Validity and reliability of a fall risk scale in older adults with chronic diseases in a high-altitude region of Peru

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These can lead to significant disability, loss of functional independence, and premature death. To determine the validity and reliability of a self-report scale for assessing the risk of falling in Peruvian older adults who live at high altitude and have chronic diseases such as osteoporosis, type II diabetes, and hypertension. Material and Methods A descriptive cross-sectional study was conducted. The sample consisted of 307 older adults (143 males and 164 females) selected in a non-probabilistic manner. The age range was 60 to 80 years. Fall risk was assessed using the fall risk scale proposed by Rubenstein et al. (2011). The scale consists of 13 items with dichotomous responses (knows and does not know). Descriptive statistics were applied. Validation was performed using construct analysis [(confirmatory factor analysis). Reliability was determined using internal consistency (Cronbach's alpha). Results The reliability determined using Cronbach's alpha ranged from 0.81 to 0.85, indicating high reliability. In terms of validity, the CFA yielded acceptable values for the CFI, TLI, and NFI indices, showing values ≥ 0.90 and an adequate RMSEA fit of 0.056. Conclusion The fall risk scale applied to OAs in a high-altitude Andean region of Peru showed acceptable values of validity and reliability. The results suggest its use and application in clinical and epidemiological settings. risk of falling older adult altitude validity reliability Background Older adults (OAs) are characterized by a particular vulnerability, where the deterioration of physical and functional abilities associated with aging, combined with barriers in their neighborhood environment, significantly increase their fear and risk of falling [ 1 ]. In fact, falling has been classically defined by Tinetti et al. [ 2 ] as an event that causes a person to involuntarily end up on the ground or at a lower level, without this being due to a serious intrinsic event (such as a stroke) or an overwhelming danger [ 2 ]. More recently, it has been defined as the result of interactions between long-term predisposing factors and short-term environmental predisposing factors, such as an adverse reaction to medication, an acute illness, or a trip on an uneven surface [ 3 ]. In general, falls are one of the most serious public health problems for OAs worldwide. They cause considerable disability, loss of functional independence, premature mortality [ 3 , 4 ], deterioration in physiological condition, limitation in the performance of activities of daily living, and negatively affect quality of life (Centers for Disease Control Prevention [CDC] [ 5 ]). In addition, they are the fifth leading cause of death and hospitalization worldwide [ 6 ]. In general, the prevention of falls in older adults represents a critical challenge for public health, not only because of its direct consequences on the health of older adults, But also because of the collateral impact that a fall can have on the life of the informal caregiver [ 7 ]. Therefore, it is essential to have accurate methods to measure the risk of falling and thus guide effective interventions in older adults. This will prevent adverse events, maintain their functional autonomy, and reduce the burden on health services and formal and informal caregivers. In this regard, various fall risk assessment tools have been designed to establish the degree of risk. These are based on a range of recognized risk factors covering different domains, some objective and/or subjective (National Institute for Health and Care Excellence [NICE] [ 8 ]). In particular, self-report scales represent a viable alternative for assessing fall risk and could demonstrate acceptable levels of reliability in Peruvian older adults. In fact, as far as is known, Peru does not have a scale specifically validated for assessing the risk of falls in older adults, particularly those who live in high-altitude geographical regions and have chronic conditions such as osteoporosis, type II diabetes, and hypertension. Although some recent studies conducted in the country have reported prevalences and risk factors for falls in different geographical regions [ 9 – 12 ]. These studies have used instruments proposed in different geographical and sociocultural contexts, whose validity and reliability in Peruvian populations have not yet been rigorously tested. This raises the urgent need for adequate and validated tools for older adults living in a high-altitude region of Peru. To this end, this study will use the scale originally developed by Rubenstein et al. [ 4 ] for the US population, and recently validated and adapted for the Chilean population [ 13 ], whose psychometric properties have demonstrated adequate levels of validity and reliability. These results suggest its potential applicability to the Peruvian OAs population, due to its simplicity and low number of questions. Therefore, this study aimed to determine the validity and reliability of a self-report scale for assessing fall risk in Peruvian older adults who live at high altitude and have chronic diseases such as osteoporosis, type II diabetes, and hypertension. Materials and Methods Type of study and sample A descriptive cross-sectional study was designed in OAs from a high-altitude region of Peru. The sample consisted of 307 OAs (143 males and 164 females) aged between 60 and 80 years. The sample selection was non-probabilistic (accidental). The OAs were patients at a public hospital in the