	M (SD) or n (%)		Raw Data for Noncompleters
Characteristic	Enrolled (n = 14)	Completers (n = 12)	Removed (n = 1)	Excluded (n = 1)
ASRS total score	63.43 (9.49)	65.5 (8.4)	55	47
BSI–GSI	1.25 (0.39)	1.25 (0.38)	0.82	1.67
Age	31.00 (9.33)	32 (9.75)	24	25
Female gender	7 (50)	6 (50)	Male	Female
ADHD medication	10 (71)	10 (83)	None	None
Worker/student	13 (93)	12 (100)	No productivity role	Worker

Note. ADHD = attention deficit hyperactivity disorder; ASRS = Adult ADHD Self-Report Scale; BSI–GSI = Brief Symptom Inventory–Global Severity Index.

Completion and Attrition Rates

Twelve (86%) participants completed the intervention. One participant was removed upon completion of five sessions because of a self-report of severe substance abuse that was unreported at the study’s onset. This participant lived alone, held no identified productivity role, and was unable to adhere to the treatment schedule. A second participant dropped out after completing 10 sessions because of a stressful employment situation and was subsequently unavailable to continue in the study. This participant reported a chaotic and unpredictable work schedule.

Preliminary Effectiveness of the Cog–Fun A

The findings based on data from the 12 study completers constituted the final analyzed sample. The noncompleters had scored within 2 SDs of the final sample’s mean baseline scores on all outcome measures. Ten participants (83%) returned the AAQoL follow-up measure at 3 mo postintervention. A comparison of baseline and posttreatment scores revealed statistically significant improvements in QoL (AAQoL), EF (Brief–A), SA (SRSI), and OP (COPM; see Table 3 for results). Life Productivity showed the largest change of the AAQoL domains (d = 1.56). The 3-mo follow-up showed some deterioration in all domains, with a moderate decrease in Life Productivity (d = 0.57).

In regard to the BRIEF–A indices, statistically significant improvements were found postintervention with moderate to large effect sizes (BRI, d = 0.59; MI, d = 1.02). Statistically significant improvements also were found in both the AL and SB domains of the SRSI. In addition, very large improvements were found on both COPM rating scales. Overall, 104 goals were set within all of the occupational domains (see Table 4 for results related to goal attainment).

Table 3.

Cog–Fun A Outcomes From Baseline to Posttreatment and Posttreatment to 3-Mo Follow-Up (N = 12)

Measure	M (SD)			T1–T2		T2–T3
Measure	T1	T2	T3	p	d	p	d
AAQoL
Total average	49.58 (14.17)	64.90 (10.18)	61.15 (12.44)	.002	1.24	.104	0.33
LP	39.67 (16.17)	61.16 (10.77)	53.36 (15.99)	.000	1.56	.038	0.57
LO	58.78 (17.21)	70.09 (14.13)	66.75 (16.07)	.005	0.72	.210	0.22
PH	58.33 (17.76)	64.92 (12.24)	65.78 (13.16)	.293	0.43	.658	0.07
Relationships	47.08 (16.30)	65.00 (12.61)	62.50 (16.20)	.007	1.23	.466	0.17
BRIEF–A
MI	77.17 (9.04)	67.17 (10.47)	—	.007	1.02	—	—
BRI	70.58 (9.39)	65.75 (6.76)	—	.069	0.59	—	—
GEC	76.25 (7.59)	66.58 (10.64)	—	.007	1.05	—	—
SRSI
AL	2.21 (1.97)	0.71 (0.75)	—	.007	1.00	—	—
SB	5.72 (2.20)	0.92 (1.25)	—	.000	2.68	—	—
COPM
PL	2.54 (0.87)	7.12 (1.00)	—	.000	4.86	—	—
SL	2.38 (0.90)	7.61 (1.23)	—	.000	4.85	—	—

Note. Dash indicates not administered at follow-up; AAQoL = Adult ADHD Quality of Life scale; AL = Awareness Level; BRI = Behavioral Regulation Index; BRIEF–A = Behavior Rating Inventory of Executive Function–Adult Version; Cog–Fun A = Cognitive–Functional Intervention for Adults; COPM = Canadian Occupational Performance Measure; GEC = Global Executive Composite; LO = Life Outlook; LP = Life Productivity; MI = Metacognitive Index; PH = Psychological Health; PL = Performance Level; SB = Strategy Behavior; SL = Satisfaction Level; SRSI = Self-Regulation Skills Interview; T1 = Time 1 (baseline); T2 = Time 2 (posttreatment); T3 = Time 3 (3-mo follow-up).

