Reviewer's report
Title:HIV risks vary according to type of sex work in a cross-sectional survey
from Nagaland, India
Version:2Date:4 September 2014
Reviewer: Valerio Bacak
Reviewer's report:
1. I did not expect the authors to apply or develop a theory to support their
analysis, but instead, similar to what they have done in the paragraph they added
to the Discussion section, explain the underlying rationale of the study – i.e. why
we would expect to see an association between place of sex work and
STI-related outcomes. Providing such an explanation would better motivate the
analysis by showing how the results can go either way.
In that respect, the authors should adapt the paragraph they added in the
Discussion section for the introduction. I think the authors did a fine job in that
paragraph – as well as in the additions to the Introduction section. With some
rearranging the authors could make the paper more compelling. The authors
should also add, at least briefly, some conceptual background. I would strongly
suggest the authors consult the following review paper that could provide
theoretical motivation: Gieryn, T. F. (2000). A space for place in sociology.
Annual Review of Sociology, 463-496.
I would like to highlight, by the way, that even though the paper is an “applied”
paper, as the authors write in their response, that does not relieve the authors of
the responsibility to convince the reader that the associations they find in their
analysis are nothing more than a product of chance. But I don’t expect the
authors to further expand on this.
2. I am not convinced with the authors’ response that “This applied method is
common practice.” I would like to see an explanation of what exactly the authors
refer to by the “parsimonious” model and show, by using references to a
literature that shows how this method is “common practice.” As it stands, it
seems that a “parsimonious” model is simply a model with few covariates, mainly
demographic characteristics, chosen relatively haphazardly. In other words, the
authors should provide backing for their models – and these are still models that
aim to represent some underlying social and behavioral processes – before they
can make a strong contribution. Alternatively, I would encourage the authors to
consider automated procedures for model selection. A most simple example is
something along the lines of stepwise regression, with all its known limitations.
Better methods are available, though, but any method would probably do a fine
job in this case, particularly given that the aim is not to generalize the results. I
would suggest the authors consult chapter 6 in the clearly written book by James
et al. (2013): An Introduction to Statistical Learning with Applications in R (freely
available at: http://www-bcf.usc.edu/~gareth/ISL/).
3. I would insist that the authors be very cautious when discussing the
implications of their findings for prevention efforts. For instance, in the last
sentence in the Introduction, the authors write: “The findings from this analysis
can be used to design more efficient, better targeted HIV prevention interventions
[7].” Given the limitations of this study, the authors could at most say that their
findings can help inform discussion on the most efficient intervention.
Level of interest: An article whose findings are important to those with closely
related research interests
Quality of written English: Acceptable
Statistical review: Yes, and I have assessed the statistics in my report.
Declaration of competing interests:
I declare that I have no competing interests.