Depression and anxiety are common mental disorders [1,2], with estimated 1-year global prevalence rates ranging from 5% to 7% for major depressive disorder and 5% to 10% for anxiety disorders [3-5]. Despite the high level of burden associated with these disorders, many people do not seek professional help [6,7]. The provision of evidence-based digital mental health interventions (DMHIs) such as cognitive behavioral therapy (CBT) is proposed as a strategy to address this unmet need. Relative to in-person interventions, DMHIs can improve the reach and accessibility of care, are often available for free or at a lower cost, and may overcome several attitudinal barriers (eg, concerns about stigma and a preference for self-management) [8,9]. These programs also offer scalable solutions when traditional mental health services are displaced or demand for support increases, such as during public health crises [10]. Digital CBT programs deliver cognitive and behavioral skills and information via websites, smartphone apps, virtual reality, video games, or conversational agents [11]. There is considerable evidence showing that guided and unguided digital CBT can be effective in preventing and treating symptoms of depression and anxiety in adults [12-14] and young people [15,16].

Despite the promise of DMHIs, limited or low engagement with these programs is common. A systematic review of self-guided interventions for depression (most of which were based on CBT) found that >80% of research trial participants failed to complete all intervention modules, and only approximately 40% completed half of all modules [17]. Engagement with these programs in community settings is often much lower [18,19] as research trials typically recruit motivated participants, include human contact, and use explicit assessment procedures. Developing a better understanding of program engagement represents an important goal for research on DMHIs as there is meta-analytic evidence indicating that greater engagement is associated with better postintervention mental health outcomes [20,21]. However, notably, there is also limited evidence regarding what level of engagement, or dosage, is sufficient to achieve the intended outcomes [22], and some studies have demonstrated that outcomes are not always linearly related to engagement [23]. Nevertheless, research aimed at identifying the characteristics of individuals and interventions that influence engagement may enable the targeted development of strategies to facilitate engagement.

However, challenges remain regarding how to define and measure engagement with DMHIs [22]. Beintner et al [24] found that a range of indicators can be used to quantify engagement or adherence, the most common of which include indicators of module progression (eg, the percentage of participants completing a full intervention or completion of a minimum number of modules), log-ins, and time spent using the program. These metrics capture the extent to which individuals are exposed to intervention materials or progress through an intervention but may not elucidate engagement with other relevant behaviors that may also be important for mental health outcomes (eg, enactment of skills or accessing crisis support) [25]. Accordingly, there is current evidence suggesting that, although improvements in mental health outcomes are modestly associated with the number of modules accessed, they may not be associated with other use indicators [21,22]. The limitations of existing program use measures are further reinforced by observations that some individuals do not need to complete a full intervention to achieve symptom benefits (ie, e-attainers or early completers) [26,27].

Recognizing the need to improve how engagement with DMHIs is measured and reported, recent recommendations have proposed the use of multiple approaches [24,25,28], with a particular focus on measures that may be more indicative of effective engagement (ie, engagement necessary to produce outcomes) [29]. Evaluating whether individuals implement the strategies and techniques they have learned from a DMHI in their daily lives (hereafter referred to as skill enactment) may be especially important [30]. For example, Donkin et al [31] recommended using measures to assess the real-world implementation of skills taught during web-based interventions and suggested that this may be central to understanding the impact of engagement on mental health outcomes. Similar recommendations were provided in at least 3 subsequent reviews [24,25,28].

The importance of skill enactment for positive outcomes has also been instantiated in several frameworks of engagement with face-to-face and digital health interventions [32-34], which broadly correspond to some cognitive behavioral theories of the mechanisms of action in CBT [35,36]. These frameworks generally characterize enacting skills as an important causal mechanism by which interventions produce outcomes and, in particular, that program use (or attendance at in-person sessions) results in improvements in relevant health or mental health outcomes when an individual implements the strategies taught in a program effectively [32-34]. The literature on CBT skill use and emotion regulation extends this idea, suggesting that improvements in outcomes may occur through improvement in one of several skill enactment domains, including the frequency (ie, how often a person uses skills, regardless of the skill type), quantity (ie, the range of strategies used), or quality (ie, how well a person enacts skills in line with how they were taught) of skill enactment [35,37]. A further distinction is made between formal skill enactment (eg, completing a thought record) and informal skill enactment (eg, briefly reviewing the evidence against a negative automatic thought) [35]. However, questions remain regarding how program participation can produce changes in skill enactment and what factors might affect this process.

