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Record W2766254472 · doi:10.1017/s1463423617000688

Development and preliminary validation of the physician support of skin self-examination scale

2017· article· en· W2766254472 on OpenAlexafffund
Adina Coroiu, Chelsea Moran, Rosalind Garland, Annett Körner

Bibliographic record

VenuePrimary Health Care Research & Development · 2017
Typearticle
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsBivariate analysisScale (ratio)Context (archaeology)Convergent validityExploratory factor analysisPsychologyClinical psychologyMedicinePsychometricsComputer scienceInternal consistencyMachine learning

Abstract

fetched live from OpenAlex

Skin self-examination (SSE) is a crucial preventive health behaviour in melanoma survivors, as it facilitates early detection. Physician endorsement of SSE is important for the initiation and maintenance of this behaviour. This study focussed on the preliminary validation of a new nine-item measure assessing physician support of SSE in melanoma patients. English and French versions of this measure were administered to 188 patients diagnosed with melanoma in the context of a longitudinal study investigating predictors and facilitators of SSE. Structural validity was investigated using exploratory factor analysis conducted in Mplus and convergent and divergent validity was assessed using bivariate correlations conducted in spss. Results suggest that the scale is a unidimensional and reliable measure of physician support for SSE. Given the uncertainty regarding the optimal frequency of SSE for at-risk individuals, we recommend that future psychometric evaluations of this scale consider tailoring items according to the most up-to-date research on SSE effectiveness.

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)0.000
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 score0.962
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.032
GPT teacher head0.349
Teacher spread0.317 · 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

Citations8
Published2017
Admission routes2
Has abstractyes

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