An Evaluation of Pain and Gingival Health of Patients Undergoing Fixed Orthodontic Treatment: A Questionnaire Study
Bibliographic record
Abstract
Background Fixed orthodontic appliances are essential for correcting malocclusions but often induce discomfort and pose challenges to maintaining oral hygiene. Pain and gingival issues are among the most common complaints, yet few studies have assessed both parameters comprehensively. Aim This study aimed to evaluate the levels of pain and gingival health among patients undergoing fixed orthodontic treatment using a structured, questionnaire-based approach. Methods A cross-sectional study was carried out among 110 orthodontic patients, aged 18–35 years, who had received treatment using the 0.22-slot MBT bracket system. Two questionnaires were administered: one assessing pain 24 hours after appliance placement using the Modified McGill Pain Questionnaire and visual analog scale (VAS) and another evaluating gingival health 2 months post-treatment initiation. Descriptive statistics were employed for data analysis. Results Over 70% of participants reported nonpainful sensations such as pressure, aching, and soreness according to the McGill Pain Questionnaire descriptors. Descriptive terms like miserable, strange, and annoying were frequently associated with higher subjective pain perception. Numeric pain intensity measured by the VAS showed that average scores remained within the mild-to-moderate range, with no participants reporting consistently severe pain. Regarding gingival health, 30% reported bad breath, 29.1% had difficulty brushing, and 24.5% experienced spontaneous gum bleeding. Only 18.2% perceived an improvement in gingival health during treatment. Conclusion The study highlights that while many patients experience discomfort during fixed orthodontic treatment, subjective pain perception varies and is best understood through qualitative descriptors alongside numeric VAS scores. Gingival health issues remain prevalent, underscoring the importance of targeted oral hygiene reinforcement. A comprehensive assessment of both pain quality and intensity is essential for improving patient management and compliance during orthodontic care.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".