| Literature DB >> 35242785 |
Sabyasachi Maity1, Jadzia Wray2, Tamara Coffin2, Reetuparna Nath3, Shreya Nauhria4, Ramsagar Sah5, Randall Waechter1, Prakash Ramdass6, Samal Nauhria7.
Abstract
BACKGROUND: The stressful academic schedule of medical students poses an obvious challenge to their daily lifestyle. Psychosomatic discomfort poses a significant risk for inaccurate self-medication for ameliorating menstrual complications and feeling better, thus directly impacting personal and academic wellbeing.Entities:
Keywords: dysmenorrhea; medical students; menstrual disturbances; pre-menstrual dysphoric disorder; pre-menstrual syndrome; prevalence; undergraduate students
Year: 2022 PMID: 35242785 PMCID: PMC8886240 DOI: 10.3389/fmed.2022.821908
Source DB: PubMed Journal: Front Med (Lausanne) ISSN: 2296-858X
Figure 1PRISMA protocol of literature search process.
Qualitative synthesis of the 26 included studies.
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| Alkhamis et al. ( | Saudi Arabia | Cross sectional | Not indicated | Female medical student, 20–23 | PMS, PMDD/self-administered questionnaire | 258 | 29 (11.2%) | 32 (12.5%) | Not indicated adequately |
| Kushwaha et al. ( | Nepal | Cross sectional | October 2019 to December 2019 | Female medical student, 17–25 | Primary dysmenorrhea/verbal multidimensional scoring system (VMSS) | 75 | Not indicated adequately | Mild primary dysmenorrhea is prevalent in 42 (49.4%) MBBS students and moderate to severe primary dysmenorrhea is prevalent in 33 (56.9%) MBBS students | |
| Al-Shahrani ( | Saudi Arabia | Cross sectional | Not indicated | Female medical student, 18–25 | PMS/The Premenstrual Syndrome Scale (PSS) | 388 | 252 (64.9%) | Not indicated adequately | 152 (39.2%) |
| Hashim et al. ( | Saudi Arabia | Cross sectional | September 2017 and May 2018 | Female medical student, 19–22.4 | Primary dysmenorrhea/SF-36 | 336 | Not indicated adequately | Not indicated adequately | 269 (80.1%) |
| Shah and Christian ( | India | Cross sectional | Not indicated | Female medical student, 18–24 | PMS and PMDD/Premenstrual Symptoms Screening Tool | 166 | 31 (18.9%) had moderate to severe PMS | 10 (6.09%) | Not indicated adequately |
| Kanti et al. ( | India | Cross sectional | July to August 2019 | Female medical student, 21–23 | PMS and Dysmenorrhea/Menstrual symptom questionnaire and menstrual bleeding questionnaire | 150 | 86 (56%) | Not indicated adequately | 86 (56%) |
| Minichil et al. ( | Ethiopia | Cross sectional | May to June, 2019 | Female medical student, 18–26 | PMDD/DSM-5 | 386 | Not indicated adequately | 134 (34.7%) | Not indicated adequately |
| Bilir et al. ( | Turkey | Cross sectional | December 2017 and January 2018 | Female medical student, 18–27 | PMS and Dysmenorrhea | 50 | Not indicated adequately | Not indicated adequately | 12 (26%) |
| Özder and Salduz ( | Turkey | Cross sectional | May 2017 to June 2017 | Female medical student, 17–26 | Dysmenorrhea/structured questionnaires to state socio-demographic and medical characteristics, and their dysmenorrheal status and habits, and Visual analog scale to assess the severity of dysmenorrhea | 413 | Not indicated adequately | Not indicated adequately | 329 (79.7%) |
| Verma et al. ( | India | Cross sectional | Within 1 weeks' time | Female medical student, 17–28 | PMS and Dysmenorrhea | 183 | 156 (85.24%) | Not indicated adequately | 111 (60.66%) |
| Majeed-Saidan et al. ( | Pakistan | Cross sectional | December 2017 to May 2018 | Female medical student, 12–51 | PMS/ACOG PMS diagnostic criteria | 280 of them were medical students | Moderate PMS: 166(59.4%). Severe PMS 22 (8%). But no differentiation for medical students. | Not indicated adequately | Not indicated adequately |
