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Record W4306377174 · doi:10.3390/curroncol29100609

Clinical Management of Financial Toxicity–Identifying Opportunities through Experiential Insights of Cancer Survivors, Caregivers, and Social Workers

2022· article· en· W4306377174 on OpenAlexaffvenue
Christopher J. Longo, Louisa G. Gordon, Rebecca L. Nund, Nicolas H. Hart, Laisa Teleni, Carla Thamm, Olivia Hollingdrake, Fiona Crawford‐Williams, Bogda Koczwara, Tamara Ownsworth, Stephen M. Born, Sue Schoonbeek, Leanne Stone, Christie Barrett, Raymond J. Chan

Bibliographic record

VenueCurrent Oncology · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsMcMaster University
FundersNational Health and Medical Research CouncilQueensland University of Technology
KeywordsMedicineCancer survivorCLARITYCancerFocus groupSocial workNonprobability samplingConsistency (knowledge bases)NursingFamily medicineBusinessEnvironmental health

Abstract

fetched live from OpenAlex

Perspectives of cancer survivors, caregivers, and social workers as key stakeholders on the clinical management of financial toxicity (FT) are critical to identify opportunities for better FT management. Semi-structured interviews (cancer survivors, caregivers) and a focus group (social workers) were undertaken using purposive sampling at a quaternary public hospital in Australia. People with any cancer diagnosis attending the hospital were eligible. Data were analysed using inductive-deductive content analysis techniques. Twenty-two stakeholders (n = 10 cancer survivors of mixed-cancer types, n = 5 caregivers, and n = 7 social workers) participated. Key findings included: (i) genuine concern for FT of cancer survivors and caregivers shown through practical support by health care and social workers; (ii) need for clarity of role and services; (iii) importance of timely information flow; and (iv) proactive navigation as a priority. While cancer survivors and caregivers received financial assistance and support from the hospital, the lack of synchronised, shared understanding of roles and services in relation to finance between cancer survivors, caregivers, and health professionals undermined the effectiveness and consistency of these services. A proactive approach to anticipate cancer survivors’ and caregivers’ needs is recommended. Future research may develop and evaluate initiatives to manage cancer survivors and families FT experiences and outcomes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.788

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 studies0.0000.000
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 head0.259
GPT teacher head0.397
Teacher spread0.137 · 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 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

Citations9
Published2022
Admission routes2
Has abstractyes

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