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Record W3012214361 · doi:10.1177/1742395320910490

Choices are inevitable: A qualitative exploration of the lifecosts of systemic lupus erythematosus

2020· article· en· W3012214361 on OpenAlexaffabout
Jenna Dixon, FS Cardwell, Ann E. Clarke, SJ Elliott

Bibliographic record

VenueChronic Illness · 2020
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of CalgaryUniversity of Waterloo
Fundersnot available
KeywordsBiopsychosocial modelLupus erythematosusContext (archaeology)MedicineSystemic therapyQuality of life (healthcare)Systemic lupus erythematosusQualitative researchHealth careImmunologyDiseaseNursingPsychiatrySociologyInternal medicineEconomic growthEconomics

Abstract

fetched live from OpenAlex

OBJECTIVES: (direct and indirect economic costs and beyond) to those with systemic lupus erythematosus in Canada. METHODS: Using a biopsychosocial conceptual framework and integrated knowledge translation approach, qualitative semi-structured interviews were conducted with 3 physicians, 5 representatives from systemic lupus erythematosus advocacy groups, and 29 adult systemic lupus erythematosus patients. Themes emerged deductively and inductively, and the theme code set was used to code all transcripts. RESULTS: Three dominant themes emerged: (1) impacts of systemic lupus erythematosus on quality of life, relationships, and health; (2) costs linked to healthcare; and (3) impacts of living with systemic lupus erythematosus on employment/economic standing. DISCUSSION: Whereas previous work has focused almost exclusively on the direct, individual costs of systemic lupus erythematosus, the biopsychosocial approach taken here emphasizes not only the individual and intermediate factors (such as the workplace and family), but also the system-level factors (i.e. system-level policies) that influence quality of life, healthcare, and employment/economic experiences of those with systemic lupus erythematosus. Results indicate a need to target interventions beyond the individual and their immediate context, and recognize that lifecosts are shaped significantly by systems-level action.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.061
GPT teacher head0.341
Teacher spread0.279 · 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 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

Citations19
Published2020
Admission routes2
Has abstractyes

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