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Record W3087426731

A Psychoeducational Intervention for People Affected by Pancreatic Cancer

2019· dissertation· W3087426731 on OpenAlexfundno aff
Eryn Tong

Bibliographic record

VenueTSpace · 2019
Typedissertation
Language
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
FundersHealth CanadaPancare FoundationPrincess Margaret Cancer FoundationHirshberg Foundation for Pancreatic Cancer ResearchPancreatic Cancer Action Network
KeywordsIntervention (counseling)Pancreatic cancerCancerMedicinePsychologyPsychotherapistInternal medicineNursing
DOInot available

Abstract

fetched live from OpenAlex

The two aims of this thesis were to: (1) develop an interdisciplinary psychoeducational intervention for people affected by pancreatic cancer; and 2) evaluate the feasibility, acceptability, and preliminary efficacy of its implementation. All stages of research were informed by implementation science principles. In Study One, we developed Living Well with Pancreatic Cancer—an empirically-based, single session, manualized group intervention focused on supportive care needs in pancreatic cancer. Study Two was a mixed methods study to examine early phase implementation of our intervention in a pancreatic oncology clinic. Content and delivery were acceptable to patients, caregivers, and health care professionals (HCPs). Benefits included improved relationships with HCPs and knowledge of palliative and supportive care. Implementation was feasible, facilitated by stakeholder commitment and research support; however, additional human resourcing is required for sustainability. This research presents an innovative approach to operationalize supportive care and promote uptake of complex interventions into practice.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.364
Teacher spread0.339 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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