city of Puno (located at 3,820 meters above sea level). They were invited to participate in the study on a voluntary basis. The characteristics of the sample are shown in Table 1 . All patients were informed about the purpose of the study and signed the informed consent form. All GPs who had attended consultations at least once a month in the last six months and who were in the defined age range of 60 to 80 years were included in the study. Older adults with functional dependence, severe visual impairments that would hinder the application of the scale, and/or hearing problems were excluded. The study was conducted in accordance with the Declaration of Helsinki for human subjects and in accordance with the UNAP Ethics Committee (UNA-2024-23 ). Techniques and procedures A survey was used to assess the risk of falling. The instrument used for this study was the 13-item fall risk scale proposed by Rubenstein et al. [ 4 ]. This scale was translated, adapted, and validated into Spanish for the Chilean population by Cossio-Bolaños et al. [ 13 ]. All items have dichotomous responses (knows and does not know). For example, a higher score indicates a higher risk of falling (≤ 3 points: low risk of falling and ≥ 4 points: high risk). This procedure was carried out in the traditional manner: with pen and paper. Two highly trained interviewers (nurses) conducted the surveys with the volunteer OAs. This procedure was carried out on the hospital premises. The entire procedure was carried out in April and May 2025 during the hours when the OAs attended their consultations. The application of the scale took approximately 10 to 12 minutes. The instrument was organized into two parts: a) Sociodemographic variables: age, sex, level of education, and health status (collected from the patient's medical record) and b) information on the 13 fall risk items. Statistics The data obtained from the scale were previously analyzed using the Kolmogorov-Smirnov (K-S) test, as well as through asymmetry and kurtosis values. In both analyses, the data showed a normal distribution pattern. A descriptive analysis of frequencies and percentages (%) was performed for each category. Absolute and relative frequencies (percentages) were calculated to describe the distribution of sociodemographic and health variables according to gender. Pearson's chi-square test was used to evaluate the differences between men and women. The scale was validated using construct analysis. Cronbach's alpha internal consistency coefficient was used to assess reliability. Confirmatory factor analysis (CFA) was used for construct validity. Incremental and absolute indices were considered. Incremental indices such as: Comparative Fit Index (CFI), Goodness of Fit Index (GFI), and Tucker-Lewis Index (TLI). The cut-off points considered by Knekta et al. [ 14 ] for the three cases were ≥ 0.90. Absolute indices were estimated from the root mean square error of approximation (RMSEA), with an adjustment ≤ 0.05. In all cases, p < 0.05 was used. Calculations were performed in SPSS 25 and AMOS V.26. Results Table 1 shows the sociodemographic characteristics of the sample of OAs studied. There were no significant differences between age ranges (p < 0.05). However, there were significant differences in terms of educational level and health status (p < 0.05). For example, a higher proportion of women had only primary education, while men had higher levels of secondary and higher education. It was also observed that osteoporosis was the most prevalent condition in women, while men had a higher proportion of “other conditions.” Table 1 Sociodemographic characteristics of the sample studied Variables Males Females Both genders X 2 n % n % n % Age group 60 to 64 30 21,0 52 31,7 82 26,7 X 2 = 7.65; (p = 0.105) 65 to 69 33 23,1 38 23,2 71 23,1 70 to 74 31 21,7 37 22,6 68 22,1 75 to 79 25 17,5 22 13,4 47 15,3 > 80 24 16,8 15 9,1 39 12,7 Total 143 164 307 Level of education Primary 47 32,9 94 57,3 141 45,9 X 2 = 18.39; (p = 0.0001) Secondary 58 40,6 42 25,6 100 32,6 Higher education 38 26,6 28 17,1 66 21,5 Total 143 164 307 Health condition Osteoporosis 6 4,2 22 13,4 28 9,1 X 2 = 15.89; (p = 0.007) Diabetes 16 11,2 17 10,4 33 10,7 Hypertension 17 11,9 22 13,4 40 13,0 Combination of diseases 2 1,4 12 7,3 13 4,2 Other ailments 56 39,2 45 27,4 101 32,9 No disease 46 32,2 46 28,0 92 30,0 Total 143 164 307 Table 2 shows the shape of a data distribution using asymmetry and kurtosis. In the first case, all items on the scale show asymmetry close to 0. This suggests an approximately symmetrical distribution, with values distributed symmetrically around the mean between − 1 and + 1 (acceptable). Meanwhile, in the second case, the kurtosis shows acceptable values, between − 2 and + 2. In addition, the reliability determined using Cronbach's alpha ranges from 0.81 to 0.85. This indicates that no item reduces the overall reliability of the instrument. Therefore, it is highly reliable. Table 2 Distribution values (skewness and kurtosis) and internal consistency of the items on the fall risk scale. Ítem Asymmetry Kurtosis Cronbach 1 0 -2,01 0,81 2 -0,39 -1,86 0,82 3 -0,34 -1,89 0,82 4 0,71 -1,51 0,83 5 0,85 -1,29 0,81 6 -0,09 -2,01 0,81 7 0,26 -1,94 0,82 8 0,64 -1,6 0,81 9 0,75 -1,44 0,81 10 1,35 -0,17 0,85 11 2,02 2,07 0,83 12 0,17 -1,98 0,82 13 0 -2,01 0,82 Total 0,02 -1,03 0,82 The indicators of the AFC model are described in Table 3 . The study model shows acceptable values for the FRS scale (CFI, TLI, and NFI), with values ≥ 0.90 and adequate RMSEA fit (0.056). These results confirm the structure of the scale and the grouping of its items for the MAs investigated. Table 