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Record W4200274492 · doi:10.5737/cvaa-1531524

‘Pinholes in my arms’: The vicious cycle of vascular access

2021· article· en· W4200274492 on OpenAlexvenueno aff
Linda J Kelly, Austyn Snowden

Bibliographic record

VenueVascular Access · 2021
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsnot available
Fundersnot available
KeywordsVenous accessSuperordinate goalsCompetence (human resources)Embodied cognitionInterpretative phenomenological analysisMedicineVascular accessPsychologyNonprobability samplingQualitative researchSocial psychologySurgerySociologyComputer science

Abstract

fetched live from OpenAlex

Background: Vascular access devices (VADs) are essential for delivery of intravenous therapies. There are notable gaps in the literature regarding a focus on patient experience and meaning-making related to living with a VAD, specifically a central venous access device (CVAD). Aims: To explore how patients make sense of living with a CVAD. Methods: This study followed an interpretive phenomenological analysis (IPA) approach. Purposive sampling was used to identify 11 cancer patients who had a CVAD in situ. One-to-one semi-structured interviews were performed. Interviews were digitally recorded, transcribed and analysed by the lead author. Findings: Four superordinate themes were identified: the self under attack; being rescued/being robbed; protection of others/protection of self; bewilderment and dismay at lack of staff competence. Conclusion: Having a CVAD affects the psychological, social, and personal self and impacts on self-esteem and self-image. Despite this, CVADs are accepted by patients and are eventually ‘embodied’ by them.

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)0.008
metaresearch head score (Gemma)0.026
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 score0.011
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.043
Scholarly communication0.0100.011
Open science0.0020.009
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.388
Teacher spread0.340 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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