Measuring Religiosity’s Associations with Mental Health and Mental Health Stigma: A Two Study Approach Comparing Linear and Curvilinear Models

This study assesses religiosity and its association with mental health in college student samples from Healthy Minds Network’s 2021-2022 dataset (Study 1; N = 95,680) and from a Prolific 2023 dataset (Study 2; N = 250). Study 1 found that religiosity, operationalized as religious affiliation and religious importance, had a small to null practical (but statistically significant) association with all measures of both mental health (i.e., depression, anxiety, suicidality, loneliness, and flourishing) and mental health stigma. Study 2, however, found that religious importance had a statistically significant and small practical effect only on flourishing (r = .23, p < .001) and that religious belief salience had a significant effect only on flourishing (r = .20, p < .001) and the Self-Stigma of Seeking Help scale (r =.13, p = .04); all other measures did not meet statistical or practical significance levels. Findings suggest that religiosity is associated with mental health, especially flourishing, and mental health stigma. However, differences in how religiosity is assessed led to different associations. Further research, using multiple measures of religiosity, and assessing their relationships with statistical and practical significance is needed to further understand religiosity’s relationships with mental health and stigma in college student samples. Implications for researchers, higher education institution administrators, and university health and counseling center providers are discussed.

Institutions

Publication Details

Journal
ThinkTech (Texas Tech University)
Published
2024-12-01
Primary Topic
Magnetic confinement fusion research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Measuring Religiosity’s Associations with Mental Health and Mental Health Stigma: A Two Study Approach Comparing Linear and Curvilinear Models

ThinkTech (Texas Tech University)
Magnetic confinement fusion research
article

Measuring Religiosity’s Associations with Mental Health and Mental Health Stigma: A Two Study Approach Comparing Linear and Curvilinear Models

article en

Abstract

This study assesses religiosity and its association with mental health in college student samples from Healthy Minds Network’s 2021-2022 dataset (Study 1; N = 95,680) and from a Prolific 2023 dataset (Study 2; N = 250). Study 1 found that religiosity, operationalized as religious affiliation and religious importance, had a small to null practical (but statistically significant) association with all measures of both mental health (i.e., depression, anxiety, suicidality, loneliness, and flourishing) and mental health stigma. Study 2, however, found that religious importance had a statistically significant and small practical effect only on flourishing (r = .23, p < .001) and that religious belief salience had a significant effect only on flourishing (r = .20, p < .001) and the Self-Stigma of Seeking Help scale (r =.13, p = .04); all other measures did not meet statistical or practical significance levels. Findings suggest that religiosity is associated with mental health, especially flourishing, and mental health stigma. However, differences in how religiosity is assessed led to different associations. Further research, using multiple measures of religiosity, and assessing their relationships with statistical and practical significance is needed to further understand religiosity’s relationships with mental health and stigma in college student samples. Implications for researchers, higher education institution administrators, and university health and counseling center providers are discussed.

ThinkTech (Texas Tech University)
Texas Tech University (US)
Openalex Percentile: Top 44%
Magnetic confinement fusion research
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.