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Record W2001442019 · doi:10.5430/jha.v3n4p119

Support services for people who have undergone treatment for head and neck cancer: an approach to evaluating services

2014· article· en· W2001442019 on OpenAlexvenueno aff
Ann Richardson, Pauline Barnett, Liz Horn, Kate Reid, W. N. Mann, Frankie Roake, Catherine Dwan, Robert D. Allison, Catriona R. Mackay

Bibliographic record

VenueJournal of Hospital Administration · 2014
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisMultidisciplinary approachService (business)MedicineBest practiceService providerQualitative researchNursingHead and neckService delivery frameworkMedical educationPublic relationsBusinessMarketingSurgeryManagementPolitical scienceSociology

Abstract

fetched live from OpenAlex

The purpose of this qualitative research was to (1) determine whether support services for people who have undergone treatment for head and neck cancer in Canterbury, New Zealand, align with current national and international guidelines and recommendations for best practice, (2) investigate the views of consumers and health service providers, about current support services and service needs, (3) develop recommendations for a coordinated support service. Interviews with consumers and with service providers, including multidisciplinary team members, were undertaken to collect information about support services for people with head and neck cancer in Canterbury. The analysis was undertaken in two stages. First, information was compared with current guidelines, and second, transcripts of interviews were analysed thematically, using a general inductive approach, to understand any issues arising for both consumers and providers. Comparison with guidelines identified many strengths and a few limitations of the current service compared with international best-practice. A number of other issues arose from the thematic analysis which suggested potential areas for improvement. Recommendations were made to support a best-practice, evidence-based coordinated support service for people with head and neck cancer in Canterbury. The method used to evaluate this service could be used in the evaluation of other intersectoral, multidisciplinary health services.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.497

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 studies0.0010.000
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 head0.079
GPT teacher head0.470
Teacher spread0.391 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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