Efficacy of eHealth Interventions for Adults with Diabetes: A Systematic Review and Meta-Analysis.
Giulia BassiElisa MancinelliGaia Dell'ArcipreteSilvia RizziSilvia GabrielliSilvia SalcuniPublished in: International journal of environmental research and public health (2021)
The aim is to provide meta-analytical evidence on eHealth interventions' efficacy in supporting the psychosocial and physical well-being of adults with type 1 or type 2 Diabetes Mellitus (DM), and to investigate differences in interventions primarily targeted at providing glycemic control vs. psychosocial support. A PRISMA-guided systematic search was conducted. Randomized Controlled Trials (RCTs) regarding eHealth interventions for adults (18-65 years) with DM were included. Data were pooled using Standard Mean Difference (SMD); sub-group analysis and meta-regressions were performed when appropriate. Outcomes were Hemoglobin A1c (HbA1c), diabetes distress, quality of life, anxiety, stress, and depression. Intervention acceptability was assessed performing the Odds Ratio (OR) of drop-out rates. Thirteen RCTs comprising 1315 participants were included (52.09% females; Mage = 46.18, SD = 9.98). Analyses showed intervention efficacy on HbA1c (SMD = -0.40; 95% CI = -0.70, -0.12; k = 13) and depressive symptoms (SMD = -0.18; 95% CI = -0.33, -0.02; k = 6) at RCTs endpoint and were well accepted (OR = 1.43; 95% CI = 0.72, 2.81; k = 10). However, efficacy on HbA1c was not maintained at follow-up (SMD = -0.13; 95% CI = -0.31, 0.05; k = 6). eHealth interventions providing medical support were acceptable and effective in fostering glycemic control and decreasing depressive symptoms in the short-term only. Digital solutions should be developed on multiple levels to fully support the psychophysical well-being of people with DM.
Keyphrases
- glycemic control
- type diabetes
- depressive symptoms
- blood glucose
- physical activity
- randomized controlled trial
- weight loss
- sleep quality
- mental health
- insulin resistance
- social support
- cardiovascular disease
- machine learning
- mass spectrometry
- metabolic syndrome
- adipose tissue
- drug delivery
- double blind
- heat stress
- phase iii
- data analysis