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Pace and determinants of implementation of the self-management of well-being group intervention: a multilevel observational study.

ABSTRACT: BACKGROUND:When implementing an empirically supported intervention (ESI) arrays of influencing factors operate on the professional and organizational level, but so far dependency between these levels has often been ignored. The aim of this study is to describe the pace and identify determinants of implementation of the Self-Management of Well-being (SMW) group intervention while taking the dependency between professionals and organizations into account. METHODS:Pace of implementation was measured as the time between training of professionals and first use of the SMW intervention in months. Determinants of first use were derived from the Fleuren framework and assessed using web-based questionnaires and telephone interviews. First, univariate analyses, Fisher's exact tests and t-tests, were performed to identify determinants of first use of the SMW intervention on the individual professional and the organizational level independently. Second, multilevel analyses were performed to correct for the dependency between professionals and organizations. Simple multilevel logistic regression analyses were performed with determinants found significant in the univariate analyses as independent variables, first use as dependent variable, professionals entered in the first level, and organizations in the second level. RESULTS:Forty-eight professionals from 18 organizations were trained to execute the SMW intervention. Thirty-two professionals achieved first use, at a mean pace of 7.5?months ± 4.2. Determinants on the professional level were 'ownership', 'relative advantage', 'support from colleagues' and 'compatibility'. Determinants on the organizational level were 'organizational size' and 'innovation-task orientation fit'. Multilevel analysis showed that 'compatibility', a factor on the professional level, was the only significant determinant contributing to first use in the multilevel model. CONCLUSIONS:This implementation study revealed a strong dependency between professionals and organizations. Results showed that a majority of professionals used the SMW intervention in about 8?months. When the dependency between professionals and organization was taken into account, the professionals' perception of compatibility was the only remaining determinant of implementation on the professional level. Organizational size and managers' perception of 'innovation-task orientation fit' were determinants of implementation on the organizational level. It is advisable to discuss the compatibility between new and current tasks among managers and professionals before adopting a new intervention.

SUBMITTER: Kuiper D

PROVIDER: S-EPMC6346574 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Pace and determinants of implementation of the self-management of well-being group intervention: a multilevel observational study.

Kuiper Daphne D Steverink Nardi N Stewart Roy E RE Reijneveld Sijmen A SA Sanderman Robbert R Goedendorp Martine M MM

BMC health services research 20190125 1

<h4>Background</h4>When implementing an empirically supported intervention (ESI) arrays of influencing factors operate on the professional and organizational level, but so far dependency between these levels has often been ignored. The aim of this study is to describe the pace and identify determinants of implementation of the Self-Management of Well-being (SMW) group intervention while taking the dependency between professionals and organizations into account.<h4>Methods</h4>Pace of implementat ...[more]

PMID: 30683092

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Project description:BACKGROUND:Chronic conditions account for 75% of health care costs, and the impact of chronic illness is expected to grow over time. Although subjective well-being predicts better health outcomes, people with chronic conditions tend to report lower well-being. Improving well-being might mitigate costs associated with chronic illness; however, existing interventions can be difficult to access and draw from a single theoretical approach. Happify, a digital well-being intervention program drawing from multiple theoretical traditions to target well-being, has already been established as an efficacious means of improving well-being in both distressed and nondistressed users. OBJECTIVE:This study aimed to compare change in well-being over time after using Happify for users with and without a chronic condition. METHODS:Data were obtained from Happify users, a publicly available digital well-being program accessible via website or mobile phone app. Users work on tracks addressing a specific issue (eg, conquering negative thoughts) composed of games and activities based on positive psychology, cognitive behavioral therapy, and mindfulness principles. The sample included 821 users receiving at least 6 weeks' exposure to Happify (ranging from 42 to 179 days) who met other inclusion criteria. As part of a baseline questionnaire, respondents reported demographic information (age and gender) and whether they had any of the prespecified chronic conditions: arthritis, diabetes, insomnia, multiple sclerosis, chronic pain, psoriasis, eczema, or some other condition (450 reported a chronic condition, whereas 371 did not). Subjective well-being was assessed with the Happify Scale, a 9-item measure of positive emotionality and life satisfaction. To evaluate changes in well-being over time, a mixed effects linear regression model was fit for subjective well-being, controlling for demographics and platform usage. RESULTS:At baseline, users with a chronic condition had significantly lower subjective well-being (mean 38.34, SD 17.40) than users without a chronic condition (mean 43.65, SD 19.13). However, change trajectories for users with or without a chronic condition were not significantly different; both groups experienced equivalent improvements in well-being. We also found an effect for time from baseline (b=0.071; SE=0.010; P<.01) and number of activities completed (b=0.03; SE=0.009; P<.01), and a 2-way interaction between number of activities completed and time from baseline (b=0.0002; SE=0.00006; P<.01), such that completing more activities and doing so over increasingly longer periods produced improved well-being scores. CONCLUSIONS:Data from this study support the conclusion that users with a chronic condition experienced significant improvement over time. Despite reporting lower subjective well-being on the whole, their change trajectory while using Happify was equivalent to those without a chronic condition. Consistent with past research, users who completed more activities over a longer period showed the most improvement. In short, the presence of a chronic condition did not prevent users from showing improved well-being when using Happify.

Project description:BackgroundEvaluation of complex interventions should include a process evaluation to give evaluators, researchers, and policy makers greater confidence in the outcomes reported from RCTs. Implementation fidelity can be part of a process evaluation and refers to the degree to which an intervention is delivered according to protocol. The aim of this implementation fidelity study was to evaluate to what extent a dialogue-based psychosocial intervention was delivered according to protocol. A modified conceptual framework for implementation fidelity was used to guide the analysis.MethodsThis study has an explanatory, sequential two-phase mixed methods design. Quantitative process data were collected longitudinally along with data collection in the RCT. Qualitative process data were collected after the last data collection point of the RCT. Descriptive statistical analyses were conducted to describe the sample, the intervention trajectories, and the adherence measures. A scoring system to clarify quantitative measurement of the levels of implementation was constructed. The qualitative data sources were analyzed separately with a theory-driven content analysis using categories of adherence and potential moderating factors identified in the conceptual framework of implementation fidelity. The quantitative adherence results were extended with the results from the qualitative analysis to assess which potential moderators may have influenced implementation fidelity and in what way.ResultsThe results show that the core components of the intervention were delivered although the intervention trajectories were individualized. Based on the composite score of adherence, results show that 80.1% of the interventions in the RCT were implemented with high fidelity. Although it is challenging to assess the importance of each of the moderating factors in relation to the other factors and to their influence on the adherence measures, participant responsiveness, comprehensiveness of policy description, context, and recruitment appeared to be the most prominent moderating factors of implementation fidelity in this study.ConclusionsThis evaluation of implementation fidelity and the discussion of what constitutes high fidelity implementation of this intervention are crucial in understanding the factors influencing the trial outcome. The study also highlights important methodological considerations for researchers planning process evaluations and studies of implementation fidelity.Trial registrationClinicalTrials.gov , NCT02338869; registered 10/04/2014.

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Pace and determinants of implementation of the self-management of well-being group intervention: a multilevel observational study.

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Pace and determinants of implementation of the self-management of well-being group intervention: a multilevel observational study.

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