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The Lived Experience of Patients with an Ostomy: A Pilot Study on the Effect of Ostomy Pouch Opacity

2021· article· en· W3217314255 on OpenAlexaffabout
Corey Heerschap, Victoria Duff

Bibliographic record

VenueAdvances in Skin & Wound Care · 2021
Typearticle
Languageen
FieldMedicine
TopicStoma care and complications
Canadian institutionsRoyal Victoria Regional Health Centre
Fundersnot available
KeywordsMedicinePouchOpacityPatient experiencePsychosocialThematic analysisNursingQualitative researchSurgeryHealth carePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore the effects of ostomy pouch opacity on the lived experience of patients with ostomies in the postoperative period. METHODS: This qualitative, descriptive phenomenology study used purposive sampling to recruit seven participants who were inpatients in an acute care facility in Central Ontario, Canada, after their first ostomy surgery. Face-to-face, audio-recorded, semistructured interviews were used to collect data regarding patient experience with either a transparent or opaque ostomy pouch. Data were collected between August and November 2019. Audio tapes were transcribed verbatim and analyzed using a thematic analysis technique focused on describing patient lived experience. RESULTS: Five themes were discovered: "undercover," "fiscal consideration," "past medical experience," "self-esteem," and "functionality." Most participants focused on appliance functionality over pouch opacity in the immediate postoperative period. However, participants did describe difficulties adjusting to their new stoma and noted that an opaque pouch can improve postoperative comfort. Past exposure to medical devices, particularly in terms of their cost, may impact the decision to use a transparent or opaque pouching system. CONCLUSIONS: Pouching systems that are opaque while still allowing for assessment of the pouching contents and stoma are ideal. When this is not available, providers should consider the patient's wishes to alleviate any psychosocial effects the opacity of the pouching system may have.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.320
Teacher spread0.302 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes2
Has abstractyes

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