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Objectives: Measuring implementation outcomes for digital mental health interventions is essential for examining the effective delivery of these interventions. The “Implementation Outcome Scale of Digital Mental Health” (iOSDMH) has been validated and used in several trials. This study aimed to compare the iOSDMH for participants in six randomized controlled trials (RCTs) involving web-based interventions and to discuss the implications of the iOSDMH for improving the interventions. Additionally, this study examined the associations between iOSDMH scores and program completion rate (adherence). Methods: Variations in total scores and subscales of the iOSDMH were compared in six RCTs of digital mental health interventions conducted in Japan. The web-based intervention programs were based on cognitive behavioral therapy (2 programs), behavioral activation (1 program), acceptance and commitment (1 program), a combination of mindfulness, behavioral activation, and physical activity (1 program), and government guidelines for suicide prevention (1 program). Participants were full-time employees (2 programs), perinatal women (2 programs), working mothers with children (1 program), and students (1 program). The total score and subscale scores were tested using analysis of variance for between-group differences. Results: Total score and subscale scores of the iOSDMH among six trials showed a significant group difference, reflecting users’ perceptions of how each program was implemented, including aspects such as acceptability, appropriateness, feasibility, overall satisfaction, and harm. Subscale scores showed positive associations with completion rate, especially in terms of acceptability and satisfaction (R-squared = 0.93 and 0.89, respectively). Conclusions: The iOSDMH may be a useful tool for evaluating participants’ perceptions of features implemented in web-based interventions, which could contribute to improvements and further development of the intervention.

Background Implementation science and health services outcomes research each focus on many constructs that are likely interrelated. Both fields would be informed by increased understanding of these relationships. However, there has been little to no investigation of the relationships between implementation outcomes and service outcomes, despite general acknowledgement that both types of outcomes are important in the pathway to individual and population health outcomes. Given the lack of objective data about the links between implementation and service outcomes, an initial step in elucidating these relationships is to assess perceptions of these relationships among researchers and practitioners in relevant fields. The purpose of this paper is to assess perceived relationships between Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework outcomes and service outcomes, testing five a priori hypotheses about which perceived relationships may be strongest. Methods A cross-sectional online survey was administered to a convenience sample of implementation scientists, health services researchers, and public health and medical practitioners from a variety of settings. Respondents provided information on their discipline, training, practice and research settings, and levels of experience in health service outcomes research, implementation science, and the RE-AIM framework. Next, they rated perceived relationships between RE-AIM and service outcomes. Repeated measures analysis of variance were used to test a priori hypotheses. Exploratory analyses assessed potential differences in mean ratings across groups of respondents categorized by discipline, setting, and levels of implementation science, health services, and RE-AIM experience. Results Surveys were completed by 259 respondents, most of whom were employed in academic and medical settings. The majority were doctoral-level researchers and educators or physicians. Reported levels of experience with implementation research, health services research, and the RE-AIM framework varied. The strongest perceived relationships overall were between Implementation/Fidelity and Effectiveness (as a service outcome); Maintenance and Efficiency; Reach and Equity; Adoption and Equity; Implementation/Adaptation and Patient-Centeredness; Adoption and Patient-Centeredness; and Implementation/Fidelity and Safety. All but one of the a priori hypotheses were supported. No significant differences in ratings of perceived relationships were observed among subgroups of respondents. Conclusions This study is an initial step in developing conceptual understanding of the links between implementation outcomes, health services outcomes, and health outcomes. Our findings on perceived relationships between RE-AIM and services outcomes suggest some areas of focus and identify several areas for future research to advance both implementation science and health services research toward common goals of improving health outcomes.

Background The challenges of implementing evidence-based innovations (EBIs) are widely recognized among practitioners and researchers. Context, broadly defined as everything outside the EBI, includes the dynamic and diverse array of forces working for or against implementation efforts. The Consolidated Framework for Implementation Research (CFIR) is one of the most widely used frameworks to guide assessment of contextual determinants of implementation. The original 2009 article invited critique in recognition for the need for the framework to evolve. As implementation science has matured, gaps in the CFIR have been identified and updates are needed. Our team is developing the CFIR 2.0 based on a literature review and follow-up survey with authors. We propose an Outcomes Addendum to the CFIR to address recommendations from these sources to include outcomes in the framework. Main text We conducted a literature review and surveyed corresponding authors of included articles to identify recommendations for the CFIR. There were recommendations to add both implementation and innovation outcomes from these sources. Based on these recommendations, we make conceptual distinctions between (1) anticipated implementation outcomes and actual implementation outcomes, (2) implementation outcomes and innovation outcomes, and (3) CFIR-based implementation determinants and innovation determinants. Conclusion An Outcomes Addendum to the CFIR is proposed. Our goal is to offer clear conceptual distinctions between types of outcomes for use with the CFIR, and perhaps other determinant implementation frameworks as well. These distinctions can help bring clarity as researchers consider which outcomes are most appropriate to evaluate in their research. We hope that sharing this in advance will generate feedback and debate about the merits of our proposed addendum.

