Substantial Falls Increase Concern About Falling: a 12-Month Longitudinal Cohort Study Running title: Understanding the Development of Concerns About Falling in Older Adults

Substantial Falls Increase Concern About Falling: a 12-Month Longitudinal Cohort Study Running title: Understanding the Development of Concerns About Falling in Older Adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Substantial Falls Increase Concern About Falling: a 12-Month Longitudinal Cohort Study Running title: Understanding the Development of Concerns About Falling in Older Adults Mira Eileen Unverzagt, Kimberley S. Schooten, Christopher McCrum, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7830071/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background: Concern about falling (CaF) is common in older adults and predict falls, disability and loss of independence. However, it is unclear whether CaF is relatively stable or whether new falls contribute to increased CaF over time. The purpose is to examine whether experiencing falls predicts CaF, independent of other physical, cognitive, and psychological characteristics. Methods: We analysed data from 489 community-living older adults aged 70-90 years. CaF was measured using the Falls Efficacy Scale-International (FES-I) at baseline and 12-months. Falls and injuries were prospectively monitored. Baseline predictors included physical and cognitive performance, mood, personality traits, and demographic variables. Single predictor variable and multivariable linear regression analyses examined predictors of CaF at follow-up, adjusting for baseline CaF. Results: Many physical, cognitive and mood variables were associated with CaF in the adjusted single predictor analyses. Experiencing one injurious fall or multiple falls during follow-up was a significant predictor of CaF (β = 1.55, p = 0.007). Other independent predictors included baseline CaF (β = 0.70, p < 0.001), slower Timed Up and Go performance (β = 0.63, p < 0.001), lower conscientiousness (β = –0.11, p = 0.016), and older age (β = 0.17, p = 0.01). Conclusion: Our findings suggest that while CaF exhibits some stability, it can be significantly elevated following injurious or multiple falls. Targeted assessment and support following injurious or recurrent falls may help prevent persistent concern, particularly in people with reduced mobility or lower psychological resilience. These findings highlight the importance of post-fall review in clinical care. HIGHLIGHTS Baseline and 12-month follow-up Concern about Falling (CaF) were strongly associated, indicating relative stability. Injurious or multiple falls over 12 months significantly increased CaF. Slower mobility, older age, and lower conscientiousness were additional independent predictors of increased CaF. Clinical fall management should include follow-up of CaF to better guide support and intervention. INTRODUCTION Concern about falling (CaF) is common in community-living older adults ( 1 – 3 ) and is associated with reduced confidence, restricted activity, increased risk of falls and functional decline. It affects both fallers and non-fallers ( 4 ), and is linked to multiple risk factors. These include modifiable factors that can be improved through targeted interventions or lifestyle changes ( 5 ), such as impaired gait and balance, and non-modifiable factors like female sex, older age and a history of falling ( 6 ). Up to half of older people who have experienced a fall report concern, suggesting that falling may trigger changes in perceptions and confidence ( 4 ). For some older people, CAF may represent a realistic appraisal of their risk of falls ( 7 ), but for others, CaF may contribute to further falls by increasing anxiety, altering gait and leading individuals to limit or avoid physical activities that are essential for maintaining strength, balance and mobility ( 4 , 5 , 8 ). Based on these findings, a bidirectional relationship between falls and CaF has been proposed, in which concern may act as both a cause and a consequence ( 1 , 2 , 9 – 11 ). While the role of CaF as a risk factor for falls is supported by systematic review evidence ( 8 ), the extent to which falls contribute to sustained elevated CaF is less well understood. Some studies suggest a short-term, transient increase in CaF following a fall ( 1 , 12 ), while others suggest that CaF can persist and worsen even in the absence of further falls ( 13 ). It also remains unclear whether individual characteristics, such as age, mobility, mood, cognitive function and personality, modify the relationship between falls and CaF ( 5 , 6 ). Previous research on the relationship between falls and CaF has predominantly relied on cross-sectional designs and retrospective self-reports, both of which are susceptible to bias and inaccuracies. With the exception of one study ( 12 ), there is a notable absence of investigations employing repeated measures to explore this relationship. In contrast, prospective longitudinal designs enable continuous monitoring of falls, allow for tracking changes in CaF over time, and facilitate adjustment for baseline levels. This methodological approach provides a clearer understanding of whether CaF is relatively stable in older age or a dynamic construct that may be influenced by incident falls, changes in health status, or psychological factors. To address this research gap, we conducted a longitudinal study in a representative sample of 489 community-living older people to determine: (i) whether experiencing certain types of falls independently predicted increased CaF over 12 months; (ii) whether physical, cognitive and psychological factors also predicted change in CaF; and (iii) the extent to which CaF is stable over time. We hypothesised that falls, reduced mobility, poorer cognitive function and certain psychological traits would predict increased CaF over time. METHODS Study design and participants This longitudinal cohort study used data from the Balance and Falls sub-study of the Sydney Memory and Aging Study (MAS) ( 14 ). Of the 500 participants, 489 had complete data for the variables of interest and were included in this analysis (Supplementary Figure S1). No a priori power calculation was conducted, as the parent study determined the sample size. Participants were community-living individuals aged 70–90 years without dementia, residing in two electoral divisions of Sydney, Australia ( 14 ). Individuals with neurodegenerative or major psychiatric conditions were excluded. All participants provided written informed consent, and ethical approvals were obtained from the Ethics Committees of the University of New South Wales and the South Eastern Sydney and Illawarra Area Health Service ( 14 ). Study procedures Participants completed a baseline face-to-face assessment at a research facility or in their homes. The assessment session typically took three to four hours, conducted across one or two appointments and included a medical interview, questionnaires, and neuropsychological and physical performance assessments. Primary outcome CaF at baseline and the 12-month follow-up was assessed using the Falls Efficacy Scale International (FES-I), a 16-item questionnaire with excellent psychometric properties (Cronbach's alpha = 0.97 and test-retest reliability = 0.94) ( 9 ). Participants rated their CaF during 16 daily life activities, such as cleaning the house or walking in the neighbourhood, using a 4-point Likert Scale (1 = "not concerned at all" and 4 = "very concerned"), leading to a total score range of 16 to 64 ( 7 ). Baseline predictor variables Balance was assessed using established tests. Physiological fall risk was assessed using the Physiological Profile Assessment score ( 15 , 16 ). Controlled leaning balance during standing was assessed using the coordinated stability test ( 15 , 16 ). Near tandem balance was measured by assessing how long participants could maintain balance while standing with one foot slightly in front of and to the side of the other (maximum 30 seconds) ( 15 , 16 ). Functional mobility and strength were assessed. The timed up-and-go (TUG) evaluated mobility by timing the participants standing up from a chair, walking three meters, turning, returning, and sitting down, with longer times indicating greater impairment ( 17 – 19 ). Gait speed was measured as the time (in seconds) to walk 3m, turn and walk back at a normal pace. The five-times sit-to-stand test assessed lower-limb strength and endurance, requiring participants to rise from a chair five times as quickly as possible without using their arms ( 19 , 20 ). Cognitive function was evaluated using several complementary assessments: global cognitive impairment was assessed with the Standardised Mini-Mental State Examination ( 21 ), processing speed/ working memory was assessed with the Trail Making test (part A) ( 22 ), executive function was assessed with the Trail Making test (part B minus part A) ( 22 ), verbal fluency with the animal naming task; ( 23 ), and symbol-number matching was assessed with the Digit Symbol Substitution Test ( 24 ). Psychological assessments encompassed measures of depression, anxiety, and personality traits. Depressive symptoms were assessed with the 15-item Geriatric Depression Scale ( 25 ), and anxiety was assessed with the Goldberg Anxiety Scale ( 26 ). Personality traits were derived from the Neuroticism, Extraversion, Openness Personality Inventory (Likert scale:1–5) and subscores for neuroticism (emotional instability and a tendency toward negative affect) ( 27 – 29 ), openness (imagination and curiosity) ( 27 – 29 ), and conscientiousness (organizational skills, responsibility, and goal-directed behaviour) ( 27 – 29 ) were obtained. Participants were also asked how many falls they had experienced in the past year to document their fall history. Falls during follow-up Falls and fall-related injuries were monitored prospectively over 12 months using daily fall calendars returned monthly, with telephone follow-up for missing data, in line with international guidelines ( 30 ). A fall was defined as “an unexpected event in which the participants came to rest on the ground, floor, or lower level” ( 30 ). From this, four fall variables were derived: ( 1 ) falls: 1 or more falls, ( 2 ) multiple falls: 2 or more falls, ( 3 ) injurious falls: 1 or more falls where participants reported suffering an injury, including cuts and abrasions, bruising and bone fractures, and ( 4 ) substantial falls: 2 or more