A factor that has been suggested to be important for both skill enactment and mental health outcomes is the acquisition of knowledge about mental health and awareness of strategies to address symptoms (hereafter referred to as knowledge acquisition) [33,38]. In comprehensive CBT interventions for depression and anxiety, psychoeducational components in the form of text, video, or audio tutorials are usually introduced early in the intervention process to improve knowledge and understanding of the signs and symptoms of depressive or anxiety disorders. Psychoeducation may help improve an individual’s ability to recognize and appropriately manage symptoms of depression or anxiety and has been shown to result in small improvements in symptoms even in the absence of other strategies [39]. In addition, information and instructions on the rationale for CBT and strategies for actively managing symptoms (eg, cognitive restructuring and behavioral activation) are provided throughout an intervention. If an individual does not acquire or understand the information related to these strategies, effective implementation and, thus, improvement in mental health outcomes are unlikely [38,40].

Although there is robust evidence for the effectiveness of digital CBT and the logical and theoretical importance of knowledge acquisition and skill enactment in achieving these outcomes, little is known about whether users acquire knowledge or enact skills from these interventions. Consequently, it is unclear whether skill enactment and knowledge acquisition are important for mental health outcomes or which factors influence skill enactment and knowledge acquisition. Although several reviews have investigated the predictors and outcomes of engagement or adherence [17,21,22,41,42], these studies have focused predominantly on indicators of program use (eg, module completion). Some reviews have also been conducted to evaluate the effectiveness of digital interventions in improving mental health literacy and its impact on mental health–related outcomes [43-45]. However, these previous reviews have not examined specialized knowledge acquired during participation in digital CBT interventions. Moreover, it is also important to examine how skill enactment and knowledge acquisition have been measured and reported in the literature to examine the extent to which measurement approaches align with theoretical conceptualizations of these concepts and to identify recommendations for future research on engagement with DMHIs.

This systematic review builds on previous reviews by investigating skill enactment as a component of engagement with digital CBT interventions for depression and anxiety. Although we focused on skill enactment, the review adhered to a broader definition of engagement that includes initial uptake, ongoing use of a program, and enactment of skills in everyday life [33]. Given that knowledge acquisition is proposed to be essential for the enactment of skills and may itself be an important determinant of outcomes, we also reported data on knowledge acquisition as a secondary objective. Our specific review questions were as follows: (1) What methods have been used to measure skill enactment and knowledge acquisition in randomized controlled trials (RCTs) of digital CBT interventions for depression and anxiety? (2) Are digital CBT programs effective in improving skill enactment and knowledge acquisition? (3) Is there an association between mental health outcomes and skill enactment or knowledge acquisition? and (4) What predictors of skill enactment and knowledge acquisition have been identified?

This review was reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [46] (refer to Multimedia Appendix 1 [46] for a PRISMA checklist) and was prospectively registered in PROSPERO (registration CRD42021275270). The review team originally intended to investigate skill enactment and knowledge acquisition in technology-based skills training interventions for depression and anxiety from any therapeutic orientation. However, we subsequently limited the scope of the review to digital CBT programs to facilitate comparisons across studies and because of the established evidence base for CBT in the treatment of depression and anxiety [16,47]. We added a criterion to exclude studies targeting people with physical illnesses given the potential for these programs to target specific types of knowledge and skills associated with the target condition. These decisions were made before the completion of screening and were added to the registered protocol as an amendment on March 24, 2022. No other substantive changes were made to the original protocol.

We searched the Cochrane CENTRAL, PubMed, and PsycINFO databases for peer-reviewed articles published between January 1, 2000, and July 26, 2022. The start date was selected to coincide with the publication of RCTs related to the first digital interventions for depression and anxiety [48,49]. The search strategy used combinations of relevant Medical Subject Heading terms and keywords for “technology-based intervention,” “randomized controlled trial,” and “depression” or “anxiety.” The full search strategy for each database is provided in Multimedia Appendix 2. Searches were rerun before final analyses. In addition, we supplemented the electronic search with forward citation searching of published self-report measures of CBT skill use to identify studies that may have been missed in the text-based searches. Citation searching is an effective way to retrieve studies when central concepts are difficult to capture using keyword searches [50]. Forward searching was carried out in Scopus on July 26, 2022, and included the following skill use measures: the Behavioral Activation for Depression Scale [51] and its short form [52], Cognitive Behavioral Therapy Skills Questionnaire [53], Skills of Cognitive Therapy [54], Competencies of Cognitive Therapy Scale [55], Frequency of Actions and Thoughts Scale [56], and Ways of Responding Scale [57].

