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World J Meta-Anal. Jun 18, 2025; 13(2): 107388
Published online Jun 18, 2025. doi: 10.13105/wjma.v13.i2.107388
Frailty models and social frailty
Dilara Donmez Guler, Zeynep Kemik, Esra Ates Bulut, Department of Geriatric Medicine, University of Health Sciences, Adana City Research and Training Hospital, Adana 01130, Türkiye
ORCID number: Dilara Donmez Guler (0000-0001-6757-5886); Zeynep Kemik (0009-0003-8475-8205); Esra Ates Bulut (0000-0002-1124-9720).
Author contributions: Donmez Guler D and Kemik Z contributed to the review of literature, writing the draft; Ates Bulut E contributed to the design of the manuscript, critical revision; and all authors thoroughly reviewed and endorsed the final manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Esra Ates Bulut, MD, Associate Professor, Department of Geriatric Medicine, University of Health Sciences, Adana City Research and Training Hospital, No. 1 Yüreğir, Adana 01130, Türkiye. esraates@yahoo.com
Received: March 24, 2025
Revised: April 18, 2025
Accepted: June 9, 2025
Published online: June 18, 2025
Processing time: 86 Days and 5.7 Hours

Abstract

Frailty is a geriatric syndrome characterized by a reduced ability to maintain homeostasis due to age-related declines in physiological reserves. It increases the risk of adverse health outcomes such as falls, hospitalization, disability, and mortality, especially in older adults. Key risk factors for frailty include cancer, chronic obstructive pulmonary disease, and cerebrovascular disease. Several models of frailty exist, including the physical frailty phenotype, the deficit accumulation model, and mixed physical-psychosocial models. Numerous tools are available for assessment. Cognitive dysfunction is closely related to frailty, sharing underlying mechanisms such as oxidative stress, inflammation, and vascular pathologies. Additionally, social frailty, which can be exacerbated by isolation and limited social support, further complicates the challenges faced by frail individuals. It is recommended that frailty screening, particularly through gait speed assessment, can be conducted in primary healthcare settings. Despite existing guidelines, there is still no consensus on the definition, screening, and diagnosis of frailty. This emphasizes the necessity for additional research to conduct a conceptual diagnosis and screen the older population. Artificial intelligence approaches show promise in identifying frail patients and managing their care.

Key Words: Frailty; Cognitive frailty; Physical frailty; Social frailty; Frailty screening

Core Tip: Frailty is a geriatric syndrome defined by a diminished capacity to maintain homeostasis with aging. There are several models of frailty, including the physical frailty phenotype, cognitive frailty, social frailty, and mixed physical-psychosocial models. Although there have been suggestions to screen older adults for frailty, there is still no consensus on its definition or diagnosis. Artificial intelligence approaches show promise in identifying frail patients and managing their care.



INTRODUCTION

Frailty refers to the difficulty in maintaining homeostatic balance when responding to stressors, resulting from a decline in physiological reserves that often accompanies aging. Aging is associated with biological changes at the cellular level in most tissues and organs, an increase in chronic diseases, and a consequent decline in physiological and functional reserve, predisposing individuals to frailty[1]. This reduced capacity increases the risk of adverse health outcomes, such as falls, hospitalization, disability, placement in care facilities, and mortality, when faced with both external and internal challenges[2]. Contrary to common belief, not all elderly individuals are frail; only 3% to 7% of those aged 65 to 75 are considered frail, and this percentage increases to 32% in individuals over 90 years of age. Advanced age, a history of cancer, chronic obstructive pulmonary disease, and cerebrovascular disease are established risk factors for frailty[3]. While comorbidity, frailty, and disability often coexist among older adults, these conditions represent distinct concepts. Disability refers to difficulties in performing daily living activities or mobility, which do not necessarily impact organ systems. Frailty and disability are closely related; however, it is imperative to acknowledge that they are fundamentally different conditions. Recognizing this distinction is essential for effective intervention and support[4].

