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Factors included in adult fall risk assessment tools (FRATs): a systematic review

Published online by Cambridge University Press:  22 April 2020

Hendrika de Clercq Open the ORCID record for Hendrika de Clercq [Opens in a new window] ,
Alida Naudé  and
Juan Bornman
Hendrika de Clercq*
Affiliation:
Centre for Augmentative and Alternative Communication, Faculty of Humanities, University of Pretoria, South Africa
Alida Naudé
Affiliation:
Centre for Augmentative and Alternative Communication, Faculty of Humanities, University of Pretoria, South Africa
Juan Bornman
Affiliation:
Centre for Augmentative and Alternative Communication, Faculty of Humanities, University of Pretoria, South Africa
*
*Corresponding author. Email: hendrika@hdcinc.co.za
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Abstract

Falls often have severe financial and environmental consequences, not only for those who fall, but also for their families and society at large. Identifying fall risk in older adults can be of great use in preventing or reducing falls and fall risk, and preventative measures that are then introduced can help reduce the incidence and severity of falls in older adults. The overall aim of our systematic review was to provide an analysis of existing mechanisms and measures for evaluating fall risk in older adults. The 43 included FRATs produced a total of 493 FRAT items which, when linked to the ICF, resulted in a total of 952 ICF codes. The ICF domain with the most used codes was body function, with 381 of the 952 codes used (40%), followed by activities and participation with 273 codes (28%), body structure with 238 codes (25%) and, lastly, environmental and personal factors with only 60 codes (7%). This review highlights the fact that current FRATs focus on the body, neglecting environmental and personal factors and, to a lesser extent, activities and participation. This over-reliance on the body as the point of failure in fall risk assessment clearly highlights the need for gathering qualitative data, such as from focus group discussions with older adults, to capture the perspectives and views of the older adults themselves about the factors that increase their risk of falling and comparing these perspectives to the data gathered from published FRATs as described in this review.

Keywords

accidental fallsaging/ageingbalancedisability and healthfall risk factorsfall risk assessment tools (FRATs)
Type
Review Article
Information
Ageing & Society , Volume 41 , Issue 11 , November 2021 , pp. 2558 - 2582
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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References

Adair, B, Ullenhag, A, Rosenbaum, P, Granlund, M, Keen, D and Imms, C (2018) Measures used to quantify participation in childhood disability and their alignment with the family of participation-related constructs: a systematic review. Developmental Medicine & Child Neurology 60, 1101–1116.CrossRefGoogle ScholarPubMed
Altman, DG (1991) Practical Statistics for Medical Research. London: Chapman and Hall.Google Scholar
Arksey, H and O'Malley, L (2005) Scoping studies: towards a methodological framework. International Journal of Social Research Methodology: Theory and Practice 8, 19–32.CrossRefGoogle Scholar
Baran, L and Gunes, U (2018) Predictive validity of three fall risk assessment tools in nursing home residents in Turkey: a comparison of the psychometric properties. International Journal of Caring Sciences 11, 36–44.Google Scholar
Barker, AL, Nitz, JC, Low Choy, NL and Haines, T (2009) Measuring fall risk and predicting who will fall: clinimetric properties of four fall risk assessment tools for residential aged care. Journals of Gerontology: Biological Sciences and Medical Sciences 64A, 916–924.CrossRefGoogle Scholar
Berg, K, Wood-Dauphinée, S, Williams, JI and Gayton, D (1989) Measuring balance in the elderly: preliminary development of an instrument. Physiotherapy Canada 41, 304–311.CrossRefGoogle Scholar
