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Stigmatization and Mental Health Impact of Chronic Pediatric Skin Disorders

2024· article· en· W4395071654 on OpenAlexaffabout
Amy S. Paller, Stephanie M. Rangel, Sarah L. Chamlin, Aleena Hajek, Sheshanna Phan, Marcia Hogeling, Leslie Castelo‐Soccio, Irene Lara‐Corrales, Lisa M. Arkin, Leslie P. Lawley, Tracy Funk, Fabiana Castro Porto Silva Lopes, Richard J. Antaya, Michele Ramien, Karina L. Vivar, Joyce Teng, Carrie C. Coughlin, Wingfield Rehmus, Deepti Gupta, Lionel Bercovitch, Sarah L. Stein, Christina Boull, Wynnis L. Tom, Marilyn G. Liang, Raegan Hunt, Minnelly Luu, Kristen E. Holland, Jennifer J. Schoch, David Cella, Jin‐Shei Lai, James W. Griffith

Bibliographic record

VenueJAMA Dermatology · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsUniversity of British ColumbiaAlberta Children's HospitalHospital for Sick Children
FundersNational Center for Advancing Translational Sciences
KeywordsMedicineMental healthPsychiatryMEDLINE

Abstract

fetched live from OpenAlex

Importance: Chronic skin disorders in children frequently are visible and can cause stigmatization. However, the extent of stigmatization from chronic skin disease and association with mental health needs further study. Objective: To examine the extent of stigma, dependence on disease visibility and severity, and association with mental health and quality of life (QOL) in chronic pediatric skin disease. Design, Setting, and Participants: A cross-sectional, single-visit study was conducted at 32 pediatric dermatology centers in the US and Canada from November 14, 2018, to November 17, 2021. Participants included patients aged 8 to 17 years with chronic skin disease and 1 parent. Main Outcomes and Measures: Using the Patient-Reported Outcomes Measurement Instrumentation System (PROMIS) Stigma-Skin, the extent of stigma with child-, caregiver-, and physician-assessed disease visibility (primary outcome) and severity was compared, as well as reduced QOL (assessed by Skindex-Teen), depression, anxiety, and poor peer relationships (PROMIS child and proxy tools) (secondary outcomes). Results: The study included 1671 children (57.9% female; mean [SD] age, 13.7 [2.7] years). A total of 56.4% participants had self-reported high disease visibility and 50.5% had moderate disease severity. Stigma scores significantly differed by level of physician-assessed and child/proxy-assessed disease visibility and severity. Among children with chronic skin disorders, predominantly acne, atopic dermatitis, alopecia areata, and vitiligo, only 27.0% had T scores less than 40 (minimal or no stigma) and 43.8% had at least moderate stigma (T score ≥45) compared with children with a range of chronic diseases. Stigma scores correlated strongly with reduced QOL (Spearman ρ = 0.73), depression (ρ = 0.61), anxiety (ρ = 0.54), and poor peer relationships (ρ = -0.49). Overall, 29.4% of parents were aware of bullying of their child, which was strongly associated with stigma (Cohen d = -0.79, with children who were not bullied experiencing lower levels of stigma). Girls reported more stigma than boys (Cohen d = 0.26). Children with hyperhidrosis and hidradenitis suppurativa were most likely to have increased depression and anxiety. Conclusions and Relevance: The findings of this study suggest that physician assessment of disease severity and visibility is insufficient to evaluate the disease impact in the patient/caregiver. Identifying stigmatization, including bullying, and tracking improvement through medical and psychosocial interventions may be a key role for practitioners.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.006
GPT teacher head0.256
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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

Citations62
Published2024
Admission routes2
Has abstractyes

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