Table 4.

Number of Occupational Goals and Examples of Goals and Strategies in Each Functional Domain

Domains	Goals, n (% of Total Goals)	Examples of Goals and Strategies
Self-care	28 (27)	• Go to sleep on time by looking at my reminder above my desk • Take the right medication by stopping and calculating how many hours I need coverage for today
IADLs	25 (24)	• Execute “boring” tasks around the house by connecting to what’s really important to me
Studies or work	18 (17)	• Adapt my physical environment by communicating my needs to others • Take breaks at work to eat and drink by using phone reminders
Leisure	4 (4)	• Follow through with leisure tasks by committing to meet a friend at a certain time and place
Social participation	29 (28)	• Stop and check with my spouse that I understood their intention before responding • Remember to ask my wife about her day using preset cellphone reminders

Note. N = 104 goals. IADLs = instrumental activities of daily living.

Discussion

In this study we measured the Cog–Fun A’s preliminary effectiveness as an occupation-centered treatment to improve self-management of adults with ADHD. The results showed a low attrition rate and statistically significant, moderate to large improvements in EF, SA, OP, and QoL. Treatment gains in QoL modestly decreased at the 3-mo follow-up. These findings provide a sound rationale for further controlled examination of the Cog–Fun A’s effectiveness in helping adults with ADHD.

Participants’ baseline scores on the AAQoL and BRIEF–A reflect levels of QoL and EF consistent with those of other samples of adults with ADHD and demonstrate the marked negative implications of ADHD for these constructs (Rotenberg-Shpigelman et al., 2008; Stern & Maeir, 2014). On the BRIEF–A, the MI index change scores were sizably larger than the BRI change scores, which may be attributed to the more severe baseline impairment in MI than in BRI that is typical in adults with ADHD (Biederman et al., 2011; Miranda et al., 2017; Stern & Maeir, 2014). Thus, the overall positive change in the Global Executive Composite may indicate the participants’ experience of successful implementation of strategies in daily activities requiring cognitive, behavioral, and emotional self-regulation.

In regard to awareness, baseline SRSI SB scores showed comparably more impairment than the AL scores, possibly indicating that adults with ADHD have more difficulties in awareness of coping strategies than in awareness of deficits (Fuermaier et al., 2014; Salomone et al., 2020). The SB change scores were sizably larger than the AL changes. Similar to the intervention outcomes for people with acquired brain injury described by Miyahara et al. (2018), the larger SB change scores in the current study may have been facilitated by the Cog–Fun A’s concentrated focus on awareness of personal strengths and strategic coping rather than awareness of deficits. It is important to note that although two raters scored the SRSI upon intervention completion to improve its reliability, the scores remain subject to bias because complete blinding was not attainable given the nature of the interview. Further studies are needed to examine the reliability of changes in awareness and strategy use as well as to determine the relationship of each parameter to OP and QoL.

Occupational goals were set in all domains of functioning, possibly reflecting the pervasive impact of adult ADHD on OP. Of note is that many goals were set in the self-care domain. Change scores on both COPM subscales revealed statistically significant improvements. Although the positive outcomes found on the AAQoL and COPM highlight the potential contribution of the Cog–Fun A to improve OP and QoL in adults with ADHD, the decrease in AAQoL treatment gains at 3-mo follow-up likely reflects the consensus regarding ADHD as a chronic health condition that requires long-term support and management (Faraone et al., 2015). Future studies should examine the effectiveness of the Cog–Fun A when applied within a broader, longer term treatment framework.

Limitations

This study provides preliminary evidence regarding the feasibility and effectiveness of the Cog–Fun A in a clinical research setting and cannot speak to the extent to which findings would generalize to clinical, community-based practice settings. Overall, the positive outcomes upon intervention completion cannot be attributed to changes in treatment status because we did not control for this. However, because of the open-label nature of the study, a participant-expectancy effect needs to be accounted for. Moreover, the sample was not large enough to examine interactions with medication status and personal factors such as age and gender.

Recommendations for Future Studies

Controlled studies are required so that the specific effectiveness of the Cog–Fun A compared with other treatment methods for adults with ADHD can be determined. The use of both performance-based objective measures and informant-report measures of EF would add to the validity of the evidence-level findings. The mode of delivery (e.g., individual or group setting, face to face or virtual) could also be examined as a potential mediating factor on the effectiveness of the Cog–Fun A for adults with ADHD. Finally, future studies should consider how best to maintain treatment gains over time for people with ADHD.