Bohannon, RW, Andrews, AW and Thomas, MW (1996) Walking speed: reference values and correlates for older adults. Journal of Orthopaedic & Sports Physical Therapy 24, 86–90.CrossRefGoogle ScholarPubMed
Callisaya, ML, Blizzard, L, Martin, K and Srikanth, VK (2016) Gait initiation time is associated with the risk of multiple falls – a population-based study. Gait and Posture 49, 19–24.CrossRefGoogle ScholarPubMed
Calys, M, Gagnon, K and Jernigan, S (2013) A validation study of the Missouri Alliance for Home Care Fall Risk Assessment Tool. Home Health Care Management & Practice 25, 39–44.CrossRefGoogle Scholar
Cattelani, L, Palumbo, P, Palmerini, L, Bandinelli, S, Becker, C, Chesani, F and Chiari, L (2015) FRAT-up, a fall-risk assessment tool for elderly people living in the community. Journal of Medical Internet Research 17, 41–45.CrossRefGoogle ScholarPubMed
Chang, SY, Chen, W, Teng, T, Yeh, C and Yen, H (2018) Fall risk program for oncology inpatients: addition of the ‘Traffic Light’ Fall Risk Assessment Tool. Journal of Nursing Care Quality 34, 139–144.CrossRefGoogle Scholar
Chapman, J, Bachand, D and Hyrkas, K (2011) Testing the sensitivity, specificity and feasibility of four falls risk assessment tools in a clinical setting: falls risk assessment. Journal of Nursing Management 19, 133–142.CrossRefGoogle Scholar
Chow, RB, Lee, A, Kane, BG, Jacoby, JL, Barraco, RD, Dusza, SW, Meyers MC, Greenberg MR. et al. (2018) Effectiveness of the Timed Up and Go (TUG) and the Chair test as screening tools for geriatric fall risk assessment in the ED. American Journal of Emergency Medicine 37, 457–460.CrossRefGoogle ScholarPubMed
Cieza, A, Fayed, N, Bickenbach, J and Prodinger, B (2016) Refinements of the ICF Linking Rules to strengthen their potential for establishing comparability of health information. Disability and Rehabilitation 41, 574–583.CrossRefGoogle ScholarPubMed
Collins, T, McGann, A, Jessup, R, Vrantsidis, F, Hill, KD and Pearce, J (2004) Validation of a falls risk assessment tool in the sub-acute hospital setting: a pilot study. Australasian Journal of Podiatric Medicine 38, 99–108.Google Scholar
Conley, D, Schultz, AA and Selvin, R (1999) The challenge of predicting patients at risk for falling: development of the Conley Scale. MedSurg Nursing 8, 348–354.Google ScholarPubMed
Cumming, RG (2013) Fall prevention in older persons. CME 31, 378–381.Google Scholar
Currie, LM, Mellino, LV, Cimino, JJ and Bakken, S.2004) Development and representation of a fall-injury risk assessment instrument in a clinical information system. In Fieschi, M, Coiera, E and Li, YJ (eds), pp. 721–725. Amsterdam: IOS Press.Google Scholar
Da Costa, BR, Rutjes, AWS, Mendy, A, Freund-Heritage, R and Vieira, ER (2012) Can falls risk prediction tools correctly identify fall-prone elderly rehabilitation in patients? A systematic review and meta-analysis. PLOS ONE 7, 41–47.CrossRefGoogle ScholarPubMed
Delfante, B, Patel, H, Zake, A and Emmerton, L (2018) A retrospective audit evaluating the effectiveness of a falls risk assessment tool. Research in Social and Administrative Pharmacy 14, 33.CrossRefGoogle Scholar
Demura, S, Sato, S, Yokoya, T and Sato, T (2010) Examination of useful items for the assessment of fall risk in the community-dwelling elderly Japanese population. Environmental Health and Preventive Medicine 15, 169–179.CrossRefGoogle ScholarPubMed
Deschamps, T, Le Goff, CG, Berrut, G, Cornu, C and Mignardot, JB (2016) A decision model to predict the risk of the first fall onset. Experimental Gerontology 81, 51–55.CrossRefGoogle ScholarPubMed
Dite, W and Temple, VA (2002) A clinical test of stepping and change of direction to identify multiple falling older adults. Archives of Physical Medicine and Rehabilitation 83, 1566–1571.CrossRefGoogle ScholarPubMed
Downton, JH (1993) Falls in the Elderly. Sevenoaks, UK: Edward Arnold.Google Scholar
