Table 4 Possible effect modifiers that may contribute to between study variability

Different Risk of Bias

 Studies with high RoB might show large effect than those with low RoB.

Different study Population:

 Baseline risk like gender, age (e.g., in some interventions, the effect could be larger in infants than in adolescents).

 Disease severity (e.g., in children with severe diseases the effect of x intervention might be smaller than in case of patients with mild disease).

 Treatment setting (e.g., patient with asthma enrolled from the emergency room will have different characteristics than those enrolled from the outpatient clinic).

Different Interventions:

 Dose (larger doses are expected to be associated with larger effect ad sometimes with larger effect in terms of side effects).

 Route (intravenous administration may have larger effect if oral administration is impacted by absorption or hepatic metabolism).

 Duration (using the medication for longer duration may be associated with larger effect compared to shorter duration).

Different comparators:

 Different standards of care when the standard of care is the comparator (e.g., in a diarrhea study, oral rehydration solution (ORS) is given to the control group in study A vs. ORS+ zinc supplement given to the control group in study B).

Different ways in Outcome assessment:

 Definition (e.g., if fever is defined as 38.0 C in study A vs. 39.0 C in study B, this may result in diagnosing more patients with the fever in the study A).

 Measurement (e.g., if fever is measured using rectal temperature, compared to axillary temperature in another study; or standard methods in one study compared to non standard way).