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Record W2052417541 · doi:10.1177/1043659611405531

The Impact of Cancer on Family Relationships Among Chinese Patients

2011· article· en· W2052417541 on OpenAlexafffund
Joyce Lee, Kirsten Bell

Bibliographic record

VenueJournal of Transcultural Nursing · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsUniversity of British Columbia
FundersBC Cancer AgencyCanadian Institutes of Health Research
KeywordsFocus groupPsychological interventionDistressMedicineAnxietyQualitative researchSupport groupFamily memberPsychologyClinical psychologyFamily medicineNursingPsychiatry

Abstract

fetched live from OpenAlex

This study examines the impact of cancer on family relationships among members of a Chinese cancer support group. A qualitative research design was used, including participant observation of 96 participants at group meetings over an 8-month period and in-depth interviews with seven group members. Findings indicated that family members were integral to the support group, constituting almost 40% of the participants. Patients in the group expressed concerns about family, with family members identified as having "equal suffering" when caring for patients. Notably, among both patients and family members, there was a strong emphasis on the need to conceal emotion, coupled with a focus on instrumental support in caregiving. Furthermore, patients' anxiety about "burdening" their family appeared to inflate their own experience of distress, as patients and their family carers both sought to maintain a positive front. The findings highlight the need for practitioners to focus on the entire family when designing interventions to help patients cope with cancer. More important, interventions need to be culturally sensitive that will empower patients and family members in living with the illness.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.063
GPT teacher head0.353
Teacher spread0.290 · 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

Citations56
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Transcultural NursingSame topicFamily Support in IllnessFrench-language works237,207