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Record W2048766738 · doi:10.1002/pon.1078

Cancer support groups: a critical review of empirical studies

2006· review· en· W2048766738 on OpenAlexaff
Benjamin H. Gottlieb, Elizabeth D. Wachala

Bibliographic record

VenuePsycho-Oncology · 2006
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPsychosocialRandomized controlled trialEmpirical researchQuality of life (healthcare)Intervention (counseling)PsychologyCancerOutcome (game theory)Clinical psychologyGerontologyMedicinePsychotherapistPsychiatryEconomics

Abstract

fetched live from OpenAlex

Support groups for adults affected by cancer are widely offered by local community and national agencies in North America. This type of psychosocial intervention is defined in terms of its structure and functions, and its theoretical underpinnings and models of practice are described. Forty-four empirical studies of professionally led cancer support groups are summarized and critically reviewed. These studies include 32 outcome evaluations of randomized controlled trials, two process evaluations, and 10 consumer satisfaction studies. The findings reveal high levels of consumer satisfaction, and the outcome evaluations substantiate the morale and other quality of life benefits short of prolonging life. Discussion centers on priorities for future research and practice.

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)0.007
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0110.014
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.244
GPT teacher head0.571
Teacher spread0.327 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations182
Published2006
Admission routes1
Has abstractyes

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