← Back to cohort
Changes in mental health symptoms from pre-COVID-19 to COVID-19 among participants with systemic sclerosis from four countries: A Scleroderma Patient-centered Intervention Network (SPIN) Cohort study
Brett D. Thombs, Linda Kwakkenbos, Richard S. Henry, Marie‐Eve Carrier, Scott B. Patten, Sami Harb, Angelica Bourgeault, Lydia Tao, Susan J. Bartlett, Luc Mouthon, John Varga, Andrea Benedetti, Catherine Fortuné, Amy Gietzen, Geneviève Guillot, Nancy Lewis, Michelle Richard, Maureen Sauvé, Joep Welling, Kim Fligelstone, Karen Gottesman, Catarina Leite, Murray Baron, Vanessa L. Malcarne, Maureen D. Mayes, Warren R. Nielson, Robert J. Riggs, Shervin Assassi, Carolyn Ells, C.H.M. van den Ende, Tracy Frech, Daphna Harel, Monique Hinchcliff, Marie Hudson, Sindhu R. Johnson, Maggie Larché, Christelle Nguyen, Janet Pope, François Rannou, Tatiana Sofía Rodríguez Reyna, Anne A. Schouffoer, María E. Suarez‐Almazor, C. Agard, Alexandra Albert, Elana J. Bernstein, S. Berthier, Lyne Bissonnette, Alessandra Bruns, Patrícia Carreira, Benjamin Chaigne, Chase Correia, Christopher P. Denton, Robyn T. Domsic, James V. Dunne, Bertrand Dunogué, Dominique Farge, Paul R. Fortin, Jessica Gordon, Brigitte Granel-Rey, Pierre‐Yves Hatron, Ariane L. Herrick, Sabrina Hoa, Niall Jones, Artur José de Brum Fernandes, Suzanne Kafaja, Nader Khalidi, David Launay, Joanne Manning, Isabelle Marié, Maria Martin, A. Mékinian, Sheila Melchor, Mandana Nikpour, Louis Olagne, Susanna Proudman, Alexis Régent, Sébastien Rivière, David Robinson, Esther Rodríguez, Sophie Roux, Vincent Sobanski, Virginia Steen, Evelyn Sutton, Carter Thorne, Pearce Wilcox, Mara Cañedo Ayala, Andrea Carboni-Jiménez, Maria Gagarine, Julia Nordlund, Nora Østbø, Danielle B. Rice, Kimberly A. Turner, Nicole Culos-Reed, Laura Dyas, Ghassan El‐Baalbaki, Shannon Hebblethwaite, Laura Bustamante, Delaney Duchek, Kelsey Ellis
Bibliographic record
VenueJournal of Psychosomatic Research · 2020
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsUniversity of AlbertaMcMaster UniversityUniversity of British ColumbiaToronto Western HospitalCentre Hospitalier de l’Université de MontréalUniversité LavalMount Sinai HospitalUniversity of CalgarySt Joseph's Health CareWestern UniversityUniversity of TorontoUniversité de SherbrookeMcGill UniversityMcGill University Health CentreSt. Paul's HospitalAlberta Children's HospitalMultiple Sclerosis Society of CanadaHotchkiss Brain InstituteJewish General Hospital
FundersNational Center for Advancing Translational SciencesCanadian Institutes of Health ResearchMitacsMcGill University
KeywordsAnxietyMedicineMinimal clinically important differenceDepression (economics)Odds ratioCohortConfidence intervalMental healthCohort studyLogistic regressionPatient Health QuestionnaireOddsPhysical therapyPsychiatryDemographyInternal medicineRandomized controlled trialDepressive symptoms
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 head0.154
GPT teacher head0.413
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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
Citations44
Published2020
Admission routes2
Has abstractno