Implications for Occupational Therapy Practice

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

Adults with ADHD demonstrate pervasive difficulties in occupational domains and lower QoL; the Cog–Fun A can be useful in addressing and ameliorating these difficulties.

Adults with ADHD attained improved OP and QoL after receiving the Cog–Fun A, an occupation-based, metacognitive–functional intervention. Treatment gains in QoL may decrease after a period without intervention, indicating a probable need for longer term treatment and follow-up.

Conclusion

The findings presented here lend preliminary support to the effectiveness of the Cog–Fun A, an intervention based on a metacognitive–functional treatment model for adults with ADHD. The results contribute to the body of knowledge regarding occupational therapy interventions for adults with ADHD and provide evidence supporting the provision of treatment to improve the OP and QoL of this population.

Footnotes

Acknowledgments

We express gratitude to the participants in the Cog–Fun A intervention study. This study was registered at ClinicalTrials.gov (NCT02681575).

References

Adler

L. A.

Kessler

R. C.

, & Spencer

(2003). Adult ADHD Self-Report (ASRS-v1. 1) symptom checklist. https://add.org/wp-content/uploads/2015/03/adhd-questionnaire-ASRS111.pdf

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596

Asherson

Buitelaar

Faraone

S. V.

, & Rohde

L. A.

(2016). Adult attention-deficit hyperactivity disorder: Key conceptual issues. Lancet Psychiatry , 3 , 568–578. https://doi.org/10.1016/S2215-0366(16)30032-3

Barkley

R. A.

(2015). Executive functioning and self-regulation viewed as an extended phenotype: Implications of the theory for ADHD and its treatment. In Barkley

R. A.

(Ed.), Attention-deficit hyperactivity disorder: A handbook for diagnosis and treatment (4th ed., pp. 405–434). Guilford Press.

Biederman

Mick

Fried

Wilner

Spencer

T. J.

, & Faraone

S. V.

(2011). Are stimulants effective in the treatment of executive function deficits? Results from a randomized double blind study of OROS-methylphenidate in adults with ADHD. European Neuropsychopharmacology , 21 , 508–515. https://doi.org/10.1016/j.euroneuro.2010.11.005

Brod

Adler

L. A.

Lipsius

Tanaka

Heinloth

A. N.

, & Upadhyaya

(2015). Validation of the Adult Attention-Deficit/Hyperactivity Disorder Quality-of-Life Scale in European patients: Comparison with patients from the USA. ADHD Attention Deficit and Hyperactivity Disorders , 7 , 141–150. https://doi.org/10.1007/s12402-014-0160-z

Brod

Perwien

Adler

Spencer

, & Johnston

(2005). Conceptualization and assessment of quality of life for adults with attention-deficit/hyperactivity disorder. Primary Psychiatry , 12 , 58–64.

Carswell

McColl

M. A.

Baptiste

Law

Polatajko

, & Pollock

(2004). The Canadian Occupational Performance Measure: A research and clinical literature review. Canadian Journal of Occupational Therapy , 71 , 210–222. https://doi.org/10.1177/000841740407100406

Chen

C. Y.

Yen

J. Y.

Yen

C. F.

Chen

C. S.

Liu

G. C.

Liang

C. Y.

, & Ko

C. H.

(2015). Aberrant brain activation of error processing among adults with attention deficit and hyperactivity disorder. Kaohsiung Journal of Medical Sciences , 31 , 179–187. https://doi.org/10.1016/j.kjms.2015.01.001

10.

Cortese

Kelly

Chabernaud

Proal

Di Martino

Milham

M. P.

, & Castellanos

F. X.

(2012). Toward systems neuroscience of ADHD: A meta-analysis of 55 fMRI studies. American Journal of Psychiatry , 169 , 1038–1055. https://doi.org/10.1176/appi.ajp.2012.11101521

11.

Dalrymple

R. A.

Maxwell

L. M.

Russell

, & Duthie

(2019). NICE guideline review: Attention deficit hyperactivity disorder: Diagnosis and management (NG87). Archives of Disease in Childhood—Education and Practice , 105 , 289–293. https://doi.org/10.1136/archdischild-2019-316928

12.

Dawson

D. R.

Gaya

Hunt

Levine

Lemsky

, & Polatajko

H. J.

(2009). Using the Cognitive Orientation to Occupational Performance (CO-OP) with adults with executive dysfunction following traumatic brain injury. Canadian Journal of Occupational Therapy , 76 , 115–127. https://doi.org/10.1177/000841740907600209

13.