3 Fit indicators for the fall risk scale (FRS) obtained through confirmatory factor analysis and other studies Indicators Model (study) Model (Chile)** Model (reference)* X 2 (p) 1,951 (0,06) 126748 (0.05) < 0.05 Excellent Between 0.06 and 0.08 Acceptable RMSEA 0,056 0.04 0.96 excellent, between 0.90 and 0.95 acceptable TLI 0,91 0.95 > 0.96 excellent, between 0.90 and 0.95 acceptable NFI 0,91 0.90 > 0.96 excellent, between 0.90 and 0.95 acceptable Legend: **: Chile model (Cossio-Bolaños et al, 2024), *: Reference model [ 14 ], CFI: Comparative Fit Index, NFI: Normalized Fit Index, TLI: Tucker-Lewis Index, RMSEA: Root Mean Square Error of Approximation. Discussion The results of the study have shown that the fall risk scale validated in this study has demonstrated high internal consistency values (Cronbach 0.82). At the same time, these findings have confirmed that the model used fits the scale in all its indicators, with these values being acceptable. These results are consistent with the Chilean study [ 13 ] and the values proposed by the reference for the AFC [ 14 ]. This clearly shows that the theoretical construct is adequately articulated and that the indicators used (CFI, GFI, TLI, and RMSEA) coherently represent the underlying structure of the model. In recent years, several previous studies have validated self-reported fall risk scales in OAs in populations with various conditions and geographical regions around the world [ 4 , 15 – 17 ]. In fact, regardless of the type of validation and reliability used, the diagnostic accuracy and overall usefulness of the scales often vary widely between scales [ 18 ]. It is therefore necessary to carefully consider the selection of the instrument, ensuring that it is the most relevant and appropriate, and that it is adapted and/or validated to the sociocultural, socioeconomic, and geographic characteristics of the region. In this context, high-altitude geographical regions, not only in Peru but also in neighboring countries such as Bolivia, Ecuador, Colombia, and Chile, often present socioeconomic and demographic inequalities that impact the living conditions of their populations [ 19 ]. Therefore, the development and validation of self-report scales for fall risk in the OAs population are essential in order to have tools adapted to the characteristics of these contexts. Essentially, the scale validated in this study can be used to assess the threat or risk of falling. For example, some studies conducted in Peru have reported a 27.8% prevalence of frailty in the capital (Lima) [ 9 ] and a 64.1% prevalence of falls in the Peruvian Andes [ 11 ]. These results reinforce the importance of having the scale validated in this study, as it facilitates the early identification of people at high risk of falling. This scale can be an alternative tool to be applied in Andean populations living at high altitudes in Peru. In addition, it can help researchers and professionals develop more individualized prevention strategies and allow for individualized monitoring of the progression of risk in older adults over time [ 20 ]. It can also be used by the public health system to assess, monitor, and identify older adults at higher risk of falling, thus facilitating the development of timely preventive interventions targeted at this vulnerable population [ 21 ]. Despite this, as far as we know, there is no ideal tool that can be used in any context or that performs a perfect fall risk assessment [ 22 ]. It will therefore be necessary in the future to complement the assessment with some quantitative instruments or strategies. The study has some strengths that should be recognized. It is the first nationwide study to validate a fall risk scale for older adults living in a high-altitude Andean region of Peru. This scale is easy to apply, quick to administer, and suitable for use in primary health care, facilitating early detection and continuous monitoring of older adults. It is a practical tool for use in clinical and/or community settings. In addition, the results obtained in this study can serve as a baseline for future trend studies and as a reference for comparisons with other realities and sociocultural contexts. The study also has some weaknesses, for example, the sample selection was non-probabilistic and the study design was cross-sectional. This prevents the results from being generalized to other realities and makes it impossible to establish causal relationships. We also note that it was not possible to apply functional aptitude tests to the OAs, which would have allowed these findings to be contrasted with functional tests such as balance and agility. Future studies should take these aspects into consideration, and it is even suggested that other scales be applied and contrasted with the findings of this study. Conclusions The results of the study have shown that the fall risk scale applied to older adults in a high-altitude Andean region of Peru shows acceptable values of validity and reliability. The fit indicators were adequate, confirming that the theoretical structure of the scale is well founded. The results suggest its use and application in clinical and epidemiological settings. Abbreviations OA older adults CFA confirmatory factor analysis CFI Comparative Fit Index TLI Tucker-Lewis Index NFI Normalized Fit Index RMSEA Root Mean Square Error of Approximation NICE National Institute for Health and Care Excellence Declarations Acknowledgements We would like to express our gratitude to all adult participants for their tremendous support. Availability of data and materials The datasets supporting the conclusions of this research