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Record W4386927155 · doi:10.6000/1929-6029.2023.12.16

Dysmenorrhea Impact and Insights: A Statistical Analysis among Allied Health Professional Students in West Bengal, India

2023· article· en· W4386927155 on OpenAlexvenueno aff
Haimanti Goswami, Debolina Kumar, Swarnava Biswas

Bibliographic record

VenueInternational Journal of Statistics in Medical Research · 2023
Typearticle
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsWest bengalMenstruationDescriptive statisticsMedicineFamily medicineAlternative medicineData collectionPsychologyDemographySocial scienceSocioeconomicsPathologySociology

Abstract

fetched live from OpenAlex

Introduction: Dysmenorrhea is a prevalent gynecological disorder that is characterized by the presence of unpleasant menstrual cramps. This condition has been found to have significant medical, psychological, and social implications for individuals who experience it. Although commonly seen as an inherent characteristic of a properly functioning reproductive system, it can potentially operate as a diagnostic tool for underlying illnesses. Regrettably, dialogues pertaining to dysmenorrhea are sometimes prohibited, particularly among males, within diverse cultural contexts.
 Objective: The primary objective of this study is to evaluate the level of knowledge and attitudes among allied health professions students enrolled at various universities of West Bengal (WB), India with regard to dysmenorrhea. This study aims to examine the impact of cultural variables on the knowledge and communication surrounding dysmenorrhea, specifically within conservative Indian districts.
 Methods: The study sample consisted of 494 students enrolled in allied health professions faculties at different universities of WB. Data collection took place from September 2021 to February 2023. A meticulously designed survey was employed to gather data pertaining to the various sources of knowledge, levels of awareness, attitudes toward discussing dysmenorrhea, and willingness to engage in conversations about menstruation with prospective females. Data interpretation involved the utilization of statistical analysis techniques, such as descriptive statistics and correlation analysis.
 Results: In terms of demographic composition, the study consisted of 86% female participants and 14% male participants. The mean knowledge scores of females (14.41 ± 3.14) were found to be considerably higher compared to males (13.75 ± 4.56). The primary sources of information were the internet (58.3%), maternity figures (48.8%), and educational institutions (46.2%). An observed positive connection (r = 0.244) was found between age and knowledge levels. The participants exhibited a general hesitancy to openly engage in conversations on menstrual symptoms, however, they demonstrated a readiness to engage in discussions about menstruation with their prospective daughters.
 Conclusions: The present study brings attention to the gender discrepancies in knowledge levels pertaining to dysmenorrhea among allied health professions university students of WB. Additionally, it emphasizes the influence of cultural norms on knowledge acquisition and communication around this topic. The statement underscores the need for destigmatization initiatives, comprehensive teaching on menstruation health, and fostering open communication within academic institutions and the broader community. The aforementioned findings offer valuable insights that can inform future educational endeavors and healthcare procedures within this particular subject.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.572
Teacher spread0.504 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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