Dueñas, L, Balasch i Bernat, M, Mena del Horno, S, Aguilar-Rodríguez, M and Alcántara, E (2016) Development of predictive models for the estimation of the probability of suffering fear of falling and other fall risk factors based on posturography parameters in community-dwelling older adults. International Journal of Industrial Ergonomics 54, 131–138.CrossRefGoogle Scholar
Duncan, PW, Weiner, DK, Chandler, J and Studenski, S (1990) Functional reach: a new clinical measure of balance. Journal of Gerontology 45, 192–197.CrossRefGoogle Scholar
Ek, S (2019) Predictors and Consequences of Injurious Falls Among Older Adults: A Holistic Approach. Solna, Sweden: The Aging Research Center (ARC), Department of Neurobiology, Care Sciences and Society, Karolinska Institute.Google Scholar
Farre, A and Rapley, T (2017) The new old (and old new) medical model: four decades navigating the biomedical and psychosocial understandings of health and illness. Healthcare 5, 1–9.CrossRefGoogle ScholarPubMed
Flaherty, LM and Josephson, NC (2013) Screening for fall risk in patients with haemophilia. Haemophilia 19, 103–109.CrossRefGoogle ScholarPubMed
Flarity, K, Pate, T and Finch, H (2013) Development and implementation of the Memorial Emergency Department Fall Risk Assessment Tool. Advanced Emergency Nursing Journal 35, 57–66.CrossRefGoogle ScholarPubMed
Forrest, G, Chen, E, Huss, S and Giesler, A (2013) A comparison of the Functional Independence Measure and Morse Fall Scale as tools to assess risk of fall on an inpatient rehabilitation. Rehabilitation Nursing 38, 186–192.CrossRefGoogle Scholar
Gallagher, R, Stith, N and Southard, V (2013) Evaluation of the Missouri Alliance for Home Care Fall Risk Assessment Tool and home-based ‘Balanced Approach’ fall reduction initiative. Home Health Care Management & Practice 25, 224–228.CrossRefGoogle Scholar
Gamage, N, Rathnayake, N and Alwis, G (2018) Knowledge and perception of falls among community dwelling elderly: a study from southern Sri Lanka. Current Gerontology and Geriatrics Research 2018, 7653469.CrossRefGoogle ScholarPubMed
Granberg, S (2015) Functioning and Disability in Adults with Hearing Loss (Thesis). Örebro University, Örebro, Sweden.Google Scholar
Greenberg, SA, Sommers, MLS, Chittams, J and Cacchione, PZ (2016) Measuring fear of falling among high-risk, urban, community-dwelling older adults. Geriatric Nursing 37, 489–495.CrossRefGoogle ScholarPubMed
Gu, Y and Dennis, SM (2016) Are falls prevention programs effective at reducing the risk factors for falls in people with type-2 diabetes mellitus and peripheral neuropathy: a systematic review with narrative synthesis. Journal of Diabetes and Its Complications 31, 504–516.CrossRefGoogle ScholarPubMed
Guralnik, JM, Simonsick, EM, Ferrucci, L, Glynn, RJ, Berkman, LF, Blazer, DG, Scherr, PA, Wallace, RB. et al. (1994) A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. Journal of Gerontology 49, 85–94.CrossRefGoogle Scholar
Guzzo, AS, Meggiolaro, A, Mannocci, A, Tecca, M, Salomone, I and La Torre, G (2015) Conley Scale: assessment of a fall risk prevention tool in a general hospital. Journal of Preventive Medicine and Hygiene 56, 77–87.Google ScholarPubMed
Hendrich, A, Nyhuis, A, Kippenbrock, T and Soja, ME (1995) Hospital falls: development of a predictive model for clinical practice. Nursing Research 8, 129–139.Google ScholarPubMed
Higaonna, M (2015) The predictive validity of a modified Japanese Nursing Association fall risk assessment tool: a retrospective cohort study. International Journal of Nursing Studies 52, 1484–1494.CrossRefGoogle ScholarPubMed
Higaonna, M, Enobi, M and Nakamura, S (2017) Development of an evidence-based fall risk assessment tool and evaluation of interrater reliability and nurses’ perceptions of the tool's clarity and usability. Japan Journal of Nursing Science 14, 146–160.CrossRefGoogle ScholarPubMed
