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Record W2931478639 · doi:10.1016/j.arrct.2019.100004

Employment Concerns and Associated Impairments of Women Living With Advanced Breast Cancer

2019· article· en· W2931478639 on OpenAlexaff
Kathleen Doyle Lyons, Robin Newman, Michael Sullivan, Mackenzi Pergolotti, Brent Braveman, Andrea Cheville

Bibliographic record

VenueArchives of Rehabilitation Research and Clinical Translation · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsMcGill University
Fundersnot available
KeywordsBreast cancerMedicineMetastatic breast cancerDistressActivities of daily livingLogistic regressionMultivariate analysisCancerGerontologyVocational educationPsycho-oncologyDescriptive statisticsFamily medicinePsychologyClinical psychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the clinical and personal factors associated with work status, distress regarding work status, and the desire to resume employment and receive help to address work challenges reported by women living with advanced breast cancer. DESIGN: Descriptive statistics and univariate and multivariate logistic regression were used to explore factors related to employment challenges in this secondary analysis of an existing dataset. SETTING: Participants were recruited from an outpatient oncology clinic specializing in breast cancer at a free-standing comprehensive cancer center. PARTICIPANTS: English-speaking women older than 18 years living with metastatic breast cancer with intact mental status and Karnofsky Performance Scale scores between 40 and 90 (N=163). INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: Dependent variables included (1) continued employment if working at the time of cancer diagnosis; (2) interest in resuming employment if working at the time of cancer diagnosis and now no longer working; (3) distress regarding vocational limitations; and (4) interest in receiving help to resume work. RESULTS: values<.01). CONCLUSIONS: With more people living longer with metastatic cancer, there is a need to assess and support survivors' desire and capacity to maintain employment. Participants' reduced employment was strongly associated with potentially actionable clinical targets (ie, higher symptom burden and lower functional status) that fall within cancer rehabilitation's mission.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.040
GPT teacher head0.411
Teacher spread0.370 · 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 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

Citations24
Published2019
Admission routes1
Has abstractyes

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