MétaCan
Menu
Back to cohort
Record W4408863789 · doi:10.33235/wcet.45.1.27-33

Adults’ and their care partners’ perspectives of living with a stoma: a qualitative descriptive, community-based inquiry

2025· article· en· W4408863789 on OpenAlexaboutno aff
Janet L. Kuhnke, Tracy Lillington

Bibliographic record

VenueWCET Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicStoma care and complications
Canadian institutionsnot available
Fundersnot available
KeywordsQualitative researchDescriptive researchPsychologyDescriptive statisticsSociologyNursingMedicineSocial science

Abstract

fetched live from OpenAlex

Individuals living with ostomies in small communities rely on friends, family, and health-care professionals for support, otherwise, they risk becoming isolated, which may affect quality-of-life.Objective This study explored how individuals and their partners manage ostomy care and engage in daily activities.Method This study utilised semi-structured interviews to explore perspectives of six participants living with an ostomy and two care partners in eastern Canada.Participants were recruited through a hospital ostomy service and community libraries.Adults with ostomies and their partners willing to articulate the journey of living with a stoma were recruited.All data were analysed using reflexive thematic analysis. ResultsParticipants were challenged to receive consistent support from an ostomy nurse.Partners were not included in education sessions.Participants quickly adopted an independent self-management approach, were resilient and resourceful.Consistent connection to the ostomy clinics and accessible face-to-face or online supports were lacking.Participants searched web-based platform for support to manage complications. ConclusionNurses specialised in ostomy care are in a position to support adults living with ostomies, and their care partners.Consistent, relevant education and supports should be offered by interprofessional teams.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.307

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 head0.063
GPT teacher head0.379
Teacher spread0.316 · 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 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueWCET JournalSame topicStoma care and complicationsFrench-language works237,207