Hill, K, Vrantsidis, F, Jessup, R, McGann, A, Pearce, J and Colins, T (2004) Validation of a falls risk assessment tool in the sub-acute hospital setting: a pilot study. Australasian Journal of Podiatric Medicine 38, 99–108.Google Scholar
Hirase, T, Inokuchi, S, Matsusaka, N, Nakahara, K and Okita, M (2014) A modified fall risk assessment tool that is specific to physical function predicts falls in community-dwelling elderly people. Journal of Geriatric Physical Therapy 37, 159–165.CrossRefGoogle ScholarPubMed
Hnizdo, S, Archuleta, RA, Taylor, B and Kim, SC (2013) Validity and reliability of the modified John Hopkins Fall Risk Assessment Tool for elderly patients in home health care. Geriatric Nursing 34, 423–427.CrossRefGoogle Scholar
Homer, ML, Palmer, NP, Fox, KP, Armstrong, J and Mandl, KD (2017) Predicting falls in people aged 65 years and older from insurance claims. American Journal of Medicine 130, 717–744.CrossRefGoogle ScholarPubMed
Horak, FB, Wrisley, DM and Frank, J (2009) The Balance Evaluation Systems Test (BESTest) to differentiate balance deficits. Physical Therapy 89, 484–498.CrossRefGoogle ScholarPubMed
Hung, C-H, Wang, C-J, Tang, T-C, Chen, L-Y, Peng, L-N, Hsiao, F-Y and Chen, L-K (2017) Recurrent falls and its risk factors among older men living in the veterans retirement communities: a cross-sectional study. Archives of Gerontology and Geriatrics 70, 214–218.CrossRefGoogle ScholarPubMed
Hur, EY, Jin, Y, Jin, T and Lee, S-M (2016) Longitudinal evaluation of Johns Hopkins Fall Risk Assessment Tool and nurses' experience. Journal of Nursing Care Quality 32, 242–251.CrossRefGoogle Scholar
Jensen, DR (2006) Medical Model Influence in Counseling and Psychotherapy: Counseling Psychology Training Directors’ Views (ProQuest Dissertations and Theses No. 139). Utah: Bringham Young University.Google Scholar
Jester, R, Wade, S and Henderson, K (2005) A pilot investigation of the efficacy of falls risk assessment tools and prevention strategies in an elderly hip fracture population. Journal of Orthopaedic Nursing 9, 27–34.CrossRefGoogle Scholar
Jones, CJ, Rikli, RE and Beam, WC (1999) A 30-s chair-stand test as a measure of lower body strength in community-residing older adults. Research Quarterly for Exercise and Sport 70, 113–119.CrossRefGoogle ScholarPubMed
Kehinde, JO (2009) Instruments for measuring fall risk in older adults living in long-term care facilities: an integrative review. Journal of Gerontological Nursing 35, 46–55.CrossRefGoogle ScholarPubMed
Kenny, RA, Romero-Ortuno, R and Kumar, P (2016) Falls in older adults. Medicine in Older Adults 45, 28–33.Google Scholar
Kim, T and Xiong, S (2017) Comparison of seven fall risk assessment tools in community-dwelling Korean older women. Ergonomics 60, 421–429.CrossRefGoogle ScholarPubMed
Kim, EA, Mordiffi, SZ, Bee, WH, Devi, K and Evans, D (2007) Evaluation of three fall-risk assessment tools in an acute care setting. Journal of Advanced Nursing 60, 427–435.CrossRefGoogle Scholar
Kim, SR, Yoo, S-H, Shin, YS, Jeon, JY, Kim, JY, Kang, SJ and An, YH (2013) Comparison of the reliability and validity of fall risk assessment tools in patients with acute neurological disorders. Korean Journal of Adult Nursing 25, 24–32.CrossRefGoogle Scholar
Klenk, J, Becker, C, Palumbo, P, Schwickert, L, Rapp, K, Helbostad, JL and Kerse, N (2017) Conceptualizing a dynamic fall risk model including intrinsic risks and exposures. Journal of the American Medical Directors Association 18, 921–927.CrossRefGoogle ScholarPubMed
Klinkenberg, W and Potter, P (2017) Validity of the Johns Hopkins fall risk assessment tool for predicting falls on inpatient medicine services. Journal of Nursing Care Quality 32, 108–113.CrossRefGoogle Scholar
LeCuyer, M, Lockwood, B and Locklin, M (2016) Development of a fall prevention program in the ambulatory surgery setting. Journal of PeriAnesthesia Nursing 32, 472–479.CrossRefGoogle ScholarPubMed