falls without injury or 1 or more injurious falls. The substantial fall variable was derived as it has been shown to capture falls with psychological or clinical impact (31, 32). Statistical analysis Missing item-level data for the 12-month FES-I assessment were imputed according to the FES-I scoring protocol (31, 33). For participants missing a complete 12-month FESI assessment, the mean of available 3-, 6-, and 9-month FESI-I assessment scores was used if two or more time points were available. Predictor variable missingness was addressed through multiple imputations, supported by Little’s MCAR test, resulting in five imputed datasets. Initial linear regression analyses assessed each predictor adjusted for baseline FES-I, with the cognitive variables additionally adjusted for level of education. A principal component analysis was performed to categorise the baseline predictor variables into domains, i.e. physical, psychological, cognitive, and demographics/anthropometrics (Table 2 ; Supplementary Figure S2). The variables from each domain with the strongest association with 12-month FES-I scores in the single predictor analyses, along with the most strongly associated fall variable, were then selected for inclusion in a multivariable linear regression model (provided p < 0.05). This regression was conducted using backward elimination to identify independent predictors of CaF at 12 months, while adjusting for baseline FES-I. Residuals were checked to confirm normality. All analyses were conducted using IBM SPSS Statistics version 27 (SPSS Inc.). RESULTS Participant characteristics are presented in Table 1 (Table 1 ). The comprised 489 participants had a mean age of 77.9 (SD = 4.6) years, of whom 54.6% were female. One hundred and sixty-eight participants (34.4%) reported moderate CaF at baseline (FES-I scores ≥ 23). During follow-up, 213 participants (43.6%) reported at least one fall, 94 (19.2%) reported two or more falls, 141 (28.8%) reported at least one injurious fall, and 166 (34.0%) reported a substantial fall. Table 1 Participant characteristics at baseline Variable Mean (SD) or Median [IQR] or n (%) Demographics Age (years) 77.9 (4.6) Female (n) 267 (54.6%) Living alone (n) 213 (43.6%) Concern About Falling Baseline FES-I (score) 20.0 [7.0] Fall history ≥ 1 Falls past year (n) 151 (30.8%) Cognition SMMSE (score) 28.0 [2.0] Functional Status WHODAS (total score) 16.0 [9.0] Note: SMMSE = Standardised Mini-Mental State Examination; WHODAS = World Health Organization Disability Assessment Schedule; ≥1 fall history = at least one fall in the year prior to baseline Single predictor analysis CaF at 12 months was significantly associated with CaF at baseline (r = 0.69, 95% confidence interval: 0.64 to 0.73). In the regression models examining single predictors while adjusting for baseline CaF, several factors were significantly associated with CaF at the 12-month follow-up (Table 2 ). These included older age, experiencing substantial falls during follow-up, balance impairments (higher physiological fall risk and shorter near-tandem stance time) and slower performance in the Timed Up and Go, 6-meter walk and five-times sit-to-stand mobility tests. In addition, cognitive factors (slower processing speed, lower Digit Symbol scores, and reduced verbal fluency) and psychological traits (higher depressive symptoms, greater neuroticism and lower conscientiousness) were associated with CaF at this time-point. Some notable variables were not significantly associated with CaF: SMMSE, executive function (Trails B minus A scores), anxiety (GAS scores), sex, BMI and falls prior to baseline. Table 2 Regression models examining single predictors for CaF at 12-month follow-up while adjusting for baseline CaF # Predictor variables Mean (SD) or Median [IQR] or n (%) B SE 95% CI Sig. Demographics BMI (kg/m 2 ) 27.5 (5.3) 0.06 0.05 -0.04, 0.17 0.251 Age (yrs) 77.9 (4.6) 0.25 0.06 0.13, 0.37 < 0.001 Female (n) 267 (54.6%) 0.23 0.58 -0.9, 1.37 0.687 ≥ 1 Falls past year (n) 151 (30.8%) 0.23 0.35 -0.45, 0.92 0.506 Balance PPA (score) 0.89 (0.94) 0.6 0.31 -0.01, 1.20 0.054 Coordinated Stability (errors) 13.5 [21.2] 0.02 0.02 -0.02, 0.06 0.356 Near tandem balance (s) 10.0 [1.0] -0.35 0.17 –0.68, -0.03 0.034 Cognition ~ SMMSE (score) 28.0 [2.0] -0.06 0.19 -0.43, 0.32 0.763 Trails A (s) 42.0 [18.0] 0.05 0.02 0.01, 0.09 0.01 Trails B-A (s) 60.0 [50.0] -0.004 0.01 0.02, 0.01 0.574 Digit symbol (score) 49.0 (12.1) -0.07 0.02 -0.12, -0.02 0.006 Verbal fluency (score) 16.2 (4.4) -0.14 0.07 –0.27, -0.01 0.033 Functional mobility TUG (s) 9.2 [3.0] 0.68 0.11 0.48, 0.89 < 0.001 6m walk (s) 8.0 [3.0] 0.29 0.1 0.09, 0.50 0.005 Sit to stand (s) 16.0 [6.0] 0.28 0.06 0.16, 0.39 < 0.001 Mood GDS (score) 2.0 [2.0] 0.43 0.15 0.13, 0.73 0.005 GAS (score) 0.0 [1.0] 0.17 0.2 -0.22, 0.56 0.396 Personality Neuroticism (score) 14.5 (6.7) 0.1 0.04 0.01, 0.18 0.029 Openness (score) 26.5 (5.9) -0.02 0.05 -0.11, 0.08 0.705 Conscientiousness (score) 34.0 (5.9) -0.13 0.05 -0.23, -0.04 0.006 Falls during follow-up One or more falls (n) 213 (43.6%) 1.04 0.11 -0.09, 2.17 0.072 Two or more falls (n) 94 (19.2%) 1.12 0.3 -0.31, 2.54 0.125 Injurious falls (n) 141 (28.8%) 0.98 0.26 -0.26, 2.23 0.123 Substantial falls (n) 166 (34.0%) 1.36 0.24 0.17, 2.55 0.025 # Analyses adjusted for baseline FES-I scores; ~ additionally adjusted for years of education Notes: B = Unstandardised regression coefficients; SMMSE = Standardised Mini-Mental State Examination; Substantial falls = at least one injurious fall or two or more falls; TUAG = Timed Up-and-Go; GDS = Geriatric Depression Scale; GAS = Geriatric Anxiety Scale. Associations with p < .05 are bolded. Multivariable analysis In the multivariable model (Table 3 ), substantial falls, slower TUG times, lower conscientiousness and older age emerged as independent and significant predictors of 12-month CaF, after adjusting for baseline CaF. This model explained 51% of the variance in 12-month CaF (adjusted R² of 0.508). All variance inflation factors were < 2, indicating no multicollinearity and model diagnostics supported the assumptions of linear regression (Supplementary Tables S1 and 2, Figures S3-5). Table 3 Multivariable associations with CaF at 12-month follow-up B SE 95% CI Sig. Baseline FES-I (score) 0.70 0.05 0.61, 0.80 0.000 Substantial Falls (yes = 1/no = 0) 1.55 0.58 0.42, 2.67 0.007 TUG (s) 0.63 0.1 0.43, 0.84 < 0.001 Conscientiousness (score) -0.11 0.05 -0.20, -0.02 0.016 Age (yrs) 0.17 0.06 0.05, 0.29 0.005 (Constant) -8.14 4.94 -17.83, 1.55 0.100 Note: TUG = Timed Up-and-Go; Substantial Falls = at least one injurious fall or two or more falls DISCUSSION Using a longitudinal study design, we found many physical, cognitive and mood variables predicted 12-month CaF in single predictor analyses, and of these, baseline CaF, slower TUG, lower conscientiousness, older age and substantial falls during follow-up were identified as independent predictors of CaF. These results extend previous cross-sectional findings by showing that, even after accounting for baseline concern, certain physical, cognitive and psychological characteristics are linked to a measurable and clinically meaningful increase in CaF over time. This indicates that while CaF is relatively stable in older age, it can be significantly elevated following substantial falls, highlighting the importance of ongoing monitoring in clinical and community settings. The identification of substantial falls as an independent predictor of increased CaF suggests that injurious or repeated falls may trigger a psychological shift that extends beyond what is captured by baseline function or personality (2, 34). Substantial falls were associated with a 1.55-point increase in CaF over 12 months, exceeding the validated one-point FES-I threshold indicative of heightened fall risk, highlighting the significant psychological impact of such falls ( 8 ). This finding, however, contrasts with a previous study by Weijer et al. ( 12 ), who found that CaF following a fall was transient and did not increase with subsequent falls. Differences in baseline concern, age, sex distribution, and cultural or healthcare contexts may account for these contrasting findings (35). It is also possible that substantial falls, encompassing an injurious fall or multiple falls, may have captured clinically meaningful events that contribute to a lasting shift in perceived vulnerability, rather than a short-term increase in CaF. The final multivariable model also included poor mobility, lower conscientiousness, older age, and baseline CaF as independent predictors of CaF at 12 months. The association with poor mobility, as indicated by slow TUG completion times, is consistent with previous work demonstrating poor physical function increases CaF and perceived fall risk ( 5 , 17 – 19 ). Lower conscientiousness may reflect maladaptive coping, reduced self-efficacy and heightened health-related anxiety (26, 36), and given its established connection to frailty and functional decline, may represent a key psychological marker of vulnerability to persistent CaF (37). The independent effect of age on CaF may reflect age-related declines in mobility not captured by the TUG, as well as greater cumulative exposure to falls and fear-based learning (38, 39). Finally, baseline CaF was the strongest predictor of CaF at one year, reinforcing its relative stability over time in older people, and the role of persistent cognitive-emotional patterns in shaping perceptions of vulnerability ( 1 , 2 , 4 ). Collectively, these findings indicate that CaF is shaped by a combination of physical, emotional and personality-related factors. Several factors significant in our single predictor variable analyses, such as neuroticism, depressive symptoms and cognitive slowing, were excluded from the final model, likely due to shared variance with stronger predictors. Higher neuroticism, characterised by heightened emotional reactivity and sensitivity to perceived threat ( 12 , 26 ), and reduced executive function, attention, and processing speed have been shown to influence concern about falling (CaF) by disrupting risk appraisal and gait control (40–42). In parallel, depressive symptoms may intensify perceived vulnerability and promote avoidance behaviours ( 5 , 6 ). The exclusion of these factors from the multivariable model suggests their impact on CaF may be mediated through mobility limitations or maladaptive coping styles. Strengths of the study include the inclusion of a population-based