FRAILTY MODELS AND SCREENING

Frailty models can be classified into three main categories: The physical frailty phenotype, the deficit accumulation model (also known as the frailty index), and mixed physical and psychosocial models. In the physical frailty model, frailty is defined by the presence of three or more of the following criteria: Exhaustion, reduced muscle strength, weight loss, low walking speed, and low physical activity[2]. The deficit accumulation model focuses on the documentation of multimorbidity and counts the total number of deficits across various areas, such as physical function and cognition[5]. This model includes various assessments that evaluate different conditions, such as clinical findings, symptoms, chronic diseases, disabilities, and abnormal laboratory tests. The number of variables assessed can vary. A higher number of deficits suggests a greater degree of frailty. Since this model relies on a computer-based database program for evaluation, it requires an application-based assessment. This approach depends on either self-reported or clinically recorded deficits, which may introduce the potential for measurement bias[6]. The Canadian research team later developed the Clinical Frailty Scale, which is more practical for daily use and has demonstrated validity. In this scale, one of nine categories is selected based on a thorough geriatric assessment of the patient's clinical status[7]. Additionally, there are other screening tools that integrate psychosocial aspects of patients with physical parameters. The Edmonton FRAIL scale, Groningen Frailty Indicator (GFI), and Tilburg Frailty Indicator (TFI) are tools used to assess frailty in the older adults, addressing physical, cognitive, and social aspects[8]. Research indicates that cognitive functions are often affected in frail individuals. The relationship between physical frailty and cognitive dysfunction is emphasized in many studies. A large-scale study involving 22952 patients showed that the prevalence of dementia in frail patients was 40%, whereas in non-frail patients, this rate was 11%[9]. Therefore, cognitive assessment should be performed on all frail patients. In 2013, criteria for diagnosing cognitive frailty were established, identifying it as the coexistence of physical frailty and mild cognitive impairment in patients who do not have a dementia diagnosis[10]. It is believed that similar pathophysiological factors exist between cognitive dysfunction and frailty. The most important factors include oxidative damage, vascular pathologies, mitochondrial dysfunction, inflammation, nutritional habits, and genetic factors[11].

Frailty makes it challenging for individuals to perform daily activities and increases their need for social support. Physical frailty is the most commonly studied subtype of frailty, and numerous studies have demonstrated its predictive value for disability, hospitalization, and mortality[2,12,13]. In recent years, social frailty has emerged as a growing area of interest in the field of geriatric research. Research has shown that a lack of psychosocial support, often found alongside physical frailty, is more closely associated with negative health outcomes[14]. Social frailty is defined as the gradual loss of ability or resources needed to engage in social activities that fulfill basic social needs[15]. Social frailty in the older population should be considered a significant public health issue due to common social challenges faced by older individuals, such as family relationships, social exclusion and isolation, and financial difficulties[14]. The shift from an active lifestyle to a more sedentary one, along with a decrease in social activities, can lead older adults to feel increasingly isolated from their communities. The recent coronavirus disease 2019 pandemic exacerbated this isolation, particularly affecting seniors and increasing social frailty. Importantly, the social support received by older individuals is closely linked to both physical and cognitive frailty. There is a bidirectional relationship between social and physical frailty. Studies have shown that limited social interaction or a reduction in social connections can lead to a decline in physical activity and physical function[16-18]. Social frailty worsens physical frailty by limiting access to resources, reducing mobility, and leading to worse nutritional status and functional decline. Physical frailty reinforces social frailty by restricting independence, increasing isolation, and diminishing involvement in social activities[19]. A lack of social fulfillment and exhaustion may be linked to depression and slower gait speed, which can lead to further reduced social engagement. Conversely, difficulties in self-management are associated with cognitive function and can result in physical weakness, often leading to more limited physical and social activity[15]. A study has shown that low gait speed and low muscle strength, which are criteria of physical frailty, are independent risk factors for social decline[20]. In this regard, interventions focused on maintaining walking capacity and muscle strength could play a crucial role in the prevention of social frailty. Therefore, physical and social frailty should be evaluated holistically. The relationship between social, physical and cognitive frailty illustrated in Figure 1.

Figure 1
Figure 1 The relationship between physical, social and cognitive frailty.
CLINICAL IMPLEMENTATION