Lee, Y and Kim, S (2017) Correlation between the fear of falling and fall risk assessment tools in the community-dwelling frail elderly in Korea. Journal of Clinical Gerontology and Geriatrics 8, 123–126.Google Scholar
Légaré, F, Adekpedjou, R, Stacey, D, Turcotte, S, Kryworuchko, J, Graham, ID and Donner-Banzhoff, N (2018) Cochrane Database of Systematic Reviews 7.Google Scholar
Lovallo, C, Rolandi, S, Rossetti, AM and Lusignani, M (2010) Accidental falls in hospital inpatients: evaluation of sensitivity and specificity of two risk assessment tools. Journal of Advanced Nursing 66, 690–696.CrossRefGoogle ScholarPubMed
Lundin-Olsson, L, Jensen, J, Nyberg, L and Gustafson, Y (2003) Predicting falls in residential care by a risk assessment tool, staff judgement, and history of falls. Aging Clinical and Experimental Research 15, 51–59.CrossRefGoogle ScholarPubMed
Lundin-Olsson, L, Nyberg, L and Gustafson, Y (2006) The Mobility Interaction Fall Chart. Physiotherapy Research International 5, 190–201.CrossRefGoogle Scholar
Ma, C, Evans, K, Bertmar, C and Krause, M (2014) Predictive value of the Royal Melbourne Hospital Falls Risk Assessment Tool (RMH FRAT) for post-stroke patients. Journal of Clinical Neuroscience 21, 607–611.CrossRefGoogle ScholarPubMed
Majkusova, K and Jarosova, D (2017) Validity of tools for assessing the risk of falls in patients. Central European Journal of Nursing and Midwifery 8, 697–705.CrossRefGoogle Scholar
McDowell, I and Newell, C (1996) Measuring Health: A Guide to Rating Scales and Questionnaires, 2nd Edn. New York, NY: Oxford University Press.Google Scholar
McNair, DS and Simpson, RL (2016) Bayesian cost-effectiveness analysis of falls risk assessment tools: falls: sensitivity and specificity – asking for decision support changes? Nursing Administration Quarterly 40, 364–369.CrossRefGoogle ScholarPubMed
Meyer, G, Kopke, S, Bender, R and Muhlhauser, I (2005) Predicting the risk of falling – efficacy of a risk assessment tool compared to nurses’ judgement: a cluster-randomised controlled trial. BMC Geriatrics 5, 14.CrossRefGoogle ScholarPubMed
Meyer, G, Kopke, S, Haastert, B and Muhlhauser, I (2009) Comparison of a fall risk assessment tool with nurses’ judgement alone: a cluster-randomised controlled trial. Age and Ageing 38, 417–423.CrossRefGoogle ScholarPubMed
Miyakoshi, K, Nasu, T, Takahashi, S and Natsume, T (2014) Validation of the Japanese Association of Rehabilitation Medicine Fall Risk Assessment Tool. Physical Medicine and Rehabilitation 6, 130–135.Google Scholar
Moher, D, Liberati, A, Tetzlaff, J, Altman, DG and the PRISMA Group (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Physical Therapy 89, 873–880.CrossRefGoogle ScholarPubMed
Moore, K, Fearn, M, Cyarto, E, Renehan, E, Haralambous, B, Hill, K, Robinson, A, Nitz, J, Haines, T, Andrews, S, Churchill, B and Fu, S (2006) Star project: an individualized, facilitated and sustainable approach to implementing the evidence in preventing falls in residential aged care facilities. Report to the Australian Government Department of Health and Ageing. Australia: National Ageing Research Institute.Google Scholar
Morse, JM, Morse, RM and Tylko, SJ (1989) Development of a scale to identify the fall-prone patient. Canadian Journal on Aging 8, 366–377.CrossRefGoogle Scholar
Narayanan, V, Dickinson, A, Victor, C, Griffiths, C and Humphrey, D (2016) Falls screening and assessment tools used in acute mental health settings: a review of policies in England and Wales. Physiotherapy 102, 178–183.CrossRefGoogle ScholarPubMed
Noohu, MM, Dey, AB, Sharma, S and Hussain, ME (2017) International classification of function, disability and health framework for fall risk stratification in community dwelling older adults. Geriatric Care 3, 1–7.CrossRefGoogle Scholar
Nunan, S, Brown Wilson, C, Henwood, T and Parker, D (2018) Fall risk assessment tools for use among older adults in long-term care settings: a systematic review of the literature. Australasian Journal on Ageing 37, 23–33.CrossRefGoogle ScholarPubMed