Background Many implementation efforts fail, even with highly developed plans for execution, because contextual factors can be powerful forces working against implementation in the real world. The Consolidated Framework for Implementation Research (CFIR) is one of the most commonly used determinant frameworks to assess these contextual factors; however, it has been over 10 years since publication and there is a need for updates. The purpose of this project was to elicit feedback from experienced CFIR users to inform updates to the framework. Methods User feedback was obtained from two sources: (1) a literature review with a systematic search; and (2) a survey of authors who used the CFIR in a published study. Data were combined across both sources and reviewed to identify themes; a consensus approach was used to finalize all CFIR updates. The VA Ann Arbor Healthcare System IRB declared this study exempt from the requirements of 38 CFR 16 based on category 2. Results The systematic search yielded 376 articles that contained the CFIR in the title and/or abstract and 334 unique authors with contact information; 59 articles included feedback on the CFIR. Forty percent ( n  = 134/334) of authors completed the survey. The CFIR received positive ratings on most framework sensibility items (e.g., applicability, usability), but respondents also provided recommendations for changes. Overall, updates to the CFIR include revisions to existing domains and constructs as well as the addition, removal, or relocation of constructs. These changes address important critiques of the CFIR, including better centering innovation recipients and adding determinants to equity in implementation. Conclusion The updates in the CFIR reflect feedback from a growing community of CFIR users. Although there are many updates, constructs can be mapped back to the original CFIR to ensure longitudinal consistency. We encourage users to continue critiquing the CFIR, facilitating the evolution of the framework as implementation science advances.

Background Acceptability, appropriateness, and feasibility are established implementation outcomes used to understand stakeholders’ perceptions of an intervention. Further, they are thought to provide insight into behaviors, such as adoption. To date, measurement instruments for the three outcomes have focused on their individual assessment whilst nodding to the idea that they may interrelate. Despite this acknowledgment, there is little empirical evidence of the association among these constructs. Using the example of genetic health professionals providing additional genomic results to patients, this study aimed to examine the interrelationships among acceptability, appropriateness, and feasibility. Methods A sequential explanatory mixed methods approach was employed. All genetic counsellors and clinical geneticists involved in a large research program were invited to complete pre/post surveys using existing measures of acceptability, appropriateness, and feasibility. Follow-up interviews, informed by the survey results, explored clinicians’ perspectives of the three outcomes in relation to providing additional genomic results to patients. To categorize interrelationships and generate feedback loops, survey data were analyzed using descriptive and correlation statistics and interpreted alongside interview data analyzed using content analysis. Results The survey results (pre n  = 53 and post n  = 40) for each outcome showed a similar midpoint mean, wide ranges, and little change post implementation (Acceptability: pre M  = 3.55, range 2–5 post M  = 3.56, range 1.5–5; Appropriateness: pre M  = 3.35, range 1–5, post M  = 3.48, range 1–5; Feasibility: pre M  = 3.30, post M  = 3.32; range 1.25–5). The strength of correlation among outcomes ranged from 0.54 to 0.78. Five interrelationships were categorized from analysis of interview data ( n  = 14) and explain how clinicians’ perceptions of the intervention, positive or negative, were determined by interrelating factors of acceptability, appropriateness, and feasibility and that in different scenarios, the function and emphasis of importance among outcomes switched. Conclusions Rather than existing separately, our study promotes the need to consider interrelationships among acceptability, appropriateness, and feasibility to better characterize clinicians’ perceptions of complex health care interventions and aid in the development of implementation strategies that have real world impact. Further, in the interest of reducing research waste, more research is needed to determine if the outcomes could serve as proxies for each other.

