Effect of orthodontic pain on quality of life of patients undergoing orthodontic treatment
Bibliographic record
Abstract
INTRODUCTION: Pain is an important aspect of oral health-related quality of life (OHRQOL). Understanding how patients' pain experiences during their treatment affect their quality of life (QOL) is important and the absence of pain/discomfort is important for achieving a high QOL. AIM AND OBJECTIVE: The objective of this study was to assess the relationship between pain and OHRQOL among patients wearing fixed orthodontic appliances and to evaluate whether patient motivation and counseling had an effect on the pain and discomfort. MATERIALS AND METHODS: The McGill-Short-Form with visual analog scale and present pain intensity and Oral Health Impact Profile-14 indices were used to determine the intensity and severity of pain and to evaluate the QOL of 200 adolescents undergoing fixed orthodontic treatment during different phases of treatment. RESULTS: There was a significant correlation found between pain and the QOL of patients undergoing orthodontic treatment. Overall score of OHRQOL increased significantly (mean 43.5 ± 10.9) in the initial phase of treatment where the incidence of severe to moderate pain was reported in 80% patients. Ninety-five percent patients felt pain or discomfort. After 1 day of appliance placement, more than 85% of patients experienced severe to mild pain whereas 9% of patients suffered very severe pain. Pain reduced over a week, and at the end of a month, 10.5% patients had moderate pain whereas majority, i.e., 58% of patients complained of only mild pain (P < 0.05). CONCLUSION: Pain is important sequelae of orthodontic treatment and has a significant effect on the QOL of orthodontic patients, especially during the initial phases of treatment. Patient motivation and counseling by the orthodontist have a profounding effect in reducing the pain and discomfort, improving the QOL, and an overall improvement in the patient compliance affecting the successful outcome of the treatment.
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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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".