Frailty screening is recommended to all persons older than 70 years[3]. Frailty assessment tools differ in their focus, methodology, and clinical applicability. The Edmonton FRAIL scale and TFI are multidimensional tools that evaluate physical, psychological, and social domains, making them valuable in community and outpatient settings, although they rely on subjective reporting[21]. In contrast, the Physical Frailty Phenotype (Fried Criteria) focuses solely on physical markers, such as grip strength and gait speed, and is considered the gold standard for frailty research; however, it overlooks psychosocial factors. The Clinical Frailty Scale, a rapid clinician-rated tool, categorizes frailty based on functional dependence and comorbidities, making it practical for hospitals and emergency triage[22]. A study evaluating six frailty screening tools among nearly 1200 community-dwelling older adults compared these tools with a comprehensive geriatric assessment. The screening tools included the physical frailty index, FRAIL scale, Study of Osteoporotic Fractures, and three multidimensional tools: The TFI, GFI, and Comprehensive Frailty Assessment Instrument. All six tools demonstrated high specificity, with rates ranging from 81.1% to 98.7%. Among these, the three multidimensional tools (TFI, GFI, and Comprehensive Frailty Assessment Instrument) showed higher sensitivity[23]. Although there are various screening suggestions for frailty, it is recommended to assess gait speed using the 4-meter walking test due to its high sensitivity in the primary care settings. A walking speed of < 0.8 m/second and for the timed get-up-and-go test of 10 seconds are indicative of frailty[24]. Additionally, a score of 3 or higher on the PRISMA-7 questionnaire, which assesses the patient’s social, physical, and demographic characteristics, is considered an indicator of frailty[25]. The referral of patients for further evaluation is essential, as the frailty status can be modified or even reversed because it is dynamic process. A comprehensive geriatric assessment is the preferred holistic approach to define patients’ frailty status, enabling us to manage frailty through a personalized patient-centered plan that includes the prevention of polypharmacy, nutritional support, and a physical exercise program focused on flexibility, balance, strength, and endurance.

With the advancement of technology in recent years, artificial intelligence (AI) based applications may be useful for frailty screening in different settings[26]. AI-based applications may be beneficial for screening large populations and for the development of decision-making algorithms. In patients without cognitive impairment, self-administered scales can be utilized. Moreover, AI-driven programs may be developed to provide exercise recommendations, medication reminders, and notifications to local authorities for nutritional support in cases where patients require social assistance. As an example, virtual reality has become widely used in post-stroke cognitive rehabilitation, as well as in training for balance and gait abilities[27,28]. One benefit is that advancements in information technology may alleviate social isolation, which results from reduced human interaction and promote closer connections through remote communication[28].

Frailty prevention necessitates an interdisciplinary approach, and evidence suggests that multi-component interventions delivered by a multidisciplinary team, including geriatricians, physiotherapists, nurses, and nutritionists, effectively reduce frailty and contribute to the preservation of physical function[29,30].

CONCLUSION

In conclusion, frailty is a significant geriatric syndrome encompassing physical, cognitive, and social dimensions, and it can be screened by assessing gait speed in older patients. Despite the numerous frailty guidelines published to date, there remains no consensus on its definition, screening, and diagnosis. AI-based frailty prediction models and AI-based approaches show promise in identifying frail patients and managing their care.

Footnotes

Provenance and peer review: Invited article; Externally peer reviewed.

Peer-review model: Single blind

Corresponding Author’s Membership in Professional Societies: European Geriatric Medicine Society.

