Abstract
The Adult Executive Functioning Inventory (ADEXI) offers occupational therapy practitioners serving Hebrew-speaking populations a validated tool for assessing executive functions.
Executive functions (EFs) are higher level cognitive abilities that facilitate goal-directed behavior. These skills are essential in adults’ everyday lives, highlighting the need to identify early strategies to evaluate and rehabilitate these disorders (Borgnis et al., 2022; Ferguson et al., 2021). Three EF components are most acknowledged: (1) inhibition, controlling automatic and impulsive responses, delaying gratification, or resisting distractions; (2) working memory, retaining and manipulating information, and keeping it active during tasks; and (3) cognitive flexibility, adapting to changing demands or priorities, and switching focus as needed (Diamond, 2013; Toglia & Katz, 2018).
One accepted way to assess EFs among adults is through self-report questionnaires reflecting their daily life experiences over time (Scholz & Donders, 2024). The most widely used measures for assessing EFs are the Behavior Rating Inventory of Executive Function–Adult Version (Roth et al., 2005) and the Barkley Deficits in Executive Functioning Scale (BDEFS; Barkley, 2011), with 75 and 89 items, respectively. Moreover, the Dysexecutive Questionnaire (DEX; Wilson et al., 1996) was established as a supplement to the Behavioral Assessment of the Dysexecutive Syndrome (BADS; Wilson et al., 1996). In addition, some questionnaires, such as the Executive Function Index (Spinella, 2005), have been criticized for assessing a broad range of cognitive and emotional functions that do not all pertain to core EF components or for including items that measure attention deficit hyperactivity disorder (ADHD) symptoms.
The Adult Executive Functioning Inventory (ADEXI; Holst & Thorell, 2018) is a short, reliable, valid, and easy-to-complete self-report questionnaire for assessing working memory and inhibitory control. The ADEXI builds on the Childhood Executive Function Inventory (Catale et al., 2015), freely available in multiple languages (https://www.chexi.se/). In this study, we evaluated ADEXI Hebrew version construct validity through exploratory factor analysis (EFA) and convergent validity by correlating scores with a similar measure of EF.
ADEXI, EFA, and convergent validity were evaluated in an Israeli adult sample. We hypothesized to find good internal consistency for the full-scale score and subscales after factor analysis as well as medium to large significant correlations among all four ADEXI scores and the DEX total and subscales scores for convergent validity.
Method
Participants
In this study, we used convenience sampling to recruit 239 participants from various areas in Israel. The inclusion criteria were adults ages 18 to 80 yr who were proficient in reading and understanding Hebrew. Participants who reported severe cognitive or emotional dysfunction were excluded from the analysis.
Procedure
The Ariel University Institutional Ethics Committee approved the study (AU-HEA-YF-20221031), on October 31, 2022, and the study was conducted from November 2022 to June 2023. Potential participants were recruited via local online groups and social media. Participants who met the inclusion criteria and consented completed three anonymous online surveys presented in a fixed sequence: demographic characteristics, ADEXI, and DEX.
We used the simplified Guillemin criteria (Guillemin et al., 1993) to translate the ADEXI under the developer’s guidance. A panel of bilingual (Hebrew–English) speaking experts for translation (Yael Fogel and Yafit Gilboa) and back translation (Sonya Meyer) ensured the preservation of the original item meanings. The Hebrew translation closely mirrored the original ADEXI version.
Measures
Demographic Questionnaire
The demographic questionnaire developed for this study included information about age, gender, family status, years of education, and profession.
ADEXI
The ADEXI (Holst & Thorell, 2018) is a 14‐item questionnaire measuring EF that is divided into two subscales: The Working Memory subscale comprises nine items (Items 1, 2, 5, 7–9, and 11–13), and the Inhibition subscale comprises five items (Items 3, 4, 6, 10, and 14). The respondent rates each item on a 5-point scale ranging from 1 (definitely not true) to 5 (definitely true). The total score is calculated as the average, with a higher score indicating worse EF.
The ADEXI has good psychometric properties. Internal consistency has been reported as .91 for the full scale, .90 for the Working Memory subscale, and .77 for the Inhibition subscale. Discriminant validity was demonstrated by significant differences between adults with ADHD and a control group (Holst & Thorell, 2018). The significant correlation with the BDEFS (Barkley, 2011) supports its concurrent validity (Range, 2023).
DEX
The self-report DEX (Wilson et al., 1996) is used to examine EFs in day-to-day functioning through 20 items on a 5-point Likert scale ranging from 0 (never) to 4 (very often). It is part of the BADS assessment but stands independently. The DEX covers behavioral, cognitive, motivational, and emotional changes from premorbid functioning. As a standalone tool within the BADS, it demonstrates strong psychometric reliability, consistency, and validity (Burgess et al., 1996; Simblett & Bateman, 2011), with an internal consistency of α = .89 in this study.
Data Analysis
We analyzed the data using IBM SPSS Statistics (Version 29). We presented demographic characteristics using descriptive statistics, and we used Cronbach’s α to assess internal consistency. We determined construct validity through EFA using the principal components extraction method. To justify EFA in our sample, the accepted rule of thumb is 10 participants per group, with 14 items needing a minimum of 140 participants (Lloret-Segura et al., 2014). The Kaiser value was used to measure sampling adequacy to determine suitability for EFA, and Bartlett’s test for sphericity, factor loading, and sampling adequacy measure determined item adequacy. Items were considered for analysis if they yielded factor-loading values <.35. Pearson correlations were conducted between the DEX and the ADEXI subscales. The significance level was set at p < .05.
