A systematic review of ecological momentary assessment studies on weight stigma and a call for a large-scale collaboration.
Hugh BidstrupLeah BrennanLeah M KaufmannAngela MeadowsXochitl de la Piedad GarciaPublished in: Obesity reviews : an official journal of the International Association for the Study of Obesity (2023)
Consistent with previous research, studies from this review suggest weight stigma leads to adverse outcomes. EMA has the potential to overcome many of the limitations present in cross-sectional research on weight stigma and provide more ecologically valid and reliable results. We argue for a collaborative data-sharing consortium with standardized EMA methodologies, so researchers worldwide can contribute to and make use of a large, collective dataset on weight stigma and health correlates (see osf.io/s5ru6/).
Keyphrases
- mental health
- mental illness
- hiv aids
- body mass index
- weight loss
- social support
- physical activity
- weight gain
- cross sectional
- body weight
- human health
- public health
- health information
- depressive symptoms
- social media
- electronic health record
- climate change
- case control
- big data
- risk assessment
- antiretroviral therapy
- machine learning
- artificial intelligence
- deep learning
- hepatitis c virus
- quantum dots