Inclusion and exclusion criteria were developed using the participants, intervention, comparator, outcome, and study design framework [58]. Only peer-reviewed articles published in English between 2000 and 2022 were included in this review.

The search results were uploaded to EndNote (version 20; Clarivate Analytics), and duplicate records were removed automatically and through hand searching. Study selection was completed in 3 stages. At stage 1, titles and abstracts were screened by 1 of 2 reviewers (HJ or AT) and discussed with the last author (LF) to exclude irrelevant records. A third reviewer (GF) screened 10% of the abstracts to confirm that the review criteria had been applied consistently (percentage of agreement=99.6%; Cohen κ=0.97). At stage 2, full-text articles were uploaded to the Covidence systematic review software (Veritas Health Innovation) and coded by the first author (HJ) according to whether the studies (1) evaluated a CBT-based program and (2) reported a measure of skill enactment or knowledge acquisition (“yes,” “no,” or “unclear”). Relevant construct definitions and inclusion criteria were piloted with 50 full-text articles and refined through discussion within the review team before completion of this stage. A second reviewer screened 10% of the full-text articles to check for coder bias at stage 2, which did not result in the inclusion of any additional manuscripts (percentage of agreement=98.4%; Cohen κ=0.90). At stage 3, all articles coded as “yes” or “unclear” were referred to a third stage for double screening by 2 reviewers (HJ and GF) against all inclusion criteria. Discrepancies were resolved through discussion, and a third author (LF) was consulted if an agreement could not be reached.

A data extraction form was developed in Microsoft Excel (Microsoft Corp) and pilot-tested on 5 papers. Data extraction was completed by the first author (HJ), and accuracy was confirmed by a second author (GF). The key data elements extracted included skill enactment and knowledge acquisition data to address the objectives of the review (described in the Strategy for Data Synthesis section). In addition, we extracted the following descriptive data: country where the study was conducted, study design and type of comparison, participant characteristics and recruitment setting, intervention details and the type of technology, the length of the treatment period and intervention structure, the presence of guidance, and adherence or use data. We only extracted information for eligible interventions, and data for all eligible interventions were extracted if more than one eligible intervention was evaluated in the study. We accessed and cited primary reports or protocol papers to retrieve information if relevant data were not available in the paper under review.

The presence of guidance was categorized as guided (support related to treatment content was provided), unguided (no support related to treatment content provided), or supported (support was provided by educational staff for interventions delivered in educational settings, but this support was not related to treatment content). We included a supported category as interventions delivered in school settings involve a captive audience. Studies were also categorized according to the age group of the sample. Age classifications were established based on the mean age of the trial sample and included adolescents (aged 12-17 years), young adults (aged 18-24 years), and adults (aged ≥25 years). These classifications are consistent with the age categorizations used by the Australian Institute of Health and Welfare [62] and the legal age in Australia.

The methodological quality of the included studies was independently assessed by 2 reviewers (HJ and LF) using the Joanna Briggs Institute Critical Appraisal Checklist for RCTs [63]. The checklist includes 13 items to evaluate randomization procedures, allocation concealment, selection bias, blinding, postassignment attrition, outcome measurement, and appropriateness of the statistical analyses and trial design. Items were scored as “Yes,” “No,” “Unclear,” or “Not applicable” according to the guidelines provided by Tufanaru et al [63]. For secondary reports, we referred to primary outcome papers to obtain ratings where necessary. Disagreements between reviewers were resolved through discussion until a consensus was reached. A score of 1 was awarded for each item adequately addressed in the paper, with possible scores ranging from 0 to 13.