Results
Of the 305 participants who opened the online survey link, 58 partially completed the entire survey (e.g., missing or incomplete responses), and 8 reported severe cognitive or emotional dysfunction. They were subsequently excluded from the analysis. Thus, 239 participants (ages 18–73 yr) were included in the final sample (Table 1).
Participants’ Demographic Characteristics and Descriptive Statistics (N = 239)
Note. ADEXI = Adult Executive Functioning Inventory.
Factorial Validity of ADEXI Scores: Construct Validation
We conducted an EFA using varimax rotation. Kaiser’s measure of sampling confirmed the adequacy of the sample for analysis (with a value of .89), and Bartlett’s test of sphericity was significant, χ2(91) = 1,155.4, p < .001. A three‐factor solution fit the data well because all items were loaded with different factors. The three‐factor solution accounted for 55.71% of the variance. As expected, Items 3, 4, 6, 10, and 14 assembled under the inhibition factor, and Items 1, 2, 5, 8, and 9 assembled under the working memory factor, as in the original English ADEXI version. However, Items 7, 11, 12, and 13 assembled under a new factor theoretically labeled flexibility because those items aligned with the flexibility definition: “the appropriate adjustment of thoughts and behaviors in response to changing environmental demands” (Uddin, 2021, p. 167). The internal consistency scores were α = .86 for the full scale, α = .84 for working memory, α = .65 for inhibition, and α = .74 for the new factor, flexibility. Table 2 presents the item loadings from the rotated component matrix.
Item Factor Loadings for the ADEXI Hebrew Version (N = 239)
Note. ADEXI = Adult Executive Functioning Inventory.
Convergent Validity
As expected, we found medium to large significant correlations (r =.29–.76) between the ADEXI and the DEX scores. The ADEXI full scale and three subscales (Working Memory, Inhibition, Flexibility) were most strongly related to the DEX behavioral (r =.44–.69) and cognition (r =.58–.74) factors, whereas the emotional factor demonstrated low correlation values (r =.28–.38; Table 3).
Correlations Between the ADEXI and the DEX (N = 239)
Note. ADEXI = Adult Executive Functioning Inventory; DEX = Dysexecutive Questionnaire.
*p < .001.
Discussion
This study demonstrates the psychometrics properties of the Hebrew version of the ADEXI on 239 nonclinical Israeli adults. Whereas the original English version proposed two factors (inhibition and working memory; Holst & Thorell, 2018), our EFA supports three—adding flexibility—because some items loaded on multiple factors, indicating overlapping EFs. Cultural differences that underpin executive skills may explain the differences between the English and Hebrew versions (Campbell et al., 2014). Moreover, the Hebrew ADEXI version showed that the three factors captured 55% of the variance, similar to the original ADEXI finding (50.02% of the variance; Holst & Thorell, 2018). Moreover, the internal consistency observed in the full scale and the three new factors in this study (α = .65–.86) is similar to previous ADEXI research. All these results advocate using the ADEXI as an EF measure (Holst & Thorell, 2018; López et al., 2022).
The ADEXI’s positive correlations with the DEX affirm its convergent validity. These findings are consistent with previous studies that reported similar correlation patterns between the ADEXI and other cognitive and EF questionnaires (López et al., 2022), such as the BDEFS (Holst & Thorell, 2018) and DEX when examined in adults with autism spectrum disorders or intellectual disabilities (García-Villamisar et al., 2020). Moreover, the weak correlation between the ADEXI and the emotional dimension of the DEX highlights the distinctions between EF and emotional functioning.
The ADEXI, a concise self-report tool, efficiently evaluates adult EFs, complementing and augmenting clinical observations and setting therapeutic goals (Toplak et al., 2013). Limitations include the absence of a clinical sample, which restricts the breadth of dimensions and patterns identifiable through EFA, and potential bias because of completing the survey in a fixed order. Future studies would benefit from exploring other psychometrics properties, such as discriminant and predictive validity, in different age groups and education levels, comparing scores across cultures and diverse clinical samples.
Implications for Occupational Therapy Practice
The results of this study have the following implications for occupational therapy practice: This study’s findings suggest that the ADEXI Hebrew version could benefit occupational therapy practitioners conducting evaluations for adults with EF deficits that affect their participation. The ADEXI Hebrew version can help gather information on clients’ inhibition, working memory, and flexibility skills. The ADEXI can complement performance-based assessments to obtain a more complete clinical picture.
Conclusion
This study emphasizes the various EF dimensions (inhibition, working memory, and flexibility) that the ADEXI can measure, and it offers evidence supporting the psychometric properties of the translated ADEXI as a valuable tool for assessing Hebrew-speaking adults. However, further validation in diverse clinical settings and populations is needed.
Footnotes
Acknowledgments
We thank Professor Lisa Thorell for permitting us to translate the Adult Executive Functioning Inventory (ADEXI) into Hebrew.
