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Record W2015596210 · doi:10.1682/jrrd.2009.07.0097

Prevention of fall-related injuries: A clinical research agenda 2009-2014

2009· editorial· en· W2015596210 on OpenAlexaboutno aff
Pat Quigley

Bibliographic record

VenueThe Journal of Rehabilitation Research and Development · 2009
Typeeditorial
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical medicine and rehabilitationFall preventionPhysical therapyPoison controlInjury preventionMedical emergencyPsychology

Abstract

fetched live from OpenAlex

Decades of research have been conducted on the risk, prevention, and management of falls. Extensive research addresses the identified intrinsic and extrinsic fall risks and the importance of screening for these risks. The emphasis for patient safety interventions surrounding falls and injury prevention must be on patient-centered, multifactorial, individualized care plans that are population-based. Yet the link between risk assessment and the effectiveness of population-based interventions remains weak. Early efforts focused on risk factors for prevention of falls in the elderly, largely ignoring interventions and also considering all fallers as one single group. Research then moved into fall screening and risk assessment, but these two processes were often intermingled, leading to confusion about linking risk to specific interventions. Still the focus was on fall prevention and the elderly, lumping all fallers into one single group. Next, research focused on interventions, but the focus was on fall prevention and the elderly, again lumping all fallers together. A new agenda begins to question this focus on fall prevention and addresses fall protection and injury prevention, emphasizing therapeutic risk associated with activity and community participation. This new agenda also recognizes the need to segment high-risk patient populations to identify unique risks and tailor interventions (e.g., peripheral neuropathy, wheelchair fallers) using new three-dimensional techniques to assess gait and balance as well as other key risk factors. The new agenda also goes beyond fall screening and fall risk assessment, emphasizing the need to screen individuals, follow up with in-depth risk assessment protocols, and link interventions to specific modifiable risk factors. As more evidence is available to clinicians, for translational research efforts are needed to develop clinical tools to make it easier for clinicians to provide evidence-based practice and to explore more effective and efficient strategies for implementing evidence-based programs across clinical settings and facilities. To advocate for evidence-based practice in fall prevention and fall protection, the Veterans Integrated Service Network (VISN) 8 Patient Safety Center of Inquiry held its second international call across professions and experts to articulate the state of the science, elucidate research priorities, and facilitate the translation of research into practice. In April 2007, fall experts from the United States and Canada participated in a three-day national conference, Transforming Fall Prevention Practices. After presenting state-of-the-art knowledge and practices in fall prevention, risk assessment, and interventions, they joined with invited research methodologists and expert clinicians over another half day for the research agenda-setting session. Participants reached consensus on the research needed to advance both science and clinical practice. Priorities were grouped into three research domains: * Clinical interventions. * Biomechanics. * Implementation/translation. The criteria used for selecting research priorities were the-- * Need for consensus among all members. * Feasibility of the research being conducted within 5 years. * Presence of an existing program of research on which to build. * Fit with the mission and vision of the Veterans Health Administration (VHA) in primary health promotion, patient safety, function, and independence. This editorial focuses solely on clinical intervention. We examined the current state of the science relevant to clinical intervention research and developed a research agenda for studies that can be conducted as 5-year research programs likely to result in new discoveries, improved clinical practice, reduced variations in practice, and improved patient outcomes. Clinical intervention research is needed to test the effects of specific interventions related to special populations, medication prescribing, clinical units and staffing, and interdisciplinary approaches to fall prevention [1]. …

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)0.100
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.444
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1000.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.007
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 head0.114
GPT teacher head0.535
Teacher spread0.421 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

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
Published2009
Admission routes1
Has abstractyes

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