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Record W2297895156 · doi:10.1177/2333393616630672

Purposeful Agency in Support Seeking During Cancer Treatment From a Person-Centered Perspective

2016· article· en· W2297895156 on OpenAlexaff
Filipa Ventura, Ingalill Koinberg, Per Karlsson, Richard Sawatzky, Joakim Öhlén

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsTrinity Western UniversityCentre for Advancing Health OutcomesWestern University
Fundersnot available
KeywordseHealthGeneral partnershipPerspective (graphical)Needs assessmentAgency (philosophy)Focus groupPsychologySocial supportNursingMedicineHealth careMedical educationPsychotherapistBusinessSociologyComputer scienceMarketing

Abstract

fetched live from OpenAlex

People diagnosed with early-stage breast cancer (ESBC) manifest high supportive needs. eHealth supportive programs successfully satisfy those needs, but the process of generating supportive outcomes is less understood. We conducted this study to explore patients' efforts to satisfy their supportive needs throughout the treatment course, not limited to but particularly considering their use of the Internet. Guided by interpretive description, 19 women undergoing treatment for ESBC participated in two phases of focus group meetings. Our results disclose women as self-driven resourceful agents, a perspective that underlay the process of reaching out as women appraised their need for support and intentionally engaged their supportive resources. Our findings convey a need to shift the paradigm of professionals' provision of support in scheduled appointments toward achieving a continuous reciprocal care partnership. This is especially significant for the development of eHealth supportive programs, which assist in the enhancement of the health care accessibility.

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 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 score0.236
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.215
GPT teacher head0.512
Teacher spread0.297 · 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
Published2016
Admission routes1
Has abstractyes

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