Title: Factors Associated with Premenstrual Symptoms: A Study among Graduate-Level
Students of the Institute of Science and Technology, Tribhuvan University
Version: 3 Date: 04 Jun 2025
Reviewer's report:
The abstract provides a concise overview of the study’s background, methods, results, and
conclusions, but it lacks specificity in some areas and omits key details that would enhance
its informativeness. For example, it states that “40% reported experiencing Premenstrual
Symptoms” but does not clarify whether this refers to PMS or PMDD, nor does it specify
the severity distribution (e.g., mild, moderate, severe). Additionally, the methods description
is vague, mentioning “institutional-based cross-sectional research methods” and a “self-
administered questionnaire” without detailing the study population size or key tools like
the PSST and DASS-21. The results section lists significant factors (e.g., age at menarche,
dysmenorrhea) but does not contextualize their relative importance or practical implications.
To improve, the abstract should specify the sample size (n=285), clarify the use of PSST for
PMS assessment and DASS-21 for stress, and briefly note the severity of symptoms (e.g., “40%
reported PMS, with 56.49% experiencing joint/muscle pain”). Additionally, the conclusion
should highlight one key actionable implication, such as stress management interventions, to
make the findings more impactful. Aim for 150–250 words, ensuring all sections (background,
methods, results, conclusion) are balanced and precise.
The introduction adequately outlines the background of premenstrual symptoms (PMS) and their
prevalence but has gaps in clarity, specificity, and literature synthesis that weaken its foundation.
For instance, it broadly lists symptoms like “irritability, mood fluctuations, fatigue” but does
not clearly define PMS versus PMDD, which is critical given their different diagnostic criteria
(e.g., DSM-V for PMDD). The literature review cites global prevalence (e.g., 47.8% from a
meta-analysis) but inconsistently jumps between regions (e.g., Iran, France, Nepal) without
synthesizing how these findings relate to the study’s context in Nepalese students. The research
gap is mentioned (“there is a gap in the factors associated with the prevalence of PMS, especially
in the case of IOST, T.U.”), but it lacks specificity about why this population or institution is
unique. To address these issues, the introduction should clearly define PMS and PMDD, using
DSM-V criteria for clarity, and streamline the literature review to focus on studies most relevant
to Nepalese or South Asian populations, such as references 2 and 12. The research gap should
be sharpened by explaining why graduate-level students at IOST, T.U., might face unique PMS-
related challenges (e.g., academic stress). Finally, explicitly state the study’s hypothesis, such as
“We hypothesize that stress and menstrual health factors significantly influence PMS prevalence
among IOST students,” to guide readers.
The methods section provides a detailed description of the study design, population, and data
collection but has gaps in reproducibility, justification of methodological choices, and handling
of potential biases. For example, the use of the PSST and DASS-21 tools is well-documented,
with internal consistency reported (Cronbach’s alpha of 0.961 and 0.848, respectively), but
the manuscript does not justify why these tools were chosen over others (e.g., ACOG
criteria for PMS). The exclusion criteria (e.g., pregnancy, PCOD) are listed, but there is no
explanation of how these conditions were verified (e.g., self-report vs. medical records), risking
misclassification bias. Additionally, the statistical analysis section mentions dropping ordinal
logistic regression due to violated assumptions but does not provide diagnostic details (e.g., test
results for proportional odds assumption), which reduces transparency. To improve, justify the
choice of PSST and DASS-21 by citing their validation in similar populations (e.g., reference
15 for PSST). Clarify how exclusion criteria were confirmed, such as through medical history
questionnaires, and report specific diagnostic tests (e.g., Brant test for proportional odds) to
support the shift to binary logistic regression. Finally, address potential recall bias (noted in
limitations) by describing efforts to minimize it, such as using structured questionnaires with
clear timeframes (e.g., “symptoms in the past two cycles”).
The results section effectively presents descriptive and inferential findings but suffers
from inconsistent organization and incomplete reporting of data, which affects clarity
and interpretability. For example, Table 1 lists categorical variables (e.g., marital status,
dysmenorrhea) but does not provide p-values or test statistics to indicate significance in the
descriptive comparisons, making it hard to assess differences between PMS and non-PMS
groups. The multivariate analysis (Table 4) reports odds ratios for significant variables like
menstrual delaying medicine (OR=11.015) but omits non-significant variables tested in the
model, reducing transparency about the full regression. Additionally, Figure 1 is referenced
for physical symptoms, but the manuscript does not describe its format (e.g., bar chart, pie
chart) or ensure it is self-explanatory with a clear legend. To enhance this section, organize
results using subheadings (e.g., “Prevalence of PMS,” “Bivariate Analysis,” “Multivariate
Analysis”) and include p-values or test statistics in Table 1 for clarity. Report all variables
included in the multiple logistic regression, even non-significant ones, in a supplementary table
if space is limited. Ensure Figure 1 is clearly described in the text (e.g., “Figure 1: Bar chart
of physical PMS symptoms”) and includes a standalone caption with statistical annotations
(e.g., percentages with confidence intervals). Avoid interpretive statements like “moderately
associated” in the results, reserving them for the discussion.
The discussion provides a reasonable interpretation of findings but has gaps in depth, critical
engagement with limitations, and connection to broader literature. For example, it compares
the 40% PMS prevalence to a study in South India (reference 17) but does not explore why
the prevalence is lower than other Nepalese studies (e.g., 53.5% in reference 2), missing an
opportunity to discuss methodological or population differences. The strong association between
menstrual delaying medicine and PMS (OR=11.015) is noted, but the discussion lacks a detailed
mechanistic explanation, such as how norethisterone alters estrogen-progesterone balance,
despite citing reference 22. Additionally, the mention of “confounding factors” like academic
stress is vague, as these were not measured or controlled for in the analysis. To improve, deepen
the comparison with prior studies by discussing specific methodological differences (e.g., PSST
vs. other tools) and their impact on prevalence estimates. Provide a clearer biological rationale
for findings, such as linking hormonal fluctuations from menstrual delaying medicine to specific
PMS symptoms (e.g., mood swings via serotonin pathways). Explicitly address all limitations
(e.g., recall bias, lack of clinician input) and propose specific solutions, such as longitudinal
designs to reduce recall bias. Finally, suggest actionable interventions, like stress reduction
programs at IOST, to align with the study’s implications.
The conclusion summarizes key findings (e.g., 40% PMS prevalence, significant factors
like stress and dysmenorrhea) but is overly brief and lacks a strong call to action or
broader implications. For instance, it recommends stress management through “medication or
diverting minds” without specifying evidence-based strategies (e.g., mindfulness, counseling)
or addressing feasibility in the Nepalese context. It also mentions unexplored dietary factors
but does not integrate this into a cohesive future research agenda. To strengthen the conclusion,
concisely restate the main finding (e.g., “Stress and menstrual delaying medicine significantly
increase PMS likelihood among IOST students”) and propose specific, context-relevant
recommendations, such as “Implementing university-based stress management workshops could
mitigate PMS severity.” Include a focused future research direction, such as “Longitudinal
studies incorporating dietary assessments and clinical evaluations are needed to confirm these
findings.” Keep the conclusion to 1–2 sentences for brevity, ensuring alignment with the abstract
and discussion for consistency.