1. The Effects of a Digital Well-Being Intervention on Patients With Chronic Conditions: Observational Study
- Author
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Parks, AC, Williams, AL, Kackloudis, GM, Stafford, JL, Boucher, EM, Honomichl, RD, Parks, AC, Williams, AL, Kackloudis, GM, Stafford, JL, Boucher, EM, and Honomichl, RD
- Abstract
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 lo
- Published
- 2020