cohort, longitudinal design, validated outcome measures and comprehensive assessment across physical, cognitive and psychological domains. The use of multiple imputations further minimised bias due to missing data and strengthened the validity of the analyses. Several limitations should, however, also be considered when interpreting the findings. First, no a priori power calculation was performed, which may limit the ability to detect smaller effects. Second, the limited temporal resolution of our data means we cannot determine the exact timing of changes in CaF relative to falls. Finally, although the FES-I is a widely applied and validated instrument for assessing CaF, all self-reported measures are subject to the potential for bias by cognitive status, mood, or cultural context, and repeated questioning may cause heightened concern (43). This study adds to the growing recognition of CaF as a multifactorial construct aligning with the biopsychosocial model of ageing, which emphasises the interplay between biological, psychological and social factors in shaping health and quality of life in older adults ( 4 ). In this context, CaF appears to arise not only from new fall events or personality traits, but also as a dynamic outcome influenced by changes in physical function. Clinically, our findings support routine CaF screening after falls, particularly those that are injurious or recurrent, to identify those at risk of escalating CaF and functional decline (44). Intervention strategies could be tailored accordingly, drawing on integrated approaches that address both physical and psychological contributors. For instance, moderate to high challenging balance exercises aimed at reducing fall risk (45) may prove most effective when combined with cognitive behavioural techniques designed to target CaF (46, 47). Further work is required to explore the benefits of personalising fall prevention programs based on psychological profiles, such as levels of conscientiousness ( 27 , 28 ), and determine whether people with lower conscientiousness respond better to structured support strategies involving routine check-ins and caregiver involvement ( 27 , 29 ). In parallel, psychological interventions that address maladaptive coping styles could help mitigate excessive or persistent CaF (48). Finally, the longitudinal tracking of modifiable risk factors such as mood and mobility may reveal critical windows for early intervention and enable more responsive, person-centred care. In summary, we found that CaF is relatively stable over one year. Concerns about falling are significantly associated with poorer functional mobility, lower conscientiousness and older age, and can be significantly elevated following substantial falls. These findings highlight the complex and multifactorial nature of CaF and reinforce its role as both a consequence of falls and a contributor to activity restriction and loss of independence. Screening for CaF should be embedded in clinical practice, not only following falls, but also in those with declining mobility or psychological risk profiles to interrupt the cycle of fear and decline before it intensifies. Recognising CaF as both a modifiable risk factor and a clinical red flag offers an opportunity to shift fall prevention from reactive management to proactive care. Declarations Acknowledgements We thank the study participants and staff involved in collection and management of the data used in this manuscript. Ethics, Consent to Participate, and Consent to Publish declaration: All participants provided written informed consent to participate and for their information to be saved and published anonymously, and ethical approvals were obtained from the Ethics Committees of the University of New South Wales and the South Eastern Sydney and Illawarra Area Health Service (14). Procedures followed the principles of the Declaration of Helsinki and were in line with the Medical Research Involving Human Subjects Act (WMO) (49). Competing interests The physiological profile assessment (NeuRA FallScreen) is commercially available through Neuroscience Research Australia. Data availability De-identified data that support the findings of this study are available from the corresponding author on reasonable request. Access will be provided for research purposes in accordance with institutional and ethical requirements. Contributions Stephen R. Lord, Kim Delbaere and Kim S. van Schooten devised the research question. Mira E. Unverzagt conducted the data analysis and drafted the manuscript. All authors provided critical feedback on the analysis and draft. Sponsor’s Role The funders of the study had no role in the study design, data collection, data analysis, data interpretation, writing of the report, decision to publish, or preparation of the manuscript. Funding Declaration The participants in this study were drawn from the Memory and Ageing Study of the Brain and Ageing Program, School of Psychiatry, University of New South Wales, funded by a National Health and Medical Research Council grant (No 350833), and NHMRC Project Grant 400941. Stephen R. Lord and Kim Delbaere are funded by NHMRC Investigator grants. References Lavedán A, Viladrosa M, Jürschik P, Botigué T, Nuín C, Masot O et al. vol 13, e0194967,. Fear of falling in community-dwelling older adults: A cause of falls, a consequence, or both? (2018). Plos One. 2018;13(5). Friedman SM, Munoz B, West SK, Rubin GS, Fried LP. Falls and fear of falling: which comes first? A longitudinal prediction model suggests strategies for primary and secondary prevention. J Am Geriatr Soc. 2002;50(8):1329–35. van Schooten KS, Taylor ME, Close JCT, Davis JC, Paul SS, Canning CG, et al. Sensorimotor, Cognitive, and Affective Functions Contribute to the Prediction of Falls in Old Age and Neurologic Disorders: An Observational Study. Arch Phys Med Rehabil. 2021;102(5):874–80. Legters K. Fear of falling. Phys Ther. 2002;82(3):264–72. Huang WNW, Mao HF, Lee HM, Chi WC. Association between Fear of Falling and Seven Performance-Based Physical Function Measures in Older Adults: A Cross-Sectional Study. Healthcare. 2022;10(6). Scheffer AC, Schuurmans MJ, van Dijk N, van der Hooft T, de Rooij SE. Fear of falling: measurement strategy, prevalence, risk factors and consequences among older persons. Age Ageing. 2008;37(1):19–24. Delbaere K, Close JC, Mikolaizak AS, Sachdev PS, Brodaty H, Lord SR. The Falls Efficacy Scale International (FES-I). A comprehensive longitudinal validation study. Age Ageing. 2010;39(2):210–6. Ellmers TJ, Ventre JP, Freiberger E, Hauer K, Hogan DB, Lim ML, et al. Does concern about falling predict future falls in older adults? A systematic review and meta-analysis. Age Ageing. 2025;54(4):afaf089. Yardley L, Beyer N, Hauer K, Kempen G, Piot-Ziegler C, Todd C. Development and initial validation of the Falls Efficacy Scale-International (FES-I). Age Ageing. 2005;34(6):614–9. Kuo C-T, Chen D-R, Chen Y-M, Chen P-Y. Validation of the short falls efficacy scale-international for Taiwanese community-dwelling older adults: Associations with fall history, physical frailty, and quality of life. Geriatr Nurs. 2021;42(5):1012–8. Delbaere K, Close JCT, Mikolaizak AS, Sachdev PS, Brodaty H, Lord SR. The Falls Efficacy Scale International (FES-I). A comprehensive longitudinal validation study. Age Ageing. 2010;39(2):210–6. Weijer RH, Hoozemans MJ, Meijer OG, van Dieën JH, Pijnappels M. The short-and long-term temporal relation between falls and concern about falling in older adults without a recent history of falling. PLoS ONE. 2021;16(7):e0253374. Howland J, Peterson EW, Levin WC, Fried L, Pordon D, Bak S. Fear of falling among the community-dwelling elderly. J Aging Health. 1993;5(2):229–43. Sachdev PS, Brodaty H, Reppermund S, Kochan NA, Trollor JN, Draper B, et al. The Sydney Memory and Ageing Study (MAS): methodology and baseline medical and neuropsychiatric characteristics of an elderly epidemiological non-demented cohort of Australians aged 70–90 years. Int Psychogeriatr. 2010;22(8):1248–64. Wang T, Yang L, Li X, Su P, Meng D. Characteristics of static balance performance in 4-stage balance test in the healthy older adults. Int J Neurosci. 2024:1–7. Lord SR, Menz HB, Tiedemann A. A physiological profile approach to falls risk assessment and prevention. Phys Ther. 2003;83(3):237–52. Podsiadlo D, Richardson S. The timed Up & Go: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39(2):142–8. Schoene D, Wu SM, Mikolaizak AS, Menant JC, Smith ST, Delbaere K, et al. Discriminative ability and predictive validity of the timed up and go test in identifying older people who fall: systematic review and meta-analysis. J Am Geriatr Soc. 2013;61(2):202–8. Alosaimi RM, Almegbas NR, Almutairi GR, Alqahtani MA, Batook SG, Alfageh IA, et al. The Five Times Sit-to-Stand Test is associated with both history of falls and fear of falling among community adults aged 50 years and older. Ir J Med Sci. 2023;192(5):2533–40. Lord SR, Murray SM, Chapman K, Munro B, Tiedemann A. Sit-to-Stand Performance Depends on Sensation, Speed, Balance, and Psychological Status in Addition to Strength in Older People. Journals Gerontology: Ser A. 2002;57(8):M539–43. Molloy DW, Standish TI. A guide to the standardized Mini-Mental State Examination. Int Psychogeriatr. 1997;9(Suppl 1):87–94. discussion 143 – 50. Tombaugh TN. Trail Making Test A and B: normative data stratified by age and education. Arch Clin Neuropsychol. 2004;19(2):203–14. Bloomberg M, Brocklebank L, Hamer M, Steptoe A. Joint associations of physical activity and sleep duration with cognitive ageing: longitudinal analysis of an English cohort study. Lancet Healthy Longev. 2023;4(7):e345–53. Jaeger J. Digit Symbol Substitution Test: The Case for Sensitivity Over Specificity in Neuropsychological Testing. J Clin Psychopharmacol. 2018;38(5):513–9. Stone-Bury L, Granier K, Segal D. Geriatric Depression Scale. 