Difficulties in emotional regulation: association with poorer oral health‐related quality of life in the general population
Bibliographic record
Abstract
Personality is one of the strongest predictors of subjective well-being and may, according to a few previous studies, affect how people report oral health-related quality of life (OHRQoL). Alexithymia, a personality trait involving difficulties in emotional regulation, is associated with poorer health-related quality of life in the general population. We studied if alexithymia is also associated with poorer OHRQoL in a general population sample of 4,460 adults. Oral health-related quality of life was measured using the 14-item Oral Health Impact Profile (OHIP-14) and alexithymia was measured using the 20-item Toronto Alexithymia Scale (TAS-20). Controlling for clinically assessed dental health, depression, anxiety, and socio-demographic variables, higher scores on the TAS-20 as well as on its three dimensions [difficulties in identifying feelings (DIF), difficulties in describing feelings (DDF), and externally oriented thinking (EOT)] were associated with higher OHIP-14 composite scores according to Poisson regression analyses. In adjusted logistic regression analyses, the TAS-20 and two of its dimensions (DIF and DDF) were positively and significantly associated with the seven OHIP-14 dimensions and the prevalence of those reporting one or more OHIP-14 items fairly often or very often. The study showed that difficulties in emotional regulation might be reflected in poorer OHRQoL, regardless of the dental health status, depression, anxiety, and socio-demographic variables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 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 | 0.000 | 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) | 0.000 | 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".