Premenstrual Syndrome and Psychological Well-Being Among Adolescent Girls: The Indirect Role of Psychological Distress in a Cross-Sectional Study
DOI:
https://doi.org/10.33700/jhrs.5.2.252Keywords:
premenstrual syndrome, psychological distress, psychological well-being, adolescent girls, cross-sectional indirect associationAbstract
Introduction: Premenstrual syndrome (PMS) is associated with psychological distress and reduced well-being among adolescent girls. However, the extent to which distress statistically accounts for the association between PMS screening status and eudaimonic psychological well-being remains insufficiently examined in Indian adolescents.
Aim: To examine whether psychological distress is associated with the indirect statistical pathway linking PMS screening status with psychological well-being among adolescent girls in Bangalore, India.
Methods: A cross-sectional study included 350 adolescent girls aged 13–17 years from private schools in Bangalore. PMS screening status was assessed using the PSST-A, while psychological distress and well-being were measured using the DASS-Y and PWBS-SDCP, respectively. A bootstrapped path-analytic indirect-association model was estimated using lavaan in R with 5,000 resamples and bias-corrected 95% confidence intervals.
Results: PMS screening status was positively associated with distress (rpb = .46, p < .001) and negatively associated with well-being (rpb = −.26, p < .001). The indirect association through distress was significant (β = −.21, B = −10.46, 95% CI [−13.98, −7.57], p < .001), accounting for 78.7% of the total association. The direct association was not significant (β = −.06, B = −2.82, p = .291). The model explained 23.0% of the variance in well-being.
Conclusions: Psychological distress statistically accounted for a substantial proportion of the cross-sectional association between PMS screening status and well-being. Given the cross-sectional design, these findings indicate a statistical indirect association rather than a temporal or causal mediation mechanism and should inform future longitudinal research.
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References
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173 DOI: https://doi.org/10.1037/0022-3514.51.6.1173
Craner, J. R., Sigmon, S. T., Martinson, A. A., & McGillicuddy, M. L. (2014). Premenstrual disorders and rumination. Journal of Clinical Psychology, 70(1), 32–47. https://doi.org/10.1002/jclp.22007 DOI: https://doi.org/10.1002/jclp.22007
Deecher, D., Andree, T. H., Sloan, D., & Schechter, L. E. (2008). From menarche to menopause: Exploring the underlying biology of depression in women experiencing hormonal changes. Psychoneuroendocrinology, 33(1), 3–17. https://doi.org/10.1016/j.psyneuen.2007.10.006 DOI: https://doi.org/10.1016/j.psyneuen.2007.10.006
Derman, O., Kanbur, N. Ö., Tokur, T. E., & Kutluk, T. (2004). Premenstrual syndrome and associated symptoms in adolescent girls. European Journal of Obstetrics & Gynecology and Reproductive Biology, 116(2), 201–206. https://doi.org/10.1016/j.ejogrb.2004.04.021 DOI: https://doi.org/10.1016/j.ejogrb.2004.04.021
Direkvand-Moghadam, A., Sayehmiri, K., Delpisheh, A., & Sattar, K. (2014). Epidemiology of premenstrual syndrome: A systematic review and meta-analysis study. Journal of Clinical and Diagnostic Research, 8(2), 106–109. https://doi.org/10.7860/jcdr/2014/8024.4021 DOI: https://doi.org/10.7860/JCDR/2014/8024.4021
Dutta, A., & Sharma, A. (2021). Prevalence of premenstrual syndrome and premenstrual dysphoric disorder in India: A systematic review and meta-analysis. Health Promotion Perspectives, 11(2), 161–170. https://doi.org/10.34172/hpp.2021.20 DOI: https://doi.org/10.34172/hpp.2021.20
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(3), 175–191. https://doi.org/10.3758/BF03193146 DOI: https://doi.org/10.3758/BF03193146
Hantsoo, L., Rangaswamy, S., Voegtline, K., Salimgaraev, R., Zhaunova, L., & Payne, J. L. (2022). Premenstrual symptoms across the lifespan in an international sample: Data from a mobile application. Archives of Women’s Mental Health, 25(5), 903–910. https://doi.org/10.1007/s00737-022-01261-5 DOI: https://doi.org/10.1007/s00737-022-01261-5
Hayes, A. F., & Rockwood, N. J. (2017). Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behaviour Research and Therapy, 98, 39–57. https://doi.org/10.1016/j.brat.2016.11.001 DOI: https://doi.org/10.1016/j.brat.2016.11.001
Hobfoll, S. E. (1989). Conservation of resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), 513–524. https://doi.org/10.1037/0003-066X.44.3.513 DOI: https://doi.org/10.1037/0003-066X.44.3.513
Imai, K., Keele, L., & Tingley, D. (2010). A general approach to causal mediation analysis. Psychological Methods, 15(4), 309–334. https://doi.org/10.1037/a0020761 DOI: https://doi.org/10.1037/a0020761
