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Evaluation of DermSat-7 for Assessing Treatment Satisfaction in Patients with Acne

2023· article· en· W4388895980 on OpenAlexafffund
Ali Shields, April W. Armstrong, Manraj Kaur, Alison Layton, Diane Thiboutot, Jerry Tan, John S. Barbieri

Bibliographic record

VenueJAMA Dermatology · 2023
Typearticle
Languageen
FieldMedicine
TopicAcne and Rosacea Treatments and Effects
Canadian institutionsWindsor Clinical ResearchWestern University
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesCanadian Institutes of Health Research
KeywordsMedicineAcneCronbach's alphaConstruct validityExploratory factor analysisConfirmatory factor analysisPatient satisfactionPatient-reported outcomePhysical therapyOutpatient clinicClinical psychologyQuality of life (healthcare)PsychometricsDermatologyInternal medicineSurgeryStructural equation modelingNursing

Abstract

fetched live from OpenAlex

Importance: Treatment satisfaction is important to achieving therapeutic success in patients with inflammatory dermatological diseases, such as acne. Objective: To evaluate the structural validity, internal consistency, and construct validity of the DermSat-7, a questionnaire-based measure of treatment satisfaction, in patients with acne seen in routine clinical practice. Design, Setting, and Participants: This cross-sectional study included adults with acne who were fluent in English and treated at an outpatient clinic at Brigham and Women's Hospital between July 2022 and May 2023. At each visit, patients completed a self-administered, patient-reported outcome questionnaire, including a patient global assessment (PGA) of their acne severity and the DermSat-7. The DermSat-7 consists of 7 items assessing 3 domains of treatment: effectiveness (3 items), convenience (3 items), and overall satisfaction (1 item). At subsequent visits, patients were asked an anchor item related to change in disease severity ("How has your acne changed compared to your last visit?") that was scored on a 7-point scale (-3 = much worse to 3 = much better). Also at each visit, a dermatologist completed the Comprehensive Acne Severity Scale (CASS). Main Outcomes and Measures: The main outcomes were structural validity (assessed by factor analysis), internal consistency (assessed by Cronbach α), and construct validity (assessed using linear regression models and Pearson correlation coefficients). Results: The analysis included 142 patients with acne (mean [SD] age, 25.1 [5.1] years; 96 females [67.6%]) taking acne medication who completed the DermSat-7. Exploratory factor and confirmatory factor analysis supported the unidimensionality of the 3 DermSat-7 domains. Cronbach α values of 0.89 and 0.80 supported good internal consistency in the effectiveness and convenience domains, respectively. Known-groups validity was supported by increasing DermSat-7 effectiveness and overall satisfaction scores with increasing levels of positive change in disease severity (linear regression coefficient, 7.51; 95% CI, 4.94-10.08; P < .001). Construct validity was further supported by moderate correlations with the anchor, PGA, and CASS scores (effectiveness domain: anchor r = 0.567, PGA r = -0.538, and CASS r = -0.485; overall satisfaction domain: anchor r = 0.467, PGA r = -0.486, and CASS r = -0.489). Conclusion and Relevance: This cross-sectional study found that the DermSat-7 may be an effective tool for measuring treatment satisfaction, particularly effectiveness and overall satisfaction domains, among patients with acne. Further research is needed to examine additional measurement properties of the DermSat-7, such as content validity and interpretability, as well as to validate the DermSat-7 in other populations of patients with acne.

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)0.000
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 score0.133
Threshold uncertainty score0.222

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.035
GPT teacher head0.342
Teacher spread0.307 · 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".

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Citations4
Published2023
Admission routes2
Has abstractyes

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