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Record W1684879496 · doi:10.1097/ncc.0000000000000275

Canadian Nurses’ Perspectives on Prostate Cancer Support Groups

2015· article· en· W1684879496 on OpenAlexfundaboutno aff
Wellam F. Yu Ko, John L. Oliffe, Christina Han, Bernie Garrett, Timothy Henwood, Anthony Tuckett, Armin Sohrevardi

Bibliographic record

VenueCancer Nursing · 2015
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsPsychosocialMedicineLikert scaleNursingFace-to-faceDescriptive statisticsSocial supportFamily medicineQualitative researchContent analysisSupport groupMedical educationPsychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Prostate cancer support groups (PCSGs) are community-based organizations that offer information and psychosocial support to men who experience prostate cancer and their families. Nurses are well positioned to refer men to a range of psychosocial resources to help them adjust to prostate cancer; however, little is known about nurses' perspectives on PCSGs. OBJECTIVE: The aim of this study was to describe nurses' views about PCSGs as a means to making recommendations for advancing the effectiveness of PCSGs. METHODS: A convenience sample of 101 Canadian nurses completed a 43-item Likert-scale questionnaire with the additional option of providing comments in response to an open-ended question. Univariate descriptive statistics and content analysis were used to analyze the quantitative and qualitative data, respectively. RESULTS: Participants held positive views about the roles and potential impact of PCSGs. Participants strongly endorsed the benefits of support groups in disseminating information and providing support to help decrease patient anxiety. Online support groups were endorsed as a practical alternative for men who are reluctant to participate in face-to-face groups. CONCLUSIONS: Findings suggest that nurses support the value of Canadian face-to-face and online PCSGs. This is important, given that nurses can help connect individual patients to community-based sources providing psychosocial support. IMPLICATIONS FOR PRACTICE: Many men benefit from participating in PCSGs. Aside from positively endorsing the work of PCSGs, nurses are important partners for raising awareness of these groups among potential attendees and can directly contribute to information sharing in face-to-face and online PCSGs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.455

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0240.006
Scholarly communication0.0050.002
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.027
GPT teacher head0.336
Teacher spread0.309 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2015
Admission routes2
Has abstractyes

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