Evaluating The Agreement Between K-Median And Latent Class Analysis For Clustering Of Psychological Distress Prevalence
Evaluating the agreement between k-median and LCR
Abstract
Introduction: Psychological distress (PD) is one of the most common mental disorders in the general population. Psychological distress is considered a public health priority due to its adverse effects on quality of life, health, performance, and productivity. It can also predict several serious mental illnesses, such as depressive disorder and anxiety. In this study, we intend to identify the behavioral pattern of PD in the population of 18 to 65 years old in Mashhad using two methods, K-median and Latent Class Analysis (LCA), and evaluate the agreement between the two methods.
Methods: This cross-sectional study was performed on 38058 individuals referred to community health care centers at Mashhad of Iran in 2019. The information used in this study was extracted from Sina Electronic Health Record System (SinaEHR) database. A demographic information checklist and 6-item Kessler psychological distress scale (K-6) were used for data collection. K-median and LCA were used for data analysis.
Results: Out of 38058 participants, 49.3% were women, 86.1% were married, and 63.6% had a diploma and under diploma education. The LCA identified three patterns of PD in answering the items of the K-6 questionnaire, including severe PD (19.7%), low PD (36.7%), and no PD (43.5%). Three clusters were identified by the K-Median method: 1) severe PD (22.0%), 2) low PD (31.1%), and 3) and no PD (46.9%). The agreement between K-Median and LCA was kappa = 0.862.
Conclusion: About 20% of people were classified as having severe PD. Both LCA and k-median methods can reasonably identify the latent pattern of PD with significant entropy, and there was almost complete agreement between the two methods in data clustering. Considering the advantages of the LCA, this method is recommended to identify the latent pattern of PD based on the k-6 questionnaire.
2. Rehm J, Shield KD. Global Burden of Disease and the Impact of Mental and Addictive Disorders. Current psychiatry reports. 2019;21(2):10.
3. Noorbala AA, Bagheri Yazdi SA, Yasamy MT, Mohammad K. Mental health survey of the adult population in Iran. The British journal of psychiatry : the journal of mental science. 2004;184:70-3.
4. Pouretemad HR, Naghavi HR, Malekafzali H, Noorbala AA, Davidian H, Ghanizadeh A, et al. Prevalence of Mood Disorders in Iran. Iranian Journal of Psychiatry. 2006;1(2).
5. Rahimi Z, Esmaily H, Taghipour A, Mosa Farkhani E, Jamali J. Evaluation of the Prevalence of Psychological Distress and Its Related Demographic Factors in 18-65 Year-Old Population of Khorasan Razavi: A Cross-Sectional Study. Iranian Journal of Epidemiology. 2021;16(4):316-24.
6. Emami H, Ghazinour M, Rezaeishiraz H, Richter J. Mental health of adolescents in Tehran, Iran. The Journal of adolescent health : official publication of the Society for Adolescent Medicine. 2007;41(6):571-6.
7. Jafari N, Loghmani A, Montazeri A. Mental health of Medical Students in Different Levels of Training. International journal of preventive medicine. 2012;3(Suppl 1):S107-12.
8. Wang C, Tee M, Roy AE, Fardin MA, Srichokchatchawan W, Habib HA, et al. The impact of COVID-19 pandemic on physical and mental health of Asians: A study of seven middle-income countries in Asia. PloS one. 2021;16(2):e0246824.
9. Javed B, Sarwer A, Soto EB, Mashwani Z-U-R. The coronavirus (COVID-19) pandemic's impact on mental health. Int J Health Plann Manage. 2020;35(5):993-6.
10. Qiu J, Shen B, Zhao M, Wang Z, Xie B, Xu Y. A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: implications and policy recommendations. General psychiatry. 2020;33(2):e100213.
11. Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet (London, England). 2020;395(10227):912-20.
12. Wu T, Jia X, Shi H, Niu J, Yin X, Xie J, et al. Prevalence of mental health problems during the COVID-19 pandemic: A systematic review and meta-analysis. Journal of affective disorders. 2021;281:91-8.
13. Feigin VL, Roth GA, Naghavi M, Parmar P, Krishnamurthi R, Chugh S, et al. Global burden of stroke and risk factors in 188 countries, during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. 2016;15(9):913-24.
