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Record W2901472266 · doi:10.2196/12319

eHealth-Based Behavioral Intervention for Increasing Physical Activity in Persons With Multiple Sclerosis: Fidelity Protocol for a Randomized Controlled Trial

2018· article· en· W2901472266 on OpenAlexvenueno aff
Stephanie L. Silveira, Justin McCroskey, Brooks C. Wingo, Robert W. Motl

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
FundersMultiple Sclerosis SocietyNational Multiple Sclerosis Society
KeywordseHealthRandomized controlled trialFidelityPsychological interventionBehavior changePopulationIntervention (counseling)Protocol (science)MedicineCognitive behavioral therapyWorkgroupSocial cognitive theoryBehavioural sciencesPhysical therapyPsychologyNursingAlternative medicineComputer scienceDevelopmental psychologyEnvironmental healthSocial psychologyHealth carePsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: The rate of physical activity is substantially lower in persons with multiple sclerosis (MS) than in the general population. This problem can be reversed through rigorous and reproducible delivery of behavioral interventions that target lifestyle physical activity in MS. These interventions are, in part, based on a series of phase II randomized controlled trials (RCTs) supporting the efficacy of an internet-delivered behavioral intervention, which is based on social cognitive theory (SCT) for increasing physical activity in MS. OBJECTIVE: This paper outlines the strategies and monitoring plan developed based on the National Institutes of Health Behavior Change Consortium (NIH BCC) treatment fidelity workgroup that will be implemented in a phase III RCT. METHODS: The Behavioral Intervention for Physical Activity in Multiple Sclerosis (BIPAMS) study is a phase III RCT that examines the effectiveness of an internet-delivered behavioral intervention based on SCT and is supported by video calls with a behavioral coach for increasing physical activity in MS. BIPAMS includes a 6-month treatment condition and 6-month follow-up. The BIPAMS fidelity protocol includes the five areas outlined by the NIH BCC. The study design draws on the SCT behavior-change strategy, ensures a consistent dose within groups, and plans for implementation setbacks. Provider training in theory and content will be consistent between groups with monitoring plans in place such as expert auditing of calls to ensure potential drift is addressed. Delivery of treatment will be monitored through the study website and training will focus on avoiding cross-contamination between conditions. Receipt of treatment will be monitored via coaching call notes and website monitoring. Lastly, enactment of treatment for behavioral and cognitive skills will be monitored through coaching call notes among other strategies. The specific strategies and monitoring plans will be consistent between conditions within the constraints of utilizing existing evidence-based interventions. RESULTS: Enrollment began in February 2018 and will end in September 2019. The study results will be reported in late 2020. CONCLUSIONS: Fidelity-reporting guidelines provided by the NIH BCC were published in 2004, but protocols are scarce. This is the first fidelity-monitoring plan involving an electronic health behavioral intervention for increasing physical activity in MS. This paper provides a model for other researchers utilizing the NIH BCC recommendations to optimize the rigor and reproducibility of behavioral interventions in MS. TRIAL REGISTRATION: ClinicalTrials.gov NCT03490240; https://www.clinicaltrials.gov/ct2/show/NCT03490240. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12319.

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)0.058
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.058
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.054
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0110.005
Bibliometrics0.0040.004
Science and technology studies0.0040.004
Scholarly communication0.0050.004
Open science0.0030.003
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0560.009

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 head0.378
GPT teacher head0.584
Teacher spread0.205 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations14
Published2018
Admission routes1
Has abstractyes

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