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Record W2315498121 · doi:10.1097/npt.0000000000000121

Development of a Theory-Based Intervention to Increase Clinical Measurement of Reactive Balance in Adults at Risk of Falls

2016· article· en· W2315498121 on OpenAlexafffund
Kathryn M. Sibley, Dina Brooks, Paula Gardner, Tania Janaudis‐Ferreira, Mandy McGlynn, Sachi O’Hoski, Sara McEwen, Nancy M. Salbach, Jennifer Shaffer, Paula Shing, Sharon E. Straus, Susan Jaglal

Bibliographic record

VenueJournal of Neurologic Physical Therapy · 2016
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsBridgepoint Active HealthcareToronto Rehabilitation Institute
FundersCanadian Institutes of Health Research
KeywordsBalance (ability)Intervention (counseling)MedicinePhysical medicine and rehabilitationPsychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Effective balance reactions are essential for avoiding falls, but are not regularly measured by physical therapists. Physical therapists report wanting to improve reactive balance assessment, and theory-based approaches are recommended as the foundation for the development of interventions. This article describes how a behavior change theory for health care providers, the theoretical domains framework (TDF), was used to develop an intervention to increase reactive balance measurement among physical therapists who work in rehabilitation settings and treat adults who are at risk of falls. CASE DESCRIPTION: We employed published recommendations for using the TDF-guided intervention development. We identified what health care provider behavior is in need of change, relevant barriers and facilitators, strategies to address them, and how we would measure behavior change. In this case, identifying strategies required selecting both a reactive balance measure and behavior change techniques. Previous research had determined that physical therapists need to increase reactive balance measurement, and identified barriers and facilitators that corresponded to 8 TDF domains. A published review informed the selection of the Balance Evaluation Systems Test (Reactive Postural Responses Section) as addressing the barriers and facilitators, and existing research informed the selection of 9 established behavior change techniques corresponding to each identified TDF domain. OUTCOMES: The TDF framework were incorporated into a 12-month intervention with interactive group sessions, local champions, and health record modifications. Intervention effect can be evaluated using health record abstraction, questionnaires, and qualitative semistructured interviews. SUMMARY: Although future research will evaluate the intervention in a controlled study, the process of theory-based intervention development can be applied to other rehabilitation research contexts, maximizing the impact of this work.Video Abstract is available for more insights from the authors (see Supplemental Digital Content 1, http://links.lww.com/JNPT/A123).

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)0.008
metaresearch head score (Gemma)0.020
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 score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0010.002
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 head0.065
GPT teacher head0.397
Teacher spread0.331 · 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

Citations17
Published2016
Admission routes2
Has abstractyes

Explore more

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