Background Implementation outcome measures are essential for monitoring and evaluating the success of implementation efforts. Yet, currently available measures lack conceptual clarity and have largely unknown reliability and validity. This study developed and psychometrically assessed three new measures: the Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and Feasibility of Intervention Measure (FIM). Methods Thirty-six implementation scientists and 27 mental health professionals assigned 31 items to the constructs and rated their confidence in their assignments. The Wilcoxon one-sample signed rank test was used to assess substantive and discriminant content validity. Exploratory and confirmatory factor analysis (EFA and CFA) and Cronbach alphas were used to assess the validity of the conceptual model. Three hundred twenty-six mental health counselors read one of six randomly assigned vignettes depicting a therapist contemplating adopting an evidence-based practice (EBP). Participants used 15 items to rate the therapist’s perceptions of the acceptability, appropriateness, and feasibility of adopting the EBP. CFA and Cronbach alphas were used to refine the scales, assess structural validity, and assess reliability. Analysis of variance (ANOVA) was used to assess known-groups validity. Finally, half of the counselors were randomly assigned to receive the same vignette and the other half the opposite vignette; and all were asked to re-rate acceptability, appropriateness, and feasibility. Pearson correlation coefficients were used to assess test-retest reliability and linear regression to assess sensitivity to change. Results All but five items exhibited substantive and discriminant content validity. A trimmed CFA with five items per construct exhibited acceptable model fit (CFI = 0.98, RMSEA = 0.08) and high factor loadings (0.79 to 0.94). The alphas for 5-item scales were between 0.87 and 0.89. Scale refinement based on measure-specific CFAs and Cronbach alphas using vignette data produced 4-item scales (α’s from 0.85 to 0.91). A three-factor CFA exhibited acceptable fit (CFI = 0.96, RMSEA = 0.08) and high factor loadings (0.75 to 0.89), indicating structural validity. ANOVA showed significant main effects, indicating known-groups validity. Test-retest reliability coefficients ranged from 0.73 to 0.88. Regression analysis indicated each measure was sensitive to change in both directions. Conclusions The AIM, IAM, and FIM demonstrate promising psychometric properties. Predictive validity assessment is planned.

There is growing evidence of the positive effects of electronic health (eHealth) interventions for patients with chronic illness, but implementation of such interventions into practice is challenging. Implementation strategies that potentially impact implementation outcomes and implementation success have been identified. Which strategies are actually used in the implementation of eHealth interventions for patients with chronic illness and which ones are the most effective is unclear. This systematic realist review aimed to summarize evidence from empirical studies regarding (1) which implementation strategies are used when implementing eHealth interventions for patients with chronic illnesses living at home, (2) implementation outcomes, and (3) the relationship between implementation strategies, implementation outcomes, and degree of implementation success. A systematic literature search was performed in the electronic databases MEDLINE, Embase, PsycINFO, Scopus, Allied and Complementary Medicine Database, Cumulative Index to Nursing and Allied Health Literature, and Cochrane Library. Studies were included if they described implementation strategies used to support the integration of eHealth interventions into practice. Implementation strategies were categorized according to 9 categories defined by the Expert Recommendations for Implementing Change project: (1) engage consumers, (2) use evaluative and iterative strategies, (3) change infrastructure, (4) adapt and tailor to the context, (5) develop stakeholder interrelationships, (6) use financial strategies, (7) support clinicians, (8) provide interactive assistance, and (9) train and educate stakeholders. Implementation outcomes were extracted according to the implementation outcome framework by Proctor and colleagues: (1) acceptability, (2) adoption, (3) appropriateness, (4) cost, (5) feasibility, (6) fidelity, (7) penetration, and (8) sustainability. Implementation success was extracted according to the study authors' own evaluation of implementation success in relation to the used implementation strategies. The implementation strategies management support and engagement, internal and external facilitation, training, and audit and feedback were directly related to implementation success in several studies. No clear relationship was found between the number of implementation strategies used and implementation success. This is the first review examining implementation strategies, implementation outcomes, and implementation success of studies reporting the implementation of eHealth programs for patients with chronic illnesses living at home. The review indicates that internal and external facilitation, audit and feedback, management support, and training of clinicians are of importance for eHealth implementation. The review also points to the lack of eHealth studies that report implementation strategies in a comprehensive way and highlights the need to design robust studies focusing on implementation strategies in the future. PROSPERO CRD42018085539; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=85539.

Background Proctor and colleagues’ 2011 paper proposed a taxonomy of eight implementation outcomes and challenged the field to address a research agenda focused on conceptualization, measurement, and theory building. Ten years later, this paper maps the field’s progress in implementation outcomes research. This scoping review describes how each implementation outcome has been studied, research designs and methods used, and the contexts and settings represented in the current literature. We also describe the role of implementation outcomes in relation to implementation strategies and other outcomes. Methods Arksey and O’Malley’s framework for conducting scoping reviews guided our methods. Using forward citation tracing, we identified all literature citing the 2011 paper. We conducted our search in the Web of Science (WOS) database and added citation alerts sent to the first author from the publisher for a 6-month period coinciding with the WOS citation search. This produced 1346 titles and abstracts. Initial abstract screening yielded 480 manuscripts, and full-text review yielded 400 manuscripts that met inclusion criteria (empirical assessment of at least one implementation outcome). Results Slightly more than half (52.1%) of included manuscripts examined acceptability. Fidelity (39.3%), feasibility (38.6%), adoption (26.5%), and appropriateness (21.8%) were also commonly examined. Penetration (16.0%), sustainability (15.8%), and cost (7.8%) were less frequently examined. Thirty-two manuscripts examined implementation outcomes not included in the original taxonomy. Most studies took place in healthcare (45.8%) or behavioral health (22.5%) organizations. Two-thirds used observational designs. We found little evidence of progress in testing the relationships between implementation strategies and implementation outcomes, leaving us ill-prepared to know how to achieve implementation success. Moreover, few studies tested the impact of implementation outcomes on other important outcome types, such as service systems and improved individual or population health. Conclusions Our review presents a comprehensive snapshot of the research questions being addressed by existing implementation outcomes literature and reveals the need for rigorous, analytic research and tests of strategies for attaining implementation outcomes in the next 10 years of outcomes research.

Smoking cessation reduces the risk of death, improves recovery, and reduces the risk of hospital readmission. Evidence and policy support hospital admission as an ideal time to deliver smoking-cessation interventions. However, this is not well implemented in practice. In this systematic review, the authors summarize the literature on smoking-cessation implementation strategies and evaluate their success to guide the implementation of best-practice smoking interventions into hospital settings. The CINAHL Complete, Embase, MEDLINE Complete, and PsycInfo databases were searched using terms associated with the following topics: smoking cessation, hospitals, and implementation. In total, 14,287 original records were identified and screened, resulting in 63 eligible articles from 56 studies. Data were extracted on the study characteristics, implementation strategies, and implementation outcomes. Implementation outcomes were guided by Proctor and colleagues' framework and included acceptability, adoption, appropriateness, cost, feasibility, fidelity, penetration, and sustainability. The findings demonstrate that studies predominantly focused on the training of staff to achieve implementation. Brief implementation approaches using a small number of implementation strategies were less successful and poorly sustained compared with well resourced and multicomponent approaches. Although brief implementation approaches may be viewed as advantageous because they are less resource-intensive, their capacity to change practice in a sustained way lacks evidence. Attempts to change clinician behavior or introduce new models of care are challenging in a short time frame, and implementation efforts should be designed for long-term success. There is a need to embrace strategic, well planned implementation approaches to embed smoking-cessation interventions into hospitals and to reap and sustain the benefits for people who smoke.

Background This paper describes the process and results of a refinement of a framework to characterize modifications to interventions. The original version did not fully capture several aspects of modification and adaptation that may be important to document and report. Additionally, the earlier framework did not include a way to differentiate cultural adaptation from adaptations made for other reasons. Reporting additional elements will allow for a more precise understanding of modifications, the process of modifying or adapting, and the relationship between different forms of modification and subsequent health and implementation outcomes. Discussion We employed a multifaceted approach to develop the updated FRAME involving coding documents identified through a literature review, rapid coding of qualitative interviews, and a refinement process informed by multiple stakeholders. The updated FRAME expands upon Stirman et al.’s original framework by adding components of modification to report: (1) when and how in the implementation process the modification was made, (2) whether the modification was planned/proactive (i.e., an adaptation) or unplanned/reactive, (3) who determined that the modification should be made, (4) what is modified, (5) at what level of delivery the modification is made, (6) type or nature of context or content-level modifications, (7) the extent to which the modification is fidelity-consistent, and (8) the reasons for the modification, including (a) the intent or goal of the modification (e.g., to reduce costs) and (b) contextual factors that influenced the decision. Methods of using the framework to assess modifications are outlined, along with their strengths and weaknesses, and considerations for research to validate these measurement strategies. Conclusion The updated FRAME includes consideration of when and how modifications occurred, whether it was planned or unplanned, relationship to fidelity, and reasons and goals for modification. This tool that can be used to support research on the timing, nature, goals and reasons for, and impact of modifications to evidence-based interventions.