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Delbaere Delbaere, Hauer Hauer, Lord Lord
Evaluation of the Incidental and Planned Exercise Questionnaire (IPEQ) for older peopleBrit J Sport Med
G. Hawthorne, J. Richardson, R. Osborne (1999)
The Assessment of Quality of Life (AQoL) instrument: a psychometric measure of Health-Related Quality of LifeQuality of Life Research, 8
S. Willis, S. Tennstedt, M. Marsiske, K. Ball, Jeffrey Elias, K. Koepke, John Morris, G. Rebok, F. Unverzagt, A. Stoddard, E. Wright (2006)
Long-term effects of cognitive training on everyday functional outcomes in older adults.JAMA, 296 23
V. Stel, S. Pluijm, Dorly Deeg, J. Smit, L. Bouter, P. Lips (2003)
A Classification Tree for Predicting Recurrent Falling in Community‐Dwelling Older PersonsJournal of the American Geriatrics Society, 51
T. Bond (2001)
Applying the Rasch Model: Fundamental Measurement in the Human Sciences, Second Edition
J. Sheikh, J. Yesavage (1986)
Geriatric Depression Scale (GDS): Recent evidence and development of a shorter version.Clinical Gerontologist, 5
Lord (1996)
Exercise effect on dynamic stability in older womenA randomized controlled trial, 77
Hawthorne Hawthorne, Richardson Richardson, Osborne Osborne (1999)
The Assessment of Quality of Life (AQoL) instrumentA psychometric measure of health-related quality of life, 8
Rebecca BOptom, R. Cumming, P. Mitchell, K. Attebo (1998)
Visual Impairment and Falls in Older Adults: The Blue Mountains Eye StudyJournal of the American Geriatrics Society, 46
S. Lord, H. Menz, A. Tiedemann (2003)
A physiological profile approach to falls risk assessment and prevention.Physical therapy, 83 3
Watson Watson, Clark Clark, Tellegen Tellegen (1988)
Development and validation of brief measures of positive and negative affectThe PANAS scales, 54
Sheikh Sheikh, Yesavage Yesavage (1986)
Geriatric Depression Scale (GDS)Recent evidence and development of a shorter version, 5
J. O'Loughlin, Y. Robitaille, J. Boivin, S. Suissa (1993)
Incidence of and risk factors for falls and injurious falls among the community-dwelling elderly.American journal of epidemiology, 137 3
T. Salthouse (1996)
The processing-speed theory of adult age differences in cognition.Psychological review, 103 3
C. Sherrington, J. Whitney, S. Lord, R. Herbert, R. Cumming, J. Close. (2008)
Effective Exercise for the Prevention of Falls: A Systematic Review and Meta‐AnalysisJournal of the American Geriatrics Society, 56
J. Sheldon (1960)
On the Natural History of Falls in Old Age*British Medical Journal, 2
D. Goldberg, K. Bridges, P. Duncan-Jones, D. Grayson (1988)
Detecting anxiety and depression in general medical settings.British Medical Journal, 297
(2009)
Effectiveness of a multifactorial , cognitive behavioral group intervention on fear of falling and associated avoidance of activity in community - living older people : A randomized controlled trial
Tinetti (2010)
The patient who falls“It's always a trade-off.”, 303
Fastenau Fastenau, Denburg Denburg, Mauer Mauer (1998)
Parallel short forms for the Boston Naming TestPsychometric properties and norms for older adults, 20
D. King, E. Caine, C. Cox (1993)
Influence of depression and age on selected cognitive functionsClinical Neuropsychologist, 7
S. Lamb, Ellen Jørstad-Stein, K. Hauer, C. Becker (2005)
Development of a Common Outcome Data Set for Fall Injury Prevention Trials: The Prevention of Falls Network Europe ConsensusJournal of the American Geriatrics Society, 53
K. Anstey, J. Wood, G. Kerr, H. Caldwell, S. Lord (2009)
Different cognitive profiles for single compared with recurrent fallers without dementia.Neuropsychology, 23 4
Walter Sturm (2007)
Neuropsychological assessmentJournal of Neurology, 254
M. Nevitt, S. Cummings, S. Kidd, D. Black (1989)
Risk factors for recurrent nonsyncopal falls. A prospective study.JAMA, 261 18
N. Camp, M. Slattery (2002)
Classification tree analysis: a statistical tool to investigate risk factor interactions with an example for colon cancer (United States)Cancer Causes & Control, 13
M. D’Esposito, J. Detre, D. Alsop, R. Shin, S. Atlas, M. Grossman (1995)
The neural basis of the central executive system of working memoryNature, 378
Zijlstra Zijlstra, van Haastregt van Haastregt, Ambergen Ambergen (2009)
Effectiveness of a multifactorial, cognitive behavioral group intervention on fear of falling and associated avoidance of activity in community‐living older peopleA randomized controlled trial, 57
S. Lamb, C. McCabe, C. Becker, L. Fried, J. Guralnik (2008)
The optimal sequence and selection of screening test items to predict fall risk in older disabled women: the Women's Health and Aging Study.The journals of gerontology. Series A, Biological sciences and medical sciences, 63 10
M. Tinetti, Chandrika Kumar (2010)
The patient who falls: "It's always a trade-off".JAMA, 303 3