2019. Kotov R, Gámez W, Schmidt F, Watson D. Linking Big Personality Traits to Anxiety, Depressive, and Substance Use Disorders: A Meta-Analysis. Psychol Bull. 2010;136:768–821. Roberts BW, Jackson JJ, Fayard JV, Edmonds G, Meints J. Conscientiousness. Handbook of individual differences in social behavior. The Guilford Press; 2009. pp. 369–81. Bagby RM, Costa PT Jr., Widiger TA, Ryder AG, Marshall M. DSM-IV personality disorders and the Five-Factor Model of personality: a multi-method examination of domain- and facet-level predictions. Eur J Pers. 2005;19(4):307–24. Samuel DB, Widiger TA. A meta-analytic review of the relationships between the five-factor model and DSM-IV-TR personality disorders: a facet level analysis. Clin Psychol Rev. 2008;28(8):1326–42. Lamb SE, Jørstad-Stein EC, Hauer K, Becker C. Development of a common outcome data set for fall injury prevention trials: the Prevention of Falls Network Europe consensus. J Am Geriatr Soc. 2005;53(9):1618–22. Falls efficacy scale - International. The Universit of Manchester [Available from: https://sites.manchester.ac.uk/fes-i/ Additional Declarations Competing interest reported. The physiological profile assessment (NeuRA FallScreen) is commercially available through Neuroscience Research Australia Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 05 Dec, 2025 Reviewers agreed at journal 12 Nov, 2025 Reviewers agreed at journal 27 Oct, 2025 Reviewers invited by journal 27 Oct, 2025 Editor assigned by journal 26 Oct, 2025 Editor invited by journal 25 Oct, 2025 Submission checks completed at journal 23 Oct, 2025 First submitted to journal 23 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7830071","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":539820622,"identity":"0082ecf7-577e-45f9-a17d-2d7ed1123686","order_by":0,"name":"Mira Eileen Unverzagt","email":"","orcid":"","institution":"Maastricht University","correspondingAuthor":false,"prefix":"","firstName":"Mira","middleName":"Eileen","lastName":"Unverzagt","suffix":""},{"id":539820623,"identity":"4704a5e4-5ba5-40fb-a479-2cd01d9c4b97","order_by":1,"name":"Kimberley S. Schooten","email":"","orcid":"","institution":"Neuroscience Research Australia","correspondingAuthor":false,"prefix":"","firstName":"Kimberley","middleName":"S.","lastName":"Schooten","suffix":""},{"id":539820625,"identity":"be232660-8c83-4c99-94ef-0489f1cf5915","order_by":2,"name":"Christopher McCrum","email":"","orcid":"","institution":"Maastricht University","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"McCrum","suffix":""},{"id":539820627,"identity":"5ec42ece-74ba-4f59-aa04-4639c035425a","order_by":3,"name":"Jacqueline C. T. Close","email":"","orcid":"","institution":"Neuroscience Research Australia","correspondingAuthor":false,"prefix":"","firstName":"Jacqueline","middleName":"C. T.","lastName":"Close","suffix":""},{"id":539820628,"identity":"56262c14-af3b-4ce3-b36a-71412499367c","order_by":4,"name":"Henry Brodaty","email":"","orcid":"","institution":"UNSW Sydney","correspondingAuthor":false,"prefix":"","firstName":"Henry","middleName":"","lastName":"Brodaty","suffix":""},{"id":539820629,"identity":"a25f7607-9b15-40f0-b7fb-dbdde14995a2","order_by":5,"name":"Perminder S. Sachdev","email":"","orcid":"","institution":"UNSW Sydney","correspondingAuthor":false,"prefix":"","firstName":"Perminder","middleName":"S.","lastName":"Sachdev","suffix":""},{"id":539820630,"identity":"a959af5c-b26a-47f7-8a34-4e34df67d153","order_by":6,"name":"Stephen R. Lord","email":"","orcid":"","institution":"UNSW Sydney","correspondingAuthor":false,"prefix":"","firstName":"Stephen","middleName":"R.","lastName":"Lord","suffix":""},{"id":539820631,"identity":"a8f32111-ce5b-45c3-b7cd-df57d12eadf5","order_by":7,"name":"Kim Delbaere","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYBACCQYGA4aHDSAm8wGYoAFhLYlgLWwJJGvhgavEr0WygXnjg8QddnLm7T3fHnxsuyfPwN68TYKh5jBOLdIMbMUGiWeSjWXOnN1uOLOt2LCB51iZBMMx3FrkGHjMJBLbmBNnSORuk+ZtS2BskMgxk2Bgw6vF/EdiW339DPk3z6T/tiXYN8i/AWr5h89hPGYMiW2HEyQkeNikGdsSEhskgPYytuHWItnMViyReOa44QyeNDPJnnMJyW08acUWiX3pOLVIHG/e+OHjjmp5CfbDzyR+lCXY9rMf3njjwzdrnFoYmNEF2EBEAm4No2AUjIJRMAqIAABLSk0SPyum2wAAAABJRU5ErkJggg==","orcid":"","institution":"UNSW Sydney","correspondingAuthor":true,"prefix":"","firstName":"Kim","middleName":"","lastName":"Delbaere","suffix":""}],"badges":[],"createdAt":"2025-10-10 20:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7830071/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7830071/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95210309,"identity":"3db04c17-0e06-4a54-bb29-e8f75d20cd98","added_by":"auto","created_at":"2025-11-05 14:06:43","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":153321,"visible":true,"origin":"","legend":"","description":"","filename":"ConcernaboutFallingBMCGeriatrics.docx","url":"https://assets-eu.researchsquare.com/files/rs-7830071/v1/26771fbf3dadec7a751f219c.docx"},{"id":95210306,"identity":"b6460e31-9a81-4eec-8c29-e53ec1fd9d86","added_by":"auto","created_at":"2025-11-05 14:06:43","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9908,"visible":true,"origin":"","legend":"","description":"","filename":"6bf63f1a882e433bb050fa49b2abcd52.json","url":"https://assets-eu.researchsquare.com/files/rs-7830071/v1/7775a859cd59dbd4db089dc2.json"},{"id":95210311,"identity":"8c31ebc8-6e7d-4948-8e3a-594059792ebe","added_by":"auto","created_at":"2025-11-05 14:06:43","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":114294,"visible":true,"origin":"","legend":"","description":"","filename":"6bf63f1a882e433bb050fa49b2abcd521enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7830071/v1/cd684b086c0ceddd4c49fa61.xml"},{"id":95210307,"identity":"fb9940c6-7959-4c0a-b619-8cc82e383978","added_by":"auto","created_at":"2025-11-05 14:06:43","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":108350,"visible":true,"origin":"","legend":"","description":"","filename":"6bf63f1a882e433bb050fa49b2abcd521structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7830071/v1/f58cde6b9b6a8f886628d011.xml"},{"id":95228795,"identity":"9b9435f7-e9aa-472c-a5cf-ad34484dd04c","added_by":"auto","created_at":"2025-11-05 16:34:08","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126190,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7830071/v1/487ac3181307dc3fe7c1fcd8.html"},{"id":95312495,"identity":"3900ff9c-c61a-43cc-84f6-2d5641924828","added_by":"auto","created_at":"2025-11-06 15:49:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1090841,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7830071/v1/35943988-d01a-4fd7-b7b7-0ba862520e75.pdf"}],"financialInterests":"Competing interest reported. The physiological profile assessment (NeuRA FallScreen) is commercially available through Neuroscience Research Australia","formattedTitle":"Substantial Falls Increase Concern About Falling: a 12-Month Longitudinal Cohort Study Running title: Understanding the Development of Concerns About Falling in Older Adults","fulltext":[{"header":"HIGHLIGHTS","content":"\u003cul\u003e\n \u003cli\u003eBaseline and 12-month follow-up Concern about Falling (CaF) were strongly associated, indicating relative stability.\u003c/li\u003e\n \u003cli\u003eInjurious or multiple falls over 12 months significantly increased CaF.\u003c/li\u003e\n \u003cli\u003eSlower mobility, older age, and lower conscientiousness were additional independent predictors of increased CaF.\u003c/li\u003e\n \u003cli\u003eClinical fall management should include follow-up of CaF to better guide support and intervention.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eConcern about falling (CaF) is common in community-living older adults (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) and is associated with reduced confidence, restricted activity, increased risk of falls and functional decline. It affects both fallers and non-fallers (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and is linked to multiple risk factors. These include modifiable factors that can be improved through targeted interventions or lifestyle changes (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), such as impaired gait and balance, and non-modifiable factors like female sex, older age and a history of falling (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Up to half of older people who have experienced a fall report concern, suggesting that falling may trigger changes in perceptions and confidence (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). For some older people, CAF may represent a realistic appraisal of their risk of falls (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), but for others, CaF may contribute to further falls by increasing anxiety, altering gait and leading individuals to limit or avoid physical activities that are essential for maintaining strength, balance and mobility (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Based on these findings, a bidirectional relationship between falls and CaF has been proposed, in which concern may act as both a cause and a consequence (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhile the role of CaF as a risk factor for falls is supported by systematic review evidence (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), the extent to which falls contribute to sustained elevated CaF is less well understood. Some studies suggest a short-term, transient increase in CaF following a fall (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), while others suggest that CaF can persist and worsen even in the absence of further falls (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). It also remains unclear whether individual characteristics, such as age, mobility, mood, cognitive function and personality, modify the relationship between falls and CaF (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Previous research on the relationship between falls and CaF has predominantly relied on cross-sectional designs and retrospective self-reports, both of which are susceptible to bias and inaccuracies. With the exception of one study (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), there is a notable absence of investigations employing repeated measures to explore this relationship. In contrast, prospective longitudinal designs enable continuous monitoring of falls, allow for tracking changes in CaF over time, and facilitate adjustment for baseline levels. This methodological approach provides a clearer understanding of whether CaF is relatively stable in older age or a dynamic construct that may be influenced by incident falls, changes in health status, or psychological factors.\u003c/p\u003e\u003cp\u003eTo address this research gap, we conducted a longitudinal study in a representative sample of 489 community-living older people to determine: (i) whether experiencing certain types of falls independently predicted increased CaF over 12 months; (ii) whether physical, cognitive and psychological factors also predicted change in CaF; and (iii) the extent to which CaF is stable over time. We hypothesised that falls, reduced mobility, poorer cognitive function and certain psychological traits would predict increased CaF over time.