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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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0230.000

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 teacher head, not a consensus.

Study designNot applicable
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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