The Help Seeking Attitudes and Quality of Life Among People with Depression

The basic aim of the study was to see the factors predicting help seeking attitudes and quality of life among people with depression. The study explores the question that do age, gender, education, socioeconomic status, culture, stigma, self-efficacy and family satisfaction predict help seeking attitudes and quality of life among people with depression? The sample consists of people with self-reported depressive symptoms. The sample of 109 participants was gathered through snowball sampling technique. The analysis was multiple linear regression. The results show that culture and general self-efficacy are the strongest predictors of help-seeking attitudes while culture and family satisfaction are the strongest predictor of quality of life, except in the case of last subscale of Quality of life “recreation”, in which SES, education, and culture predicted quality of life. Meanwhile, family satisfaction and stigma are not predicting help seeking attitudes. General self-efficacy and stigma are not predicting Quality of life. This study would be helpful for clinical psychologists and other mental health professionals to understand why some people with depressive symptoms in this culture hesitate to seek professional help. Further research on this topic could explore more factors and variables which predict quality of life and help seeking attitudes among depressive patients.

Authors

Institutions

Publication Details

Journal
Social science review archives.
Published
2025-02-21
DOI
https://doi.org/10.70670/sra.v3i1.475
Primary Topic
Psychological Well-being and Life Satisfaction
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Help Seeking Attitudes and Quality of Life Among People with Depression

Dr Elizabeth Schwaiger, Sadia Nawaz Hiraj
Social science review archives.
Psychological Well-being and Life Satisfaction
article

The Help Seeking Attitudes and Quality of Life Among People with Depression

Dr Elizabeth Schwaiger, Sadia Nawaz Hiraj
article en

Abstract

The basic aim of the study was to see the factors predicting help seeking attitudes and quality of life among people with depression. The study explores the question that do age, gender, education, socioeconomic status, culture, stigma, self-efficacy and family satisfaction predict help seeking attitudes and quality of life among people with depression? The sample consists of people with self-reported depressive symptoms. The sample of 109 participants was gathered through snowball sampling technique. The analysis was multiple linear regression. The results show that culture and general self-efficacy are the strongest predictors of help-seeking attitudes while culture and family satisfaction are the strongest predictor of quality of life, except in the case of last subscale of Quality of life “recreation”, in which SES, education, and culture predicted quality of life. Meanwhile, family satisfaction and stigma are not predicting help seeking attitudes. General self-efficacy and stigma are not predicting Quality of life. This study would be helpful for clinical psychologists and other mental health professionals to understand why some people with depressive symptoms in this culture hesitate to seek professional help. Further research on this topic could explore more factors and variables which predict quality of life and help seeking attitudes among depressive patients.

Social science review archives.Vol. 3(1)
Forman Christian College (PK), University of South Asia (PK)
Openalex Percentile: Top 97%
Psychological Well-being and Life 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.