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Record W2538404978 · doi:10.1177/2333393616674810

Embodying a New Meaning of Being At Risk

2016· article· en· W2538404978 on OpenAlexaff
April Manuel, Fern Brunger

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsMemorial University of Newfoundland
FundersHealth Research Board
KeywordsPsychosocialCoping (psychology)DistressMedicineImplantable cardioverter-defibrillatorNarrativeMeaning (existential)PopulationPsychologyPsychotherapistClinical psychologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Arrhythmogenic Right Ventricular Cardiomyopathy/Dysplasia (ARVC/D) is a genetic condition that can cause fatal arrhythmias. The implantable cardioverter defibrillation (ICD) is a primary treatment for ARVC/D. Using a grounded theory approach, this study examines the experiences of 15 individuals living with an ICD. The ability to cope with and adjust to having an ICD is influenced by the acceptance of the ICD as something needed to survive, an understanding of the ICD's function, existing support networks, and ones' ability to manage everyday challenges. Coping well requires reshaping ideas about the meaning of being at risk and understanding how the ICD fits into that changing personal risk narrative. A thorough understanding of the unique needs of individuals with ARVC/D and of the specific factors contributing to the psychosocial distress related to having an ICD (vs. having the disease itself) is needed. Nurses must be prepared to provide ongoing support and education to this population.

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)0.010
metaresearch head score (Gemma)0.013
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 score0.010
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0070.034
Scholarly communication0.0080.008
Open science0.0010.011
Research integrity0.0020.006
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 head0.089
GPT teacher head0.491
Teacher spread0.403 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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