An exploratory pilot study to assess self-perceived changes among social assistance recipients regarding employment prospects after receiving dental treatment
Bibliographic record
Abstract
BACKGROUND: Strengthening self-efficacy in job-seeking among individuals with dental problems has been identified as an important factor in facilitating job procurement and maintenance. There is no knowledge about whether receiving dental treatment improves someone's self-efficacy in seeking a job. This work explores this relationship. METHODS: An exploratory pilot study of a convenience sample of 30 social assistance recipients of Ontario, Canada, was conducted using a pre- and post-dental treatment survey, which included both quantitative and qualitative components. The survey included two validated instruments Oral Health Impact Profile (OHIP-14) and Job-Seeking Self-efficacy scale (JSS). Changes in scores of both scales following dental treatment were calculated. Pearson correlation was performed between OHIP-14 and JSS scores. Qualitative data were transcribed and interrelated ideas were grouped together to generate themes. RESULTS: Mean scores for OHIP-14 (23.4 to 6.7, p < 0.001, effect size: 1.75) and median scores for JSS (4.9 to 5.5, p = 0.002, effect size: 0.40) changed significantly after receiving dental treatment. A significant negative correlation (-0.56, p = 0.001) was observed between OHIP-14 and JSS scores indicating that job-seeking self-efficacy improves with improvement in oral health related quality of life (OHRQoL). Qualitative analysis reveals participants' physical and psychosocial impacts of dental problems; barriers experienced in accessing dental care and seeking a job; and changes perceived after receiving dental care. CONCLUSION: Results of our survey indicate that social assistance recipients experience negative impacts of dental problems and perceive improvements in OHRQoL and job-seeking self-efficacy after receiving dental treatment.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".