Specialty type: Medicine, research and experimental

Country of origin: Türkiye

Peer-review report’s classification

Scientific Quality: Grade B, Grade C

Novelty: Grade A, Grade C

Creativity or Innovation: Grade B, Grade C

Scientific Significance: Grade B, Grade B

P-Reviewer: Oprea VD; Zhou XC S-Editor: Bai Y L-Editor: A P-Editor: Yu HG

References
1.  Thillainadesan J, Scott IA, Le Couteur DG. Frailty, a multisystem ageing syndrome. Age Ageing. 2020;49:758-763.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 23]  [Cited by in RCA: 88]  [Article Influence: 17.6]  [Reference Citation Analysis (0)]
2.  Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56:M146-M156.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 13384]  [Cited by in RCA: 15697]  [Article Influence: 654.0]  [Reference Citation Analysis (1)]
3.  Morley JE, Vellas B, van Kan GA, Anker SD, Bauer JM, Bernabei R, Cesari M, Chumlea WC, Doehner W, Evans J, Fried LP, Guralnik JM, Katz PR, Malmstrom TK, McCarter RJ, Gutierrez Robledo LM, Rockwood K, von Haehling S, Vandewoude MF, Walston J. Frailty consensus: a call to action. J Am Med Dir Assoc. 2013;14:392-397.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 2058]  [Cited by in RCA: 2697]  [Article Influence: 224.8]  [Reference Citation Analysis (0)]
4.  Fried LP, Ferrucci L, Darer J, Williamson JD, Anderson G. Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care. J Gerontol A Biol Sci Med Sci. 2004;59:255-263.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 2419]  [Cited by in RCA: 2605]  [Article Influence: 124.0]  [Reference Citation Analysis (0)]
5.  Mitnitski AB, Mogilner AJ, Rockwood K. Accumulation of deficits as a proxy measure of aging. ScientificWorldJournal. 2001;1:323-336.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 1537]  [Cited by in RCA: 1905]  [Article Influence: 79.4]  [Reference Citation Analysis (0)]
6.  Song X, Mitnitski A, Rockwood K. Prevalence and 10-year outcomes of frailty in older adults in relation to deficit accumulation. J Am Geriatr Soc. 2010;58:681-687.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 626]  [Cited by in RCA: 745]  [Article Influence: 49.7]  [Reference Citation Analysis (0)]
7.  Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, Mitnitski A. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005;173:489-495.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 4103]  [Cited by in RCA: 5709]  [Article Influence: 285.5]  [Reference Citation Analysis (0)]
8.  Ozsoy G, Ates Bulut E, Gurpinar B, Ilcin N, Isik AT. Determination of an Optimal Frailty Cutoff Score of Tilburg Frailty Indicator and Frailty Associated Factors in Community-Dwelling Turkish Older Adults. Ann Geriatr Med Res. 2021;25:294-300.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 1]  [Cited by in RCA: 7]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
9.  Armstrong JJ, Stolee P, Hirdes JP, Poss JW. Examining three frailty conceptualizations in their ability to predict negative outcomes for home-care clients. Age Ageing. 2010;39:755-758.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 102]  [Cited by in RCA: 111]  [Article Influence: 7.4]  [Reference Citation Analysis (0)]
10.  Kelaiditi E, Cesari M, Canevelli M, van Kan GA, Ousset PJ, Gillette-Guyonnet S, Ritz P, Duveau F, Soto ME, Provencher V, Nourhashemi F, Salvà A, Robert P, Andrieu S, Rolland Y, Touchon J, Fitten JL, Vellas B; IANA/IAGG. Cognitive frailty: rational and definition from an (I.A.N.A./I.A.G.G.) international consensus group. J Nutr Health Aging. 2013;17:726-734.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 610]  [Cited by in RCA: 677]  [Article Influence: 56.4]  [Reference Citation Analysis (0)]
11.  Soysal P, Stubbs B, Lucato P, Luchini C, Solmi M, Peluso R, Sergi G, Isik AT, Manzato E, Maggi S, Maggio M, Prina AM, Cosco TD, Wu YT, Veronese N. Inflammation and frailty in the elderly: A systematic review and meta-analysis. Ageing Res Rev. 2016;31:1-8.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 751]  [Cited by in RCA: 696]  [Article Influence: 77.3]  [Reference Citation Analysis (0)]
12.  Ensrud KE, Ewing SK, Taylor BC, Fink HA, Cawthon PM, Stone KL, Hillier TA, Cauley JA, Hochberg MC, Rodondi N, Tracy JK, Cummings SR. Comparison of 2 frailty indexes for prediction of falls, disability, fractures, and death in older women. Arch Intern Med. 2008;168:382-389.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 624]  [Cited by in RCA: 654]  [Article Influence: 38.5]  [Reference Citation Analysis (0)]
13.  Yamada M, Arai H. Predictive Value of Frailty Scores for Healthy Life Expectancy in Community-Dwelling Older Japanese Adults. J Am Med Dir Assoc. 2015;16:1002.e7-1002.11.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 89]  [Cited by in RCA: 145]  [Article Influence: 14.5]  [Reference Citation Analysis (0)]
14.  Yamada M, Arai H. Social Frailty Predicts Incident Disability and Mortality Among Community-Dwelling Japanese Older Adults. J Am Med Dir Assoc. 2018;19:1099-1103.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 58]  [Cited by in RCA: 115]  [Article Influence: 19.2]  [Reference Citation Analysis (0)]