Derogatis

L. R.

, & Melisaratos

(1983). The Brief Symptom Inventory: An introductory report. Psychological Medicine , 13 , 595–605. https://doi.org/10.1017/S0033291700048017

14.

Faraone

S. V.

Asherson

Banaschewski

Biederman

Buitelaar

J. K.

Ramos-Quiroga

J. A.

, . . . Franke

(2015). Attention-deficit/hyperactivity disorder. Nature Reviews Disease Primers , 1 , 15020. https://doi.org/10.1038/nrdp.2015.20

15.

Fayyad

Sampson

N. A.

Hwang

Adamowski

Aguilar-Gaxiola

Al-Hamzawi

, . . . Kessler

R. C.

; WHO World Mental Health Survey Collaborators. (2017). The descriptive epidemiology of DSM–IV adult ADHD in the World Health Organization World Mental Health Surveys. Attention Deficit and Hyperactivity Disorders , 9 , 47–65. https://doi.org/10.1007/s12402-016-0208-3

16.

Ford

(2020). Transitional care for young adults with ADHD: Transforming potential upheaval into smooth progression. Epidemiology and Psychiatric Sciences , 29 , e87. https://doi.org/10.1017/S2045796019000817

17.

Fuermaier

A. B.

Tucha

Koerts

Aschenbrenner

Weisbrod

Lange

K. W.

, & Tucha

(2014). Cognitive complaints of adults with attention deficit hyperactivity disorder. Clinical Neuropsychologist , 28 , 1104–1122. https://doi.org/10.1080/13854046.2014.964325

18.

Gallagher

, & Feder

M. A.

(2018). Adult ADHD: Psychosocial treatment components and efficacy status. Psychiatric Annals , 48 , 333–337. https://doi.org/10.3928/00485713-20180606-02

19.

Hahn-Markowitz

Berger

Manor

, & Maeir

(2017). Impact of the Cognitive–Functional (Cog–Fun) intervention on executive functions and participation among children with attention deficit hyperactivity disorder: A randomized controlled trial. American Journal of Occupational Therapy , 71 , 7105220010. https://doi.org/10.5014/ajot.2017.022053

20.

Hourzad

Pouladi

Ostovar

, & Ravanipour

(2018). The effects of an empowering self-management model on self-efficacy and sense of coherence among retired elderly with chronic diseases: A randomized controlled trial. Clinical Interventions in Aging , 13 , 2215–2224. https://doi.org/10.2147/CIA.S183276

21.

Law

Baptiste

Carswell

McColl

Polatajko

, & Pollock

(2019). Canadian Occupational Performance Measure (5th ed., rev.). COPM, Inc.

22.

Levanon-Erez

Kampf-Sherf

, & Maeir

(2019). Occupational therapy metacognitive intervention for adolescents with ADHD: Teen Cognitive–Functional (Cog–Fun) feasibility study. British Journal of Occupational Therapy , 82 , 618–629. https://doi.org/10.1177/0308022619860978

23.

Levanon-Erez

, & Maeir

(2014). The Teen Cog–Fun model of intervention for adolescents with ADHD. In Berger

& Maeir

(Eds.), ADHD—A transparent impairment, clinical, daily-life and research aspects in diverse populations (pp. 17–33). Nova Science.

24.

Maeir

Traub Bar-Ilan

Kastner

Fisher

Levanon-Erez

, & Hahn-Markowitz

(2018). An integrative Cognitive Functional (Cog–Fun) intervention model for children, adolescents, and adults with ADHD. In Katz

& Toglia

(Eds.), Cognition, occupation, and participation across the lifespan: Neuroscience, neurorehabilitation, and models of intervention (4th ed., pp. 335–351). AOTA Press.

25.

Manor

Vurembrandt

Rozen

Gevah

Weizman

, & Zalsman

(2012). Low self-awareness of ADHD in adults using a self-report screening questionnaire. European Psychiatry , 27 , 314–320. https://doi.org/10.1016/j.eurpsy.2010.08.013

26.

Matza

L. S.

Van Brunt

D. L.

Cates

, & Murray

L. T.

(2011). Test–retest reliability of two patient-report measures for use in adults with ADHD. Journal of Attention Disorders , 15 , 557–563. https://doi.org/10.1177/1087054710372488

27.

Miranda

Mercader

Fernández

M. I.

, & Colomer

(2017). Reading performance of young adults with ADHD diagnosed in childhood: Relations with executive functioning. Journal of Attention Disorders , 21 , 294–304. https://doi.org/10.1177/1087054713507977

28.

