Table S1.

Framework for judging methodological quality

Bias domain	Criterion	Score	Judgment	Final score
1. Study participation	1.1. The setting of the source population is adequately described by key characteristics (setting/geographical location)	○ Yes ○ Partly ○ No	5 × yes = yes 1 × no = no Else = partly	○ Yes ○ Partly ○ No
	1.2. The (baseline) study sample is adequately described by key characteristics (descriptive data about age, sex, diagnosis, disease duration and medication type/group), and no unacceptable level of bias is present	○ Yes ○ Partly ○ No
	1.3. The method of recruitment or sampling is adequately described. If method of recruitment is not ‘consecutive’, then, for example, descriptions are given about the sampling frame, numbers, methods to identify the sample (such as a description of referral patterns in health care) and period of recruitment, and no unacceptable level of bias is present	○ Yes ○ Partly ○ No
	1.4. Inclusion and exclusion criteria are adequately described, and no unacceptable level of bias is present	○ Yes ○ Partly ○ No
	1.5. There is adequate participation in the study by eligible individuals (power analysis is described or the sample size (n) is adequate in relation to the number of prognostic variables (K) in the statistical analyses (ratio n:K exceeds 10:1)	○ Yes ○ Partly ○ No
2. Study attrition	2.1. Response rate (ie, proportion of study sample completing the study and providing outcome data) is adequate If study sample size ≤50 participants: ‘yes’ when total number of participants lost to follow-up was <10% at follow-up ≥three months. ‘Partly’: if this percentage was between 10% and 20%. ‘No’: if this percentage was ≥20% If study sample size >50 participants: ‘yes’, when total number of participants lost to follow-up was <20% at follow-up $three months. ‘Partly’: if this percentage was between 20% and 33%. ‘No’: if this percentage was ≥33%	○ Yes ○ Partly ○ No	2.1 yes = yes (you can leave 2.2 open) 2.1 no = no OR 2.1 partly, 2.2 no = no Else = partly	○ Yes ○ Partly ○ No
	2.2. Attempts to collect information about participants who dropped out of the study are described: 1) reasons for loss to follow-up are provided OR 2) participants lost to follow-up are adequately described by key characteristics and outcomes. No unacceptable level of bias is present	○ Yes ○ Partly ○ No
3. Prognostic factor measurement	3.1. A clear description of the main prognostic factors is provided (not covariates) AND/OR measures/methods regarding the main prognostic factors, at baseline and follow-up are adequately described to allow assessment of their validity and reliability. No unacceptable level of bias is present  ○ Objective measures (such as number of life-changing events) and clear description is ‘yes’. Poor/no description = ‘partly’  ○ Validated, subjective measures (eg, opinions) and clear description = ‘yes’. Poor/no description = ‘partly’  ○ Non-validated, subjective measures and clear description = ‘partly’. Poor/no description = ‘no’	○ Yes ○ Partly ○ No	4 × yes = yes 3.1 or 3.2 no = no OR 3.1 or 3.2 partly (no no’s), 3.3 or 3.4 no = no Else = partly	○ Yes ○ Partly ○ No
	3.2. The method and setting of measurement are the same for all study participants at baseline and follow-up	○ Yes ○ Partly ○ No
	3.3. Continuous variables are reported or appropriate cut-off points are used	○ Yes ○ Partly ○ No
	3.4. Authors appropriately described and dealt with missing data on prognostic factors	○ Yes ○ Partly ○ No
4. Outcome measurement	4.1. A clear description of medication adherence is provided AND/OR measures/methods of medication adherence (at baseline and follow-up) are adequately described, to allow assessment of their validity and reliability. No unacceptable level of bias is present  ○ Objective measures (such as pill count, refill rates, MEMS) and clear description = ‘yes’. Poor/no description is ‘partly’  ○ Validated, subjective measures (eg, questionnaires) and clear description = ‘yes’. Poor/no description = ‘partly’  ○ Non-validated, subjective measures and clear description = ‘partly’. Poor/no description = ‘no’	○ Yes ○ Partly ○ No	3 × yes = yes 4.1 or 4.2 no = no OR 4.1 or 4.2 partly (no no’s), 4.3 no = no Else = partly	○ Yes ○ Partly ○ No
	4.2. The method and setting of measurement are the same for all study participants at baseline (if measured) and follow-up	○ Yes ○ Partly ○ No
	4.3. Authors appropriately described and dealt with missing outcome data	○ Yes ○ Partly ○ No
5. Confounding measurement and account	5.1. The most important confounders are measured Examples of possible confounders: age; socioeconomic status/educational level/financial situation/illiteracy; social support/networks; depression/anxiety/emotional distress/lack of acceptance of disease; fatigue/pain/physical disability; self-efficacy/coping; regimen complexity/route of administration/number of medications; satisfaction with patient-provider relationship/autonomy	○ Yes ○ Partly ○ No
	5.2. A clear description of the most important confounders measured is provided AND/OR measures/methods of the most important confounders (at baseline) are adequately described to allow assessment of their validity and reliability. No unacceptable level of bias is present  ○ Objective measures (such as age, sex) and clear description = ‘yes’. Poor/no description is ‘partly’  ○ Validated, subjective measures (eg, opinions) and clear description = ‘yes’. Poor/no description = ‘partly’  ○ Non-validated, subjective measures and clear description = ‘partly’. Poor/no description = ‘no’	○ Yes ○ Partly ○ No	One of 5.1 to 5.4 = no (if 5.1 no, you can leave 5.2 to 5.5 open) OR 5.1 to 5.4 partly, 5.5 no = no All partly = partly OR 5.1 to 5.4 partly, 5.5 yes = partly OR none of 5.1 to 5.4 no, 5.5 no = partly OR 5.1 to 5.4 yes, 5.5 not yes = partly Else = yes	○ Yes ○ Partly ○ No
	5.3. The method and setting of confounding measurement are the same for all study participants at baseline	○ Yes ○ Partly ○ No
	5.4. Important potential confounders are accounted for in the study design (eg, matching for key variables/restriction) OR in analysis (stratification/multivariate techniques)	○ Yes ○ Partly ○ No
	5.5. Authors appropriately described and dealt with missing confounding data	○ Yes ○ Partly ○ No
6. Analysis	6.1. There is sufficient presentation of data to assess the adequacy of the analysis ‘Yes’, if main findings of the study and statistical methods used are clearly described: simple outcome data, crude data and estimates of random variability should be reported, so that the reader can check the major analyses and conclusions	○ Yes ○ Partly ○ No	4 × yes = yes At least 1 × no = no Else = partly	○ Yes ○ Partly ○ No
	6.2. The statistical tests used to assess the main outcome are appropriate For example, non-parametric methods should be used for small sample sizes	○ Yes ○ Partly ○ No
	6.3. The strategy for model building (ie, inclusion of variables) is appropriate, and is based on conceptual thoughts, a framework or a model For example: variables that do not correlate with the main outcome of interest are not used in multivariate analysis. Proper variables are entered in logical steps into the multivariate model	○ Yes ○ Partly ○ No
	6.4. The selected model is adequate for the design of the study For example: in repeated measures, a repeated-measure model should be used. If outcome is binominal, logistic regression should be used, etcetera. If delta outcome is being investigated, models should to be adjusted for baseline outcome values	○ Yes ○ Partly ○ No