Title: Utilization of cervical cancer screening and its associated factors among women of child-
bearing age in Mangochi district, Malawi: a facility-based cross-sectional study
Version: 0 Date: 10 Apr 2023
Reviewer's report:
REVIEW COMMENTS
A cross-sectional study was undertaken in five health facilities from June to July, 2019 to
examine the associations between health beliefs and attitudes and CCS uptake among women
of child-bearing age in Mangochi, Malawi. A total of 482 women between 18-49 years were
interviewed.
General Comments:
There is a disconnect between the title of the work and the data collected which makes it difficult
to see why the authors have chosen to phrase the title in this way. It is not clear how the study
investigated health system factors mediating cervical screening uptake. What is clear is that the
participants were given a questionnaire eliciting their knowledge of and attitudes to screening
uptake. The study only has merit if it is presented as such. In its current form, the authors may
be overstretching the evidence at hand.
Furthermore, I will contend that the approach used by the authors to answer the research question
is quite misleading and flawed or that the research question seems to have changed after data
collection. This position could be rebutted by an appropriately large sample size that allows all
variable strata to have a count of at least 5. Unfortunately, Table 1 reveals why every reader
should be concerned: the distribution of the dependent variable is so skewed that most tests will
return a significant p-value. Authors should explain why their data analysis is not in violation
of the assumption for the chi-sq test and thus make their conclusions flawed.
Background, Line 15: Change to few
Methods, line 19: The methods section needs to be rewritten with more detail.
Results, Line 23: …with a history of CCS
Conclusion, Line 40: It is unclear what the authors meant to convey here. Consider revising this
statement to indicate clearly exactly what needs to be prioritized: the factors, or some courses
of action. In doing so, authors should be mindful of the limitation imposed by a cross-sectional
design.
Study design, Line 126: The authors should indicate adequate detail in the Methods to make
the work reproducible. Readers don’t need to read another work if they don’t want to. Merely
saying it has been published elsewhere does not suffice. Perhaps the data presented in this report
could have been presented in the cited paper.
In any case, the use of a cross-sectional design significantly impairs the study’s appropriateness
given the question the authors seek to answer with the data at hand. The authors should be guided
by the adage, “association does not infer causality”.
Questionnaire, Line 142: I disagree that a woman’s willingness is a health system factor. This
may be misleading.
Questionnaire, Line 144: I disagree that a woman’s HIV status, history of multiple sex partners
etc are individual need factors. This may be misleading
Key variables, Line 148: Authors should consider writing this section in prose and not in bullet
form.
HIV status, Line 156: Consider removing numbering
HIV status, Line 159: Was HIV testing outcome by self-report or was it actually performed by
the authors? In the case of the latter, authors need to clarify how testing was done
Life time sex partners, Line 163: Consider removing numbering
Had participants ever heard of CC, Line 168: Consider removing numbering
Source of CC information, Line 173: Consider removing numbering
Level of knowledge, Line 180: This paragraph has been written without numbering. Consider
writing other paragraphs in this format without breaking up into numbered lines. See previous
comments
Level of belief, Line 197: Consider removing numbering. See comment above
Recommendation for CCS, Line 233: Consider removing numbering
Willingness to be screened, Line 239: Consider removing numbering
Distance to the health facility, Line 244: Rephrase as “data on distance…”
Distance to the health facility, Line 246: Authors should make data collection more robust and
less open to bias. The data processing used here sounds belated and might introduce bias
Distance to the health facility, Line 249: Consider removing numbering
Statistical analysis, Line 255: Define abbreviation if possible
Results, Line 262: I will contend that the approach used by the authors to answer the research
question is quite misleading and flawed. This position could be rebutted by an appropriately
large sample size that allows all variable strata to have a count of at least 5. Unfortunately, Table
1 reveals why every reader should be concerned: the distribution of the dependent variable is so
skewed that most tests will return a significant p-value. Authors should explain why their data
analysis is not in violation of the assumption for the chi-sq test.
Results, Line 285: The value of the cell expected should be 5 or more in at least 80% of the cells,
and no cell should have an expected of less than one.
Discussion, Line 308: This point is misleading. The authors should be guided by the adage,
“association does not infer causality”. Refer to comments on choice of study design
Limitation, 394: Authors should desist from the use of this phrase. Every publication should be
reported in full to allow reproducibility. I would argue that there is no basis to split the data into
separate reports since they address the same question
Conclusion, Line 398: The conclusions are flawed because of the statistical violation mentioned
above. In a study where less than 20% of the subjects fall within one category of the dependent
variable, the distribution of all predictors is going to be skewed.  Since the outcome is not evenly
distributed in the population, a retrospective cohort design would have been more appropriate
allowing the authors to recruit even numbers of exposed and unexposed subjects
Availability of data, Line 422: The authors should consider attaching data as a supplementary
file in line with standard reporting requirements
Acknowledgement, Line 437: This section is for people who made a contribution to the work but
did not meet the requirements for authorship. I am not sure acknowledging study participants
is standard practice: if it were, every paper would acknowledge participants. Typically, anyone
who cannot be named is not eligible to be acknowledged.