The studies were not pooled for meta-analysis because of methodological diversity related to the measurement tools used to evaluate skill enactment and knowledge acquisition, as well as the use of different statistical approaches to determine the associations among skill enactment, knowledge acquisition, and mental health outcomes. Instead, descriptive narrative synthesis was conducted to address the review questions per our PROSPERO registration (CRD42021275270). All eligible measures of skill enactment and knowledge acquisition were recorded and tabulated, with tables ordered by symptoms or disorder targeted. In addition, we recorded any data on change in skill enactment or knowledge acquisition outcomes at postintervention measurement or follow-up (eg, between- or within-group comparisons or assessments of self-reported skill practice or learning), any analysis of the association between skill enactment or knowledge acquisition and primary or secondary mental health outcomes (eg, via correlation, regression, or mediation analyses), and any investigation of potential predictors of skill enactment or knowledge acquisition (eg, via regression or between-group analyses).

Definitions provided in the literature on CBT skill use [35], knowledge [64,65], and DMHI engagement [24] and information provided by the study authors were used to classify and summarize methods of measuring skill enactment and knowledge acquisition (review question 1). These classifications were used to group studies to address the subsequent review questions. Descriptive information regarding whether the study reported a significant between- or within-group effect for skill enactment or knowledge acquisition at postintervention measurement was reported to examine the effectiveness of digital CBT programs in improving skill enactment and knowledge acquisition (review question 2). Between-group analyses comparing intervention and control conditions within studies were prioritized in reporting as they provide greater certainty regarding the relationship between intervention exposure and subsequent skill enactment or knowledge change. Where possible, effect sizes using the pretest n value were calculated as the mean difference between treatment and control groups at postintervention measurement or follow-up divided by the pooled SD of the baseline scores. All estimates were adjusted using a Hedges g correction [66]. Consistent with Luo et al [67], imputed data values were used if both complete case and imputed values were provided. Negative effect sizes indicated that the comparison group performed better than the treatment group on skill enactment or knowledge acquisition.

Significant and nonsignificant findings were also summarized to examine the association between mental health outcomes and skill enactment or knowledge acquisition (review question 3) and investigate predictors of skill enactment or knowledge acquisition (review question 4). Predictor variables could include participant characteristics (eg, age and sex), disease-specific effects (eg, baseline symptom levels), intervention characteristics (eg, presence of guidance), and components of intervention engagement (eg, module completion). Previous systematic reviews of predictors of adherence or engagement [68] were used to establish broad categories of predictors. For each synthesis, all indicators of skill enactment or knowledge acquisition were summarized if multiple indicators were reported in the study. For studies reporting both intention-to-treat (ITT) and completer analyses, only ITT results were reported. In addition, if studies reported results for subscale scores in addition to total scores on skill enactment or knowledge acquisition measures, we only reported total scores to aid interpretation of the results, although changes in subscales are noted in Multimedia Appendix 3 [36,61,64,69-114]. Relevant results for follow-up time points are also summarized in Multimedia Appendix 3.

A total of 27,822 records were retrieved from the database and forward citation searches. After removing duplicates, 20,281 titles and abstracts were screened. Full texts were retrieved for 781 articles, and 43 (5.5%) papers [36,61,64,69-108] were included in the review (Figure 1). A study that appeared to meet the inclusion criteria was excluded as the trial was designed to test individual treatment components rather than an entire program of treatment, resulting in a 32-condition design [115]. On 2 occasions, more than one paper was published from a single trial, and both provided data on our outcomes of interest [89,90,101,102]. These manuscripts are reported together to describe study characteristics. In addition, one of these papers included 2 distinct trials [101]. These trials are reported separately. Therefore, 42 independent studies (reported in 43 papers) were included in the review.

Study characteristics and outcomes of the review are reported in Multimedia Appendix 3. The studies were conducted in Europe (16/42, 38%), Australia (13/42, 31%), the United States (10/42, 24%), and Asia (3/42, 7%). Most studies (38/42, 90%) were parallel RCTs, although 5% (2/42) were cluster RCTs, 2% (1/42) were factorial design studies, and 2% (1/42) were described as intervention studies. Control groups were classified as waitlist (14/42, 33%), usual care (5/42, 12%), attention control (4/42, 10%), or enhanced usual care (2/42, 5%). In 21% (9/42) of the studies, participants were assigned to a waitlist control group but also received access to usual care, attention control materials, enhanced usual care, or a web-based discussion group. A total of 19% (8/42) of the studies compared ≥2 active treatments only.

