Cluster Analysis on the Mental Health States in a Community Sample of Young Women During Pre-Pregnancy, Pregnancy, or the Postpartum Period

Lim, Hyunyoung; Moon, Eunsoo; Kim, Kyungwon; Suh, Hwagyu; Park, Jeonghyun; Kim, Du-Ri; Park, Jong Hwan; Shin, Myung Jun; Lee, Yean-Hwa

doi:10.30773/pi.2023.0002

Cited by 3 publications

(1 citation statement)

References 40 publications

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“…[20][21][22][23] The 9-item Patient Health Questionnaire-9 (PHQ-9) is another brief, reliable and valid screening tool for depression in the general population or clinical samples. [24][25][26] The PHQ-9 has been used in studies with breast cancer patients, 27,28 but there has been only one preliminarily study that examined the reliability and validity of the Portuguese version of the PHQ-9 in 49 breast cancer patients. 29 Moreover, the construct validity of PHQ-9 in breast cancer patients has not yet been reported.…”

Section: Original Articlementioning

confidence: 99%

Psychometric Properties of the Patient Health Questionnaire-9 in Patients With Breast Cancer

Park,

Kim,

Moon

et al. 2024

Psychiatry Investig

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Objective Due to the high frequency of depressive symptoms associated with breast cancer, it is crucial to screen for depression in breast cancer patients. While numerous screening tools are available for depression in this population, there is a need for a brief and convenient tool to enhance clinical use. This study aims to investigate the psychometric properties of the Patient Health Questionnaire-9 (PHQ-9) in patients with breast cancer.Methods Patients with breast cancer (n=327) who visited the Breast Cancer Clinic were included in this study. The reliability of the PHQ-9 was analyzed by Cronbach’s α, and the construct validity of the PHQ-9 was explored by factor analysis. The concurrent validity of the PHQ-9 was evaluated by Pearson correlation analysis with the Hospital Anxiety and Depression Scale (HADS) and Perceived Stress Scale (PSS).Results The values of Cronbach’s α ranged from 0.800 to 0.879 was acceptable. The exploratory factor analysis revealed that the one-factor model and two-factor model of the PHQ-9 explained 46% and 57% of the variance, respectively. The PHQ-9 were significantly correlated with those of HADS (r=0.702, p<0.001) and PSS (r=0.466, p<0.001). Consequently, the PHQ-9 demonstrated acceptable reliability and validity in breast cancer patients.Conclusion The findings of this study indicate that the PHQ-9 exhibits acceptable reliability and validity in patients with breast cancer. The convenience of this brief self-report questionnaire suggests its potential as a reliable and valid tool for assessing depression in breast cancer clinics.

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Section: Original Articlementioning

confidence: 99%

Psychometric Properties of the Patient Health Questionnaire-9 in Patients With Breast Cancer

Park,

Kim,

Moon

et al. 2024

Psychiatry Investig

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Addressing algorithmic bias in precision well-being for medical education: A socially fair approach for clustering