Oliver, D, Britton, M, Seed, P, Martin, FC and Hopper, AH (1997) Development and evaluation of evidence-based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: case control and cohort studies. British Medical Journal 315, 1049–1053.CrossRefGoogle ScholarPubMed
Ouzzani, M, Hammady, H, Fedorowicz, Z and Elmagarmid, A (2016) Rayyan – a web and mobile app for systematic reviews. Systematic Reviews 5, 210.CrossRefGoogle Scholar
Palumbo, P, Palmerini, L, Bandinelli, S and Chiari, L (2015) Fall risk assessment tools for elderly living in the community: can we do better? PLOS ONE 10, 15–18.CrossRefGoogle ScholarPubMed
Palumbo, P, Klenk, J, Cattelani, L, Bandinelli, S, Ferrucci, L, Rapp, K, Chiari, L, Rothenbacher, D. et al. (2016) Predictive performance of a fall risk assessment tool for community-dwelling older people (FRAT-up) in 4 European cohorts. Journal of the American Medical Directors Association 17, 1106–1113.CrossRefGoogle Scholar
Papaioannou, A, Parkinson, W, Cook, R, Ferko, N, Coker, E and Adachi, JD (2004) Prediction of falls using a risk assessment tool in the acute care setting. BMC Medicine 2, 1.CrossRefGoogle ScholarPubMed
Pape, H-C, Schemmann, U, Foerster, J and Knobe, M (2015) The Aachen Falls Prevention Scale – development of a tool for self-assessment of elderly patients at risk for ground-level falls. Patient Safety in Surgery 9, 7–10.CrossRefGoogle ScholarPubMed
Park, SH (2017) Tools for assessing fall risk in the elderly: a systematic review and meta-analysis. Aging Clinical and Experimental Research 30, 1–16.CrossRefGoogle ScholarPubMed
Peel, N, Bell, RAR and Smith, K (2008) Queensland Stay On Your Feet Community Good Practice Guidelines. Brisbane, Australia: Queensland Health.Google Scholar
Phelan, EA, Mahoney, JE, Voit, JC and Stevens, JA (2015) Assessment and management of fall risk in primary care settings. Medical Clinics of North America 99, 281–293.CrossRefGoogle ScholarPubMed
Pluijm, SM, Smit, JH, Tromp, EA, Stel, VS, Deeg, DJ, Bouter, LM and Lips, P (2006) A risk profile for identifying community-dwelling elderly with a high risk of recurrent falling: results of a 3-year prospective study. Osteoporosis International 17, 417–425.CrossRefGoogle ScholarPubMed
Podsiadlo, D and Richardson, S (1991) The timed ‘Up and Go’: a test of basic functional mobility for frail elderly persons. Journal of the American Geriatrics Society 39, 142–148.CrossRefGoogle Scholar
Poe, SS, Cvach, MM, Gartrell, DG, Radzik, BR and Joy, TL (2005) An evidence-based approach to fall risk assessment, prevention, and management. Lessons learned. Journal of Nursing Care Quality 20, 107–116.CrossRefGoogle ScholarPubMed
Poe, SS, Cvach, M, Dawson, PB, Straus, H and Hill, EE (2007) The Johns Hopkins Fall Risk Assessment Tool: postimplementation evaluation. Journal of Nursing Care Quality 22, 293–298.CrossRefGoogle Scholar
Powell, LE and Myers, AM (1995) The Activities-specific Balance Confidence (ABC) Scale. Journals of Gerontology: Biological Sciences and Medical Sciences 50A, 28–34.CrossRefGoogle ScholarPubMed
Renfro, M, Maring, J, Bainbridge, D and Blair, M (2016) Fall risk among older adult high-risk populations: a review of current screening and assessment tools. Current Geriatrics Reports 5, 160–171.CrossRefGoogle Scholar
Robey-Williams, C, Rush, KL, Bendyk, H, Patton, LM, Chamberlain, D and Sparks, T (2007) Spartanburg Fall Risk Assessment Tool: a simple three-step process. Applied Nursing Research 20, 86–93.CrossRefGoogle ScholarPubMed
Romli, MH, Tan, MP, Mackenzie, L, Lovarini, M, Suttanon, P and Clemson, L (2017) Falls amongst older people in Southeast Asia: a scoping review. Public Health 145, 6–9.CrossRefGoogle ScholarPubMed
Rose, DJ, Lucchese, N and Wiersma, LD (2006) Development of a multidimensional balance scale for use with functionally independent older adults. Archives of Physical Medicine and Rehabilitation 87, 1478–1485.CrossRefGoogle ScholarPubMed
