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Record W3198761403 · doi:10.15586/jptcp.2021.v28i1.837

A comprehensive evaluation of knowledge and perceptions regarding geriatric dentistry among Saudi Arabian dental students

2021· article· en· W3198761403 on OpenAlexvenueno aff
Sami Aldhuwayhi

Bibliographic record

VenueJournal of Population Therapeutics and Clinical Pharmacology · 2021
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsnot available
FundersMajmaah University
KeywordsGeriatric dentistryPsychosocialMedicineFamily medicineOral healthPopulationDentistryGerontologyPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: The purpose of this study was to evaluate the knowledge and perceptions of Arabian dental students on geriatric dentistry. MATERIALS AND METHODS: A cross-sectional survey was conducted with a total of 100 participants belonging to Group I (25 each from third- and fourth-year students) and Group II (50 fifth-year students and interns ). All participants had completed a three-part questionnaire related to geriatric dentistry: Part I (knowledge), Part II (cognitive evaluation), and Part III (awareness and attitude of psychosocial and health problems). Comparisons were made between the groups, and the data were analyzed using SPSS software. RESULTS: The responses on the Part I were not statistically significant among the groups (P > 0.05). The knowledge mean scores comparison showed an evident significant relationship among the groups (P < 0.05). Overall the Group II participants achieved the highest scores for all the Parts (all P > 0.05). CONCLUSIONS: The students belong to Group II, and the interns achieved higher scores than the Group I students. Dental students and interns in Saudi Arabia lack positive approaches in providing primary health care to geriatric individuals despite a rapidly growing geriatric population.

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 score0.028
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.101
GPT teacher head0.495
Teacher spread0.394 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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