The relation between alexithymia, eating attitude, and sleep pattern among university students during the lockdown period of COVID-19 pandemic
Bibliographic record
Abstract
Background: COVID-19 lockdown's impact on physical and mental health includes increased prevalence of alexithymia (difficulty recognizing emotions) among university students. Alexithymia is strongly correlated with eating disorders and disrupted eating behaviors. Understanding these associations is crucial for assessing the well-being of students during lockdown. Aims: The aim was to evaluate the prevalence of alexithymia and eating disorders in relation to sleep disturbance during this lockdown phase amongst university students. Settings and Design: This study employed an online cross-sectional design to collect data from participants. The study included adolescents of either gender, aged between 20 and 27 years, who were enrolled in the faculty of Allied Health Sciences at Manav Rachna International Institute of Research & Studies. Methods and Material: The study comprised 419 university students during the COVID-19 lockdown. Alexithymia was assessed using the Toronto Alexithymia Scale-20, eating disorders with the Eating Aptitude Test-26, and sleep patterns with a modified Pittsburgh Sleep Scale. Statistical Analysis Used: Descriptive statistics, including Mean±SD for continuous variables and frequency/percentages for categorical data, were calculated. Statistical analysis involved Student t-test and chi-square. Reliability of the questionnaire was assessed using Cronbach's Alpha. Results: This study involved 77.8% ( n =326) female students as compared to 22.2%( n =93) male students. The prevalence of alexithymia was found to be considerably higher(30.5%) in the present study, with female students more affected than males. An eating disorder was found to be only 16.7%, and the majority of students (65.4%) had BMI in the range of normal weight. Further, the students reported the absence of sleep apnea with 41% of students having a sleep duration of 6-7 hours and 32% more than 7 hours. Only 19% of students reported poor sleep quality. Trouble sleeping during the initial 30 minutes prior to lying down, waking up in the middle of the night, and waking up to use the bathroom were the main factors causing sleep disturbances. Conclusions: This study reported a high alexithymia prevalence since there were under house arrest and going through psychological stress during lockdown phase of COVID-19 pandemic. Eating disorders was not prevalent because the students ate healthy balanced diets at home rather than junk food. Sleep patterns were also significantly improved and did not show any relation to the increased prevalence of alexithymia.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".