article are available by emailing the corresponding author. Authors’ contributions M.C.B., and R.G.C. contributed to the design of the research study. D.A.F., T.A.P., and D.R.A. collected data. M.C.B., R.G.C., R.V.E., C.F.G., , contributed to the discussion, wrote the manuscript and reviewed/edited the manuscript. M.C.B., R.G.C., and R.V.E., edited, and reviewed the manuscript. M.C.B., R.G.C., R.V.E., and C.F.G. Analyzed data and/or reviewed/edited the manuscript. All authors revised and agreed on the views expressed in the manuscript. Ethics approval and consent to participate The study protocol was approved by the Ethics Committee of the Universidad Nacional del Altiplano, Puno (2024-23). All experiments were conducted in accordance with relevant guidelines and regulations (such as the Declaration of Helsinki). All participants signed written informed consent, acknowledging their consent to participate and their understanding of the research procedures and objectives. Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. Clinical trial number Not applicable References Plaut P, Shach-Pinsly D, Schreuer N, Kizony R. The reflection of the fear of falls and risk of falling in walking activity spaces of older adults in various urban environments. J Transp Geogr. 2021;95(103152):103152. https://doi.org/10.1016/j.jtrangeo.2021.103152 . Tinetti ME, Speechley M, Ginter SF. Risk factors for falls among elderly persons living in the community. 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BMC Public Health. 2021;21(Suppl 2):808. Published 2021 Nov 10. 10.1186/s12889-021-10813-w Phelan EA, Mahoney JE, Voit JC, Stevens JA. Assessment and management of fall risk in primary care settings. Med Clin North Am. 2015;99(2):281–93. 10.1016/j.mcna.2014.11.004 . Strini V, Schiavolin R, Prendin A. Fall Risk Assessment Scales: A Systematic Literature Review. Nurs Rep. 2021;11(2):430–43. 10.3390/nursrep11020041 . Published 2021 Jun 2. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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10:09:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":691573,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7908694/v1/76965a24-41a7-4176-9c5a-332acbef9e38.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Validity and reliability of a fall risk scale in older adults with chronic diseases in a high-altitude region of Peru","fulltext":[{"header":"Background","content":"\u003cp\u003eOlder adults (OAs) are characterized by a particular vulnerability, where the deterioration of physical and functional abilities associated with aging, combined with barriers in their neighborhood environment, significantly increase their fear and risk of falling [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn fact, falling has been classically defined by Tinetti et al. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] as an event that causes a person to involuntarily end up on the ground or at a lower level, without this being due to a serious intrinsic event (such as a stroke) or an overwhelming danger [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMore recently, it has been defined as the result of interactions between long-term predisposing factors and short-term environmental predisposing factors, such as an adverse reaction to medication, an acute illness, or a trip on an uneven surface [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn general, falls are one of the most serious public health problems for OAs worldwide. They cause considerable disability, loss of functional independence, premature mortality [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], deterioration in physiological condition, limitation in the performance of activities of daily living, and negatively affect quality of life (Centers for Disease Control Prevention [CDC] [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]). In addition, they are the fifth leading cause of death and hospitalization worldwide [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn general, the prevention of falls in older adults represents a critical challenge for public health, not only because of its direct consequences on the health of older adults, But also because of the collateral impact that a fall can have on the life of the informal caregiver [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, it is essential to have accurate methods to measure the risk of falling and thus guide effective interventions in older adults. This will prevent adverse events, maintain their functional autonomy, and reduce the burden on health services and formal and informal caregivers.\u003c/p\u003e\u003cp\u003eIn this regard, various fall risk assessment tools have been designed to establish the degree of risk. These are based on a range of recognized risk factors covering different domains, some objective and/or subjective (National Institute for Health and Care Excellence [NICE] [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]). In particular, self-report scales represent a viable alternative for assessing fall risk and could demonstrate acceptable levels of reliability in Peruvian older adults.\u003c/p\u003e\u003cp\u003eIn fact, as far as is known, Peru does not have a scale specifically validated for assessing the risk of falls in older adults, particularly those who live in high-altitude geographical regions and have chronic conditions such as osteoporosis, type II diabetes, and hypertension.