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Existential Suffering in Palliative Care: An Existential Positive Psychology Perspective

2021· preprint· en· W3187733192 on OpenAlexaff
Paul T. P. Wong, Timothy T. F. Yu

Bibliographic record

VenuePreprints.org · 2021
Typepreprint
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsUniversity of TorontoTrent University
Fundersnot available
KeywordsExistentialismPalliative carePsychotherapistDialecticPsychological interventionFlourishingPsychologyMeaning (existential)NursingPerspective (graphical)MedicineEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has exposed the inadequacies of the current healthcare system and needs a paradigm change, which is holistic, and community based illustrated by the healing wheel. The present paper proposes that existential positive psychology (PP 2.0) represents a promising approach to meet the rising needs in palliative care. This framework has a twofold emphasis on (a) How to transcend and transform suffering as the foundation for wellbeing, and (b) how to cultivate our spiritual and existential capabilities to achieve personal growth and flourishing. We propose that these objectives can be achieved simultaneously through dialectical palliative counselling, as illustrated by Wong’s integrative meaning therapy (Wong, 2020) and Lo’s Conceptual Model of CALM Therapy in palliative care (Lo et al., 2014). We then discuss existential suffering in general and at the last stage of life in particular; we also review recent research and interventions on existential suffering in palliative patients. Finally, we outline the objectives and the strategies of IMT in providing palliative counselling for palliative care and hospice 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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.137
GPT teacher head0.441
Teacher spread0.304 · 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; both teacher heads agree on what is shown here.

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

Citations6
Published2021
Admission routes1
Has abstractyes

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