When process evaluation has been conducted to interpret trial outcomes, interpretation needs to be clear in the published papers, with process evaluation data linked, in discussion, to trial outcomes.
If the likelihood of improving one level is not similar across the entire range of defined outcomes, interpretation of the common OR is highly problematic.
The results of this literature review indicate that in cardiovascular specialty journals with high impact factors, sex, despite being a biological variable that could affect outcomes, interpretation and applicability of data, is not reported consistently.
Although sex and gender could affect the outcomes, interpretation and applicability of data, it is not consistently reported in cell studies [ 8, 9], even when the effects of sex hormones are analysed [ 10, 11].
Moreover, the challenges related to the data collection process included: differences in response rates between web-based and paper-based questionnaires, validity of self-reported outcomes, interpretation of clinical measurements of women using hormonal contraceptives, and inter- and intra-observer variation of the ultrasound measurements.
These findings have necessary implications for survey design and outcome interpretations.
Finding quantitative, site-specific data for model-input parameters and outcome interpretations in Afghanistan is a challenge similar to those faced in other countries (e.g., Silliman et al. 2007).
The main limitation is that our outcome interpretations are dependent upon a small sample size.
It is paramount to assess the psychometric properties of self-assessment tools in order to check the tests' reliability and validity, also to enable proper outcome interpretation.
This scale was designed to be self-completed by the subjects, but unfortunately in a developing country with low literacy this had affected its outcome interpretation.
