In all cases, the pre-intervention value for each dependent variable was used as the covariate.
Effect sizes for primary and secondary outcomes were calculated by subtracting the pre-intervention value from the post-intervention value for both study groups.
To enhance precision, we averaged the values taken at 4 and 6 weeks to produce one intervention value for each diet in each participant.
Post-intervention values for dynamic balance was SMD -0.34 (95% CI -0.60 to -0.08), and for functional balance an overall outcome for post-intervention values revealed a SMD of 0.34, 95% CI -0.19 to 0.87 (additional file 2).
Statistical analyses of nutrient intake were performed on an intention-to-treat basis, including all participants who completed an initial diet recall, with the post-intervention values for dropouts set to the pre-intervention values.
There was small heterogeneity for post-intervention values for static balance with I2 0.00% (p = 0.896), middle heterogeneity with I2 73.2% (p = 0.024) for change values, and small heterogeneity for post-interventional values in dynamic balance with I2 42.6% (p = 0.083).
Based on the mean and S.D. post-intervention values for the CR and PBL groups in the thee CC dimensions, the sample size required to detect a significant difference would be 77 physicians per group, or a total of 154 physicians.
At 2 months after the intervention ended, no additional significant changes in the PSS, PSQI or the PSQI components were observed, but nor did scores return to pre treatment values for the intervention group.
In order to comprehensively assess whether an intervention provides value-for-money, information on non-medical resource use and productivity losses should be sought and taken into account, even though not required in assessment guidelines for some agencies (e.g. NICE).
But governments are notoriously bad at picking industrial winners, and even if they succeed, there are questions about whether their interventions provide value for money.