Royal Melbourne Hospital (1995) Predictive value of the Royal Melbourne Hospital Falls Risk Assessment Tool (RMH FRAT) for post-stroke patients. Journal of Clinical Neuroscience 21, 124–130.Google Scholar
Rubenstein, LZ (2006) Falls in older people: epidemiology, risk factors and strategies for prevention. Age and Ageing 35, 37–41.CrossRefGoogle ScholarPubMed
Ruroede, K, Pilkington, D and Guernon, A (2016) Validation study of the Marianjoy Fall Risk Assessment Tool. Journal of Nursing Care Quality 31, 146–152.CrossRefGoogle ScholarPubMed
Russell, M, Hill, K, Dharmage, S, Blackberry, I and Day, L (2006) Evaluation of the Falls Risk for Older People in the Community (FROP-Com) Assessment Tool. Australasian Epidemiologist 13, 53.Google Scholar
Russell, MA, Hill, KD, Blackberry, I, Day, LM and Dharmage, SC (2008) The reliability and predictive accuracy of the falls risk for older people in the community assessment (FROP-Com) tool. Age and Ageing 37, 634–639.CrossRefGoogle ScholarPubMed
Salb, J, Finlayson, J, Almutaseb, S, Scharfenberg, B, Becker, C, Sieber, C and Freiberger, E (2015) Test–retest reliability and agreement of physical fall risk assessment tools in adults with intellectual disabilities. Journal of Intellectual Disability Research 59, 1121–1129.CrossRefGoogle ScholarPubMed
Schmid, NA (1990) Reducing patient falls: a research-based comprehensive fall prevention program. Military Medicine 155, 202–207.CrossRefGoogle ScholarPubMed
Scott, V, Votova, K, Scanlan, A and Close, J (2007) Multifactorial and functional mobility assessment tools for fall risk among older adults in community, home-support, long-term and acute care settings. Age and Ageing 36, 130–139.CrossRefGoogle ScholarPubMed
Selb, M, Escorpizo, R, Kostanjsek, N, Stucki, G, Ustun, B and Cieza, A (2015) A guide on how to develop an International Classification of Functioning, Disability and Health Core Set. European Journal of Physical and Rehabilitation Medicine 51, 105–117.Google ScholarPubMed
Seneviratne, C (2006) The STRATIFY falls risk assessment tool was not useful in predicting falls in patients with acute stroke. Evidence-based Nursing 9, 91.CrossRefGoogle Scholar
Skelton, KW, Papanek, PE, Lynch, SB and Ryan, PA (2014) Fall incidence and self-reported health in middle aged women: need for new risk assessment tools. Medicine & Science in Sports & Exercise 46, 431.CrossRefGoogle Scholar
Stapleton, C, Hough, P, Oldmeadow, L, Bull, K, Hill, K and Greenwood, K (2009) Four-item fall risk screening tool for sub-acute and residential aged care: The first step in fall prevention. Australasian Journal on Ageing 28, 139–143.CrossRefGoogle Scholar
Stewart Williams, J, Kowal, P, Hestekin, H, O'Driscoll, T, Peltzer, K, Yawson, A and Chatterji, S (2015) Prevalence, risk factors and disability associated with fall-related injury in older adults in low- and middle-income countries: results from the WHO Study on Global Ageing and adult health (SAGE). BMC Medicine 13.CrossRefGoogle Scholar
Stretanski, M, Lusardi, M, Dumont, L and Evans, L (2002) Predicting risk of future falls among residents of health care facilities: Berg Balance Scale and Fall Risk Assessment Tool. Journal of Geriatric Physical Therapy 25, 22.CrossRefGoogle Scholar
Teh, RC, Wilson, A, Ranasinghe, D and Visvanathan, R (2017) Use and clinical efficacy of standard and health information technology fall risk assessment tools. Australasian Journal on Ageing 36, 327–331.CrossRefGoogle ScholarPubMed
Thiamwong, L, Thamarpirat, J, Maneesriwongul, W and Jitapunkul, S (2009) Thai Falls Risk Assessment Test (Thai-FRAT) developed for community-dwelling Thai elderly. Journal of the Medical Association of Thailand 91, 1823–1831.Google Scholar
Tiedemann, A (2006) The development of a validated falls risk assessment for use in clinical practice. Australia: University of New South Wales.Google Scholar
