Evaluation of psychiatric conditions in asymptomatic outpatient clinic patients
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".