Alexithymia: Prevalence and Association with Executive Function among Physiotherapy Students in Karachi, Pakistan
Bibliographic record
Abstract
Background of the Study: Alexithymia is a set of cognitive traits, including the inability to verbalize and recognize one’s emotions. Physiotherapy students are more vulnerable to developing Alexithymia due to their academic workload and intense clinical postings. This neurobiological deficit involves frontal lobe dysfunction and reduced anterior cingulate cortex function, impacting executive function. This study aims to determine the prevalence of Alexithymia and its association with executive function among physiotherapy students. Methodology: A cross-sectional survey was conducted among physiotherapy students using the Toronto Alexithymia scale (TAS-20) to assess prevalence and executive function. It was evaluated through two neurophysiological tasks: Trail making and Verbal fluency tests. Data was analyzed using SPSS Version 26.0. Result: Out of 400 participants, the private license of Alexithymia was estimated to be 55%. Among physiotherapy students 24% were found to be at risk of possible Alexithymia. Alexithymia and executive function showed significant association with 85% of students demonstrating reduced performance on the trail-making test A (p=0.001). 83.3% of students had low outcomes on the trail-making test B (p=0.002), and 90% of students had low performance on verbal fluency tests (p=0.002). Conclusion: Alexithymia is linked with male gender, marital status, academic year, smoking, internet use and bullying history. We are increasing awareness and developing interventions to enhance the mental well-being of students.
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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 | 0.001 |
| 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) | 0.002 | 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".