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Record W2616251949 · doi:10.1111/idh.12286

A cluster randomized theory‐guided oral hygiene trial in adolescents—A latent growth model

2017· article· en· W2616251949 on OpenAlexaff
Jolanta Aleksejūnienė, Vilma Brukienė

Bibliographic record

VenueInternational Journal of Dental Hygiene · 2017
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicinePsychological interventionOral hygieneBivariate analysisRandomized controlled trialCluster (spacecraft)Cluster randomised controlled trialMultivariate analysisRandomizationHygieneDemographyDentistryPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: (i) To test whether theory-guided interventions are more effective than conventional dental instruction (CDI) for changing oral hygiene in adolescents and (ii) to examine whether such interventions equally benefit both genders and different socio-economic (SES) groups. METHODS: A total of 244 adolescents were recruited from three schools, and cluster randomization allocated adolescents to one of the three types of interventions: two were theory-based interventions (Precaution Adoption Process Model or Authoritative Parenting Model) and CDI served as an active control. Oral hygiene levels % (OH) were assessed at baseline, after 3 months and after 12 months. RESULTS: A complete data set was available for 166 adolescents (the total follow-up rate: 69%). There were no significant differences in baseline OH between those who participated throughout the study and those who dropped out. Bivariate and multivariate analyses showed that theory-guided interventions produced significant improvements in oral hygiene and that there were no significant gender or socio-economic differences. CONCLUSIONS: Theory-guided interventions produced more positive changes in OH than CDI, and these changes did not differ between gender and SES groups.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
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 head0.029
GPT teacher head0.347
Teacher spread0.318 · 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 designRandomized trial
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

Citations9
Published2017
Admission routes1
Has abstractyes

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