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Record W1995419289 · doi:10.1188/02.onf.981-987

Interactive Family Learning Following a Cancer Diagnosis

2002· article· en· W1995419289 on OpenAlexaff
Patricia Friesen, Carolyn Pepler, Patricia Hunter

Bibliographic record

VenueOncology nursing forum · 2002
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineQualitative researchNursingFamily medicine

Abstract

fetched live from OpenAlex

PURPOSE/OBJECTIVES: To describe the experience of families when a member is diagnosed with cancer. DESIGN: Descriptive, qualitative study. SETTING: Patients' homes. SAMPLE: Eight adults, two to five months postdiagnosis, who were receiving radiotherapy or chemotherapy for stage I or II solid tumors and family members, including seven children between the ages of 13-18. Thirty people interviewed total. METHODS: Patients recruited from an oncology outpatient clinic and gynecologic inpatient unit of a teaching hospital interviewed on one occasion with at least two immediate family members in patients' homes. Semistructured interviews were tape-recorded and analyzed for themes and categories using the techniques of constant comparison. MAIN RESEARCH VARIABLES: Transitions from health to illness. FINDINGS: Families described a learning process in which information was gathered, interpreted, and shared. Families learned together by reviewing the past, gathering and sharing information, and sharing their experiences of living with someone undergoing treatment for cancer. By revealing their own personal perspectives, patients taught their families about their illness experiences and what constituted effective support. CONCLUSIONS: Interactive family learning is a mode of learning and a form of support in which the whole family may participate early in the process of learning to live with cancer. IMPLICATIONS FOR NURSING: Nurses can facilitate patient and family learning by considering the interactive manner in which families acquire information. By acknowledging how past experiences with cancer inform the present, nurses can help families identify beliefs influencing the illness experience. By including families in teaching sessions; facilitating communication between patients, families, physicians, and nurses; and providing take-home learning materials, nurses can facilitate shared information gathering. Nurses should acknowledge the value of learning about illness by experience, accept patients and families as experts, and encourage revelation of patients' and families' perspectives of the illness to enhance feedback on support and coping.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.003
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.121
GPT teacher head0.457
Teacher spread0.336 · 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

Citations10
Published2002
Admission routes1
Has abstractyes

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