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Self-esteem in adolescents with Angle Class I, II and III malocclusion in a Peruvian sample

2016· article· en· W2410195416 on OpenAlexaff
Karla Florián-Vargas, Marcos J. Carruitero, Eduardo Bernabé, Carlos Flores‐Mir

Bibliographic record

VenueDental Press Journal of Orthodontics · 2016
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMalocclusionMedicineOrthodonticsDentistryAnalysis of covariancePsychologyMathematicsStatistics

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare self-esteem scores in 12 to 16-year-old adolescents with different Angle malocclusion types in a Peruvian sample. MATERIAL AND METHODS: A cross-sectional study was conducted in a sample of 276 adolescents (159, 52 and 65 with Angle Class I, II and III malocclusions, respectively) from Trujillo, Peru. Participants were asked to complete the Rosenberg Self-Esteem Scale (RSES) and were also clinically examined, so as to have Angle malocclusion classification determined. Analysis of covariance (ANCOVA) was used to compare RSES scores among adolescents with Class I, II and III malocclusions, with participants' demographic factors being controlled. RESULTS: Mean RSES scores for adolescents with Class I, II and III malocclusions were 20.47 ± 3.96, 21.96 ± 3.27 and 21.26 ± 4.81, respectively. The ANCOVA test showed that adolescents with Class II malocclusion had a significantly higher RSES score than those with Class I malocclusion, but there were no differences between other malocclusion groups. Supplemental analysis suggested that only those with Class II, Division 2 malocclusion might have greater self-esteem when compared to adolescents with Class I malocclusion. CONCLUSION: This study shows that, in general, self-esteem did not vary according to adolescents' malocclusion in the sample studied. Surprisingly, only adolescents with Class II malocclusion, particularly Class II, Division 2, reported better self-esteem than those with Class I malocclusion. A more detailed analysis assessing the impact of anterior occlusal features should be conducted.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.261
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2016
Admission routes1
Has abstractyes

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