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Record W4407944873 · doi:10.1371/journal.pone.0319168

Evaluation of psychiatric conditions in asymptomatic outpatient clinic patients

2025· article· en· W4407944873 on OpenAlexaboutno aff
Osman Erinç, Soner Yesilyurt

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldMedicine
TopicHealth Promotion and Cardiovascular Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAsymptomaticOutpatient clinicBeck Depression InventoryBeck Anxiety InventoryAnxietyDepression (economics)MoodPsychiatryMental healthInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: A significant part of the internal medicine outpatient clinic burden consists of patients who are asymptomatic and intend to have routine check-up tests. In this study, we aimed to investigate the relationship between visit frequency within a year and the undiagnosed anxiety, depressive mood or obsessive-compulsive disorder. METHODS: We included in our study 129 participants who applied for routine check-up tests to our hospital's internal medicine outpatient clinic, without any complaint and known diseases. Individuals were divided into two groups: Group 1 comprised individuals who applied once a year, whereas Group 2 included those who applied more than once a year. Participants underwent routine blood testing, and their mental health was assessed with the Beck`s Depression Inventory (BDI), Beck`s Anxiety Inventory (BAI), and Vancouver Obsessinal Compulsive Inventory (VOCI). RESULTS: 66% of the 129 participants included in the study were female (n = 85/44, p < 0.001). When laboratory parameters were examined, no significant difference was found except serum vitamin D levels (14.5/19.8 µg/L, p = 0.024, respectively). BDI and BAI scores were statistically significantly higher in Group 2 (10/14, p = 0.032, 11/13.5, p = 0.027, respectively). There was no difference between the two groups in terms of VOCI scores. CONCLUSION: Asymptomatic patients who are visiting clinics for routine checkups constitute a significant part of the outpatient clinic workload. Assessing the mental health of patients who are attending frequently might be helpful in reducing this burden as well as in diagnosing and initiating treatment of undiagnosed underlying mental disorders. To ensure timely referrals of these patients to psychiatry, an adequate referral system and awareness of early signs of anxiety and depression among healthcare professionals are needed.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.116
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.073
GPT teacher head0.369
Teacher spread0.296 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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