Tiedemann, A, Lord, S and Sherrington, C (2012) The Quickscreen tool: a validated falls risk assessment, developed and implemented in Australia for use in primary care. Injury Prevention 18, 38–56.CrossRefGoogle Scholar
Tinetti, ME, Williams, TF and Mayewski, R (1986) Fall risk index for elderly patients based on number of chronic disabilities. American Journal of Medicine 80, 429–434.CrossRefGoogle ScholarPubMed
Van Swearingen, JM, Paschal, KA, Bonino, P and Yang, JF (1996) The modified Gait Abnormality Rating Scale for recognizing the risk of recurrent falls in community-dwelling elderly adults. Physical Therapy 76, 994–1002.CrossRefGoogle Scholar
Vassallo, M, Stockdale, R, Sharma, JC, Briggs, R and Allen, S (2005) A comparative study of the use of four fall risk assessment tools on acute medical wards: a comparison of four falls risk assessment tools. Journal of the American Geriatrics Society 53, 1034–1038.CrossRefGoogle Scholar
Vassallo, M, Poynter, L, Sharma, JC, Kwan, J and Allen, SC (2008) Fall risk-assessment tools compared with clinical judgment: an evaluation in a rehabilitation ward. Age and Ageing 37, 277–281.CrossRefGoogle Scholar
Verghese, J, Buschke, H, Viola, L, Katz, M, Hall, C, Kuslansky, G and Lipton, R (2002) Validity of divided attention tasks in predicting falls in older individuals: a preliminary study. Journal of the American Geriatrics Society 50, 1572–1576.CrossRefGoogle ScholarPubMed
Western Australia Department of Health (2015) Development of Falls Risk Assessment and Management Plan. Pearth: Health Strategy. Western Australia Department of Health.Google Scholar
Whitney, SL, Wrisley, DM, Marchetti, GM, Gee, MA, Redfern, MS and Furman, JM (2005) Clinical measurement of sit-to-stand performance in people with balance disorders: validity of data for the Five-Times-Sit-to-Stand Test. Physical Therapy 85, 1034–1045.CrossRefGoogle ScholarPubMed
Wildes, TM, Dua, P, Fowler, SA, Miller, JP, Carpenter, CR, Avidan, MS and Stark, S (2015) Systematic review of falls in older adults with cancer. Journal of Geriatric Oncology 6, 70–83.CrossRefGoogle ScholarPubMed
Wong Shee, A, Phillips, B and Hill, K (2012) Comparison of two fall risk assessment tools (FRATs) targeting falls prevention in sub-acute care. Archives of Gerontology and Geriatrics 55, 653–659.CrossRefGoogle ScholarPubMed
World Health Organization (2002) Towards a Common Language for Functioning, Disability and Health: ICF. WHO/EIP/GPE/CAS/01.3. Geneva: World Health Organization.Google Scholar
World Health Organization (2018) Fact Sheet: Falls. Geneva: World Health Organization. Available at http://apps.who.int/mediacentre/factsheets/fs344/en/index.html.Google Scholar
Yamashita, Y, Kogo, H, Kawaguchi, N, Toriyama, H and Mizota, K (2016) Usefulness of occlusal force measurement as a fall risk assessment tool. Rigakuryoho Kagaku 31, 303–307.CrossRefGoogle Scholar
Yardley, L, Beyer, N, Hauer, K, Kempen, G, Piot-Ziegler, C and Todd, C (2005) Development and initial validation of the Falls Efficacy Scale-International (FES-I). Age and Ageing 34, 614–619.CrossRefGoogle Scholar
Young, D, Liaw, S-T and Sulaiman, N (2005) Falls risk assessment and management system (FRAMS) – a decision support tool developed for general practitioners and their primary care team. Hong Kong Practitioner 27, 306–311.Google Scholar
Zhang, X and Lockhart, TE (2009) A reliability study of three functional mobility assessment tools in fall risk evaluation. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 53, 1719–1723.CrossRefGoogle Scholar
Zhang, J, Wang, M and Liu, Y (2016) Psychometric validation of the Chinese version of the Johns Hopkins Fall Risk Assessment Tool for older Chinese inpatients. Journal of Clinical Nursing 25, 19–20.CrossRefGoogle Scholar
Zur, O, Shaki, T and Carmeli, E (2016) Concurrent validity and reliability of a new balance scale used in older adults. Advances in Experimental Medicine and Biology 910, 63–70.CrossRefGoogle ScholarPubMed