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and participants\u003c/h2\u003e\u003cp\u003eThis longitudinal cohort study used data from the Balance and Falls sub-study of the Sydney Memory and Aging Study (MAS) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Of the 500 participants, 489 had complete data for the variables of interest and were included in this analysis (Supplementary Figure S1). No a priori power calculation was conducted, as the parent study determined the sample size. Participants were community-living individuals aged 70\u0026ndash;90 years without dementia, residing in two electoral divisions of Sydney, Australia (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Individuals with neurodegenerative or major psychiatric conditions were excluded. All participants provided written informed consent, and ethical approvals were obtained from the Ethics Committees of the University of New South Wales and the South Eastern Sydney and Illawarra Area Health Service (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy procedures\u003c/h3\u003e\n\u003cp\u003eParticipants completed a baseline face-to-face assessment at a research facility or in their homes. The assessment session typically took three to four hours, conducted across one or two appointments and included a medical interview, questionnaires, and neuropsychological and physical performance assessments.\u003c/p\u003e\n\u003ch3\u003ePrimary outcome\u003c/h3\u003e\n\u003cp\u003eCaF at baseline and the 12-month follow-up was assessed using the Falls Efficacy Scale International (FES-I), a 16-item questionnaire with excellent psychometric properties (Cronbach's alpha\u0026thinsp;=\u0026thinsp;0.97 and test-retest reliability\u0026thinsp;=\u0026thinsp;0.94) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Participants rated their CaF during 16 daily life activities, such as cleaning the house or walking in the neighbourhood, using a 4-point Likert Scale (1 = \"not concerned at all\" and 4 = \"very concerned\"), leading to a total score range of 16 to 64 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eBaseline predictor variables\u003c/h3\u003e\n\u003cp\u003eBalance was assessed using established tests. Physiological fall risk was assessed using the Physiological Profile Assessment score (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Controlled leaning balance during standing was assessed using the coordinated stability test (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Near tandem balance was measured by assessing how long participants could maintain balance while standing with one foot slightly in front of and to the side of the other (maximum 30 seconds) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFunctional mobility and strength were assessed. The timed up-and-go (TUG) evaluated mobility by timing the participants standing up from a chair, walking three meters, turning, returning, and sitting down, with longer times indicating greater impairment (\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Gait speed was measured as the time (in seconds) to walk 3m, turn and walk back at a normal pace. The five-times sit-to-stand test assessed lower-limb strength and endurance, requiring participants to rise from a chair five times as quickly as possible without using their arms (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCognitive function was evaluated using several complementary assessments: global cognitive impairment was assessed with the Standardised Mini-Mental State Examination (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), processing speed/ working memory was assessed with the Trail Making test (part A) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), executive function was assessed with the Trail Making test (part B minus part A) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), verbal fluency with the animal naming task; (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), and symbol-number matching was assessed with the Digit Symbol Substitution Test (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePsychological assessments encompassed measures of depression, anxiety, and personality traits. Depressive symptoms were assessed with the 15-item Geriatric Depression Scale (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), and anxiety was assessed with the Goldberg Anxiety Scale (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Personality traits were derived from the Neuroticism, Extraversion, Openness Personality Inventory (Likert scale:1\u0026ndash;5) and subscores for neuroticism (emotional instability and a tendency toward negative affect) (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), openness (imagination and curiosity) (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), and conscientiousness (organizational skills, responsibility, and goal-directed behaviour) (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) were obtained.\u003c/p\u003e\u003cp\u003eParticipants were also asked how many falls they had experienced in the past year to document their fall history.\u003c/p\u003e\n\u003ch3\u003eFalls during follow-up\u003c/h3\u003e\n\u003cp\u003eFalls and fall-related injuries were monitored prospectively over 12 months using daily fall calendars returned monthly, with telephone follow-up for missing data, in line with international guidelines (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). A fall was defined as \u0026ldquo;an unexpected event in which the participants came to rest on the ground, floor, or lower level\u0026rdquo; (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). From this, four fall variables were derived: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) falls: 1 or more falls, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) multiple falls: 2 or more falls, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) injurious falls: 1 or more falls where participants reported suffering an injury, including cuts and abrasions, bruising and bone fractures, and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) substantial falls: 2 or more falls without injury or 1 or more injurious falls. The substantial fall variable was derived as it has been shown to capture falls with psychological or clinical impact (31, 32).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eMissing item-level data for the 12-month FES-I assessment were imputed according to the FES-I scoring protocol (31, 33). For participants missing a complete 12-month FESI assessment, the mean of available 3-, 6-, and 9-month FESI-I assessment scores was used if two or more time points were available. Predictor variable missingness was addressed through multiple imputations, supported by Little\u0026rsquo;s MCAR test, resulting in five imputed datasets. Initial linear regression analyses assessed each predictor adjusted for baseline FES-I, with the cognitive variables additionally adjusted for level of education. A principal component analysis was performed to categorise the baseline predictor variables into domains, i.e. physical, psychological, cognitive, and demographics/anthropometrics (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Supplementary Figure S2). The variables from each domain with the strongest association with 12-month FES-I scores in the single predictor analyses, along with the most strongly associated fall variable, were then selected for inclusion in a multivariable linear regression model (provided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This regression was conducted using backward elimination to identify independent predictors of CaF at 12 months, while adjusting for baseline FES-I. Residuals were checked to confirm normality. All analyses were conducted using IBM SPSS Statistics version 27 (SPSS Inc.).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eParticipant characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The comprised 489 participants had a mean age of 77.9 (SD\u0026thinsp;=\u0026thinsp;4.6) years, of whom 54.6% were female. One hundred and sixty-eight participants (34.4%) reported moderate CaF at baseline (FES-I scores\u0026thinsp;\u0026ge;\u0026thinsp;23). During follow-up, 213 participants (43.6%) reported at least one fall, 94 (19.2%) reported two or more falls, 141 (28.8%) reported at least one injurious fall, and 166 (34.0%) reported a substantial fall.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticipant characteristics at baseline\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean (SD) or Median [IQR] or n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e77.9 (4.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e267 (54.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLiving alone (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e213 (43.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConcern About Falling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBaseline FES-I (score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.0 [7.0]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFall history\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;1 Falls past year (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e151 (30.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSMMSE (score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28.0 [2.0]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFunctional Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWHODAS (total score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.0 [9.0]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: SMMSE\u0026thinsp;=\u0026thinsp;Standardised Mini-Mental State Examination; WHODAS\u0026thinsp;=\u0026thinsp;World Health Organization Disability Assessment Schedule; \u0026ge;1 fall history\u0026thinsp;=\u0026thinsp;at least one fall in the year prior to baseline\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eSingle predictor analysis\u003c/h3\u003e\n\u003cp\u003eCaF at 12 months was significantly associated with CaF at baseline (r\u0026thinsp;=\u0026thinsp;0.69, 95% confidence interval: 0.64 to 0.73). In the regression models examining single predictors while adjusting for baseline CaF, several factors were significantly associated with CaF at the 12-month follow-up (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These included older age, experiencing substantial falls during follow-up, balance impairments (higher physiological fall risk and shorter near-tandem stance time) and slower performance in the Timed Up and Go, 6-meter walk and five-times sit-to-stand mobility tests. In addition, cognitive factors (slower processing speed, lower Digit Symbol scores, and reduced verbal fluency) and psychological traits (higher depressive symptoms, greater neuroticism and lower conscientiousness) were associated with CaF at this time-point. Some notable variables were not significantly associated with CaF: SMMSE, executive function (Trails B minus A scores), anxiety (GAS scores), sex, BMI and falls prior to baseline.