Characteristics of Depression in Outpatient Polyclinic Services at a Private Hospital in Denpasar

Background: Depression is a significant global mental health issue with a rising prevalence. According to the World Health Organization (WHO), depression affects approximately 4.4% of the global population, with the highest rates found in Southeast Asia. Depression is a mood disorder that disrupts cognitive, affective, and somatic functions. Method: A descriptive cross-sectional study with a retrospective approach was conducted using medical record data of patients diagnosed with depression at a private hospital in Denpasar from September 2024 to January 2025. Data analysis was carried out using SPSS version 25. Result: The results revealed that the majority of depression patients were female (69.7%) and within the productive age group of 21-30 years (51.5%). Most patients were married (72.7%) and employed as private-sector workers (90.9%). Hormonal factors, social role changes, and pressures from household and work life were primary contributors to depression among married women. Conclusion: This study concluded that depression was most prevalent among married women in their productive years who were employed. Early detection of depressive symptoms and targeted mental health education, especially for women, are expected to improve awareness and prevention efforts. This information is crucial for supporting more effective depression management and prevention in the future.

Authors

Publication Details

Journal
International Journal Of Scientific Advances
Published
2025-01-01
DOI
https://doi.org/10.51542/ijscia.v6i4.14
Primary Topic
Healthcare Quality and Satisfaction
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characteristics of Depression in Outpatient Polyclinic Services at a Private Hospital in Denpasar

Anak Agung Dwi Ratih Arningsih
International Journal Of Scientific Advances
Healthcare Quality and Satisfaction
article

Characteristics of Depression in Outpatient Polyclinic Services at a Private Hospital in Denpasar

Anak Agung Dwi Ratih Arningsih
article en

Abstract

Background: Depression is a significant global mental health issue with a rising prevalence. According to the World Health Organization (WHO), depression affects approximately 4.4% of the global population, with the highest rates found in Southeast Asia. Depression is a mood disorder that disrupts cognitive, affective, and somatic functions. Method: A descriptive cross-sectional study with a retrospective approach was conducted using medical record data of patients diagnosed with depression at a private hospital in Denpasar from September 2024 to January 2025. Data analysis was carried out using SPSS version 25. Result: The results revealed that the majority of depression patients were female (69.7%) and within the productive age group of 21-30 years (51.5%). Most patients were married (72.7%) and employed as private-sector workers (90.9%). Hormonal factors, social role changes, and pressures from household and work life were primary contributors to depression among married women. Conclusion: This study concluded that depression was most prevalent among married women in their productive years who were employed. Early detection of depressive symptoms and targeted mental health education, especially for women, are expected to improve awareness and prevention efforts. This information is crucial for supporting more effective depression management and prevention in the future.

International Journal Of Scientific AdvancesVol. 6(4)
Openalex Percentile: Top 70%
Healthcare Quality and Satisfaction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.