14. Necho M, Tsehay M, Birkie M, Biset G, Tadesse E. Prevalence of anxiety, depression, and psychological distress among the general population during the COVID-19 pandemic: A systematic review and meta-analysis. The International journal of social psychiatry. 2021;67(7):892-906.
15. Firdaus G. Increasing Rate of Psychological Distress in Urban Households: How Does Income Matter? Community mental health journal. 2018;54(5):641-8.
16. Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SL, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological medicine. 2002;32(6):959-76.
17. Murugan N, Mishra AK, Chauhan RC, Velavan A. Psychological distress among adult urban population of Puducherry. International Journal Of Community Medicine And Public Health. 2018;5(8):3265-9.
18. Vaziri S, Shaydayi Aghdam S, No0bakht L, Khalili M, Vaziri Y, Masumi R, et al. Comparison of physical symptoms in people with low and high psychological distress Patients Disease. Thoughts and Behavior in Clinical Psychology. 2018;13(49):57-66.
19. Enticott JC, Lin E, Shawyer F, Russell G, Inder B, Patten S, et al. Prevalence of psychological distress: How do Australia and Canada compare? The Australian and New Zealand journal of psychiatry. 2018;52(3):227-38.
20. Weissman JF, Pratt LA, Miller EA, Parker JD. Serious Psychological Distress Among Adults: United States, 2009-2013. NCHS data brief. 2015(203):1-8.
21. Tanji F, Tomata Y, Zhang S, Otsuka T, Tsuji I. Psychological distress and completed suicide in Japan: A comparison of the impact of moderate and severe psychological distress. Preventive medicine. 2018;116:99-103.
22. Farrag NS, El-Gilany AH, Abdelsalam SA. Prevalence and predictors of psychological distress among primary healthcare service users in Mansoura district, Egypt. Health & social care in the community. 2019;27(6):1451-7.
23. Takeda T, Yoshimi K, Kai S, Inoue F. Association Between Serious Psychological Distress and Loneliness During the COVID-19 Pandemic: A Cross-Sectional Study with Pregnant Japanese Women. International journal of women's health. 2021;13:1087-93.
24. Tippens JA, Hatton-Bowers H, Honomichl R, Wheeler LA, Miamidian HM, Bash KL, et al. Psychological distress prevalence and associated stressors and supports among urban-displaced Congolese adults in Kenya. The American journal of orthopsychiatry. 2021;91(5):626-34.
25. Nguyen LH, Vu HM, Vu GT, Tran TH, Pham KTH, Nguyen BT, et al. Prevalence and Factors Associated with Psychological Distress among Older Adults Admitted to Hospitals After Fall Injuries in Vietnam. International journal of environmental research and public health. 2019;16(22).
26. McGinty EE, Presskreischer R, Han H, Barry CL. Psychological Distress and Loneliness Reported by US Adults in 2018 and April 2020. Jama. 2020;324(1):93-4.
27. Daly M, Robinson E. Psychological distress and adaptation to the COVID-19 crisis in the United States. Journal of psychiatric research. 2021;136:603-9.
28. Zhang M, Zhang J, Zhang F, Zhang L, Feng D. Prevalence of psychological distress and the effects of resilience and perceived social support among Chinese college students: Does gender make a difference? Psychiatry research. 2018;267:409-13.
29. Mazza C, Ricci E, Biondi S, Colasanti M, Ferracuti S, Napoli C, et al. A Nationwide Survey of Psychological Distress among Italian People during the COVID-19 Pandemic: Immediate Psychological Responses and Associated Factors. International journal of environmental research and public health. 2020;17(9).
30. Cénat JM, Blais-Rochette C, Kokou-Kpolou CK, Noorishad PG, Mukunzi JN, McIntee SE, et al. Prevalence of symptoms of depression, anxiety, insomnia, posttraumatic stress disorder, and psychological distress among populations affected by the COVID-19 pandemic: A systematic review and meta-analysis. Psychiatry research. 2021;295:113599.
31. Noorbala AA, Faghihzadeh S, Kamali K, Bagheri Yazdi SA, Hajebi A, Mousavi MT, et al. Mental Health Survey of the Iranian Adult Population in 2015. Archives of Iranian medicine. 2017;20(3):128-34.
