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Understanding Long-Term Trajectories in Web-Based Happiness Interventions: Secondary Analysis From Two Web-Based Randomized Trials.
Sanders, Christopher A; Schueller, Stephen M; Parks, Acacia C; Howell, Ryan T.
Afiliación
  • Sanders CA; Department of Psychological Sciences, University of Missouri, Columbia, Columbia, MO, United States.
  • Schueller SM; Department of Psychological Science, University of California Irvine, Irvine, CA, United States.
  • Parks AC; Happify Health, New York, NY, United States.
  • Howell RT; Psychology Department, San Francisco State University, San Francisco, CA, United States.
J Med Internet Res ; 21(6): e13253, 2019 06 08.
Article en En | MEDLINE | ID: mdl-31199342
ABSTRACT

BACKGROUND:

A critical issue in understanding the benefits of Web-based interventions is the lack of information on the sustainability of those benefits. Sustainability in studies is often determined using group-level analyses that might obscure our understanding of who actually sustains change. Person-centric methods might provide a deeper knowledge of whether benefits are sustained and who tends to sustain those benefits.

OBJECTIVE:

The aim of this study was to conduct a person-centric analysis of longitudinal outcomes, examining well-being in participants over the first 3 months following a Web-based happiness intervention. We predicted we would find distinct trajectories in people's pattern of response over time. We also sought to identify what aspects of the intervention and the individual predicted an individual's well-being trajectory.

METHODS:

Data were gathered from 2 large studies of Web-based happiness

interventions:

one in which participants were randomly assigned to 1 of 14 possible 1-week activities (N=912) and another wherein participants were randomly assigned to complete 0, 2, 4, or 6 weeks of activities (N=1318). We performed a variation of K-means cluster analysis on trajectories of life satisfaction (LS) and affect balance (AB). After clusters were identified, we used exploratory analyses of variance and logistic regression models to analyze groups and compare predictors of group membership.

RESULTS:

Cluster analysis produced similar cluster solutions for each sample. In both cases, participant trajectories in LS and AB fell into 1 of 4 distinct groups. These groups were as follows those with high and static levels of happiness (n=118, or 42.8%, in Sample 1; n=306, or 52.8%, in Sample 2), those who experienced a lasting improvement (n=74, or 26.8% in Sample 1; n=104, or 18.0%, in Sample 2), those who experienced a temporary improvement but returned to baseline (n=37, or 13.4%, in Sample 1; n=82, or 14.2%, in Sample 2), and those with other trajectories (n=47, or 17.0%, in Sample 1; n=87, or 15.0% in Sample 2). The prevalence of depression symptoms predicted membership in 1 of the latter 3 groups. Higher usage and greater adherence predicted sustained rather than temporary benefits.

CONCLUSIONS:

We revealed a few common patterns of change among those completing Web-based happiness interventions. A noteworthy finding was that many individuals began quite happy and maintained those levels. We failed to identify evidence that the benefit of any particular activity or group of activities was more sustainable than any others. We did find, however, that the distressed portion of participants was more likely to achieve a lasting benefit if they continued to practice, and adhere to, their assigned Web-based happiness intervention.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Distribución Aleatoria / Análisis por Conglomerados / Felicidad Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Distribución Aleatoria / Análisis por Conglomerados / Felicidad Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos
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