| Nama et al. ( | India | Cross sectional | June 1, 2020 to July 31, 2020 | Female medical student, 19–25 | PMS and Dysmenorrhea/pre tested, structured, self-administered questionnaire | 100 | 83 (83%) | Not indicated adequately | 86 (86%) |
| Zalat et al. ( | Saudi Arabia | Cross sectional | Academic year [2017–2018] | Female medical student, 21–23 | PMS/Premenstrual Evaluating Questionnaire (PEQ) based on the criteria of the American college of obstetrics & gynecology (ACOG) for the diagnosis of PMS | 98 | 54 (55.10 %) | Not indicated adequately | Not indicated adequately |
| Yadav and Taneja ( | India | Cross sectional | Not indicated | Female medical student, 17–22 | PMS and Dysmenorrhea/A self-descriptive cross-sectional study | 200 | 64 (32%) | Not indicated adequately | 140 (70%) |
| Sharma et al. ( | India | Cross sectional | Not indicated | Female medical student, 18–20 | PMS/A self-administered questionnaire | 209 | 121 (57.9%) | Not indicated adequately | Not indicated adequately |
| Shamnani et al. ( | India | Not indicated | Not indicated | Female medical student, 18–25 | PMS and PMDD/diagnosis criteria proposed by American College of Obstetrician and Gynecology | 240 | 156 (65%) | 29 (12%) | Not indicated adequately |
| Rajkumari et al. ( | India | Stratified random sample method | Not indicated | Female medical student, 18–22 | PMS/Inventory to Measure Psychosocial Stress (IMPS) and menstrual questionnaire | 81 | 65 (80%) | Not indicated adequately | Not indicated adequately |
| Ghaderi et al. ( | Iran | Cross sectional | April 2013 to July 2013 | Female medical student, 19–25 | Dysmenorrhea/visual analog scale (VAS) | 197 | Not indicated adequately | Not indicated adequately | 194 (98.4%) |
| Acikgoz et al. ( | Turkey | Cross sectional | March to June 2016 | Female medical student, 17–31 | PMS/Premenstrual syndrome scale (PMSS) | 100 | 52 (52%) | Not indicated adequately | Not indicated adequately |
| Rumana Akbari et al. ( | India | Cross sectional | For a period of six months in 2015 | Female medical student, 20–25 | PMS/PMS self-evaluation questionnaire | 270 | 84 (31.1%) | Not indicated adequately | Not indicated adequately |
| Katwal et al. ( | Nepal | Cross sectional descriptive study | 1st Dec. 2012 to 31st Jan. 2013 | Female medical student, 16–24 | Dysmenorrhea/questionnaire to complete | 184 | Not indicated adequately | Not indicated adequately | 123 (67%) |
| Aryal et al. ( | Nepal | Cross sectional | November to December 2015 | Female medical student, 17–25 | PMS and PMDD/American College of Obstetrics and Gynecology (ACOG) criteria. The diagnosis of PMDD was based on Diagnostic and Statistical Manual of Mental Disorders (DSM-V). | 185 | 113 (61.1%) | 72 (38.9%) | Not indicated adequately |
| Jaiprakash et al. ( | Malyasia | Cross sectional descriptive study | March to May 2012 | Female medical student, 17–30 | PMS and Dysmenorrhea/questionnaire and verbal-multi-dimensional scoring system | 215 | 153 (91.6%) | Not indicated adequately | 167 (78%) |
| Goweda et al. ( | Saudi Arabia | Cross sectional | During the academic year 2013/2014 | Female medical student, Age not indicated | PMDD/Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition | 183 | Not indicated adequately | 67 (36.6%) | Not indicated adequately |
| Raval et al. ( | India | Cross sectional | January to August, 2012 | Female medical student, 17.3–20.5 | PMS and PMDD/DSM-IV-TR criteria and SCID-PMDD | 71 | 5 (7%) | 1 (1.5%) | Not indicated adequately |
| Maryam et al. ( | Indonesia | Cross sectional | September 2015 | Female medical student, 19–22 | Dysmenorrhea/DASS 42 | 136 | Not indicated adequately | Not indicated adequately | 74 (54.4%) |
| Total number of students | 4,874 |
Quality assessment of studies using modified Newcastle Ottawa Scale.