Alluri,

Chen,

Marrero

et al. 2024

Preprint

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BackgroundMedical students frequently experience heightened levels of anxiety, depression, and burnout. These challenges are disproportionately borne by students from underrepresented backgrounds, who are exposed to systemic inequities, discrimination, and reduced access to supportive resources. While precision well-being approaches, characterized by identifying distinct well-being phenotypes for personalized interventions, hold promise, standard machine learning clustering algorithms such as K-Means may inadvertently exacerbate these disparities. Furthermore, the underlying factors contributing to poorer mental health outcomes among underrepresented students remain insufficiently understood.ObjectiveWe aim to identify well-being phenotypes that achieve an equitable distribution of clustering costs across racial groups, identify conditions under which fair and standard clustering solutions converge, and investigate the demographic and socioeconomic factors that shape mental health patterns in students underrepresented in medicine.MethodsDrawing on a diverse sample of 4161 medical students from multiple U.S. institutions participating in the Healthy Minds Survey (2016–2021), we compared the outcomes of socially fair and standard k-Means clustering algorithms using Patient Health Questionnaire-9, General Anxiety Disorder-7, and Flourishing scores. We then employed average treatment effect analyses to identify factors that exacerbate mental health challenges and those that enhance resilience, with a particular emphasis on underrepresented populations.ResultsThe socially fair clustering algorithm significantly reduced the disproportionate burden on minority populations, aligning with standard clustering outcomes when student groups were racially and socioeconomically homogeneous. Perceived discrimination emerged as a key factor driving poorer mental health, while stable financial conditions, robust social engagement, and involvement in culturally or ethnically oriented organizations were linked to greater resilience and improved well-being.ConclusionsIncorporating fairness objectives into clustering algorithms substantially reduced the disproportionate burden on minority students and yielded a more equitable understanding of their mental health patterns. By identifying factors that influence mental health outcomes, our socially-fair precision well-being approach allows for more personalized well-being interventions. These insights equip educators and policymakers with actionable targets for developing culturally responsive, data-driven interventions that not only alleviate distress but also support resilience, ultimately advancing more inclusive, effective precision well-being strategies for all medical students.

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Exploring relationship between quality of life, life habits and occupational stress Brazilian public prosecutors: A cluster analysis approach

Oliveira,

Fernandes,

Souza

et al. 2024

WORK: A Journal of Prevention, Assessment & Rehabilitation

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Background The quality of life (QoL) of Prosecutors can be impacted by their own work. Objective To examine the relationship between sociodemographic and occupational characteristics, and QoL in public prosecutors (PP). Methods Information on life habits, sociodemographic and occupational characteristics, the World Health Organization Quality of Life assessment abbreviated version (WHOQOL-bref), and Job Stress Scale (JSS) of 355 Brazilian PP were collected by email survey. The cluster analysis used the Gower method to form groups with similar characteristics. Chi-squared, Fisher's exact, and Kruskal-Wallis tests verified differences in clusters. A multiple linear regression identified predictors of QoL in clusters. Results The analysis founded 3 distinct groups. In the cluster with highest QoL, the variables explained 48.3% of the total variance ( F(4, 91) = 21.235; p < 0.000; R2 = 0.483). Length of employment βsc = 0.288; t = 3.770; p < 0.000), sedentary lifestyle ( βsc = −0.274; t = −3.494; p < 0.001), sleep quality ( βsc = 0.402; t = 5.212; p < 0.001), and social support ( βsc = 0.296; t = 3.772; p < 0.001) were QoL predictors. In the cluster with worst QoL, sleep quality ( βsc = 0.307; t = 3.798; p < 0.001), social support ( βsc = 0.452; t = 5.140; p < 0.001), and occupational stress ( βsc = −0.210; t = −2.481; p < 0.05) were QoL predictors and explained 54.4% of total QoL variance ( F(3, 79) = 31.364; p < 0.001; R2 = 0.544). In the intermediate QoL cluster, religiosity ( βsc = 0.161; t = 2.144; p < 0.05), sleep quality ( βsc = 0.419; t = 5.541; p < 0.001), social support ( βsc = 0.214; t = 2.743; p < 0.05), and occupational stress ( βsc = −0.218; t = −2.727; p < 0.05) contributed for the model, explaining 45.2% of total QoL variance ( F(5, 104) = 17.173; p < 0.001; R2 = 0.452). Conclusion The QoL of Brazilian PP is related with their life habits, social support at work, and occupational stress, showing the need of Occupational Health Service (OHS) support to ensure individual and organizational strategies to promote better QoL in PP.

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Cluster Analysis on the Mental Health States in a Community Sample of Young Women During Pre-Pregnancy, Pregnancy, or the Postpartum Period

Cited by 3 publications

References 40 publications

Psychometric Properties of the Patient Health Questionnaire-9 in Patients With Breast Cancer

Psychometric Properties of the Patient Health Questionnaire-9 in Patients With Breast Cancer

Addressing algorithmic bias in precision well-being for medical education: A socially fair approach for clustering

Exploring relationship between quality of life, life habits and occupational stress Brazilian public prosecutors: A cluster analysis approach

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