Association between Alexithymia and Depression among King Khalid University Medical Students: An Analytical Cross-Sectional Study
Bibliographic record
Abstract
Alexithymia is a condition in which a person is unable to explain his/her emotions, bodily sensations, or discuss sentiments. This study aims to determine the prevalence of alexithymia and its relationships with socio-demographics and depression among medical students. A cross-sectional survey was conducted among medical students at King Khalid University (KKU), Saudi Arabia. A stratified random sampling technique was utilized for data collection using the Toronto Alexithymia Scale (TAS-20) and the Patient Health Questionnaire-9 (PHQ-9). A multiple logistic regression model was used to identify the factors associated with alexithymia. A total of 333 students participated in this study, almost two-thirds (64.6%) were from clinical years, and 51.4% were females. The prevalence of alexithymia and depression was 47.4% and 88.9%, respectively. Regression analysis showed females had a doubled risk (OR = 2.09), and students with high-income status showed less probability of having alexithymia (OR = 0.39), whereas people with chronic health problems showed a doubled risk for alexithymia (OR = 2.04). Moreover, depression was significantly associated with alexithymia (OR = 1.91). Our study revealed that the prevalence of alexithymia was high along with depression among studied samples. This raises attention towards finding measures to reduce it for the better performance of students and to avoid psychological problems in the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".