D. Wechsler (1981)
WAIS-R manual : Wechsler adult intelligence scale-revised
D. Cahn-Weiner, P. Malloy, P. Boyle, M. Marran, S. Salloway (2000)
Prediction of Functional Status from Neuropsychological Tests in Community-Dwelling Elderly IndividualsThe Clinical Neuropsychologist, 14
Camp Camp, Slattery Slattery (2002)
Classification tree analysisA statistical tool to investigate risk factor interactions with an example for colon cancer (United States), 13
Lamb (2008)
The optimal sequence and selection of screening test items to predict fall risk in older disabled womenThe women's health and aging study, 63
Ivers Ivers, Cumming Cumming, Mitchell Mitchell (1998)
Visual impairment and falls in older adultsThe Blue Mountains Eye Study, 46
Sherrington Sherrington, Whitney Whitney, Lord Lord (2008)
Effective exercise for the prevention of fallsA systematic review and meta-analysis, 56
T. Liu-Ambrose, Meghan Donaldson, Y. Ahamed, P. Graf, W. Cook, J. Close., S. Lord, Karim Khan (2008)
Otago Home‐Based Strength and Balance Retraining Improves Executive Functioning in Older Fallers: A Randomized Controlled TrialJournal of the American Geriatrics Society, 56
Philip Fastenau, Natalie Denburg, Beth Mauer (1998)
Parallel short forms for the Boston Naming Test: psychometric properties and norms for older adults.Journal of clinical and experimental neuropsychology, 20 6
S. Lord, Russell Clark, I. Webster (1991)
Physiological Factors Associated with Falls in an Elderly PopulationJournal of the American Geriatrics Society, 39
D. Hosmer, S. Lemeshow (1991)
Applied Logistic Regression
(1992)
NEO PI-R Professional Manual: Revised NEO PI Personality Inventory (NEO PI-R) and NEO Five-Factor Inventory (NEOFFI)
Stephen Lord, John Ward, Philippa Williams (1996)
Exercise effect on dynamic stability in older women: a randomized controlled trial.Archives of physical medicine and rehabilitation, 77 3
L. Yardley, N. Beyer, K. Hauer, G. Kempen, C. Piot‐Ziegler, C. Todd (2005)
Development and initial validation of the Falls Efficacy Scale-International (FES-I).Age and ageing, 34 6
R. Jung (2005)
Neuropsychological Assessment, 4th ed.American Journal of Psychiatry, 162
Lamb Lamb, Jorstad‐Stein Jorstad‐Stein, Hauer Hauer (2005)
Development of a common outcome data set for fall injury prevention trialsThe Prevention of Falls Network Europe consensus, 53
M. Espejo (2004)
Applying the Rasch Model: Fundamental Measurement in the Human SciencesJournal of The Royal Statistical Society Series A-statistics in Society, 167
Liu‐Ambrose Liu‐Ambrose, Donaldson Donaldson, Ahamed Ahamed (2008)
Otago home‐based strength and balance retraining improves executive functioning in older fallersA randomized controlled trial, 56
D. Watson, L. Clark, A. Tellegen (1988)
Development and validation of brief measures of positive and negative affect: the PANAS scales.Journal of personality and social psychology, 54 6
K. Delbaere, K. Hauer, S. Lord (2009)
Evaluation of the incidental and planned activity questionnaire for older peopleBritish Journal of Sports Medicine, 44
OBJECTIVE: To identify the interrelationships and discriminatory value of a broad range of objectively measured explanatory risk factors for falls. DESIGN: Prospective cohort study with 12‐month follow‐up period. SETTING: Community sample. PARTICIPANTS: Five hundred community‐dwelling people aged 70 to 90. MEASUREMENTS: All participants underwent assessments on medical, disability, physical, cognitive, and psychological measures. Fallers were defined as people who had at least one injurious fall or at least two noninjurious falls during a 12‐month follow‐up period. RESULTS: Univariate regression analyses identified the following fall risk factors: disability, poor performance on physical tests, depressive symptoms, poor executive function, concern about falling, and previous falls. Classification and regression tree analysis revealed that balance‐related impairments were critical predictors of falls. In those with good balance, disability and exercise levels influenced future fall risk—people in the lowest and the highest exercise tertiles were at greater risk. In those with impaired balance, different risk factors predicted greater fall risk—poor executive function, poor dynamic balance, and low exercise levels. Absolute risks for falls ranged from 11% in those with no risk factors to 54% in the highest‐risk group. CONCLUSIONS: A classification and regression tree approach highlighted interrelationships and discriminatory value of important explanatory fall risk factors. The information may prove useful in clinical settings to assist in tailoring interventions to maximize the potential benefit of falls prevention strategies.
Journal of American Geriatrics Society – Wiley
Published: Sep 1, 2010
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