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RESULTS OF THE MOVES STUDY: A FEASIBILITY STUDY OF THE MOTIVATING INDIVIDUALS WITH LUPUS TO EXERCISE PROGRAM

2025· article· en· W4410513062 on OpenAlexvenueno aff
Dominique Kinnett-Hopkins, Linda Ehrlich‐Jones, Rosalind Ramsey‐Goldman

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSystemic lupus erythematosusPhysical therapyPhysical medicine and rehabilitationFamily medicineInternal medicineDisease

Abstract

fetched live from OpenAlex

PV070 / #88 Poster Topic: AS09 - Emerging Approaches in SLE Management Background/Purpose Physical activity is an evidence-based modifiable lifestyle behavior that can manage symptoms of systemic lupus erythematosus (SLE). However, rates of physical activity are low among persons with SLE. This study investigated the feasibility of an exercise intervention grounded in social cognitive theory and motivational interviewing for improving patient-reported outcomes and physical function in SLE. Methods Participants were randomized into the MOVES program or a waitlist control. All participants met criteria:≥ 18 years, self-reported diagnosis of SLE and <150 minutes of moderate-to-vigorous physical activity (MVPA) per week, severe fatigue via fatigue severity scale. The MOVES intervention was a 4-month home-based exercise program that included a manual, Fitbit Inspire 2, and resistance bands. Participants completed an orientation session via Zoom and received support from a motivational interviewing coach via 6 coaching calls (weeks 3, 5, 7, 10, 13, 16). PROMIS ® measures of fatigue, physical function, sleep disturbance, pain interference, anxiety, and depression were measured at baseline, post-intervention, and follow-up (2 months post-intervention). Accelerometers were worn for 7 days during waking hours to measure daily MVPA minutes (2020+counts) at baseline and post-intervention, with valid monitoring defined as a minimum of 3 days of 10+ hours of wear time. Weekly MVPA minutes were calculated as mean daily MVPA minutes times 7. Descriptive statistics were calculated, and data were analyzed using linear mixed models. Results Twenty-eight participants, mean(SD) age was 46(9.5); 100% identified as female, 50% self-identifying as Black/African American, 46.4% White, 3.6% Asian; 85.7% having some college education, completed baseline, post, and follow-up testing (16 intervention, 12 control; no significant differences at baseline). Linear mixed model analyses showed that the intervention group had significantly larger improvements in fatigue and physical function than the control group, both clinically and statistically, at both the post-intervention (p=0.01 for both) and follow-up (fatigue p=0.01, physical function p=0.02) While no statistically significant differences were observed for pain interference, anxiety, depression, sleep disturbance, or MVPA at post-intervention or follow-up, clinically meaningful changes were evident in the intervention group at post-intervention. Clinically meaningful changes, as indicated by Cohen’s d, were observed for fatigue (d=-1.7), physical function (d=0.56), pain interference (d=-0.99), anxiety (d=-0.98), and depression (d=-1.16) between baseline and post-intervention. These clinically meaningful changes were observed for fatigue (d=-1.7), physical function (d=0.52), anxiety (d=-0.62), and depression (d=-1.09) between baseline and follow-up (Table 1). Table 1. Outcomes by Timepoint and Group Conclusions The MOVES intervention led to significant and maintained improvements in fatigue and physical function, with clinically meaningful reductions observed in fatigue, pain interference, anxiety, and depression and improvements in physical function. Findings highlight the potential of the MOVES program to address key patient-reported outcomes among persons with SLE.

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)0.012
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.029
GPT teacher head0.345
Teacher spread0.315 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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