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Record W4393228491 · doi:10.7748/nr.2024.e1919

Importance of patient and public involvement in doctoral research involving people living with dementia

2024· article· en· W4393228491 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNurse Researcher · 2024
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsScience North
Fundersnot available
KeywordsRelevance (law)Quality (philosophy)DementiaMedical educationApprenticeshipPsychologyTranslational researchProcess (computing)Public healthMedicineNursingPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: There is increasing recognition of the need to include patients and the public in the research process. There is extensive literature about patient and public involvement (PPI) in research, but fewer articles report on PPI in doctoral research. AIM: To reflect on establishing an advisory group for a doctoral study, exploring the opportunities and challenges associated with including patients with dementia in the research process. DISCUSSION: The authors discuss the practicalities of establishing an advisory group, the challenges of being a novice researcher, long-term commitment to PPI, the overall approach to PPI and ethical considerations. CONCLUSION: Establishing an advisory group for a doctoral study can facilitate mutual learning and enhance the study's quality. IMPLICATIONS FOR PRACTICE: Achieving high-quality PPI in health and social care research can ultimately improve its quality and relevance. An important aspect of the doctoral journey is developing knowledge and skills to facilitate PPI as part of a researcher's apprenticeship.

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.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.333
GPT teacher head0.489
Teacher spread0.156 · 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