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Record W3214256712 · doi:10.1002/cncr.34034

Hope and advance care planning in advanced cancer: Is there a relationship?

2021· article· en· W3214256712 on OpenAlexaboutno aff
Michael G. Cohen, Andrew D. Althouse, Robert M. Arnold, Hailey W. Bulls, Douglas B. White, Edward Chu, Margaret Rosenzweig, Kenneth J. Smith, Yael Schenker

Bibliographic record

VenueCancer · 2021
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsnot available
FundersNational Cancer InstituteNational Heart, Lung, and Blood InstituteNIH Clinical CenterNational Institute on Aging
KeywordsMedicineAdvance care planningCancerPalliative careDepression (economics)AnxietyPerformance statusMarital statusSocioeconomic statusRandomizationConversationLung cancerRandomized controlled trialInternal medicinePhysical therapyPsychiatryPopulationNursingPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Clinicians often cite a fear of giving up hope as a reason they defer advance care planning (ACP) among patients with advanced cancer. The objective of this study was to determine whether engagement in ACP affects hope in these patients. METHODS: This was a secondary analysis of a randomized controlled trial of primary palliative care in advanced cancer. Patients who had not completed ACP at baseline were included in the analysis. ACP was assessed in the forms of an end-of-life (EOL) conversation with one's oncologist and completion of a living will or advance directive (AD). Measurements were obtained at baseline and at 3 months. Hope was measured using the Herth Hope Index (HHI) (range, 12-48; higher scores indicate higher hope). Multivariate regression was performed to assess associations between ACP and hope, controlling for baseline HHI score, study randomization, patient age, religious importance, education, marital status, socioeconomic status, time since cancer diagnosis, pain/symptom burden (Edmonton Symptom Assessment System), and anxiety/depression score (Hospital Anxiety and Depression Scale)-all variables known to be associated with ACP and/or hope. RESULTS: In total, 672 patients with advanced cancer were enrolled in the overall study. The mean age was 69 ± 10 years, and the most common cancer types were lung cancer (36%), gastrointestinal cancer (20%) and breast/gynecologic cancers (16%). In this group, 378 patients (56%) had not had an EOL conversation at baseline, of whom 111 of 378 (29%) reported having an EOL conversation by 3 months. Hope was not different between patients who did or did not have an EOL conversation over the study period (mean ± standard deviation ∆HHI, 0.20 ± 5.32 vs -0.53 ± 3.80, respectively; P = .136). After multivariable adjustment, hope was significantly increased in patients who had engaged in an EOL conversation (adjusted mean difference in ∆HHI, 0.95; 95% CI, 0.08-1.82; P = .032). Similarly, of 216 patients (32%) without an AD at baseline, 67 (31%) had subsequently completed an AD. Unadjusted hope was not different between those who did and did not complete an AD (∆HHI, 0.20 ± 3.89 vs -0.91 ± 4.50, respectively; P = .085). After adjustment, hope was significantly higher in those who completed an AD (adjusted mean difference in ∆HHI, 1.31; 95% CI, 0.13-2.49; P = .030). CONCLUSIONS: The current results demonstrate that hope is not decreased after engagement in ACP and indeed may be increased. These findings may provide reassurance to clinicians who are apprehensive about having these important and difficult conversations. LAY SUMMARY: Many oncologists defer advance care planning (ACP) out of concern for giving up hope. This study demonstrates that hope is not decreased in patients who have engaged in ACP either as a conversation with their oncologists or by completing an advance directive. With this information, providers may feel more comfortable having these important conversations with their 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)0.000
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 score0.208
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.358
Teacher spread0.336 · 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 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

Citations51
Published2021
Admission routes1
Has abstractyes

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