Impact of self-esteem on the relationship between orthodontic treatment and the oral health-related quality of life in patients after orthodontic treatment – a systematic review
Bibliographic record
Abstract
OBJECTIVE: The treatment protocol in the modern health care paradigm has shifted considerably towards enhancing the quality of life in the last decade. This is particularly important in cosmetic and elective treatments, and hence the interest in oral health-related quality of life (OHRQoL) also has increased. OHRQoL always been measured by endogenous, functional, social, or psychological determinants. Self-esteem (SE) is one of the internal factors that affect the perception of malocclusion and hence OHRQoL before and after treatment. The purpose of this review is to assess whether there exists any correlation between the Oral Health-Related Quality of Life, Self-esteem (SE) in patients following orthodontic treatment. METHODS: , grey literature, and hand search on cross-references was performed to find additional data. The studies found to be suitable were selected based on the predefined inclusion and exclusion criteria. The quality of assessment and risk of bias for the included studies were evaluated independently by two invigilators utilizing "The Cochrane Collaboration's tool for assessing the risk of bias" and "Modified version of the Newcastle Ottawa scale" for Randomized Controlled Trials (RCTs) and non-randomized trials respectively. RESULTS: A total of 7688 studies were retrieved from all the sources. After screening all the titles and excluding the duplicates, 28 studies were finally included for text review, and all of them were fit for quality appraisal. The design of the final studies included comprised of 3 RCTs, 14 cohort studies, 9 cross-sectional studies, and 2 case-control studies. CONCLUSION: There is moderate evidence to show that fixed orthodontic treatment improves OHRQoL and SE in children. OHRQoL also increased in adolescents and adults. However, there is a weak correlation between SE and OHRQoL. More evidence-based studies are needed to analyze the relationship.
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".