\u003c/p\u003e\u003cp\u003eAlthough some recent studies conducted in the country have reported prevalences and risk factors for falls in different geographical regions [\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These studies have used instruments proposed in different geographical and sociocultural contexts, whose validity and reliability in Peruvian populations have not yet been rigorously tested. This raises the urgent need for adequate and validated tools for older adults living in a high-altitude region of Peru.\u003c/p\u003e\u003cp\u003eTo this end, this study will use the scale originally developed by Rubenstein et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] for the US population, and recently validated and adapted for the Chilean population [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], whose psychometric properties have demonstrated adequate levels of validity and reliability. These results suggest its potential applicability to the Peruvian OAs population, due to its simplicity and low number of questions.\u003c/p\u003e\u003cp\u003eTherefore, this study aimed to determine the validity and reliability of a self-report scale for assessing fall risk in Peruvian older adults who live at high altitude and have chronic diseases such as osteoporosis, type II diabetes, and hypertension.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eType of study and sample\u003c/h2\u003e\u003cp\u003eA descriptive cross-sectional study was designed in OAs from a high-altitude region of Peru. The sample consisted of 307 OAs (143 males and 164 females) aged between 60 and 80 years. The sample selection was non-probabilistic (accidental). The OAs were patients at a public hospital in the city of Puno (located at 3,820 meters above sea level). They were invited to participate in the study on a voluntary basis. The characteristics of the sample are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e All patients were informed about the purpose of the study and signed the informed consent form. All GPs who had attended consultations at least once a month in the last six months and who were in the defined age range of 60 to 80 years were included in the study. Older adults with functional dependence, severe visual impairments that would hinder the application of the scale, and/or hearing problems were excluded. The study was conducted in accordance with the Declaration of Helsinki for human subjects and in accordance with the UNAP Ethics Committee (UNA-2024-23 ).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTechniques and procedures\u003c/h3\u003e\n\u003cp\u003eA survey was used to assess the risk of falling. The instrument used for this study was the 13-item fall risk scale proposed by Rubenstein et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This scale was translated, adapted, and validated into Spanish for the Chilean population by Cossio-Bola\u0026ntilde;os et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAll items have dichotomous responses (knows and does not know). For example, a higher score indicates a higher risk of falling (\u0026le;\u0026thinsp;3 points: low risk of falling and \u0026ge;\u0026thinsp;4 points: high risk). This procedure was carried out in the traditional manner: with pen and paper. Two highly trained interviewers (nurses) conducted the surveys with the volunteer OAs.\u003c/p\u003e\u003cp\u003eThis procedure was carried out on the hospital premises. The entire procedure was carried out in April and May 2025 during the hours when the OAs attended their consultations. The application of the scale took approximately 10 to 12 minutes. The instrument was organized into two parts: a) Sociodemographic variables: age, sex, level of education, and health status (collected from the patient's medical record) and b) information on the 13 fall risk items.\u003c/p\u003e\u003cp\u003eStatistics\u003c/p\u003e\u003cp\u003eThe data obtained from the scale were previously analyzed using the Kolmogorov-Smirnov (K-S) test, as well as through asymmetry and kurtosis values. In both analyses, the data showed a normal distribution pattern. A descriptive analysis of frequencies and percentages (%) was performed for each category. Absolute and relative frequencies (percentages) were calculated to describe the distribution of sociodemographic and health variables according to gender. Pearson's chi-square test was used to evaluate the differences between men and women. The scale was validated using construct analysis. Cronbach's alpha internal consistency coefficient was used to assess reliability. Confirmatory factor analysis (CFA) was used for construct validity. Incremental and absolute indices were considered. Incremental indices such as: Comparative Fit Index (CFI), Goodness of Fit Index (GFI), and Tucker-Lewis Index (TLI). The cut-off points considered by Knekta et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] for the three cases were \u0026ge;\u0026thinsp;0.90. Absolute indices were estimated from the root mean square error of approximation (RMSEA), with an adjustment\u0026thinsp;\u0026le;\u0026thinsp;0.05. In all cases, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was used. Calculations were performed in SPSS 25 and AMOS V.26.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the sociodemographic characteristics of the sample of OAs studied. There were no significant differences between age ranges (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, there were significant differences in terms of educational level and health status (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For example, a higher proportion of women had only primary education, while men had higher levels of secondary and higher education. It was also observed that osteoporosis was the most prevalent condition in women, while men had a higher proportion of \u0026ldquo;other conditions.