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRegression models examining single predictors for CaF at 12-month follow-up while adjusting for baseline CaF \u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePredictor variables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean (SD) or Median [IQR] or n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSig.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eDemographics\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.5 (5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.04, 0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.251\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eAge (yrs)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e77.9 (4.6)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.25\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.06\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.13, 0.37\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e267 (54.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.9, 1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.687\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;1 Falls past year (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e151 (30.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.45, 0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.506\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eBalance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPA (score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.89 (0.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.01, 1.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoordinated Stability (errors)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.5 [21.2]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.02, 0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.356\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eNear tandem balance (s)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e10.0 [1.0]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e-0.35\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.17\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026ndash;0.68, -0.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.034\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eCognition \u003csup\u003e~\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSMMSE (score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.0 [2.0]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.43, 0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.763\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eTrails A (s)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e42.0 [18.0]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.01, 0.09\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTrails B-A (s)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60.0 [50.0]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.02, 0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.574\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eDigit symbol (score)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e49.0 (12.1)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e-0.07\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e-0.12, -0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eVerbal fluency (score)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e16.2 (4.4)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e-0.14\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.07\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026ndash;0.27, -0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eFunctional mobility\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eTUG (s)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e9.2 [3.0]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.68\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.11\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.48, 0.89\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e6m walk (s)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e8.0 [3.0]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.29\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.09, 0.50\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSit to stand (s)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e16.0 [6.0]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.28\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.06\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.16, 0.39\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eMood\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGDS (score)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e2.0 [2.0]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.43\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.15\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.13, 0.73\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGAS (score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0 [1.0]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.22, 0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.396\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003ePersonality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eNeuroticism (score)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e14.5 (6.7)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.01, 0.18\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOpenness (score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.5 (5.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.11, 0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.705\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eConscientiousness (score)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e34.0 (5.9)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e-0.13\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e-0.23, -0.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFalls during follow-up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOne or more falls (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e213 (43.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.09, 2.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTwo or more falls (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94 (19.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.31, 2.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInjurious falls (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e141 (28.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.26, 2.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSubstantial falls (n)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e166 (34.0%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.36\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.24\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.17, 2.55\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.025\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e#\u003c/sup\u003e Analyses adjusted for baseline FES-I scores; \u003csup\u003e~\u003c/sup\u003e additionally adjusted for years of education\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNotes: B\u0026thinsp;=\u0026thinsp;Unstandardised regression coefficients; SMMSE\u0026thinsp;=\u0026thinsp;Standardised Mini-Mental State Examination; Substantial falls\u0026thinsp;=\u0026thinsp;at least one injurious fall or two or more falls; TUAG\u0026thinsp;=\u0026thinsp;Timed Up-and-Go; GDS\u0026thinsp;=\u0026thinsp;Geriatric Depression Scale; GAS\u0026thinsp;=\u0026thinsp;Geriatric Anxiety Scale. Associations with p\u0026thinsp;\u0026lt;\u0026thinsp;.05 are bolded.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eMultivariable analysis\u003c/h2\u003e\u003cp\u003eIn the multivariable model (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), substantial falls, slower TUG times, lower conscientiousness and older age emerged as independent and significant predictors of 12-month CaF, after adjusting for baseline CaF. This model explained 51% of the variance in 12-month CaF (adjusted R\u0026sup2; of 0.508). All variance inflation factors were \u0026lt;\u0026thinsp;2, indicating no multicollinearity and model diagnostics supported the assumptions of linear regression (Supplementary Tables S1 and 2, Figures S3-5).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariable associations with CaF at 12-month follow-up\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSig.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBaseline FES-I (score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.70\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.61, 0.80\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubstantial Falls (yes\u0026thinsp;=\u0026thinsp;1/no\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e1.55\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.58\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.42, 2.67\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTUG (s)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.63\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.43, 0.84\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConscientiousness (score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-0.11\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e-0.20, -0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (yrs)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.17\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.06\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.05, 0.29\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-8.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-17.83, 1.