A total of 10,078 participants were included in the 42 studies (ie, the number analyzed). Among the 41 studies that reported the number of participants by group assignment, 5881 participants received a stand-alone digital CBT intervention. The sample sizes ranged from 43 to 1236 (mean 239.95, SD 278.91; median 149.50). Most studies (30/42, 71%) recruited participants from the community, although 14% (6/42) recruited from educational settings, 10% (4/42) recruited from health care settings, and 5% (2/42) recruited from occupational settings. Studies (36/42, 86%) were typically conducted with adults, although 10% (4/42) included adolescents, and 5% (2/42) included young adults. Among the 31 studies where the mean age of the total sample was reported, the mean participant age ranged from 15.00 to 51.60 years (mean 31.90, SD 8.21 years). The proportion of female participants in the study samples ranged from 16.1% to 100% (median 76.59%), and 17% (7/42) of the studies included only female or pregnant participants, all of which focused on maternal or perinatal mental health.

The number of studies that satisfied each of the quality items is shown in Table 1, and full information is provided in Multimedia Appendix 4 [36,61,64,69-108,116]. Overall, the quality of the included studies was good, with most studies (36/42, 86%) meeting ≥8 criteria (mean 8.81, SD 1.31). Most studies described adequate randomization (31/42, 74%) and allocation concealment procedures (33/42, 79%). The treatment groups were typically similar at baseline, or the subsequent analyses clearly accounted for any observed differences. Blinding was the primary issue in the included studies, with no study meeting the blinding of participants or blinding of outcome assessors criteria as all included participant-reported scales. In addition, only approximately one-third (15/42, 36%) of the studies met the blinding of those delivering treatment criterion as they evaluated unguided interventions. All studies (42/42, 100%) treated compared groups identically and measured outcomes in the same way across the groups. Most studies (33/42, 79%) reported incomplete follow-up, although patterns of loss to follow-up were generally adequately described and analyzed, and most studies (35/42, 83%) used ITT analyses. Despite all studies using validated outcome measures, close to half (22/42, 52%) did not provide clear information to determine whether outcomes were measured reliably in the study. Most studies (39/42, 93%) described appropriate statistical procedures, and the trial design was considered appropriate in all studies, with 2/2 (100%) of cluster RCTs using analytical techniques to account for clustering in the analyses.

Of the 43 papers, 28 (65%) reported ≥1 measure of skill enactment [36,74,77-82,84,85,88,90,92-106,108], fourteen (33%) reported ≥1 measure of knowledge acquisition [61,64,69-73,75,83,86,87,89,91,107], and 1 (2%) reported a measure of both skill enactment and knowledge acquisition [76].

Of the 29 studies reporting a measure of skill enactment, 26 (90%) were conducted with adults, 2 (7%) were conducted with adolescents, and 1 (3%) was conducted with young adults. The studies evaluated guided (15/29, 52%), unguided (10/29, 34%), or supported (2/29, 7%) interventions, and 7% (2/29) compared ≥1 guided and unguided intervention.

Of the 15 studies reporting a measure of knowledge acquisition, most (n=11, 73%) were conducted with adults, although 3 (20%) included adolescent samples, and 1 (7%) included a young adult sample. The studies evaluated guided (5/15, 33%), unguided (8/15, 53%), or supported (1/15, 7%) interventions, and 7% (1/15) compared guided and unguided interventions.

This review aimed to systematically examine the literature on skill enactment and knowledge acquisition in the context of digital CBT interventions for symptoms of depression or anxiety. In total, 43 papers (reporting on 42 independent trials) were included, of which 29 (67%) reported a measure of skill enactment and 15 (35%) reported a measure of knowledge acquisition.

This review highlighted several gaps in the current state of knowledge in this area. Overall, there was a lack of research that examined skill enactment and knowledge acquisition in the context of digital CBT. Very few studies (6/42, 14%) reported on skill enactment and knowledge acquisition among adolescents and young adults, and most studies (33/42, 79%) evaluated internet-based interventions accessed via a computer. Similar to other authors [24,25,73], we encourage researchers to measure and report skill enactment and knowledge acquisition in future studies of digital CBT and examine outcomes and predictors related to these constructs.