Miyahara

Shimizu

Yamane

, & Hanaoka

(2018). Occupation-based intervention to improve self-awareness in persons with acquired brain injury: A single-case experimental design. Asian Journal of Occupational Therapy , 14 , 33–41. https://doi.org/10.11596/asiajot.14.33

29.

Munro

B. A.

Weyandt

L. L.

Hall

L. E.

Oster

D. R.

Gudmundsdottir

B. G.

, & Kuhar

B. G.

(2018). Physiological substrates of executive functioning: A systematic review of the literature. Attention Deficit and Hyperactivity Disorders , 10 , 1–20. https://doi.org/10.1007/s12402-017-0226-9

30.

Ownsworth

T. L.

McFarland

K. M.

, & Young

R. M.

(2000). Development and standardization of the Self-Regulation Skills Interview (SRSI): A new clinical assessment tool for acquired brain injury. Clinical Neuropsychologist , 14 , 76–92. https://doi.org/10.1076/1385-4046(200002)14:1;1-8;FT076

31.

Ramsay

J. R.

(2017). The relevance of cognitive distortions in the psychosocial treatment of adult ADHD. Professional Psychology: Research and Practice , 48 , 62–69. https://doi.org/10.1037/pro0000101

32.

Rotenberg-Shpigelman

Rapaport

Stern

, & Hartman-Maeir

(2008). Content validity and internal consistency reliability of the Behavior Rating Inventory of Executive Function–Adult Version (BRIEF–A) in Israeli adults with attention deficit/hyperactivity disorder. Israeli Journal of Occupational Therapy , 17 , 77–96.

33.

Roth

R. M.

Isquith

P. K.

, & Gioia

G. A.

(2005). Behavior Rating Inventory of Executive Function–Adult Version. Psychological Assessment Resources.

34.

Salomone

Fleming

G. R.

Bramham

O’Connell

R. G.

, & Robertson

I. H.

(2020). Neuropsychological deficits in adult ADHD: Evidence for differential attentional impairments, deficient executive functions, and high self-reported functional impairments. Journal of Attention Disorders, 24 , 1413–1424. https://doi.org/10.1177/1087054715623045

35.

Sibley

M. H.

Pelham

W. E.

Molina

B. S. G.

Gnagy

E. M.

Waxmonsky

J. G.

Waschbusch

D. A.

, . . . Kuriyan

A. B.

(2012). When diagnosing ADHD in young adults emphasize informant reports, DSM items, and impairment. Journal of Consulting and Clinical Psychology , 80 , 1052–1061. https://doi.org/10.1037/a0029098

36.

Stern

, & Maeir

(2014). Validating the measurement of executive functions in an occupational context for adults with attention deficit hyperactivity disorder. American Journal of Occupational Therapy , 68 , 719–728. https://doi.org/10.5014/ajot.2014.012419

37.

Tanaka

Brod

Lane

J. R.

, & Upadhyaya

(2015). What is a clinically relevant improvement in quality of life in adults with ADHD? Journal of Attention Disorders , 23 , 65–75. https://doi.org/10.1177/1087054715580395

38.

Toglia

Goverover

Johnston

M. V.

, & Dain

(2011). Application of the Multicontextual Approach in promoting learning and transfer of strategy use in an individual with TBI and executive dysfunction. OTJR: Occupation, Participation and Health , 31 , S53–S60. https://doi.org/10.3928/15394492-20101108-09

39.

Toglia

, & Kirk

(2000). Understanding awareness deficits following brain injury. NeuroRehabilitation , 15 , 57–70. https://doi.org/10.3233/NRE-2000-15104

40.

Torrente

López

Alvarez Prado

Kichic

Cetkovich-Bakmas

Lischinsky

, & Manes

(2014). Dysfunctional cognitions and their emotional, behavioral, and functional correlates in adults with attention deficit hyperactivity disorder (ADHD): Is the cognitive–behavioral model valid? Journal of Attention Disorders , 18 , 412–424. https://doi.org/10.1177/1087054712443153

41.

Turgay

Goodman

D. W.

Asherson

Lasser

R. A.

Babcock

T. F.

Pucci

M. L.

, & Barkley

; ADHD Transition Phase Model Working Group. (2012). Lifespan persistence of ADHD: The Life Transition Model and its application. Journal of Clinical Psychiatry , 73 , 192–201. https://doi.org/10.4088/JCP.10m06628