Relationship between Personality and Impacts of Implant Treatment on Daily Living
Bibliographic record
Abstract
PURPOSE: The objective of this study was to investigate the relationship between satisfaction with implant-supported fixed rehabilitations (ISFPR), their impacts on daily living, and personality profiles. MATERIALS AND METHODS: Fifty patients (15 men and 35 women; mean age 44.3 ± 9 years), with fitted ISFPR, and 50 partially dentate controls matched with age and gender participated in this study. A Dental Impact on Daily Living questionnaire was used to assess dental satisfaction and impacts of ISFPR on daily living. NEO Five Factor inventory was used to assess participants' personality profiles. Pearson correlation, analysis of variance, and linear regression tests were used for statistical analysis of the data. RESULTS: Patients with ISFPR were more satisfied with their dentition than controls (p < .05). Patients and controls demonstrated different relationships between personality, impacts on daily living, and satisfaction. Neuroticism, extraversion, and conscientiousness had significant relationships with satisfaction and impacts on daily living in both groups (p < .05). Openness and agreeableness had significant relationships with satisfaction and impacts on daily living in patients' group (p < .05). CONCLUSION: ISFPR had positive impacts on participants' daily living and dental satisfaction. Personality traits (neuroticism, extraversion, openness, agreeableness, and consciousness) impact on daily living and satisfaction with ISFPR, and might predict satisfaction with ISFPR and their impacts on daily living.
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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 | 0.000 | 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) | 0.002 | 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".