\u0026rdquo;\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 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSociodemographic characteristics of the sample studied\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\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=\".\" 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colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9,1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12,7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLevel of education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e57,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e45,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;18.39; (p\u0026thinsp;=\u0026thinsp;0.0001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e25,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e32,6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigher education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17,1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e21,5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth condition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOsteoporosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e13,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e9,1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;15.89; (p\u0026thinsp;=\u0026thinsp;0.007)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10,7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e13,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e13,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCombination of diseases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther ailments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e27,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e32,9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e28,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e30,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the shape of a data distribution using asymmetry and kurtosis. In the first case, all items on the scale show asymmetry close to 0. This suggests an approximately symmetrical distribution, with values distributed symmetrically around the mean between \u0026minus;\u0026thinsp;1 and +\u0026thinsp;1 (acceptable). Meanwhile, in the second case, the kurtosis shows acceptable values, between \u0026minus;\u0026thinsp;2 and +\u0026thinsp;2. In addition, the reliability determined using Cronbach's alpha ranges from 0.81 to 0.85. This indicates that no item reduces the overall reliability of the instrument. Therefore, it is highly reliable.\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 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution values (skewness and kurtosis) and internal consistency of the items on the fall risk scale.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026Iacute;tem\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAsymmetry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKurtosis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCronbach\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2,01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0,39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1,86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0,34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1,89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1,51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1,29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0,09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2,01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1,94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1,44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0,17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2,07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1,98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2,01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1,03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe indicators of the AFC model are described in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The study model shows acceptable values for the FRS scale (CFI, TLI, and NFI), with values\u0026thinsp;\u0026ge;\u0026thinsp;0.90 and adequate RMSEA fit (0.056). These results confirm the structure of the scale and the grouping of its items for the MAs investigated.\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\u003eFit indicators for the fall risk scale (FRS) obtained through confirmatory factor analysis and other studies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndicators\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModel (study)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModel (Chile)**\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModel (reference)*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e (p)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,951 (0,06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e126748 (0.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05 Excellent Between 0.06 and 0.08 Acceptable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRMSEA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05: Very good fit, 0.05\u0026ndash;0.08: Reasonable or acceptable fit, 0.08\u0026ndash;0.10: Mediocre or limited fit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.96 excellent, between 0.90 and 0.95 acceptable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTLI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.96 excellent, between 0.90 and 0.95 acceptable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.96 excellent, between 0.90 and 0.95 acceptable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eLegend: **: Chile model (Cossio-Bola\u0026ntilde;os et al, 2024), *: Reference model [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], CFI: Comparative Fit Index, NFI: Normalized Fit Index, TLI: Tucker-Lewis Index, RMSEA: Root Mean Square Error of Approximation.