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Record W2034900214 · doi:10.1002/cncr.24386

The cancer Support Person's Unmet Needs Survey

2009· article· en· W2034900214 on OpenAlexaff
H. Sharon Campbell, Rob Sanson‐Fisher, Jill Taylor‐Brown, Lynda Hayward, X. Sunny Wang, Donna Turner

Bibliographic record

VenueCancer · 2009
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of ManitobaCancerCare ManitobaUniversity of Waterloo
Fundersnot available
KeywordsMedicineCancerFamily medicineGerontologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: A rigorous psychometric methodology was used to develop a measure of unmet needs for cancer survivors' principal support persons. Principal support person was defined as "someone you can count on and who helps you with your needs." METHODS: Development of the domains and the items followed an extensive literature review, iterative input from support persons, and consultation with health professionals and front-line staff working with cancer survivors and their supports. Cognitive interviews helped clarify item wording, and the draft questionnaire was reappraised by a group of support persons. The questionnaire was reduced to 90 items and sent to a stratified, random sample of cancer survivors selected from a provincial population-based cancer registry. They were asked to give the survey to their support person. RESULTS: The resulting 78-item Support Person Unmet Needs Survey has high acceptability, item test-retest reliability, internal consistency (Chronbach alpha = .990), and face, content, and construct validity. It captures 6 domains of unmet needs and accounts for 73.5% of total variance: Information and Relationship Needs (27 items, 22.1% of variance), Emotional Needs (16 items, 15.2%), Personal Needs (14 items, 14.0%), Work and Finance (8 items, 8.8%), Health Care Access and Continuity (9 items, 8.6%), and Worries About Future (4 items, 4.8%). CONCLUSIONS: This instrument will be of use where there is an interest in examining the impact of cancer not only on cancer survivors but also on their identified principal support persons.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.042
GPT teacher head0.327
Teacher spread0.285 · 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.

Study designNot applicable
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

Citations87
Published2009
Admission routes1
Has abstractyes

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