Facebook Addiction and Depression Among Students at the University of Douala

Background Despite an increased interest in Facebook addiction (FA) research over the past 10 years, few data are available in Cameroon. This study aimed to determine the prevalence and determinants of FA, and its relationship to depression among students in a government university. Methods A cross-sectional study was conducted in 9 institutions of the University of Douala. A total of 1133 students completed a self-administered survey including sociodemographic data, Facebook use patterns, Bergen Facebook Addiction Scale (BFAS), and Beck Depression Inventory II (BDI II). BFAS >18 was defined as FA, depression was defined as a BDI II ≥10. Data were analyzed using SPSS® 28.0. Results The mean age was 22.5 ± 3.7 years with 53.5% of female. Prevalence of FA and depression were 14.5% and 52.1% respectively. Independent Predictors of FA were multiple daily logins, virtual friends <200, and daily use ≥4 hours. Female students, medical school, teachers’ training college, and PhD/equivalent were significantly associated to depression. FA was positively correlated to depression severity (r = 0.26; ρ = 0.25; P < 0.001). Conclusion Facebook addiction is common, and often associated with depression among students at the University of Douala, highlighting the need for mental health interventions.

Authors

Institutions

Publication Details

Journal
Annals of Clinical Psychiatry
Published
2026-03-17
DOI
https://doi.org/10.1177/10401237261434902
Primary Topic
Impact of Technology on Adolescents
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Facebook Addiction and Depression Among Students at the University of Douala

Annick Mélanie Magnerou, Callixte Kuate Tegueu, Jacques Doumbé, Daniel Gams Massi et al.
Annals of Clinical Psychiatry
Impact of Technology on Adolescents
article

Facebook Addiction and Depression Among Students at the University of Douala

Annick Mélanie Magnerou, Callixte Kuate Tegueu, Jacques Doumbé, Daniel Gams Massi, Sandra Tueam Moguem, Christian Eyoum, Yacouba Mapoure Njankouo
article en

Abstract

Background Despite an increased interest in Facebook addiction (FA) research over the past 10 years, few data are available in Cameroon. This study aimed to determine the prevalence and determinants of FA, and its relationship to depression among students in a government university. Methods A cross-sectional study was conducted in 9 institutions of the University of Douala. A total of 1133 students completed a self-administered survey including sociodemographic data, Facebook use patterns, Bergen Facebook Addiction Scale (BFAS), and Beck Depression Inventory II (BDI II). BFAS >18 was defined as FA, depression was defined as a BDI II ≥10. Data were analyzed using SPSS® 28.0. Results The mean age was 22.5 ± 3.7 years with 53.5% of female. Prevalence of FA and depression were 14.5% and 52.1% respectively. Independent Predictors of FA were multiple daily logins, virtual friends <200, and daily use ≥4 hours. Female students, medical school, teachers’ training college, and PhD/equivalent were significantly associated to depression. FA was positively correlated to depression severity (r = 0.26; ρ = 0.25; P < 0.001). Conclusion Facebook addiction is common, and often associated with depression among students at the University of Douala, highlighting the need for mental health interventions.

Annals of Clinical Psychiatry
Université de Yaoundé I (CM), University of Douala (CM)
Good health and well-being
Openalex Percentile: Top 24%
Impact of Technology on Adolescents
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.