Keyes, C. L. M. (2005). Mental illness and/or mental health? Investigating axioms of the complete state model of health. Journal of Consulting and Clinical Psychology, 73(3), 539–548. https://doi.org/10.1037/0022-006X.73.3.539 DOI: https://doi.org/10.1037/0022-006X.73.3.539
Lee, H., Cashin, A. G., Lamb, S. E., Hopewell, S., Vansteelandt, S., VanderWeele, T. J., MacKinnon, D. P., Mansell, G., Collins, G. S., Golub, R. M., & McAuley, J. H. (2021). A guideline for reporting mediation analyses of randomized trials and observational studies: The AGReMA statement. JAMA, 326(11), 1045–1056. https://doi.org/10.1001/jama.2021.14075 DOI: https://doi.org/10.1001/jama.2021.14075
Liu, Q., Lin, Y., & Zhang, W. (2024). Psychological stress dysfunction in women with premenstrual syndrome. Heliyon, 10(22), e40233. https://doi.org/10.1016/j.heliyon.2024.e40233 DOI: https://doi.org/10.1016/j.heliyon.2024.e40233
Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the Depression Anxiety Stress Scales. 2 ed. Psychology Foundation. DOI: https://doi.org/10.1037/t01004-000
MacKinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000). Equivalence of the mediation, confounding, and suppression effect. Prevention Science, 1(4), 173–181. https://doi.org/10.1023/A:1026595011371 DOI: https://doi.org/10.1023/A:1026595011371
Manjrekar, S., & Patil, S. (2025). Prevalence, severity, and functional impairment of premenstrual syndrome among late reproductive-age women in rural Karnataka. National Journal of Community Medicine, 16(12), 1237–1242. https://doi.org/10.55489/njcm.161220255868 DOI: https://doi.org/10.55489/njcm.161220255868
Monroe, S. M., & Simons, A. D. (1991). Diathesis-stress theories in the context of life stress research: Implications for the depressive disorders. Psychological Bulletin, 110(3), 406–425. https://doi.org/10.1037/0033-2909.110.3.406 DOI: https://doi.org/10.1037/0033-2909.110.3.406
Peacock, A., Alvi, N. S., & Mushtaq, T. (2012). Period problems: Disorders of menstruation in adolescents. Archives of Disease in Childhood, 97(6), 554–560. https://doi.org/10.1136/adc.2009.160853 DOI: https://doi.org/10.1136/adc.2009.160853
Rapkin, A. J., & Akopians, A. L. (2012). Pathophysiology of premenstrual syndrome and premenstrual dysphoric disorder. Menopause International, 18(2), 52–59. https://doi.org/10.1258/mi.2012.012014 DOI: https://doi.org/10.1258/mi.2012.012014
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02 DOI: https://doi.org/10.18637/jss.v048.i02
Rubinow, D., & Schmidt, P. (2006). Gonadal steroid regulation of mood: The lessons of premenstrual syndrome. Frontiers in Neuroendocrinology, 27(2), 210–216. https://doi.org/10.1016/j.yfrne.2006.02.003 DOI: https://doi.org/10.1016/j.yfrne.2006.02.003
Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology, 57(6), 1069–1081. https://doi.org/10.1037/0022-3514.57.6.1069 DOI: https://doi.org/10.1037/0022-3514.57.6.1069
Sisodia, D. S., & Choudhary, P. (2012). Psychological Well Being Scale. National Psychological Corporation.
Steiner, M., Macdougall, M., & Brown, E. (2003). The premenstrual symptoms screening tool (PSST) for clinicians. Archives of Women’s Mental Health, 6(3), 203–209. https://doi.org/10.1007/s00737-003-0018-4 DOI: https://doi.org/10.1007/s00737-003-0018-4
Steiner, M., Peer, M., Palova, E., Freeman, E. W., Macdougall, M., & Soares, C. N. (2011). The premenstrual symptoms screening tool revised for adolescents (PSST-A): Prevalence of severe PMS and premenstrual dysphoric disorder in adolescents. Archives of Women’s Mental Health, 14(1), 77–81. https://doi.org/10.1007/s00737-010-0202-2 DOI: https://doi.org/10.1007/s00737-010-0202-2
Szabo, M., & Lovibond, P. F. (2022). Development and psychometric properties of the DASS-Youth (DASS-Y): An extension of the Depression Anxiety Stress Scales to adolescents and children. Frontiers in Psychology, 13, 766890. https://doi.org/10.3389/fpsyg.2022.766890 DOI: https://doi.org/10.3389/fpsyg.2022.766890
Tawakoli, M. F., Abed, A., & Sakhi, R. (2025). Prevalence of premenstrual syndrome among female biomedical students in Kabul, Afghanistan. International Journal of Women’s Health, 17, 1911–1922. https://doi.org/10.2147/IJWH.S524839 DOI: https://doi.org/10.2147/IJWH.S524839
Upadhyay, M., Mahishale, A., & Kari, A. (2023). Prevalence of premenstrual syndrome in college going girls—A cross sectional study. Clinical Epidemiology and Global Health, 20, 101234. https://doi.org/10.1016/j.cegh.2023.101234 DOI: https://doi.org/10.1016/j.cegh.2023.101234
Vichnin, M., Freeman, E. W., Lin, H., Hillman, J., & Bui, S. (2006). Premenstrual syndrome (PMS) in adolescents: Severity and impairment. Journal of Pediatric and Adolescent Gynecology, 19(6), 397–402. https://doi.org/10.1016/j.jpag.2006.06.015 DOI: https://doi.org/10.1016/j.jpag.2006.06.015
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. The Lancet, 370(9596), 1453–1457. https://doi.org/10.1016/S0140-6736(07)61602-X DOI: https://doi.org/10.1016/S0140-6736(07)61602-X
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