However, future research must go beyond simply measuring skill enactment and knowledge acquisition to also address measurement issues. A key limitation of the literature identified by this review is the heterogeneity in how knowledge acquisition, and especially skill enactment, was measured and analyzed. Heterogeneity was evident not only in the specific construct examined (eg, skill enactment frequency vs quality and CBT knowledge vs mental health literacy) but also in the mode of assessment and the way in which data were reported and analyzed. This heterogeneity hinders the pooling of data for quantitative synthesis and may be due in part to a lack of specific theoretical guidance or standards available to inform the selection, analysis, and reporting of skill enactment and knowledge acquisition measures in DMHIs. To facilitate consistency going forward, we recommend that definitions of skill enactment and knowledge acquisition in DMHIs and the subsequent selection of measures are theory-driven. For example, the literature on CBT skill use and emotion regulation provides clear conceptual definitions of skill enactment and its distinct components (eg, frequency, quantity, and quality) that can inform the selection of appropriate measures [35,37]. A theory-driven approach will be aided by developing robust and broadly applicable scales to measure skill enactment and knowledge acquisition in DMHIs more consistently and considering how these scales are related to outcomes. In the context of skill enactment, recent work by Titov et al [123] and Bisby et al [124] to develop and test a measure of daily actions associated with psychological health may align well with conceptual definitions of skill enactment frequency. In addition, psychometric research comparing different methods of measuring skill enactment and knowledge acquisition is needed to examine whether each is measuring a unitary construct or whether there are distinct types of skill enactment and knowledge acquisition beyond those highlighted within conceptual frameworks.

In addition, although the overall quality of the included studies was good, some methodological issues were evident, with most or all studies not meeting quality assessment criteria related to blinding of participants (0/42, 0%), outcome assessors (0/42, 0%), or those delivering treatment (15/42, 36%). This is an inherent problem with RCTs of psychological interventions [125]. However, it is possible to implement blinding in these interventions in some cases (eg, by not informing participants of which treatment is expected to be most effective in studies including active treatment or attention control comparisons) [125]. It is also notable that more than half (22/42, 52%) of the studies did not provide sufficient information to determine whether outcomes were measured reliably (eg, reporting the Cronbach α for the collected data) despite many reporting estimates from external sources. Unreliable measurement of outcomes can weaken the validity of inferences made about statistical relationships [63]. It is essential that studies explain in sufficient detail the methods used to allow for accurate assessments of study quality.

This review has some limitations. The inclusion of an English-language restriction and single screening of titles, abstracts, and initial full texts may have increased the risk of selection bias. Although double screening of 10% of the records at each stage did not result in the inclusion of any additional papers, it is possible that some publications were excluded erroneously. It is also possible that some studies were excluded because of insufficient or unclear reporting of the study methods or results. The review was further limited to RCTs of stand-alone digital CBT interventions for depression and anxiety. Thus, our findings cannot be generalized to open-access settings, other mental health problems, stepped-care interventions, or psychotherapeutic treatments other than CBT. Nevertheless, the examination of knowledge acquisition and skill enactment is likely to be important in any skills training intervention, and this review can inform the development of future studies in this area. In addition, we could not conduct a quantitative synthesis of skill enactment and knowledge acquisition because of methodological diversity in the included studies, meaning that we could not estimate the average effect of skill enactment or knowledge acquisition on depression and anxiety outcomes, nor could we examine the factors that modify these effects. Future meta-analytic studies will be essential to understand therapeutic mechanisms in digital CBT and advance future interventions but will require greater methodological consistency.

In digital interventions for mental health problems, it is essential to consider engagement as a concept that extends beyond program use to encompass actions that are implemented outside initial engagement with an intervention. Given that most studies on engagement with DMHIs focus on program use, this review addresses a substantial gap by focusing on skill enactment and knowledge acquisition during or following program use. This review demonstrated that digital CBT interventions for depression and anxiety appear to be effective in improving skill enactment frequency; levels of CBT knowledge; and, to a lesser extent, mental health literacy. However, only skill enactment frequency was found to be associated with positive mental health outcomes. Few studies have investigated predictors of skill enactment and knowledge acquisition, and those that have done so have mostly been limited to investigations of intervention-related factors and reported null results. This review calls for a more systematic and theory-based approach to studying the role of skill enactment and knowledge acquisition in DMHIs for depression and anxiety. The findings of this review can inform the development and selection of skill enactment and knowledge acquisition measures and promote the inclusion of these types of measures in future studies evaluating DMHIs.