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Record W4403914831 · doi:10.1002/pon.70015

The Supportive Care Needs of Individuals Living With Advanced or Metastatic Lung Cancer Receiving Targeted or Immunotherapies

2024· article· en· W4403914831 on OpenAlexafffundabout
Emma Kearns, Alanna Chu, Rinat Nissim, Paul Wheatley‐Price, Tim Aubry, Sophie Lebel

Bibliographic record

VenuePsycho-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsOttawa HospitalUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsThematic analysisMedicineLung cancerSupportive psychotherapyDistressNeeds assessmentPopulationQualitative researchSocial supportNursingFamily medicineOncologyInternal medicinePsychologyClinical psychologyPsychotherapist

Abstract

fetched live from OpenAlex

OBJECTIVE: Lung cancer is associated with the highest incidence and mortality of all cancers. New treatments, called targeted therapies (TT) and immunotherapies (IO), offer higher treatment efficacy and fewer side effects compared to traditional treatments but are accompanied by uncertainty and an unpredictable treatment course. There is a paucity of research on the experiences of individuals living with advanced or metastatic lung cancer receiving TT/IO, and even less is known about the supportive care needs of this population. METHODS: Twenty four participants from across Canada participated in semi-structured interviews regarding their supportive care needs. Thematic analysis was utilized to identify their supportive care needs. RESULTS: Qualitative coding identified unmet needs and challenges. All participants indicated difficulties with unmet supportive care needs, including psychological, informational, and practical needs. CONCLUSIONS: The exploration of supportive care experiences of patients receiving TT/IO exposes high distress and unmet needs. Results indicate the need for timely and accessible supportive cancer care. Results can inform patient advocacy efforts and the development of new services.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.365
Teacher spread0.345 · 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 designQualitative
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

Citations3
Published2024
Admission routes3
Has abstractyes

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