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Record W2795222453 · doi:10.1177/1049909118767136

Hope Tree: An Interactive Art Installation to Facilitate the Expression of Hope in a Hospice Setting

2018· article· en· W2795222453 on OpenAlexaff
Andrew Collins, Darpanjot Bhathal, Tara Field, Randene Larlee, Rachael Paje, Daneen Young

Bibliographic record

VenueAmerican Journal of Hospice and Palliative Medicine® · 2018
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsSurrey Memorial HospitalPeace Arch HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineHospice careExpression (computer science)NursingTree (set theory)Palliative careGerontology

Abstract

fetched live from OpenAlex

BACKGROUND: Individuals confronting a terminal illness can experience intense psychological distress. Previous research has shown that hope can enhance one's ability to acknowledge, accept, and fight a terminal illness. Patients can continue to have hope or be hopeful, even in the face of a terminal illness. Can participation in a creative writing practice improve the expression of hope in a hospice setting? METHODS: In this program evaluation, each expressed hope placed on the "Hope Tree" was independently coded by all research team members utilizing inductive content analysis. Overall themes were derived using a constant comparative approach and arranged into overarching themes based on consensus. RESULTS: Eight major themes emerged from the data: "Peace," "Dreams," "Total well-being," "Acknowledgment of loss," "Relationships," "Hospice care," "Spirituality," and "Dichotomies." CONCLUSION: The Hope Tree is a creative art project that can be used within a hospice environment to promote hope among family members and the health-care professionals who care for patients.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.027
GPT teacher head0.341
Teacher spread0.315 · 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

Citations10
Published2018
Admission routes1
Has abstractyes

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