Psychosocial Characteristics by Weight Loss and Engagement in a Digital Intervention Supporting Self-Management of Weight.
Ellen Siobhan MitchellQiuchen YangHeather BehrAnnabell HoLaura DeLucaChristine N MayAndreas MichaelidesPublished in: International journal of environmental research and public health (2021)
There is substantial variability in weight loss outcomes. Psychosocial characteristics underlying outcomes require better understanding, particularly on self-managed digital programs. This cross-sectional study examines differences in psychosocial characteristics by weight loss and engagement outcome, and which characteristics are most associated with weight loss, on a self-managed digital weight loss program. Some underexplored psychosocial characteristics are included, such as flourishing, or a sense of meaning and purpose in life. A questionnaire was emailed to a random sample of 10,000 current users at week 5 in the program and 10,000 current users at week 17. The questionnaire was completed by 2225 users, and their self-reported weight and recorded program engagement data were extracted from the program's database. Multiple comparison tests indicated that mental health quality of life, depression, anxiety, work-life balance, and flourishing differed by weight loss outcome at program end (week 17; ≥5%, 2-5%, below 2%) and by engagement tertile at program beginning and end (weeks 5 and 17). Only anxiety was associated with weight loss in a backward stepwise regression controlling for engagement and sociodemographic characteristics. Flourishing did not predict weight loss overall but predicted the weight loss outcome group. Our findings have implications for creating more effective interventions for individuals based on psychosocial characteristics and highlight the potential importance of anxiety in underexplored self-managed digital programs.
Keyphrases
- weight loss
- bariatric surgery
- roux en y gastric bypass
- mental health
- gastric bypass
- quality improvement
- glycemic control
- social media
- weight gain
- obese patients
- public health
- randomized controlled trial
- emergency department
- sleep quality
- machine learning
- depressive symptoms
- cross sectional
- psychometric properties
- gestational age
- patient reported
- preterm birth
- study protocol