Patient Satisfaction Following Orthodontic Treatment: A Systematic Review
Bibliographic record
Abstract
Patient-reported outcome measures (PROMs) have become increasingly important in orthodontic treatment as they reflect patients' perceptions of treatment outcomes. Understanding patient satisfaction with orthodontic treatment is crucial for improving healthcare delivery and patient-centered care. This systematic review aimed to critically appraise the evidence regarding patient satisfaction after orthodontic treatment, exploring the effects of different treatment types, patient demographics, and other factors on satisfaction levels. Eight electronic bibliographic databases were searched without publication time or language restrictions, including PubMed®, Scopus®, the Cochrane Central Register of Controlled Trials, Web of Science™, Embase®, Google™ Scholar, Trip, and OpenGrey. A manual search was conducted on the references in the included papers. Eligibility criteria were established based on the Population, Intervention, Comparison, Outcomes, and Study (PICOS) framework. Studies were included if they reported patient satisfaction levels following orthodontic treatment using standardized questionnaires. Two reviewers independently collected and analyzed the data. The risk of bias was assessed using Cochrane's risk of bias tool (RoB2) for randomized clinical trials, and the methodologic quality for cohort and cross-sectional studies was assessed using the modified version of the Newcastle-Ottawa scale. Fourteen studies employed various questionnaires and timings to gauge post-orthodontic treatment satisfaction. Patient satisfaction levels were generally high, with most studies reporting satisfaction rates above 91%. Fixed orthodontic appliances were associated with higher satisfaction levels compared to removable appliances. While age and gender did not significantly influence satisfaction, the quality of care and doctor-patient relationships were crucial factors in patient satisfaction. This systematic review proves that patient satisfaction with orthodontic treatment is generally high, with fixed appliances and positive doctor-patient relationships contributing to higher satisfaction levels. However, the quality of the evidence was moderate to low, highlighting the need for further high-quality clinical studies in this area.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".