Title: KNOWLEDGE AND ATTITUDE TOWARDS PRECONCEPTION CARE AND
ASSOCIATED FACTORS AMONG WOMEN OF REPRODUCTIVE AGE WITH CHRONIC
DISEASE IN AMHARA REGION REFERRAL HOSPITALS, ETHIOPIA, 2022
Version: 1 Date: 09 Oct 2023
Reviewer:  Desire Habonimana
Reviewer's report:
Review of the manuscript
KNOWLEDGE AND ATTITUDE ON  PRECONCEPTION CARE AND ASSOCIATED
FACTORS AMONG WOMEN OF REPRODUCTIVE AGE WITH CHRONIC DISEASE
WHO HAVE FOLLOW-UP AT AMHARA REGIONAL STATE REFERRAL HOSPITALS,
ETHIOPIA, 2022; MULTICENTER CROSS-SECTIONAL STUDY
Title: the title is very long and less accurate. Plus, there is inappropriate use of words e.g., “to
have follow-up” and “at … hospitals” do not seem to be the ‘correct’ wording.
Abstract: already, the abstract demonstrates the need for “language improvement” as I notice
deficient academic writing and lots of grammatical flaws.  The methods section is scant and does
not clearly tell what they did and how they did it e.g., they allude to “multistage sampling” and
“data collection” but we can’t tell which sampling stages and which data, etc. Right in the first
sentence of the results, authors use an uncommon acronym “PCC” without however having put a
mention of this earlier in the text, and this testifies the fact that they necessarily need an academic
proof-reader before sending to a journal. I understand PCC stands for preconception care, but
readers don’t need to figure out or puzzle over anything which should rather be made clear. Most
importantly, results need to be rewritten e.g., “women who attended formal education (AOR
xxx) … were significantly associated with knowledge on PCC” is incorrect. The true meaning
is that formal education, etc. etc. are associated with PCC knowledge, not women. The same
issue presents in the next sentence.
Introduction: the introduction continues to demonstrate language concerns, albeit minor,
which need to be comprehensively addressed by a more academic proof-reader. Also, ideas
flow awkwardly, with some paragraphs lacking sentence coherence e.g., para L85-89 seems
to contradict L54-57. Other issues include long and vague sentences e.g., L90-93 which
further lacks a reference that proves that women with chronic diseases are likely to develop
complications during pregnancy. Most importantly, the introduction lacks a detailed note on
which underlying or pre-existing health conditions they refer to (e.g., can we assume all chronic
conditions are equally associated with an increased risk of maternal complications?).
Methods:
Study area and period: unnecessarily long, could be shorten. The use of “was” makes little sense
as prevailing truth can’t be in the past e.g., Amhara national regional state was served by 80
hospitals, 220 health centers, and 2941 health posts. Did the government build new facilities
after the study? This sentence could be, for instance, “there are 80 hospitals, etc. in Amhara
national regional state”. Other sentences are very unclear: e.g., around 1700 reproductive-age
women with chronic disease were expected to have  follow–up at follow–up OPD for six
weeks at the time of the study (which chronic affections? What does “to have follow-up at
follow-up OPD” mean, in academic writing?). Next sections, of which there are many subtitles
with short content, prove unsatisfactory. For instance, authors doubled the sample size with a
mere justification that they used multistage sampling and this lacks scientific reference. They
randomly selected 4 facilities (from 8 facilities) and used a proportional sampling based on
the total number mothers with chronic conditions: this is unclear, which chronic conditions?
Researchers randomly selected the “first participant” and then every 2nd participant: does this
mean that your ‘step’ was just 2? Why did you choose this step?
Operational definitions: they are inaccurate. For example, they used the mean score (19.4) to
define good and bad knowledge. This approach isn’t genuine. I would suggest, if possible,
employing another statistical approach e.g., principal component analysis (PCA) to generate a
continuous knowledge score. The cut-off to the mean strongly penalises individuals e.g., there
should not be a difference between individual i who scored 19.3 and another individual with
a score of 19.5; for instance. Similarly, another statistical approach (PCA?) should be used to
analyse Likert scale data, instead of just adding values (1 to 5) and computing a mean by dividing
by six … and I don’t know why six (questions). This is fundamentally untrue and ignore possible
correlations between questions. There is an attempt to define “chronic diseases” but little is
meant in relation to the current study. And what does “adherence to follow up appointments”
has to do in the current study?
Review and rewrite all sections. For instance, you mention that the data collection form had
five sections, and you only give four. And the frequent use of capital letters inside a sentence
is appallingly unprofessional.
I did not continue to read as already major edits.
I will be happy to read a much better improved version in the future.