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Record W4226218878 · doi:10.32920/ihtp.v1i3.1439

Perception of self-care ability among patients with stroke post-discharge: A qualitative descriptive study in Iran

2021· article· en· W4226218878 on OpenAlexaffvenue
Nasrin Jafari-Golestan, Asghar Dalvandi, Mohammadali Hosseini, Masoud Fallahi‐Khoshknab, Abbas Ebadi, Mahdi Rahgozar, Souraya Sidani

Bibliographic record

VenueInternational Health Trends and Perspectives · 2021
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMedicineQualitative researchAnxietyFeelingWorryClinical psychologyPsychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Background: Patients with stroke, once at home, experience different perceptions of their ability for self-care. The purpose of this qualitative descriptive study was to elucidate patients’ perception of their self-care ability. Methods: Semi-structured interviews were held with 10 patients with stroke, within one month following discharge from hospital. Sampling was purposeful and continued until data saturation was reached. All recorded interviews were transcribed and imported to MAXQDA software. The transcripts were content analyzed, following the five-step method by Granheim and Lundman. Results: Three main categories and ten subcategories were revealed: immersion in distress (feeling of sorrow and sadness, lack of control of life, feeling of anxiety and worry), perceived difficulty (dependency on others, disabling nature of the disease, multiple underlying diseases and mental health problems) and compatible adaptive reaction (acceptance of disability, improving health literacy, enhancement of spiritual health). Conclusions: Patients with stroke reported limited ability for self-care post-discharge, which had a considerable effect on their engagement in self-care behaviors and application of recommended treatment methods at home. The findings have implications for designing nurse-led interventions to promote self-care in this vulnerable patient 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 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 score0.082
Threshold uncertainty score0.380

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 head0.029
GPT teacher head0.366
Teacher spread0.337 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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