Critical comment on a cramping conundrum: Awareness, impact, and treatment-seeking behavior regarding dysmenorrhea among college students in central Kerala

Dear Editor, I appreciate the article “A cramping conundrum: Awareness, impact, and treatment-seeking behavior regarding dysmenorrhea among college students in central Kerala” published in Muller Journal of Medical Sciences and Research 15 (2): P 97-100, July 2024–December 2024. However, I have a few concerns about the methods and results mentioned in the study. Authors have mentioned that “Six colleges (which do not train in nonmedical/paramedical subjects) were randomly selected out of the colleges in Pathanamthitta district. Thirty girls were randomly selected from the attendance register and interviewed after taking consent. A pilot-tested semi-structured questionnaire was used to interview the study participants who gave consent for participation.” How many total colleges are there in Pathanamthitta district out of which 6 colleges were randomly selected? This is not mentioned. How these 30 girls were selected? Were they all from these 6 colleges or from a single college and how the sample of 30 was taken as a pilot study? What was the reliability and validity of the research tool or semi-structured questionnaire? As pilot studies are not driven by hypothesis so formal power calculation is not required, but still justification of the sample size is required, and it needs to be based on the primary goal of the research study.[1] Authors cannot take a self-proclaimed sample for undertaking a pilot study. A well-planned pilot study should have clear goals, details of assessment of these goals, justification of sample size, and methodological rigor for how the pilot study would be conducted. In the Results section, authors have not used any statistical test except calculating the percentage to infer the results of this study. The authenticity of results is determined by the statistical test used by the investigators. Statistical analysis gives resuscitation to lifeless data and meaningless numbers.[2] Results would have been authenticated had the authors used a statistical test of significance to find the association of various demographic variables with the levels of knowledge and methods of management of dysmenorrhea among college students. For this purpose, Chi-square test should have been employed to find out the association of knowledge of dysmenorrhea and sociodemographic factors and methods of management of dysmenorrhea with sociodemographic factors. It would have been prudent had the authors included family history of dysmenorrhea and family income in the demographic variables as both these factors have a major influence in determining a women’s physiological and mental health. Furthermore, a logistic regression test could have been employed to see the relationship of family history of dysmenorrhea, family income, place of residence, poor knowledge, and history of chronic health conditions with dysmenorrhea. In descriptive research studies, logistic regression test calculates the probability of an outcome and determines the strength and direction of the relationships between variables, apart from handling both categorical and continuous data. Merely displaying the percentage does not make the results meaningful and justified. To validate the results, statistical data analysis is a must, as insufficient analysis paves the way for an array of errors ranging from study design to analysis to interpretation of results.[3] Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.