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: TUG\u0026thinsp;=\u0026thinsp;Timed Up-and-Go; Substantial Falls\u0026thinsp;=\u0026thinsp;at least one injurious fall or two or more falls\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eUsing a longitudinal study design, we found many physical, cognitive and mood variables predicted 12-month CaF in single predictor analyses, and of these, baseline CaF, slower TUG, lower conscientiousness, older age and substantial falls during follow-up were identified as independent predictors of CaF. These results extend previous cross-sectional findings by showing that, even after accounting for baseline concern, certain physical, cognitive and psychological characteristics are linked to a measurable and clinically meaningful increase in CaF over time. This indicates that while CaF is relatively stable in older age, it can be significantly elevated following substantial falls, highlighting the importance of ongoing monitoring in clinical and community settings.\u003c/p\u003e\u003cp\u003eThe identification of substantial falls as an independent predictor of increased CaF suggests that injurious or repeated falls may trigger a psychological shift that extends beyond what is captured by baseline function or personality (2, 34). Substantial falls were associated with a 1.55-point increase in CaF over 12 months, exceeding the validated one-point FES-I threshold indicative of heightened fall risk, highlighting the significant psychological impact of such falls (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This finding, however, contrasts with a previous study by Weijer et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), who found that CaF following a fall was transient and did not increase with subsequent falls. Differences in baseline concern, age, sex distribution, and cultural or healthcare contexts may account for these contrasting findings (35). It is also possible that substantial falls, encompassing an injurious fall or multiple falls, may have captured clinically meaningful events that contribute to a lasting shift in perceived vulnerability, rather than a short-term increase in CaF.\u003c/p\u003e\u003cp\u003eThe final multivariable model also included poor mobility, lower conscientiousness, older age, and baseline CaF as independent predictors of CaF at 12 months. The association with poor mobility, as indicated by slow TUG completion times, is consistent with previous work demonstrating poor physical function increases CaF and perceived fall risk (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Lower conscientiousness may reflect maladaptive coping, reduced self-efficacy and heightened health-related anxiety (26, 36), and given its established connection to frailty and functional decline, may represent a key psychological marker of vulnerability to persistent CaF (37). The independent effect of age on CaF may reflect age-related declines in mobility not captured by the TUG, as well as greater cumulative exposure to falls and fear-based learning (38, 39). Finally, baseline CaF was the strongest predictor of CaF at one year, reinforcing its relative stability over time in older people, and the role of persistent cognitive-emotional patterns in shaping perceptions of vulnerability (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Collectively, these findings indicate that CaF is shaped by a combination of physical, emotional and personality-related factors.\u003c/p\u003e\u003cp\u003eSeveral factors significant in our single predictor variable analyses, such as neuroticism, depressive symptoms and cognitive slowing, were excluded from the final model, likely due to shared variance with stronger predictors. Higher neuroticism, characterised by heightened emotional reactivity and sensitivity to perceived threat (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), and reduced executive function, attention, and processing speed have been shown to influence concern about falling (CaF) by disrupting risk appraisal and gait control (40\u0026ndash;42). In parallel, depressive symptoms may intensify perceived vulnerability and promote avoidance behaviours (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The exclusion of these factors from the multivariable model suggests their impact on CaF may be mediated through mobility limitations or maladaptive coping styles.\u003c/p\u003e\u003cp\u003eStrengths of the study include the inclusion of a population-based cohort, longitudinal design, validated outcome measures and comprehensive assessment across physical, cognitive and psychological domains. The use of multiple imputations further minimised bias due to missing data and strengthened the validity of the analyses. Several limitations should, however, also be considered when interpreting the findings. First, no a priori power calculation was performed, which may limit the ability to detect smaller effects. Second, the limited temporal resolution of our data means we cannot determine the exact timing of changes in CaF relative to falls. Finally, although the FES-I is a widely applied and validated instrument for assessing CaF, all self-reported measures are subject to the potential for bias by cognitive status, mood, or cultural context, and repeated questioning may cause heightened concern (43).\u003c/p\u003e\u003cp\u003eThis study adds to the growing recognition of CaF as a multifactorial construct aligning with the biopsychosocial model of ageing, which emphasises the interplay between biological, psychological and social factors in shaping health and quality of life in older adults (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In this context, CaF appears to arise not only from new fall events or personality traits, but also as a dynamic outcome influenced by changes in physical function. Clinically, our findings support routine CaF screening after falls, particularly those that are injurious or recurrent, to identify those at risk of escalating CaF and functional decline (44). Intervention strategies could be tailored accordingly, drawing on integrated approaches that address both physical and psychological contributors. For instance, moderate to high challenging balance exercises aimed at reducing fall risk (45) may prove most effective when combined with cognitive behavioural techniques designed to target CaF (46, 47). Further work is required to explore the benefits of personalising fall prevention programs based on psychological profiles, such as levels of conscientiousness (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), and determine whether people with lower conscientiousness respond better to structured support strategies involving routine check-ins and caregiver involvement (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In parallel, psychological interventions that address maladaptive coping styles could help mitigate excessive or persistent CaF (48). Finally, the longitudinal tracking of modifiable risk factors such as mood and mobility may reveal critical windows for early intervention and enable more responsive, person-centred care.\u003c/p\u003e\u003cp\u003eIn summary, we found that CaF is relatively stable over one year. Concerns about falling are significantly associated with poorer functional mobility, lower conscientiousness and older age, and can be significantly elevated following substantial falls. These findings highlight the complex and multifactorial nature of CaF and reinforce its role as both a consequence of falls and a contributor to activity restriction and loss of independence. Screening for CaF should be embedded in clinical practice, not only following falls, but also in those with declining mobility or psychological risk profiles to interrupt the cycle of fear and decline before it intensifies. Recognising CaF as both a modifiable risk factor and a clinical red flag offers an opportunity to shift fall prevention from reactive management to proactive care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/h2\u003e\n\u003caddress\u003eWe thank the study participants and staff involved in collection and management of the data used in this manuscript.\u003c/address\u003e\n\u003ch2\u003e\u003cstrong\u003eEthics, Consent to Participate, and Consent to Publish declaration:\u003c/strong\u003e\u003c/h2\u003e\n\u003caddress\u003eAll participants provided written informed consent to participate and for their information to be saved and published anonymously, and ethical approvals were obtained from the Ethics Committees of the University of New South Wales and the South Eastern Sydney and Illawarra Area Health Service (14). Procedures followed the principles of the Declaration of Helsinki and were in line with the Medical Research Involving Human Subjects Act (WMO) (49).\u003c/address\u003e\n\u003ch2\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe physiological profile assessment (NeuRA FallScreen) is commercially available through Neuroscience Research Australia.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eDe-identified data that support the findings of this study are available from the corresponding author on reasonable request. Access will be provided for research purposes in accordance with institutional and ethical requirements.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eStephen R. Lord, Kim Delbaere and Kim S. van Schooten devised the research question. Mira E. Unverzagt conducted the data analysis and drafted the manuscript. All authors provided critical feedback on the analysis and draft.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSponsor’s Role\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe funders of the study had no role in the study design, data collection, data analysis, data interpretation, writing of the report, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe participants in this study were drawn from the Memory and Ageing Study of the Brain and Ageing Program, School of Psychiatry, University of New South Wales, funded by a National Health and Medical Research Council grant (No 350833), and NHMRC Project Grant 400941. Stephen R. Lord and Kim Delbaere are funded by NHMRC Investigator grants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLaved\u0026aacute;n A, Viladrosa M, J\u0026uuml;rschik P, Botigu\u0026eacute; T, Nu\u0026iacute;n C, Masot O et al. vol 13, e0194967,. Fear of falling in community-dwelling older adults: A cause of falls, a consequence, or both? (2018). Plos One. 2018;13(5).