32. Sharif F, Joulaei H, Kadivar MR, Rajaeifard AAR. Mental health status and its related demographic variables of families referring to shiraz health centers - 2002. Armaghan Danesh. 2004;9(35):-.
33. Tran TT, Adams-Bedford J, Yiengprugsawan V, Seubsman SA, Sleigh A. Psychological Distress following Injury in a Large Cohort of Thai Adults. PloS one. 2016;11(10):e0164767.
34. Nahidi S, Blignault I, Hayen A, Razee H. Psychological Distress in Iranian International Students at an Australian University. Journal of immigrant and minority health. 2018;20(3):651-7.
35. Hajebi A, Motevalian A, Amin-Esmaeili M, Rahimi-Movaghar A, Sharifi V, Hoseini L, et al. Adaptation and validation of short scales for assessment of psychological distress in Iran: The Persian K10 and K6. International journal of methods in psychiatric research. 2018;27(3):e1726.
36. Jamali J, Ayatollahi SM, Jafari P. A New Measurement Equivalence Technique Based on Latent Class Regression as Compared with Multiple Indicators Multiple Causes. Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH. 2016;24(3):168-71.
37. Brusco MJ, Shireman E, Steinley D. A comparison of latent class, K-means, and K-median methods for clustering dichotomous data. Psychological methods. 2017;22(3):563-80.
38. Everitt B. An R and S-PLUS companion to multivariate analysis. London: Springer Science & Business Media; 2005.
39. Tein JY, Coxe S, Cham H. Statistical Power to Detect the Correct Number of Classes in Latent Profile Analysis. Structural equation modeling : a multidisciplinary journal. 2013;20(4):640-57.
40. Jamali J, Roustaei N, Ayatollahi SMT, Sadeghi E. Factors affecting minor psychiatric disorders in Southern Iranian nurses: A latent class regression analysis. Nurs Midwifery Stud. 2015 4(2):e28017.
41. Vergara VM, Salman M, Abrol A, Espinoza FA, Calhoun VD. Determining the number of states in dynamic functional connectivity using cluster validity indexes. Journal of neuroscience methods. 2020;337:108651.
42. McHugh ML. Interrater reliability: the kappa statistic. Biochemia medica. 2012;22(3):276-82.
43. Barragán A, Yamada AM, Gilreath TD. Psychological Distress Behavioral Patterns Among Latinos: We Don't See Ourselves as Worthless. Community mental health journal. 2019;55(2):232-40.
44. Papachristou N, Barnaghi P, Cooper BA, Hu X, Maguire R, Apostolidis K, et al. Congruence Between Latent Class and K-Modes Analyses in the Identification of Oncology Patients With Distinct Symptom Experiences. Journal of pain and symptom management. 2018;55(2):318-33.e4.
45. Jamali J, Ayatollahi SMT. Classification of Iranian Nurses According to their Mental Health Outcomes Using GHQ-12 Questionnaire: a Comparison Between Latent Class Analysis and K-means Clustering with Traditional Scoring Method. Materia socio-medica. 2015;27(5):337-41.
46. Magidson J, Vermunt JJCjomr. Latent class models for clustering: A comparison with K-means. Canadian Journal of Marketing Research. 2002;20(1):36-43.
47. Fahey MT, Thane CW, Bramwell GD, Coward WA. Conditional Gaussian mixture modelling for dietary pattern analysis. J R Statist Soc. 2007;170(1):149-66.
48. Flann N, Xu B, Recker M, Qi X, Ye LJR. Clustering Educational Digital Library Usage Data: A Comparison of Latent Class Analysis and K-means Algorithms. 2013;5(2).
49. Wagstaff K, Cardie C, Rogers S, Schrödl S, editors. Constrained k-means clustering with background knowledge. Icml; 2001.
50. Anderlucci L, Hennig C. The Clustering of Categorical Data: A Comparison of a Model-based and a Distance-based Approach. Communications in Statistics - Theory and Methods. 2014;43(4):704-21.
Files | ||
Issue | Vol 8 No 4 (2022) | |
Section | Articles | |
DOI | https://doi.org/10.18502/jbe.v8i4.13353 | |
Keywords | ||
Cross-sectional study psychological distress k-6 questionnaire latent class analysis k-median Mashhad |
Rights and permissions | |
![]() |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |