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Record W4366982196 · doi:10.1186/s12969-023-00819-6

Barriers to care in juvenile localized and systemic scleroderma: an exploratory survey study of caregivers’ perspectives

2023· article· en· W4366982196 on OpenAlexaff
Leigh A. Stubbs, Andrew M. Ferry, Danielle Guffey, Christina Loccke, Erin Moriarty Wade, Pamela Pour, Kaveh Ardalan, Peter Chira, Ingrid M. Ganske, Daniel Glaser, Gloria C. Higgins, Nadia Luca, Katharine Moore, Vidya Sivaraman, Katie Stewart, Natalia Vasquez‐Canizares, Raegan Hunt, Renata S. Maricevich, Kathryn S. Torok, Suzanne C. Li

Bibliographic record

VenuePediatric Rheumatology · 2023
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersScleroderma Foundation
KeywordsMedicineScleroderma (fungus)RheumatologySocioeconomic statusFamily medicineEthnic groupHousehold incomeHealth carePediatricsInternal medicineEnvironmental healthPopulationPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Juvenile localized scleroderma (LS) and systemic sclerosis (SSc) are rare pediatric conditions often associated with severe morbidities. Delays in diagnosis are common, increasing the risk for permanent damage and worse outcomes. This study explored caregiver perspectives on barriers they encountered while navigating diagnosis and care for their child's scleroderma. METHODS: In this cross-sectional study, caregivers of juvenile LS or SSc patients were recruited from a virtual family scleroderma educational conference and a juvenile scleroderma online interest group. The survey queried respondents about their child's condition and factors affecting diagnosis and treatment. RESULTS: The response rate was 61% (73/120), with 38 parents of LS patients and 31 parents of SSc patients. Most patients were female (80%) and over half were non-Hispanic white (55%). Most families had at least one person with a college education or higher (87%), traveled ≤ 2 h to see their rheumatologist (83%), and had private insurance (75%). Almost half had an annual household income ≥ $100,000 (46%). Families identified the following factors as barriers to care: lack of knowledge about scleroderma in the medical community, finding reliable information about pediatric scleroderma, long wait times/distances for a rheumatology/specialist appointment, balance of school/work and child's healthcare needs, medication side effects, and identifying effective medications. The barrier most identified as a major problem was the lack of knowledge about juvenile scleroderma in the medical community. Public insurance, household income less than $100,000, and Hispanic ethnicity were associated with specific barriers to care. Lower socioeconomic status was associated with longer travel times to see the rheumatologist/specialist. Diagnosis and systemic treatment initiation occurred at greater than one year from initial presentation for approximately 28% and 36% of patients, respectively. Families of LS patients were commonly given erroneous information about the disease, including on the need and importance of treating active disease with systemic immunosuppressants in patients with deep tissue or rapidly progressive disease. CONCLUSION: Caregivers of children with LS or SSc reported numerous common barriers to the diagnosis, treatment, and ongoing care of juvenile scleroderma. The major problem highlighted was the lack of knowledge of scleroderma within the general medical community. Given that most of the caregiver respondents to the survey had relatively high socioeconomic status, additional studies are needed to reach a broader audience, including caregivers with limited English proficiency, geographical limitations, and financial constraints, to determine if the identified problems are generalizable. Identifying key care barriers will help direct efforts to address needs, reduce disparities in care, and improve patient 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.023
GPT teacher head0.277
Teacher spread0.255 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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