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Record W2397264791 · doi:10.3928/19404921-20151019-04

Pilot Enhancement of the Arthritis Foundation Exercise Program with a Healthy Aging Program

2015· article· en· W2397264791 on OpenAlexaboutno aff
Elizabeth A. Schlenk, Joni Vander Bilt, Wei-Hsuan Lo-Ciganic, Mini E. Jacob, Sarah E. Woody, Molly B. Conroy, C. Kent Kwoh, Steven M. Albert, Robert M. Boudreau, Anne B. Newman, Janice C. Zgibor

Bibliographic record

VenueResearch in Gerontological Nursing · 2015
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersNational Center for Chronic Disease Prevention and Health PromotionNational Institute on AgingCenters for Disease Control and PreventionUniversity of Pittsburgh
KeywordsMedicinePhysical therapyAttendanceOsteoarthritisArthritisGerontologyAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

Older adults with arthritis or joint pain were targeted for a pilot program enhancing the Arthritis Foundation Exercise Program with the 10 Keys™ to Healthy Aging Program. Using a one-group, pre-post design, feasibility was examined and improvements in preventive behaviors, arthritis outcomes, and cardiometabolic outcomes were explored. A 10-week program was developed, instructors were recruited and trained, and four sites and 51 participants were recruited. Measures included attendance, adherence, satisfaction, preventive behaviors, Western Ontario and McMaster Universities Osteoarthritis Index (pain and stiffness), glucose, and cholesterol. Three fourths of participants attended >50% of the sessions. At 6 and 12 months, more than one half performed the exercises 1 to 2 days per week, whereas 28% and 14% exercised 3 to 7 days per week, respectively. Participants (92%) rated the program as excellent/very good. Nonsignificant changes were observed in expected directions. Effect sizes were small for arthritis and cardiometabolic outcomes. This program engaged community partners, demonstrated feasibility, and showed improvements in some preventive behaviors and health risk profiles. [Res Gerontol Nurs. 2016; 9(3):123-132.].

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.987
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.197
GPT teacher head0.453
Teacher spread0.256 · 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 designOther design
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

Citations3
Published2015
Admission routes1
Has abstractyes

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