Risk of bias assessment of included studies.
| Study | Study design | Tool used | Key bias domains | Overall risk |
|---|---|---|---|---|
| Adisa and Fakeye (2014) [15] | Observational (cross-sectional) | ROBINS-I | Self-reported adherence; selection bias; confounding | Moderate-Serious |
| Alatawi et al. (2016) [16] | Observational | ROBINS-I | Confounding; measurement bias; self-report | Moderate |
| Almutairi et al. (2023) [11] | RCT | RoB 2.0 | Small sample; possible attrition bias; reporting limitations | Moderate |
| Branda et al. (2013) [21] | RCT | RoB 2.0 | Lack of blinding; potential performance bias | Moderate |
| Brundisini et al. (2015) [24] | Qualitative meta-synthesis | CASP | Selection of studies; interpretive bias; transferability | Moderate |
| Cheng et al. (2018) [12] | RCT | RoB 2.0 | Limited sample size; imprecision; unclear allocation concealment | Moderate |
| Habte et al. (2017) [25] | Mixed-methods | CASP | Integration bias; sampling limitations | Moderate |
| Haque et al. (2014) [26] | Qualitative | CASP | Limited generalisability; recall bias | Moderate |
| Islam et al. (2018) [13] | RCT | RoB 2.0 | Performance bias; intervention fidelity concerns | Moderate |
| Lauffenburger et al. (2019) [17] | RCT | RoB 2.0 | Lack of blinding; outcome assessment bias | Moderate |
| Lee and Lin (2010) [18] | Observational | ROBINS-I | Confounding; selection bias | Moderate |
| Peyrot et al. (2018) [1] | Observational | ROBINS-I | Self-reported outcomes; residual confounding | Moderate |
| Rossi et al. (2015) [22] | Observational | ROBINS-I | Confounding; selection bias; missing data | Serious |
| Schoenthaler et al. (2012) [19] | Observational | ROBINS-I | Confounding; reporting bias; missing data | Serious |
| Schunk et al. (2015) [2] | Observational | ROBINS-I | Recall bias; self-reported adherence; confounding | Moderate-Serious |
| Skinner et al. (2015) [14] | RCT | RoB 2.0 | Allocation concealment unclear; performance bias | Moderate |
| Varming et al. (2019) [20] | RCT | RoB 2.0 | Lack of blinding; implementation variability | Moderate |
| Wang et al. (2019) [23] | Cross-sectional observational study | CASP | Selection bias, Measurement bias | Moderate-High |