Engaging Stakeholders to Adapt an Evidence-Based Family Healthy Weight Program.
Katherine E DarlingJacqueline F HayesE Whitney EvansIrene SanchezJessica ChachraAndrea GrengaA Rani ElwyElissa JelalianPublished in: Translational behavioral medicine (2023)
Childhood obesity is associated with negative physical and psychosocial outcomes, especially for children from low-income backgrounds. It is critical to adapt evidence-based family healthy weight programs to meet the needs of this population. The Framework for Reporting Adaptations and Modifications to Evidence-Based Interventions was used to describe the process of using qualitative data from community and intervention stakeholders, children with overweight or obesity from low-income backgrounds, and caregivers to guide adaptations to the JOIN for ME pediatric weight management intervention. Qualitative interviews were conducted with key community and intervention stakeholders (e.g., nurse care managers, prior JOIN for ME coaches; N = 21). Focus groups were conducted in both Spanish and English with children with overweight or obesity from low-income backgrounds (N = 35) and caregivers of children with overweight or obesity from low-income backgrounds (N = 71). Qualitative data analysis informed modifications including content adaptations to simplify and tailor materials, contextual adaptations to improve intervention engagement and framing, resource awareness, and modality of delivery, training adaptations, and implementation/scale-up activities to increase connections with community partners. The process of engaging multiple stakeholder perspectives to tailor an existing intervention can provide a model for future researchers to improve the potential disseminability of an intervention.
Keyphrases
- weight loss
- weight gain
- randomized controlled trial
- physical activity
- healthcare
- mental health
- young adults
- data analysis
- high intensity
- body mass index
- metabolic syndrome
- palliative care
- insulin resistance
- type diabetes
- primary care
- quality improvement
- systematic review
- machine learning
- high fat diet induced
- adipose tissue
- current status
- deep learning
- pain management
- body weight
- men who have sex with men
- hiv testing
- adverse drug