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Record W4409433084 · doi:10.1017/gmh.2025.39

Rising prevalence of depression and widening sociodemographic disparities in depressive symptoms among Filipino youth: findings from two large nationwide cross-sectional surveys

2025· article· en· W4409433084 on OpenAlexaff
Joseph H. Puyat, Divine L. Salvador, Anna Cristina A. Tuazon, Sanny D. Afable

Bibliographic record

VenueCambridge Prisms Global Mental Health · 2025
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of British ColumbiaProvidence Health Care
FundersUniversity of the PhilippinesUniversity of Cambridge
KeywordsDepression (economics)Cross-sectional studyDepressive symptomsPsychiatryMedicineClinical psychologyDemographyPsychologyAnxietySociology

Abstract

fetched live from OpenAlex

Youth depression is a critical target for early intervention due to its strong links with adult depression and long-term functional impairment. In low- and middle-income countries (LMICs) like the Philippines, limited epidemiological data hampers mental health service planning for youth. This study analyzed nationally representative survey data from 2013 (n = 10,949) and 2021 (n = 19,178) to estimate the prevalence of moderate to severe depressive symptoms (MSDS) among Filipinos aged 15-24 years, using the 11-item version of the Center for Epidemiologic Studies Depression Scale. Survey-weighted analyses revealed that MSDS prevalence more than doubled from 9.6% in 2013 to 20.9% in 2021. The rise was most pronounced among females (10.8% to 24.3%), non-cisgender or homonormative individuals (9.7% to 32.3%), youth with primary education or less (10.8% to 26.5%), youth from economically disadvantaged households (10.6% to 25.1%) and youth who were separated, widowed or divorced (18.3% to 41.3%). Disparities in MSDS also widened over time, with some groups bearing a disproportionate burden. These findings underscore the need to expand accessible, high-quality mental health services for youth in LMICs, such as the Philippines. Continued monitoring and targeted interventions are essential to address the rising burden of depression, particularly among underserved and disproportionately affected groups.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.325
Teacher spread0.310 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2025
Admission routes1
Has abstractyes

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