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of the study have shown that the fall risk scale validated in this study has demonstrated high internal consistency values (Cronbach 0.82). At the same time, these findings have confirmed that the model used fits the scale in all its indicators, with these values being acceptable.\u003c/p\u003e\u003cp\u003eThese results are consistent with the Chilean study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and the values proposed by the reference for the AFC [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This clearly shows that the theoretical construct is adequately articulated and that the indicators used (CFI, GFI, TLI, and RMSEA) coherently represent the underlying structure of the model.\u003c/p\u003e\u003cp\u003eIn recent years, several previous studies have validated self-reported fall risk scales in OAs in populations with various conditions and geographical regions around the world [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In fact, regardless of the type of validation and reliability used, the diagnostic accuracy and overall usefulness of the scales often vary widely between scales [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. It is therefore necessary to carefully consider the selection of the instrument, ensuring that it is the most relevant and appropriate, and that it is adapted and/or validated to the sociocultural, socioeconomic, and geographic characteristics of the region.\u003c/p\u003e\u003cp\u003eIn this context, high-altitude geographical regions, not only in Peru but also in neighboring countries such as Bolivia, Ecuador, Colombia, and Chile, often present socioeconomic and demographic inequalities that impact the living conditions of their populations [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Therefore, the development and validation of self-report scales for fall risk in the OAs population are essential in order to have tools adapted to the characteristics of these contexts.\u003c/p\u003e\u003cp\u003eEssentially, the scale validated in this study can be used to assess the threat or risk of falling. For example, some studies conducted in Peru have reported a 27.8% prevalence of frailty in the capital (Lima) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and a 64.1% prevalence of falls in the Peruvian Andes [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These results reinforce the importance of having the scale validated in this study, as it facilitates the early identification of people at high risk of falling.\u003c/p\u003e\u003cp\u003eThis scale can be an alternative tool to be applied in Andean populations living at high altitudes in Peru. In addition, it can help researchers and professionals develop more individualized prevention strategies and allow for individualized monitoring of the progression of risk in older adults over time [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIt can also be used by the public health system to assess, monitor, and identify older adults at higher risk of falling, thus facilitating the development of timely preventive interventions targeted at this vulnerable population [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Despite this, as far as we know, there is no ideal tool that can be used in any context or that performs a perfect fall risk assessment [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. It will therefore be necessary in the future to complement the assessment with some quantitative instruments or strategies.\u003c/p\u003e\u003cp\u003eThe study has some strengths that should be recognized. It is the first nationwide study to validate a fall risk scale for older adults living in a high-altitude Andean region of Peru. This scale is easy to apply, quick to administer, and suitable for use in primary health care, facilitating early detection and continuous monitoring of older adults. It is a practical tool for use in clinical and/or community settings. In addition, the results obtained in this study can serve as a baseline for future trend studies and as a reference for comparisons with other realities and sociocultural contexts.\u003c/p\u003e\u003cp\u003eThe study also has some weaknesses, for example, the sample selection was non-probabilistic and the study design was cross-sectional. This prevents the results from being generalized to other realities and makes it impossible to establish causal relationships. We also note that it was not possible to apply functional aptitude tests to the OAs, which would have allowed these findings to be contrasted with functional tests such as balance and agility. Future studies should take these aspects into consideration, and it is even suggested that other scales be applied and contrasted with the findings of this study.