Introduction: This study aimed to (a) review what theories have been applied to the development of digital self-management interventions for people with neurological disorders; (b) examine their effectiveness to improve depression, anxiety, fatigue and self-efficacy; and (c) identify the optimal mode of intervention delivery. Methods: Electronic databases (SCOPUS, MEDLINE, EMBASE, CINAHL, Cochrane Library and Clinicaltrials.gov) were searched. Two investigators independently screened studies and extracted data. Study quality and use of theory were also assessed Results: A total of 944 studies were screened, and 16 randomised controlled trials were included. Theory-based digital self-management interventions were effective in reducing depression (standardised mean difference (SMD) = –0.77, 95% confidence interval (CI) –1.04 to –0.49), anxiety (SMD = –0.88, 95% CI –1.54 to –0.21) and fatigue (SMD = –0.62, 95% CI –0.96 to –0.27) and in enhancing self-efficacy (SMD = 1.15, 95% CI 0.11–2.18). Cognitive–behavioural theory (CBT)-based interventions were effective in reducing depression (SMD = –0.81, 95% CI –1.22 to –0.39), anxiety (SMD = –1.15, 95% CI –1.85 to –0.44) and fatigue (SMD = –0.75, 95% CI –0.97 to –0.54) and in improving self-efficacy (SMD = 0.84, 95% CI 0.63–1.05), whereas social cognitive theory (SCT)-based interventions were effective in reducing depression (SMD = –0.73, 95% CI –1.17 to –0.28). Partially digital interventions were more effective than fully digital interventions. Discussion: Our findings support the use of theory to guide the development of digital self-management interventions to increase intervention effectiveness. In particular, CBT-based interventions have a positive impact on depression, anxiety, fatigue and self-efficacy, whereas SCT-based interventions have a positive impact on depression.
- behavioural theory