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| Alkhamis et al. ( | * | – | – | * | * | *** |
| Kushwaha et al. ( | * | * | – | * | * | **** |
| Al-Shahrani ( | * | – | – | * | * | *** |
| Hashim et al. ( | * | * | * | * | * | ***** |
| Shah and Christian ( | * | * | – | * | – | **** |
| Kanti et al. ( | * | – | – | * | * | *** |
| Minichil et al. ( | * | * | – | * | * | **** |
| Bilir et al. ( | * | * | * | * | * | ***** |
| Özder and Salduz ( | * | – | – | * | * | *** |
| Verma et al. ( | * | – | – | * | * | *** |
| Majeed-Saidan et al. ( | – | * | – | * | – | ** |
| Nama et al. ( | * | – | – | * | * | *** |
| Zalat et al. ( | * | – | – | * | * | *** |
| Yadav and Taneja ( | * | – | – | * | * | *** |
| Sharma et al. ( | * | * | – | * | * | **** |
| Shamnani et al. ( | * | – | – | * | * | *** |
| Rajkumari et al. ( | * | * | – | * | * | **** |
| Ghaderi et al. ( | * | * | – | * | * | **** |
| Acikgoz et al. ( | * | – | – | * | * | *** |
| Rumana Akbari et al. ( | * | – | – | * | * | *** |
| Katwal et al. ( | * | – | – | * | * | *** |
| Aryal et al. ( | * | – | – | * | * | *** |
| Jaiprakash et al. ( | * | – | – | * | * | *** |
| Goweda et al. ( | * | * | – | * | * | **** |
| Raval et al. ( | * | * | – | * | * | **** |
| Maryam et al. ( | * | – | – | * | * | *** |
Academic and social impact of menstrual abnormalities and the adopted intervention by the medical students to reduce complications.
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| E. G. Alkhamis et al. ( | • One third of students was leaving early during the class | • Coffee (71.3%) and painkillers (57.4%) as the most common type of treatment. |
| Kushwaha et al. ( | • Impairment of social and personal life | • Over two-thirds used home remedies alone or in combination with analgesic drugs. |
| Al-Shahrani ( | • Menstruation significantly affected the related quality of life subscales concerning the homework interface | • Among the students who responded yes to PMS, only 4.1% use of drugs for menstrual regulation and 60% did not use any drug |
| Hashim et al. ( | • More than half reported increase in their absenteeism. | • Periodical awareness programs should be introduced to minimize the consequences |
| Shah and Christian ( | • The school/work efficiency or productivity impaired | • Less than one-fourth were using heating pads for their cramps. Herbal tea was used for its soothing effects and preventing menstrual cramps for some. |
| Kanti et al. ( | • 18% remained absent from class for 1 or 2 days due to pain. | • Only 7.1% were using medication. |
| Minichil et al. ( | • 35.5% perceived menstrual pain has an impact on their academic performance. | • Some self-medication with paracetamol and ibuprofen. Tea and coffee were consumed by 37 and 51%, respectively. |
| Bilir et al. ( | 18.2% reported school absenteeism due to PMS | • 92.6% used analgesic very commonly. Only 10% were on oral contraceptive pills. |
| Özder and Salduz ( | • 34% students skipped a class | • 44% felt the need for analgesics. Only 14% sought medical advice. |
| Verma et al. ( | • 12 reported absenteeism from the college. | • More than 50% needed some form of medication |
| Majeed-Saidan et al. ( | • The overall wellbeing is impaired. | • More than 50% used over-the-counter medications 76.8% used alternative therapy |
| Nama et al. ( | • Decreased academic performance, difficulty in concentrating, forgetfulness, adjustment difficulties, loneliness | • Authors recommend inclusive and more flexible medical education curriculum design |
| Zalat et al. ( | • 35% reported forgetfulness and 40% reported confusion | • More than 80% did not have history of taking medical advice for PMS |
| Yadav and Taneja ( | • 29% missed social activities and 12% missed college | • 55% needed drugs to treat menstrual disorders and 82.5% had misconceptions and taboos related to menstruation. |
