JMIR Publications

ABSTRACT

Background:

eHealth interventions offer vital support for cancer patients through education, behavior change, and monitoring. Despite their potential, patient adherence to these self-help interventions is challenging. Factors like user characteristics, technology, and intervention design influence adherence. Existing reviews have gaps in exploring diverse factors associated with adherence in cancer care.

Objective:

This systematic review aimed to identify factors influencing adherence to eHealth interventions with self-help components in cancer care. It examined sociodemographic, psychosocial, health-related, and intervention-related factors that affect patients' adherence to these digital health solutions.

Methods:

Following PRISMA guidelines, a search was conducted across PubMed, Embase, Cochrane Library, and PsycINFO to find studies published from January 2010 to September 2021. The studies included in this review focused on adult cancer patients using eHealth interventions with self-help features. Data were extracted and synthesized using a standardized approach. Factors associated with adherence were synthesized according to their type: sociodemographic factors, psychosocial factors, health-related factors, technology-related factors, and intervention-related factors.

Results:

Among 9,386 studies initially screened, 61 were eligible for analysis. These studies covered diverse eHealth intervention types, cancer types, and outcome measures. Investigating the determinants of adherence to eHealth was the main objective for 42.6% of the included studies. Adherence was gauged using varied measures such as drop-out rates, log-ins, and self-reported measures. Results regarding factors influencing adherence were inconsistent across studies. Most sociodemographic (e.g., age) and health-related factors (e.g., cancer stage) yielded mixed outcomes. However, comorbidity consistently predicted lower adherence. Results regarding psychosocial factors were more stable across studies. In particular, higher social support was associated with lower adherence. Finally, intervention-related factors like intervention type or human support showed conflicting results.

Conclusions:

This review highlights the complexity of adherence to eHealth interventions in cancer care. While some factors, notably comorbidities and low social support, consistently influenced adherence, others displayed mixed associations. The review underscores the need to standardize measures, investigate specific intervention features, and enhance study quality to optimize eHealth interventions for cancer patients. Further research is crucial to better understand and improve adherence to digital health solutions in cancer care.