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A systematic review of the use and reporting of evaluation frameworks within evaluations of physical activity interventions.

ABSTRACT: BACKGROUND:Evaluation of physical activity interventions is vital to inform, and justify, evidence-based policy and practice to support population-wide changes in physical activity. Several evaluation frameworks and guidance documents have been developed to facilitate the evaluation and reporting of evaluation studies in public health. However, there is a lack of evidence about whether frameworks are being used to guide evaluation. There continues to be claims of poor and inconsistent reporting in evaluation studies. The aim of this review was to assess the use of evaluation frameworks and the quality of reporting of how they were applied within evaluation studies of physical activity interventions. OBJECTIVES:1. To identify whether evaluation frameworks are reported to have been used within evaluation studies of physical activity interventions, and which frameworks have been used. 2. To appraise the quality of reporting with regards to how evaluation frameworks have been used. METHOD:We developed a checklist of indicators to enable a critical appraisal of the use and reporting of different evaluation frameworks in evaluation studies. We conducted a systematic search and review of evaluation studies published between 2015 and the date of the search to appraise the use and reporting of evaluation frameworks. A narrative synthesis is provided. RESULTS:The review identified 292 evaluation studies of physical activity interventions, only 69 (23%) of these mentioned using an evaluation framework, and only 16 different frameworks were referred to. There was variation in the quality of reporting of framework use. 51 (74%) studies were identified as being explicitly based on the stated framework, however only 26 (38%) provided detailed descriptions consistently across all the checklist indicators. Details of adaptations and limitations in how frameworks were applied were less frequently reported. The review also highlighted variability in the reporting of intervention components. More consistent and precise reporting of framework and intervention components is needed. CONCLUSION:Evaluation frameworks can facilitate a more systematic evaluation report and we argue their limited use suggests missed opportunities to apply frameworks to guide evaluation and reporting in evaluation studies. Variability in the quality of reporting of framework use limits the comparability and transferability of evidence. Where a framework has been used, the checklist of indicators can be employed to facilitate the reporting of an evaluation study and to review the quality of an evaluation report.

SUBMITTER: Fynn JF

PROVIDER: S-EPMC7444034 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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A systematic review of the use and reporting of evaluation frameworks within evaluations of physical activity interventions.

Fynn Judith F JF Hardeman Wendy W Milton Karen K Murphy Joseph J Jones Andy A

The international journal of behavioral nutrition and physical activity 20200824 1

<h4>Background</h4>Evaluation of physical activity interventions is vital to inform, and justify, evidence-based policy and practice to support population-wide changes in physical activity. Several evaluation frameworks and guidance documents have been developed to facilitate the evaluation and reporting of evaluation studies in public health. However, there is a lack of evidence about whether frameworks are being used to guide evaluation. There continues to be claims of poor and inconsistent re ...[more]

PMID: 32831111

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Project description:BACKGROUND:Previous reviews of rural physical activity interventions were focused on intervention effectiveness and had reported overall mixed findings. The purpose of this systematic review was to apply the Reach, Efficacy, Adoption, Implementation and Maintenance (RE-AIM) framework to evaluate the extent to which rural physical activity interventions in the U.S. have reported on dimensions of internal and external validity and to offer suggestions for future physical activity interventions for rural U.S. POPULATIONS: METHODS:Pubmed, PsychINFO, CINAHL, PAIS, and Web of Science were searched through February 2019 to identify physical activity intervention studies conducted in rural regions in the U.S. with adult populations. Titles, abstracts, and full texts of articles were reviewed against inclusion and exclusion criteria. Data extraction from included articles included a summary of study details, rural classification system used, and the presence or absence of a total 61 RE-AIM indicators, including reach (n?=?13), efficacy/effectiveness (n?=?10), adoption (n?=?21), implementation (n?=?9), and maintenance (n?=?8). RESULTS:A total of 40 full-text articles representing 29 unique studies were included. Classifications of rurality included self-statements by authors (n?=?19, 65.5%), population/census-based definitions (n?=?3, 10.3%), Rural Urban Continuum Codes (n?=?3, 10.3%), Rural Urban Commuting Area codes (n?=?2, 6.9%), the 2014 Alabama Rural Health Association classification system (n?=?1, 3.4%) and the U.S. Office of Management and Budget classification system (n?=?1, 3.4%). Individual studies reported between 14.8 to 52.5% of total RE-AIM indicators. Studies reported 15.4 to 84.6% indicators for reach; 20.0 to 70.0% indicators for efficacy/effectiveness; 4.8 to 47.6% indicators for adoption; 11.1 to 88.9% indicators for implementation; and 0 to 25.0% indicators for maintenance. CONCLUSIONS:We found an overall poor reporting of components related to external validity, which hinders the generalizability of intervention findings, and a lack of consistency in the definition of rurality. Future research should focus on balancing factors of internal and external validity, and should aim to develop a greater understanding of how rurality influences health and behavior to provide contextual knowledge needed to advance the translation of physical activity interventions into practice in rural communities and reduce rural health disparities. TRIAL REGISTRATION:The review protocol was registered with PROSPERO: CRD42019116308.

Project description:BackgroundCo-creation strategies, such as cooperative planning, are promising as a means to ensure that physical activity interventions address real-world problems and are tailored to the target group. This has already been validated in diverse settings. However, questions targeting the transferability of cooperative planning to new settings and the key factors influencing its success or failure remain unclear. At the same time, co-creation processes are complex, and evaluation can be challenging. Following calls for detailed reporting, this paper describes the programme activities, the underlying logic, and methodological design of a study that aims to evaluate the transfer of cooperative planning to new settings and to explore the associated key determinants.MethodsCooperative planning was utilized as a strategy to target physical activity promotion in three real-world German settings in the nursing care and automotive mechatronics sectors. This involved researchers working alongside stakeholders from practice and policy to conjointly develop new interventions to promote physical activity in physically demanding jobs. A pragmatic approach is used to evaluate both the transferability and key determinants of this strategy. We developed a logic model for this co-creation process that describes the underlying assumptions and guides the evaluation. The evaluation outcomes of this study include planning meetings, newly developed interventions, and the determinants that are likely to affect cooperative planning. Quantitative and qualitative data will be collected using questionnaires, documents, and interviews. The quantitative data will be analysed descriptively, while the qualitative data will mainly be analysed using qualitative content analysis, split by settings. Subsequently, data triangulation will be used to integrate the quantitative and qualitative findings, which will then be compared across all three settings.DiscussionThe study findings will contribute to a better understanding of co-creation strategies, their transferability, and key determinants. The practical implications can include a checklist for assessing key determinants and a guideline for transferring cooperative planning into new settings to benefit more people. Ultimately, this study will help to advance co-creation strategies and may be relevant for researchers, practitioners, and policy-makers targeting physical activity promotion in various contexts.Trial registrationOpen Science Framework: https://osf.io/r6xnt/ (retrospectively registered).

Project description:Objectives: Health economic evaluations (HEEs) help healthcare decision makers understand the value of new technologies. Artificial intelligence (AI) is increasingly being used in healthcare interventions. We sought to review the conduct and reporting of published HEEs for AI-based health interventions. Methods: We conducted a systematic literature review with a 15-month search window (April 2021 to June 2022) on 17th June 2022 to identify HEEs of AI health interventions and update a previous review. Records were identified from 3 databases (Medline, Embase, and Cochrane Central). Two reviewers screened papers against predefined study selection criteria. Data were extracted from included studies using prespecified data extraction tables. Included studies were quality assessed using the National Institute for Health and Care Excellence (NICE) checklist. Results were synthesized narratively. Results: A total of 21 studies were included. The most common type of AI intervention was automated image analysis (9/21, 43%) mainly used for screening or diagnosis in general medicine and oncology. Nearly all were cost-utility (10/21, 48%) or cost-effectiveness analyses (8/21, 38%) that took a healthcare system or payer perspective. Decision-analytic models were used in 16/21 (76%) studies, mostly Markov models and decision trees. Three (3/16, 19%) used a short-term decision tree followed by a longer-term Markov component. Thirteen studies (13/21, 62%) reported the AI intervention to be cost effective or dominant. Limitations tended to result from the input data, authorship conflicts of interest, and a lack of transparent reporting, especially regarding the AI nature of the intervention. Conclusion: Published HEEs of AI-based health interventions are rapidly increasing in number. Despite the potentially innovative nature of AI, most have used traditional methods like Markov models or decision trees. Most attempted to assess the impact on quality of life to present the cost per QALY gained. However, studies have not been comprehensively reported. Specific reporting standards for the economic evaluation of AI interventions would help improve transparency and promote their usefulness for decision making. This is fundamental for reimbursement decisions, which in turn will generate the necessary data to develop flexible models better suited to capturing the potentially dynamic nature of AI interventions.

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A systematic review of the use and reporting of evaluation frameworks within evaluations of physical activity interventions.

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A systematic review of the use and reporting of evaluation frameworks within evaluations of physical activity interventions.

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