| Sharma et al. ( | • Reduced productivity and inability of participate in social activities for majority | • Authors discuss the association between caffeine intake and a higher PMS |
| Shamnani et al. ( | • 12% were absent in educational activities and 32% avoided joining social activities | • 45% of symptomatic participants consulted to their mothers, 28% to their friends, 21% to others. |
| Rajkumari et al. ( | • Higher stress score | • Stress is a positive predictor for all menstrual disorders |
| Acikgoz et al. ( | • Depression, fatigue, anxiety | • Depression risk should be evaluated in students with PMS |
| Ghaderi et al. ( | • 76% had negative impact on daily activities and 35% were absent from class | • More than half used ibuprofen, diclofenac. Many preferred herbal tea, chamomile, ginger, hot pack, etc. |
| Rumana Akbari et al. ( | • Not indicated adequately | • The prevalence of PMS is directly proportional to age and academic year of study. PMS was found to be more among students residing in hostels. |
| Katwal et al. ( | 29% missed classes | • Positive relationship between psychological stress and dysmenorrhea. |
| Goweda et al. ( | Difficulty in concentrating | • Improving early detection of PMDD and proper management can improve general wellbeing and ensure a better health |
| Jaiprakash et al. ( | • 32% had social life impairment and 22% were absent from college | • Most of them did not take any medications. |
| Aryal et al. ( | Overall wellbeing is decreased | • Dysmenorrhea symptoms should be effectively screened by healthcare providers |
| Raval et al. ( | • Majority had reduced school/work efficiency or productivity | • Various screening and assessment tools are available such as PSST for PMS and SCID-PMDD |
| Maryam et al. ( | • Productivity decreased | • Stress management to prevent more severe dysmenorrhea, and increase the productivity |
Figure 2Major lifestyle factors associated with menstrual abnormalities.
Figure 3The forest plot of PMS prevalence. The diamond represents the overall results and 95% confidence interval of the random effect of the meta-analysis. Model: Random, overall effect size: 0.513, 95%CI: [0.396–0.629] (z-value: 0.220, p-value: 0.826), I2:96.93. Tau2: 0.901, s.e: 0.384, variance: 0.147, tau: 0.949.
Figure 4The funnel plot of pooled prevalence of PMS is asymmetry and suggest that overall effect of the analysis is biased. In this case the intercept (B0) is 1.06576, 95% confidence interval (−7.59403, 9.72556), with t = 0.27088, df = 11. The 1-tailed p-value (recommended) is 0.39575, and the 2-tailed p-value is 0.79150.
Figure 5The forest plot of PMDD prevalence. The diamond represents the overall results and 95% confidence interval of the random effect of the meta-analysis. The prevalence of PMDD was reported in 6 studies including 1,487 participants. The estimated prevalence, pooled from all included studies for PMDD was found to be 17.7% (95% CI: 0.102–0.289) with a high level of heterogeneity (I2 = 95.12%), p-value: <0.001, Results: significant.
Figure 6The forest plot of dysmenorrhea prevalence. The diamond represents the overall results and 95% confidence interval of the random effect of the meta-analysis. The prevalence of dysmenorrhea was reported in 13 studies including 2,497 participants. The estimated prevalence, pooled from all included studies for dysmenorrhea was found to be 17.7% (95% CI: 0.102–0.289) with a high level of heterogeneity (I2 = 94.7%), p-value: <0.001. Model name: Random, z value: 4.444, p-value <0.001, I2: 94.7%, tau2: 0.578, S.E: 0.283, variance: 0.08, Tau: 0.76.
Figure 7The funnel plot of pooled prevalence of dysmenorrhea is asymmetry and suggest that overall effect of the analysis is biased. In this case the intercept (B0) is 1.06576, 95% confidence interval (−7.59403, 9.72556), with t = 0.27088, df = 11. The 1-tailed p-value (recommended) is 0.39575, and the 2-tailed p-value is 0.79150.