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Record W3174134409 · doi:10.1080/09638288.2021.1916840

Exploring factors influencing physiotherapists’ perceptions of measuring reactive balance following a theory-based multi-component intervention: a qualitative descriptive study

2021· article· en· W3174134409 on OpenAlexafffundabout
Kathryn M. Sibley, Paula Gardner, Danielle C. Bentley, Masood Khan, Mandy McGlynn, Paula Shing, Jennifer Shaffer, Sachi O’Hoski, Nancy M. Salbach

Bibliographic record

VenueDisability and Rehabilitation · 2021
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity Health NetworkHealth Sciences CentreGeorge & Fay Yee Centre for Healthcare InnovationWest Park Healthcare CentreBridgepoint Active HealthcareMcMaster UniversityBrock UniversityUniversity of ManitobaSunnybrook Health Science CentreSinai Health SystemToronto Rehabilitation InstituteUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsThematic analysisAcknowledgementRehabilitationBalance (ability)Theory of planned behaviorIntervention (counseling)PerceptionMedicineQualitative researchPsychologyPsychological interventionPhysical therapyNursingControl (management)

Abstract

fetched live from OpenAlex

Purpose: Reactive balance is a critical consideration for mobility and fall avoidance, but is under-assessed among physiotherapists. The objective of this study was to explore factors influencing physiotherapist perceptions about measuring reactive balance upon completion of a 12-month theory-based, multi-component intervention to increase use of a measure of reactive balance.Methods: A qualitative descriptive approach was used. Semi-structured interviews were conducted with 28 physiotherapists treating adults with balance impairment in three urban Canadian rehabilitation hospitals that participated in the intervention. Interviews explored perceptions of reactive balance measurement and perceived changes in clinical behavior. Thematic analysis involved multiple rounds of coding, review and discussion, theme generation, and interpretation of findings through individual analysis and team meetings.Findings: Participants expressed contrasting views about integrating reactive balance measurement in their practice, despite consistent acknowledgement of the importance of reactive balance for function. Three themes were identified highlighting factors that mediated perceptions about measuring reactive balance: patient characteristics; trust between physiotherapist and patient; and the role of physiotherapist fear.Conclusions: The findings highlight that decision making for measuring reactive balance in rehabilitation settings is complex. There is a need for additional work to facilitate long-term implementation of clinical reactive balance measurement, such as refining patient criteria for administration, ensuring sufficient time to establish a trusting relationship, and developing and testing strategies to address physiotherapist fear.IMPLICATIONS FOR REHABILITATIONReactive balance is important for falls prevention and mobility, but is under-assessed among physiotherapists.This study identified three factors that influenced uptake of reactive balance measurement among physiotherapists in rehabilitation settings: patient characteristics; trust between physiotherapist and patient; and the role of physiotherapist fear.Knowledge of the identified factors may assist with design and use of reactive and other balance measurements.Strategies aimed at developing trusting relationships between physiotherapist and patient along with addressing physiotherapist fear could facilitate the uptake of clinical reactive balance measurement.

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)0.020
metaresearch head score (Gemma)0.043
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.043
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0060.005
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.097
GPT teacher head0.352
Teacher spread0.255 · 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".

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Citations4
Published2021
Admission routes3
Has abstractyes

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