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Financial Distress and Its Associations With Physical and Emotional Symptoms and Quality of Life Among Advanced Cancer Patients

2015· article· en· W2121508408 on OpenAlexaboutno aff
Marvin Omar Delgado-Guay, Jeanette Ferrer, Alyssa G. Rieber, Wadih Rhondali, Supakarn Tayjasanant, Jewel Ochoa, Hilda Cantu, Gary B. Chisholm, Janet L. Williams, Susan Frisbee‐Hume, Éduardo Bruera

Bibliographic record

VenueThe Oncologist · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsnot available
FundersNational Institute of Nursing ResearchNational Cancer InstituteNational Institutes of Health
KeywordsInterquartile rangeMedicinePsychosocialDistressQuality of life (healthcare)Confidence intervalHospital Anxiety and Depression ScaleAnxietyInternal medicinePsychiatryClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: There are limited data on the effects of financial distress (FD) on overall suffering and quality of life (QOL) of patients with advanced cancer (AdCa). In this cross-sectional study, we examined the frequency of FD and its correlates in AdCa. PATIENTS AND METHODS: We interviewed 149 patients, 77 at a comprehensive cancer center (CCC) and 72 at a general public hospital (GPH). AdCa completed a self-rated FD (subjective experience of distress attributed to financial problems) numeric rating scale (0 = best, 10 = worst) and validated questionnaires assessing symptoms (Edmonton Symptom Assessment System [ESAS]), psychosocial distress (Hospital Anxiety and Depression Scale [HADS]), and QOL (Functional Assessment of Cancer Therapy-General [FACT-G]). RESULTS: The patients' median age was 60 years (95% confidence interval [CI]: 58.6-61.5 years); 74 (50%) were female; 48 of 77 at CCC (62%) versus 13 of 72 at GPH (18%) were white; 21 of 77 (27%) versus 32 of 72 (38%) at CCC and GPH, respectively, were black; and 7 of 77 (9%) versus 27 of 72 (38%) at CCC and GPH, respectively, were Hispanic (p < .0001). FD was present in 65 of 75 at CCC (86%; 95% CI: 76%-93%) versus 65 of 72 at GPH (90%; 95% CI: 81%-96%; p = .45). The median intensity of FD at CCC and GPH was 4 (interquartile range [IQR]: 1-7) versus 8 (IQR: 3-10), respectively (p = .0003). FD was reported as more severe than physical distress, distress about physical functioning, social/family distress, and emotional distress by 45 (30%), 46 (31%), 64 (43%), and 55 (37%) AdCa, respectively (all significantly worse for patients at GPH) (p < .05). AdCa reported that FD was affecting their general well-being (0 = not at all, 10 = very much) with a median score of 5 (IQR: 1-8). FD correlated (Spearman correlation) with FACT-G (r = -0.23, p = .0057); HADS-anxiety (r = .27, p = .0014), ESAS-anxiety (r = .2, p = .0151), and ESAS-depression (r = .18, p = .0336). CONCLUSION: FD was very frequent in both groups, but median intensity was double among GPH patients. More than 30% of AdCa rated FD to be more severe than physical, family, and emotional distress. More research is needed to better characterize FD and its correlates in AdCa and possible interventions. IMPLICATIONS FOR PRACTICE: Financial distress is an important and common factor contributing to the suffering of advanced cancer patients and their caregivers. It should be suspected in patients with persistent, refractory symptom expression. Early identification, measurement, and documentation will allow clinical teams to develop interventions to improve financial distress and its impact on quality of life of advanced cancer 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 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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.052
GPT teacher head0.288
Teacher spread0.237 · 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 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".

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Citations237
Published2015
Admission routes1
Has abstractyes

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