A Cross-Sectional Study to Analyze the Correlation Between Alexithymia and Dental Neglect in Persons Pursuing Dental Care
Bibliographic record
Abstract
Background Alexithymia is a personality trait involving difficulties in emotional regulation (difficulties in identifying feelings, difficulties in describing feelings, and externally oriented thinking). It has a negative impact on health as it evokes poor personal hygiene, poor nutrition, and unhealthy behaviors in affected subjects. Identifying alexithymia in the dental setup is vital as it can compromise the patient-dentist relationship, especially in subjects neglecting oral hygiene. Aims The present study aimed to establish an association between alexithymia and dental neglect among adult subjects seeking dental care by using Dental Neglect Scale (DNS), and alexithymia was assessed on the 20-item Toronto Alexithymia Scale (TAS-20). Methods The present cross-sectional survey study included adult subjects of age 20 years or more. For all included participants, a structured questionnaire was given to assess dental neglect on demographic profile, six items of the DNS, and alexithymia was assessed on the 20-item TAS-20. The collected data were analyzed using a Chi-square test keeping significance at the p-value of <0.05. Results In 534 adult subjects, females had high scores for both TAS-20 and DNS along with their related factors. With higher education and increasing age, a significant increase in the mean TAS-20 scores and mean DNS scores was seen in the study participants (high mean DNS scores in females (19.55±3.98) compared to male subjects 19.36±4.34). TAS-20 scores were higher in females (59.31±10.78), factor 1 (DIF) (19.54±5.54), factor 2 (DDF) (15.46±4.05), and factor 3 (EOT) (24.34±4.64). Conclusion The present study, considering its limitations, concludes that there is no association between dental neglect and alexithymia in adult subjects seeking dental care. However, higher DNS and TAS-20 scores are seen in females showing them have difficult descriptions and identification of feelings in dental set-up increasing dental neglect among them.
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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 | 0.001 | 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".