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFriedman SM, Munoz B, West SK, Rubin GS, Fried LP. Falls and fear of falling: which comes first? A longitudinal prediction model suggests strategies for primary and secondary prevention. J Am Geriatr Soc. 2002;50(8):1329\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Schooten KS, Taylor ME, Close JCT, Davis JC, Paul SS, Canning CG, et al. Sensorimotor, Cognitive, and Affective Functions Contribute to the Prediction of Falls in Old Age and Neurologic Disorders: An Observational Study. Arch Phys Med Rehabil. 2021;102(5):874\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLegters K. Fear of falling. Phys Ther. 2002;82(3):264\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang WNW, Mao HF, Lee HM, Chi WC. Association between Fear of Falling and Seven Performance-Based Physical Function Measures in Older Adults: A Cross-Sectional Study. Healthcare. 2022;10(6).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScheffer AC, Schuurmans MJ, van Dijk N, van der Hooft T, de Rooij SE. Fear of falling: measurement strategy, prevalence, risk factors and consequences among older persons. Age Ageing. 2008;37(1):19\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDelbaere K, Close JC, Mikolaizak AS, Sachdev PS, Brodaty H, Lord SR. The Falls Efficacy Scale International (FES-I). A comprehensive longitudinal validation study. Age Ageing. 2010;39(2):210\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEllmers TJ, Ventre JP, Freiberger E, Hauer K, Hogan DB, Lim ML, et al. Does concern about falling predict future falls in older adults? A systematic review and meta-analysis. Age Ageing. 2025;54(4):afaf089.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYardley L, Beyer N, Hauer K, Kempen G, Piot-Ziegler C, Todd C. Development and initial validation of the Falls Efficacy Scale-International (FES-I). Age Ageing. 2005;34(6):614\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKuo C-T, Chen D-R, Chen Y-M, Chen P-Y. Validation of the short falls efficacy scale-international for Taiwanese community-dwelling older adults: Associations with fall history, physical frailty, and quality of life. Geriatr Nurs. 2021;42(5):1012\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDelbaere K, Close JCT, Mikolaizak AS, Sachdev PS, Brodaty H, Lord SR. The Falls Efficacy Scale International (FES-I). A comprehensive longitudinal validation study. Age Ageing. 2010;39(2):210\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWeijer RH, Hoozemans MJ, Meijer OG, van Die\u0026euml;n JH, Pijnappels M. The short-and long-term temporal relation between falls and concern about falling in older adults without a recent history of falling. PLoS ONE. 2021;16(7):e0253374.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHowland J, Peterson EW, Levin WC, Fried L, Pordon D, Bak S. Fear of falling among the community-dwelling elderly. J Aging Health. 1993;5(2):229\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSachdev PS, Brodaty H, Reppermund S, Kochan NA, Trollor JN, Draper B, et al. The Sydney Memory and Ageing Study (MAS): methodology and baseline medical and neuropsychiatric characteristics of an elderly epidemiological non-demented cohort of Australians aged 70\u0026ndash;90 years. Int Psychogeriatr. 2010;22(8):1248\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang T, Yang L, Li X, Su P, Meng D. Characteristics of static balance performance in 4-stage balance test in the healthy older adults. Int J Neurosci. 2024:1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLord SR, Menz HB, Tiedemann A. A physiological profile approach to falls risk assessment and prevention. Phys Ther. 2003;83(3):237\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePodsiadlo D, Richardson S. The timed Up \u0026amp; Go: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39(2):142\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchoene D, Wu SM, Mikolaizak AS, Menant JC, Smith ST, Delbaere K, et al. Discriminative ability and predictive validity of the timed up and go test in identifying older people who fall: systematic review and meta-analysis. J Am Geriatr Soc. 2013;61(2):202\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlosaimi RM, Almegbas NR, Almutairi GR, Alqahtani MA, Batook SG, Alfageh IA, et al. The Five Times Sit-to-Stand Test is associated with both history of falls and fear of falling among community adults aged 50 years and older. Ir J Med Sci. 2023;192(5):2533\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLord SR, Murray SM, Chapman K, Munro B, Tiedemann A. Sit-to-Stand Performance Depends on Sensation, Speed, Balance, and Psychological Status in Addition to Strength in Older People. Journals Gerontology: Ser A. 2002;57(8):M539\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMolloy DW, Standish TI. A guide to the standardized Mini-Mental State Examination. Int Psychogeriatr. 1997;9(Suppl 1):87\u0026ndash;94. discussion 143\u0026thinsp;\u0026ndash;\u0026thinsp;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTombaugh TN. Trail Making Test A and B: normative data stratified by age and education. Arch Clin Neuropsychol. 2004;19(2):203\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBloomberg M, Brocklebank L, Hamer M, Steptoe A. Joint associations of physical activity and sleep duration with cognitive ageing: longitudinal analysis of an English cohort study. Lancet Healthy Longev. 2023;4(7):e345\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJaeger J. Digit Symbol Substitution Test: The Case for Sensitivity Over Specificity in Neuropsychological Testing. J Clin Psychopharmacol. 2018;38(5):513\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStone-Bury L, Granier K, Segal D. Geriatric Depression Scale. 2019.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKotov R, G\u0026aacute;mez W, Schmidt F, Watson D. Linking Big Personality Traits to Anxiety, Depressive, and Substance Use Disorders: A Meta-Analysis. Psychol Bull. 2010;136:768\u0026ndash;821.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoberts BW, Jackson JJ, Fayard JV, Edmonds G, Meints J. Conscientiousness. Handbook of individual differences in social behavior. The Guilford Press; 2009. pp. 369\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBagby RM, Costa PT Jr., Widiger TA, Ryder AG, Marshall M. DSM-IV personality disorders and the Five-Factor Model of personality: a multi-method examination of domain- and facet-level predictions. Eur J Pers. 2005;19(4):307\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSamuel DB, Widiger TA. A meta-analytic review of the relationships between the five-factor model and DSM-IV-TR personality disorders: a facet level analysis. Clin Psychol Rev. 2008;28(8):1326\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLamb SE, J\u0026oslash;rstad-Stein EC, Hauer K, Becker C. Development of a common outcome data set for fall injury prevention trials: the Prevention of Falls Network Europe consensus. J Am Geriatr Soc. 2005;53(9):1618\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFalls efficacy scale - International. The Universit of Manchester [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sites.manchester.ac.uk/fes-i/\u003c/span\u003e\u003cspan address=\"https://sites.manchester.ac.uk/fes-i/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7830071/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7830071/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Concern about falling (CaF) is common in older adults and predict falls, disability and loss of independence. However, it is unclear whether CaF is relatively stable or whether new falls contribute to increased CaF over time. The purpose is to examine whether experiencing falls predicts CaF, independent of other physical, cognitive, and psychological characteristics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We analysed data from 489 community-living older adults aged 70-90 years. CaF was measured using the Falls Efficacy Scale-International (FES-I) at baseline and 12-months. Falls and injuries were prospectively monitored. Baseline predictors included physical and cognitive performance, mood, personality traits, and demographic variables. Single predictor variable and multivariable linear regression analyses examined predictors of CaF at follow-up, adjusting for baseline CaF.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Many physical, cognitive and mood variables were associated with CaF in the adjusted single predictor analyses. Experiencing one injurious fall or multiple falls during follow-up was a significant predictor of CaF (β = 1.55, p = 0.007). Other independent predictors included baseline CaF (β = 0.70, p \u0026lt; 0.001), slower Timed Up and Go performance (β = 0.63, p \u0026lt; 0.001), lower conscientiousness (β = –0.11, p = 0.016), and older age (β = 0.17, p = 0.01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Our findings suggest that while CaF exhibits some stability, it can be significantly elevated following injurious or multiple falls. Targeted assessment and support following injurious or recurrent falls may help prevent persistent concern, particularly in people with reduced mobility or lower psychological resilience. These findings highlight the importance of post-fall review in clinical care.\u003c/p\u003e","manuscriptTitle":"Substantial Falls Increase Concern About Falling: a 12-Month Longitudinal Cohort Study Running title: Understanding the Development of Concerns About Falling in Older Adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-05 14:06:38","doi":"10.21203/rs.3.rs-7830071/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-12-05T21:52:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33527835745725190416265055311870384560","date":"2025-11-12T16:52:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"335806230155177055298873287134192975908","date":"2025-10-27T18:36:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-27T06:31:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-26T16:27:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-25T10:44:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-24T03:55:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-10-24T03:51:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3b855400-4bd8-4639-9eb0-766022609943","owner":[],"postedDate":"November 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-05T14:06:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-05 14:06:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7830071","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7830071","identity":"rs-7830071","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}