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Record W4414549569 · doi:10.59429/esp.v10i9.3936

Barriers to accessing mental health services among university students: A systematic review

2025· article· en· W4414549569 on OpenAlexaboutno aff
Kus Hanna Rahmi, Zakiyah Jamaluddin, Mahathir Yahaya, Azlini binti Chik, Meiti Subardhini, Enung Huripah, Adi Fahrudin

Bibliographic record

VenueEnvironment and Social Psychology · 2025
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPsychological interventionInclusion (mineral)Systematic reviewCritical appraisalService (business)Scale (ratio)Cochrane Library

Abstract

fetched live from OpenAlex

Background: University students worldwide face escalating mental health challenges, yet their access to appropriate psychological support services remains critically limited. Despite growing institutional awareness of student well-being needs, systematic barriers continue to impede effective service utilization, creating a concerning gap between mental health needs and actual service engagement. Objective: This systematic review aims to comprehensively identify and analyze the multifaceted barriers that prevent university students from accessing mental health services, while simultaneously evaluating the effectiveness of interventions designed to address these obstacles. Methods: Following PRISMA guidelines [1] We conducted an extensive systematic review by searching seven electronic databases, including PubMed, PsycINFO, ERIC, CINAHL, Web of Science, Scopus, and the Cochrane Library for studies published between January 2017 and December 2024. We included empirical studies examining barriers to accessing mental health services among university students aged 18-30 years. Study quality was rigorously assessed using the Mixed Methods Appraisal Tool [2] and Newcastle-Ottawa Scale [3]. Data synthesis employed structured narrative analysis complemented by quantitative analysis where appropriate. Results: Our comprehensive search identified 2,847 initial records, from which 45 studies meeting strict inclusion criteria were analyzed, encompassing 78,392 participants across 23 countries. Through systematic analysis, three primary barrier categories emerged: individual-level barriers, including stigma, misconceptions, and help-seeking reluctance; structural barriers, encompassing financial constraints, service availability, and accessibility issues; and institutional barriers, involving inadequate resources, insufficient staff training, and system integration failures. Financial constraints emerged as the most frequently reported barrier across 69% of studies, followed closely by stigma-related concerns in 64% of studies and limited-service awareness in 58% of included research. Analysis of intervention studies revealed moderate effectiveness for comprehensive, multi-component approaches that address barriers at multiple levels simultaneously. Conclusions: Multiple interconnected barriers create complex obstacles to university students' access to mental health services. The evidence strongly supports implementing multi-level interventions that simultaneously address individual, structural, and institutional factors rather than targeting isolated barriers. Future research should prioritize implementation science approaches and examine the long-term sustainability of barrier-reduction interventions in diverse university settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.071
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0120.014
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.386
Teacher spread0.369 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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