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Record W2981855914 · doi:10.2196/13441

Website Redesign of a 16-Week Exercise Intervention for People With Spinal Cord Injury by Using Participatory Action Research

2019· article· en· W2981855914 on OpenAlexvenueno aff
Maria Cole, Katherine Froehlich-Grobe, Simon Driver, Ross Shegog, Jeffery McLaughlin

Bibliographic record

VenueJMIR Rehabilitation and Assistive Technologies · 2019
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsnot available
FundersAdministration for Community LivingAustralian GovernmentNational Institute on Disability, Independent Living, and Rehabilitation ResearchU.S. Department of Health and Human Services
KeywordsIntervention (counseling)Physical activitySpinal cord injuryPhysical therapyParticipatory action researchCitizen journalismPsychologyPhysical medicine and rehabilitationApplied psychologyMedicineComputer scienceWorld Wide WebSpinal cordNursing

Abstract

fetched live from OpenAlex

BACKGROUND: People with spinal cord injury (SCI) are at higher risk for numerous preventable chronic conditions. Physical activity is a protective factor that can reduce this risk, yet those with SCI encounter barriers to activity and are significantly less likely to be active. Limited evidence supports approaches to promote increased physical activity for those with SCI. OBJECTIVE: Building upon our previous theory- and evidence-based approach to increase participation in regular physical activity for those with SCI, this study aimed to use a participatory action research approach to translate a theory-based intervention to be delivered via the Web to individuals with SCI. METHODS: A total of 10 individuals with SCI were invited to participate in consumer input meetings to provide the research team with iterative feedback on an initial website designed as a platform for delivering a theory-based exercise intervention. RESULTS: A total of 7 individuals with SCI whose average age was 43.6 years (SD 13.4) and lived an average age of 12.5 years (SD 14.9) with SCI met on 2 occasions to provide their feedback of the website platform, both on the initial design and subsequently on the revamped site. Their iterative feedback resulted in redesigning the website content, format, and functionality as well as delivery of the intervention program. CONCLUSIONS: The substantially redesigned website offers an easier-to-navigate platform for people with SCI with greater functionality that delivers information using a module format with less text, short video segments, and presents more resources. Preliminary testing of the site is the next step.

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)0.019
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.140
GPT teacher head0.474
Teacher spread0.335 · 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 designQualitative
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

Citations10
Published2019
Admission routes1
Has abstractyes

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