Dear Behnam

You can use the Standardized Mean Difference method to combine outcomes of similar nature measued with different scales. When lower is better, simply multiply by -1.

Best regards

http://handbook-5-1.cochrane.org/chapter_9/9_2_3_2_the_standardized_mean_difference.htm

As Martin said, simply multiply the reported or calculated effect (mean difference) by -1 when lower scores indicate improved function.

Great question. Usually, SMD is the preferred method. But, first I would check if the distribution of the outcome values is normally distributed.

In generic terms, the SMD parameter is defined as the difference in population means between two groups (often this difference represents the effect of some intervention), scaled by the population standard deviation of the outcome metric. Estimates of the SMD can be obtained from a wide variety of designs. I'd just like to add a strong importance of the advantage of reporting anything in meaningful units of the original measure wherever possible. Finally, if you use SMD you loose interpretability. These estimates may serve only as quantitative measures of the strength of evidence against the null hypothesis of no difference in the population between groups.

The SMD method does not correct for differences in the direction of the scale. If some scales increase with disease severity whilst others decrease it is essential to :

1. multiply the mean values from one set of studies by –1 or

2. to subtract the mean from the maximum possible value for the scale

It ensure that all the scales point in the same direction. The standard deviation does not need to be modified.

Kind regards,