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe results of the study have shown that the fall risk scale applied to older adults in a high-altitude Andean region of Peru shows acceptable values of validity and reliability. The fit indicators were adequate, confirming that the theoretical structure of the scale is well founded. The results suggest its use and application in clinical and epidemiological settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eolder adults\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCFA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003econfirmatory factor analysis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCFI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eComparative Fit Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTLI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTucker-Lewis Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNFI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNormalized Fit Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRMSEA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRoot Mean Square Error of Approximation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNICE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNational Institute for Health and Care Excellence\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our gratitude to all adult participants for their tremendous support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets supporting the conclusions of this research article are available by emailing the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.C.B., and R.G.C. contributed to the design of the research study. D.A.F., T.A.P., and D.R.A. collected data. M.C.B., R.G.C., R.V.E., C.F.G., , contributed to the discussion, wrote the manuscript and reviewed/edited the manuscript. M.C.B., R.G.C., and R.V.E., edited, and reviewed the manuscript. M.C.B., R.G.C., R.V.E., and C.F.G. Analyzed data and/or reviewed/edited the manuscript. All authors revised and agreed on the views expressed in the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Ethics Committee of the Universidad Nacional del Altiplano, Puno (2024-23). All experiments were conducted in accordance with relevant guidelines and regulations (such as the Declaration of Helsinki). All participants signed written informed consent, acknowledging their consent to participate and their understanding of the research procedures and objectives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePlaut P, Shach-Pinsly D, Schreuer N, Kizony R. The reflection of the fear of falls and risk of falling in walking activity spaces of older adults in various urban environments. 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Published 2021 Nov 10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12889-021-10813-w\u003c/span\u003e\u003cspan address=\"10.1186/s12889-021-10813-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePhelan EA, Mahoney JE, Voit JC, Stevens JA. Assessment and management of fall risk in primary care settings. Med Clin North Am. 2015;99(2):281\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.mcna.2014.11.004\u003c/span\u003e\u003cspan address=\"10.1016/j.mcna.2014.11.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStrini V, Schiavolin R, Prendin A. Fall Risk Assessment Scales: A Systematic Literature Review. 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Published 2021 Jun 2.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"risk of falling, older adult, altitude, validity, reliability","lastPublishedDoi":"10.21203/rs.3.rs-7908694/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7908694/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e\u003cp\u003eOne of the serious health problems for older adults (OAs) is falls. These can lead to significant disability, loss of functional independence, and premature death. To determine the validity and reliability of a self-report scale for assessing the risk of falling in Peruvian older adults who live at high altitude and have chronic diseases such as osteoporosis, type II diabetes, and hypertension.\u003c/p\u003e\u003ch2\u003eMaterial and Methods\u003c/h2\u003e\u003cp\u003eA descriptive cross-sectional study was conducted. The sample consisted of 307 older adults (143 males and 164 females) selected in a non-probabilistic manner. The age range was 60 to 80 years. Fall risk was assessed using the fall risk scale proposed by Rubenstein et al. (2011). The scale consists of 13 items with dichotomous responses (knows and does not know). Descriptive statistics were applied. Validation was performed using construct analysis [(confirmatory factor analysis). Reliability was determined using internal consistency (Cronbach's alpha).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe reliability determined using Cronbach's alpha ranged from 0.81 to 0.85, indicating high reliability. In terms of validity, the CFA yielded acceptable values for the CFI, TLI, and NFI indices, showing values\u0026thinsp;\u0026ge;\u0026thinsp;0.90 and an adequate RMSEA fit of 0.056.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe fall risk scale applied to OAs in a high-altitude Andean region of Peru showed acceptable values of validity and reliability. The results suggest its use and application in clinical and epidemiological settings.\u003c/p\u003e","manuscriptTitle":"Validity and reliability of a fall risk scale in older adults with chronic diseases in a high-altitude region of Peru","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-26 16:18:57","doi":"10.21203/rs.3.rs-7908694/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2c9b4556-fbf9-4019-b872-66d63b73cd97","owner":[],"postedDate":"November 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-04T10:08:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-26 16:18:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7908694","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7908694","identity":"rs-7908694","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}