15.  Quach LT, Primack J, Bozzay M, Madrigal C, Erqou S, Rudolph JL. The Intersection of Physical and Social Frailty in Older Adults. R I Med J (2013). 2021;104:16-19.  [PubMed]  [DOI]
16.  Buchman AS, Boyle PA, Wilson RS, Fleischman DA, Leurgans S, Bennett DA. Association between late-life social activity and motor decline in older adults. Arch Intern Med. 2009;169:1139-1146.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 207]  [Cited by in RCA: 184]  [Article Influence: 11.5]  [Reference Citation Analysis (0)]
17.  Clarke CL, Sniehotta FF, Vadiveloo T, Argo IS, Donnan PT, McMurdo MET, Witham MD. Factors associated with change in objectively measured physical activity in older people - data from the physical activity cohort Scotland study. BMC Geriatr. 2017;17:180.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 16]  [Cited by in RCA: 23]  [Article Influence: 2.9]  [Reference Citation Analysis (0)]
18.  Yi X, Pope Z, Gao Z, Wang S, Pan F, Yan J, Liu M, Wu P, Xu J, Wang R. Associations between individual and environmental factors and habitual physical activity among older Chinese adults: A social-ecological perspective. J Sport Health Sci. 2016;5:315-321.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 24]  [Cited by in RCA: 29]  [Article Influence: 3.2]  [Reference Citation Analysis (0)]
19.  Yamada M, Arai H. Understanding social frailty. Arch Gerontol Geriatr. 2023;115:105123.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 15]  [Reference Citation Analysis (0)]
20.  Nagai K, Tamaki K, Kusunoki H, Wada Y, Tsuji S, Itoh M, Sano K, Amano M, Hayashitani S, Yokoyama R, Yonezawa R, Kamitani T, Shinmura K. Physical frailty predicts the development of social frailty: a prospective cohort study. BMC Geriatr. 2020;20:403.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 14]  [Cited by in RCA: 57]  [Article Influence: 11.4]  [Reference Citation Analysis (0)]
21.  Gobbens RJ, Schols JM, van Assen MA. Exploring the efficiency of the Tilburg Frailty Indicator: a review. Clin Interv Aging. 2017;12:1739-1752.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 45]  [Cited by in RCA: 72]  [Article Influence: 9.0]  [Reference Citation Analysis (0)]
22.  Dent E, Kowal P, Hoogendijk EO. Frailty measurement in research and clinical practice: A review. Eur J Intern Med. 2016;31:3-10.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 639]  [Cited by in RCA: 820]  [Article Influence: 91.1]  [Reference Citation Analysis (0)]
23.  Si H, Jin Y, Qiao X, Tian X, Liu X, Wang C. Comparison of 6 frailty screening tools in diagnostic properties among Chinese community-dwelling older people. Geriatr Nurs. 2021;42:276-282.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 6]  [Cited by in RCA: 20]  [Article Influence: 4.0]  [Reference Citation Analysis (0)]
24.  Clegg A, Rogers L, Young J. Diagnostic test accuracy of simple instruments for identifying frailty in community-dwelling older people: a systematic review. Age Ageing. 2015;44:148-152.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 216]  [Cited by in RCA: 269]  [Article Influence: 26.9]  [Reference Citation Analysis (0)]
25.  Turner G, Clegg A; British Geriatrics Society;  Age UK;  Royal College of General Practioners. Best practice guidelines for the management of frailty: a British Geriatrics Society, Age UK and Royal College of General Practitioners report. Age Ageing. 2014;43:744-747.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 327]  [Cited by in RCA: 426]  [Article Influence: 38.7]  [Reference Citation Analysis (0)]
26.  Bai C, Mardini MT. Advances of artificial intelligence in predicting frailty using real-world data: A scoping review. Ageing Res Rev. 2024;101:102529.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 2]  [Reference Citation Analysis (0)]
27.  Pacheco TBF, Oliveira Rego IA, Campos TF, Cavalcanti FADC. Brain activity during a lower limb functional task in a real and virtual environment: A comparative study. NeuroRehabilitation. 2017;40:391-400.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 10]  [Cited by in RCA: 10]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
28.  Montana JI, Tuena C, Serino S, Cipresso P, Riva G. Neurorehabilitation of Spatial Memory Using Virtual Environments: A Systematic Review. J Clin Med. 2019;8:1516.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 25]  [Cited by in RCA: 38]  [Article Influence: 6.3]  [Reference Citation Analysis (0)]
29.  Cameron ID, Fairhall N, Langron C, Lockwood K, Monaghan N, Aggar C, Sherrington C, Lord SR, Kurrle SE. A multifactorial interdisciplinary intervention reduces frailty in older people: randomized trial. BMC Med. 2013;11:65.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 242]  [Cited by in RCA: 293]  [Article Influence: 24.4]  [Reference Citation Analysis (0)]
30.  Fairhall N, Sherrington C, Cameron ID, Kurrle SE, Lord SR, Lockwood K, Herbert RD. A multifactorial intervention for frail older people is more than twice as effective among those who are compliant: complier average causal effect analysis of a randomised trial. J Physiother. 2017;63:40-44.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 15]  [Cited by in RCA: 27]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]