X hits on this document





113 / 156

    • Consider all measurement methods pertinent to the corresponding findings (not just the implementation variables). For example, in the case of the intermediate and final outcomes findings, the method of measuring OHSMS variables might also be relevant.

  • 12.

    Were appropriate statistical tests conducted on the implementation data?

    • In the comment box following your response, note the rationale for your selection.

    • The issue of whether adjustment for confounders took place is covered in Q9. In this question, one is only concerned about whether such adjustments were done correctly, if they were done

    • Do not fear choosing the option of “reviewer not qualified to answer.” We are simply using this response to flag where we need expertise from elsewhere in the group or even external to the group. If two reviewers have selected this option, then we seek expertise from elsewhere in the group, and failing this, use our external consult. If only one reviewer has selected this option, then a consensus answer can be formulated, if the remaining reviewer is highly confident of his/her answer. If not, then expertise should be sought elsewhere in the group or externally if required.

    • Was the test appropriate for the sample size and type of data?

    • If no statistical tests were used, and you think they were not needed, select the answer corresponding to this. If no statistical tests were used and you think they should have been, then use one of the following three options: minor deficiencies; inappropriate statistical test, which might modify the conclusions; inappropriate statistical tests, which could substantially affect conclusions.

    • Consider issues of statistical power in Q43 not here.

  • 13.

    Are you confident that the measurement methods did not introduce bias to the corresponding intermediate outcome(s) findings?

  • In the comment box following your response, note the rationale for your selection.

  • This question addresses measurement bias; i.e., systematic error arising from inaccurate measurement (or classification) of subjects on study variable(s).

  • Consider the validity of the measurement method; consider reliability to the extent that could bias findings. Examples:

    • o

      The introduction of an OHSMS could alter reporting practices, so this potential source of bias should be eliminated by some means

      • o

        Consider whether blinding was used in the assessment of intermediate outcome(s); e.g., was the person who observed

Institute for Work & Health


Document info
Document views639
Page views643
Page last viewedFri Jan 20 20:20:45 UTC 2017