TY - JOUR
T1 - Frameworks for implementation, uptake, and use of cardiometabolic disease--related digital health interventions in ethnic minority populations
T2 - scoping review
AU - Ramasawmy, Mel
AU - Poole, Lydia
AU - Thorlu-Bangura, Zareen
AU - Chauhan, Aneesha
AU - Murali, Mayur
AU - Jagpal, Parbir
AU - Bijral, Mehar
AU - Prashar, Jai
AU - G-Medhin, Abigail
AU - Murray, Elizabeth
AU - Stevenson, Fiona
AU - Blandford, Ann
AU - Potts, Henry W W
AU - Khunti, Kamlesh
AU - Hanif, Wasim
AU - Gill, Paramjit
AU - Sajid, Madiha
AU - Patel, Kiran
AU - Sood, Harpreet
AU - Bhala, Neeraj
AU - Modha, Shivali
AU - Mistry, Manoj
AU - Patel, Vinod
AU - Ali, Sarah N
AU - Ala, Aftab
AU - Banerjee, Amitava
PY - 2022/8/11
Y1 - 2022/8/11
N2 - Background: Digital health interventions have become increasingly common across health care, both before and during the COVID-19 pandemic. Health inequalities, particularly with respect to ethnicity, may not be considered in frameworks that address the implementation of digital health interventions. We considered frameworks to include any models, theories, or taxonomies that describe or predict implementation, uptake, and use of digital health interventions. Objective: We aimed to assess how health inequalities are addressed in frameworks relevant to the implementation, uptake, and use of digital health interventions; health and ethnic inequalities; and interventions for cardiometabolic disease. Methods: SCOPUS, PubMed, EMBASE, Google Scholar, and gray literature were searched to identify papers on frameworks relevant to the implementation, uptake, and use of digital health interventions; ethnically or culturally diverse populations and health inequalities; and interventions for cardiometabolic disease. We assessed the extent to which frameworks address health inequalities, specifically ethnic inequalities; explored how they were addressed; and developed recommendations for good practice. Results: Of 58 relevant papers, 22 (38%) included frameworks that referred to health inequalities. Inequalities were conceptualized as society-level, system-level, intervention-level, and individual. Only 5 frameworks considered all levels. Three frameworks considered how digital health interventions might interact with or exacerbate existing health inequalities, and 3 considered the process of health technology implementation, uptake, and use and suggested opportunities to improve equity in digital health. When ethnicity was considered, it was often within the broader concepts of social determinants of health. Only 3 frameworks explicitly addressed ethnicity: one focused on culturally tailoring digital health interventions, and 2 were applied to management of cardiometabolic disease. Conclusions: Existing frameworks evaluate implementation, uptake, and use of digital health interventions, but to consider factors related to ethnicity, it is necessary to look across frameworks. We have developed a visual guide of the key constructs across the 4 potential levels of action for digital health inequalities, which can be used to support future research and inform digital health policies.
AB - Background: Digital health interventions have become increasingly common across health care, both before and during the COVID-19 pandemic. Health inequalities, particularly with respect to ethnicity, may not be considered in frameworks that address the implementation of digital health interventions. We considered frameworks to include any models, theories, or taxonomies that describe or predict implementation, uptake, and use of digital health interventions. Objective: We aimed to assess how health inequalities are addressed in frameworks relevant to the implementation, uptake, and use of digital health interventions; health and ethnic inequalities; and interventions for cardiometabolic disease. Methods: SCOPUS, PubMed, EMBASE, Google Scholar, and gray literature were searched to identify papers on frameworks relevant to the implementation, uptake, and use of digital health interventions; ethnically or culturally diverse populations and health inequalities; and interventions for cardiometabolic disease. We assessed the extent to which frameworks address health inequalities, specifically ethnic inequalities; explored how they were addressed; and developed recommendations for good practice. Results: Of 58 relevant papers, 22 (38%) included frameworks that referred to health inequalities. Inequalities were conceptualized as society-level, system-level, intervention-level, and individual. Only 5 frameworks considered all levels. Three frameworks considered how digital health interventions might interact with or exacerbate existing health inequalities, and 3 considered the process of health technology implementation, uptake, and use and suggested opportunities to improve equity in digital health. When ethnicity was considered, it was often within the broader concepts of social determinants of health. Only 3 frameworks explicitly addressed ethnicity: one focused on culturally tailoring digital health interventions, and 2 were applied to management of cardiometabolic disease. Conclusions: Existing frameworks evaluate implementation, uptake, and use of digital health interventions, but to consider factors related to ethnicity, it is necessary to look across frameworks. We have developed a visual guide of the key constructs across the 4 potential levels of action for digital health inequalities, which can be used to support future research and inform digital health policies.
KW - cardiology
KW - cardiometabolic
KW - cultural
KW - digital health
KW - diverse
KW - diversity
KW - eHealth
KW - ethnicity
KW - framework
KW - health inequalities
KW - health inequality
KW - health technology
KW - metabolic
KW - metabolism
KW - minority
KW - review
UR - http://www.ncbi.nlm.nih.gov/pubmed/35969455
U2 - 10.2196/37360
DO - 10.2196/37360
M3 - Review article
SN - 2561-1011
VL - 6
JO - JMIR Cardio
JF - JMIR Cardio
IS - 2
M1 - e37360
ER -