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Record W2109235826 · doi:10.1177/0193945904265425

Dilemmas of Family Support During Cardiac Recovery

2004· article· en· W2109235826 on OpenAlexaff
Dianne M. Tapp

Bibliographic record

VenueWestern Journal of Nursing Research · 2004
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNaggingPsychologyEmpathyPsychotherapistFamily supportPhenomenonNursingMedicineDevelopmental psychologySocial psychologyEpistemology

Abstract

fetched live from OpenAlex

Family support has rarely been viewed as a relational phenomenon with interactional dynamics that shape individual and family experiences of cardiac recovery. This article describes a hermeneutic inquiry based on a retrospective review of videotapes of 24 clinical outpatient sessions between a family systems clinical nurse specialist and six families presenting with concerns related to living with heart disease. The research question that framed the analysis was "What is the relational character of family support during cardiac recovery?" One of the key patterns that emerged from the interpretations of clinical sessions with four of the six families was a dynamic well known in everyday experience and identified by families as "nagging." This article reveals nagging as an attempt to offer emotional support and encouragement for health maintenance activities. The helpful and potentially harmful consequences are discussed and possibilities for incorporating these understandings in clinical practice are explored.

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)0.021
metaresearch head score (Gemma)0.057
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 score0.021
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.057
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.022
Scholarly communication0.0060.007
Open science0.0010.007
Research integrity0.0030.004
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 head0.314
GPT teacher head0.522
Teacher spread0.208 · 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

Citations30
Published2004
Admission routes1
Has abstractyes

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