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Table 1 Definition of the domains of the Risk of Bias tool and the support for judgement according to the Cochrane handbook for systematic reviews of interventions

From: Avoidable waste related to inadequate methods and incomplete reporting of interventions: a systematic review of randomized trials performed in Sub-Saharan Africa

Domains (type of bias) Review authors’ judgement
Low risk of bias High risk of bias Unclear risk of bias.
Random sequence generation (selection bias) The investigators describe a random component in the sequence generation process such as drawing of lots The investigators describe a nonrandom component in the sequence generation process. Usually, the description would involve some systematic, nonrandom approach Insufficient information about the sequence generation process to permit judgement of “low risk” or “high risk”
Allocation concealment (selection bias) Participants and investigators enrolling participants could not foresee assignment because of the use of, for example, sequentially numbered, opaque, sealed envelopes to conceal allocation Participants or investigators enrolling participants could possibly foresee assignments and thus introduce selection bias, such as allocation based on assignment envelopes used without appropriate safeguards (e.g., if envelopes were unsealed or nonopaque or not sequentially numbered) Insufficient information to permit judgement of “low risk” or “high risk”. This is usually the case if the method of concealment is not described or not described in sufficient detail to allow a definite judgement – for example, if the use of assignment envelopes is described, but it remains unclear whether envelopes were sequentially numbered, opaque and sealed
Blinding of participants and personnel (performance bias) Any one of the following:
• No blinding or incomplete blinding, but the review authors judge that the outcome is not likely to be influenced by lack of blinding
• Blinding of participants and key study personnel ensured, and unlikely that the blinding could have been broken
Any one of the following:
• No blinding or incomplete blinding, and the outcome is likely to be influenced by lack of blinding
• Blinding of key study participants and personnel attempted but likely that the blinding could have been broken, and the outcome is likely to be influenced by lack of blinding
Any one of the following:
• Insufficient information to permit judgement of “low risk” or “high risk”
• The study did not address this outcome
Blinding of outcome assessment (detection bias) Any one of the following:
• No blinding of outcome assessment, but the review authors judge that the outcome measurement is not likely to be influenced by lack of blinding
• Blinding of outcome assessment ensured, and unlikely that the blinding could have been broken
Any one of the following:
• No blinding of outcome assessment, and the outcome measurement is likely to be influenced by lack of blinding
• Blinding of outcome assessment, but likely that the blinding could have been broken, and the outcome measurement is likely to be influenced by lack of blinding
Any one of the following:
• Insufficient information to permit judgement of “low risk” or “high risk”
• The study did not address this outcome
Incomplete outcome data (attrition bias) Any one of the following:
• No missing outcome data
• Reasons for missing outcome data unlikely to be related to true outcome (for survival data, censoring unlikely to be introducing bias)
• Missing outcome data balanced in numbers across intervention groups, with similar reasons for missing data across groups
• For dichotomous outcome data, the proportion of missing outcomes compared with observed event risk not enough to have a clinically relevant impact on the intervention effect estimate
• For continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes not enough to have a clinically relevant impact on observed effect size
• Missing data have been imputed using appropriate methods.
Any one of the following:
• Reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across intervention groups
• For dichotomous outcome data, the proportion of missing outcomes compared with observed event risk enough to induce clinically relevant bias in intervention effect estimate
• For continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes enough to induce clinically relevant bias in observed effect size
• “As-treated” analysis done with substantial departure of the intervention received from that assigned at randomization
• Potentially inappropriate application of simple imputation.
Any one of the following:
• Insufficient reporting of attrition/exclusions to permit judgement of “low risk” or “high risk” (e.g., number randomized not stated, no reasons for missing data provided)
• The study did not address this outcome.