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Record W1927821155 · doi:10.7205/milmed.172.12.1239

The Development of a Conceptual Model for Evaluating Dental Patient Satisfaction

2007· article· en· W1927821155 on OpenAlexaboutno aff
Jeffrey Chaffin, A. David Mangelsdorff, Kenn Finstuen

Bibliographic record

VenueMilitary Medicine · 2007
Typearticle
Languageen
FieldDentistry
TopicDental Anxiety and Anesthesia Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPatient satisfactionMedicineInterpersonal communicationMultilevel modelQuarter (Canadian coin)Family medicinePsychologyClinical psychologyNursingSocial psychologyStatisticsGeography

Abstract

fetched live from OpenAlex

The purpose of this study was to identify levels and predictors of patient satisfaction and develop a conceptual model for dental patient satisfaction in military treatment facilities. Respondents completed 658,443 surveys during 17 fiscal quarters, beginning with the fourth quarter of 2000. The final data set contained 309,261 surveys, with no missing data. Principal component factor analysis was used for data reduction and hierarchical multiple linear regression to assess the predictive effects of the dependent variables on the two independent variables: (1) overall satisfaction with today's visit and (2) overall satisfaction with the clinic. On a 7-point, bipolar adjective rating scale, patients' mean score was 6.53 regarding satisfaction with visit, suggesting that patients are highly satisfied. Patients' beliefs about care received and environment of care were the most important satisfaction attributes. These findings are useful in educating providers about the relationship of consumer satisfaction with the interpersonal experience.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.275

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 head0.054
GPT teacher head0.339
Teacher spread0.286 · 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 designOther design
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

Citations7
Published2007
Admission routes1
Has abstractyes

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