Title: Improving intervention design to promote cervical cancer screening among hard-to-
reach women: assessing beliefs and predicting individual attendance probabilities in Bogotá,
Colombia.
Version: 4 Date: 10 Dec 2021
Reviewer's report:
The manuscript has improved. There are still issues that need clarification. First, the aim of
the study has been now defined further “This study aims to inform the design of behavioural
interventions to increase attendance levels for cervical cancer screening, among hard-to-reach
low-income women.” and there are three different approaches: first, to study the reliability and
validity of the cervical-cancer belief assessment in the study context; next, to provide descriptive
statistics and pairwise comparison of means to analyse the health believe constructs; and finally
to develop a model to predict individual no-show probabilities using the survey results, patient
sociodemographic information and appointment characteristics. My apologies, but I have still
difficulties to follow all these different phases of the analyses because of the overall length. The
descriptive analyses take lots of space, and the same observation can show up in slightly different
light in the different phases of analysis. The paper would still improve, in some of the ‘interim’
analysis phases would be shortened and possible added into Annex, and more emphasis could
be given to the results of the final models.
I also understood from the above definition of the aims that it would be the final set of analyses,
namely, the analyses of the no-show probabilities based on the models using the combined
information on survey results on health beliefs, patient sociodemographic information and
appointments characteristics that should conform the basis for the conclusions and suggestions
about further interventions and possible tailoring of them by population groups. Now it seems
to me that the conclusions in the Abstract, or in a large extent in the main text, do not clearly
come from such results. Would it be possible to formulate conclusions better, adding  on exactly
what interventions and for which population groups could be suggested based on this study?
Further methodological comments:
Considering Table 5, I understood from the response from the authors that all the items of health
beliefs were included in just one model. Such a model could be problematic to interpret because
correlations between the responses to the various questions. Therefore, also the crude no-show
probabilities for every variable would be valuable.
I also found problematic to get the confidence limits for the ORs, could they be converted to
the same scale as the ORs. Alternatively, would it be possible to present just the model-based
predicted no-show probabilities, with their confidence intervals, from the final model(s)  instead
of the ORs? The latter way of showing the results would be preferable, because the OR point
estimates are difficult to be interpreted for so common outcomes as here and then you could
get rid of such a problem.
I also found it misleading in Tables 5 and 6 that the outcome with showing up to the appointment
was coded with 1 (and no-show by 0) so it was not the no-show probability but the ‘showing
up’ or attendance probability that was modelled; it would be easier for the reader if you would
code the probability of no-show throughout (i.e. no-show with the value 1).
I understood that the model for the Table 5 was a separate one compared with the table 6, right?
Or was it the same model? Please specify. Would it be possible to also show analyses on possible
effect modification of the various explanatory variables on the no-show probabilities? I think
that the potential of effect modification would be more important for the main aims of the study,
than adjustment.
In the Table 2 of the Additional file, would it be possible to give also the absolute numbers in
addition to the percentages? Specify also (and add a column if relevant) if there were persons
who did not respond to the specific item. Furthermore, we proposed in the first round of review
that also the no-show probabilities should be provided by the response categories, it could be
done easily if the absolute numbers were provided.
And please provide the (crude) no-show probabilities also for the variables of the Table 1 of
the Additional file.
There are some corrections required in the Table 1, as it seems (when comparing with the Table
1 of the Additional file) that age 30-49 should be 30-39? Same in the text on line 167?
There seem to be some misprints also in the Table 1 of the Additional file, e.g. the first category
for age >30 should be <30? And <59 should be >59? For lead time, category >=3 should be
<=3? And in the Table 2 ‘neural’ should read  ‘neutral’.