The Role of Feelings of Burdensomeness and Technology Use in The Daily Activities of Older Adults Living in Rural Areas

The Role of Feelings of Burdensomeness and Technology Use in The Daily Activities of Older Adults Living in Rural Areas | 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 The Role of Feelings of Burdensomeness and Technology Use in The Daily Activities of Older Adults Living in Rural Areas Betül BAL, Emine APAYDIN This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7293124/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Jan, 2026 Read the published version in BMC Geriatrics → Version 1 posted 15 You are reading this latest preprint version Abstract Objective This study aims to examine feelings of burdensomeness and technology use habits and the effects of these factors on activities of daily living in older adults living in rural areas. Methods This correlational study was conducted with 384 older adults living in rural areas in two different regions of Turkey. Information Form, Geriatric Feelings of Burdensomeness Scale, Barthel Index for Activities of Daily Living and Technology Use Habits Scale were used as data collection tools. Results This study found significant negative and positive relationships, respectively, between feelings of burdensomeness and dependence on activities of daily living (r = -0.484, p < 0.001) and between technology use habits and independence in activities of daily living (r = 0.192, p < 0.001). Scale mean scores differed significantly according to sociodemographic variables (p < 0.05). According to the multiple regression analysis, the variables that most strongly predicted dependence on activities of daily living were feelings of burdensomeness, age, and use of digital devices, and the model explained 46.3% of the variance (R² = 0.463, F = 54.157, p < 0.001). The study results indicate that the sense of perceived burdensomeness in older adults in rural areas is associated with a loss of independence in daily living activities. Additionally, technology use habits were found to have a positive effect on independence in daily activities. Age, perceived burdensomeness, and digital device usage emerged as important factors influencing the level of dependence. Conclusion Older adults living in rural areas may experience loss of independence due to limitations in daily living activities and a heightened sense of perceived burdensomeness. Nurses can support these individuals by promoting technology use, enhancing digital literacy, and developing interventions tailored to rural infrastructure conditions to help them maintain greater independence in their daily activities. This approach may reduce feelings of burdensomeness while improving psychosocial well-being and overall quality of life. Clinical trial number: Not applicable. Activities of daily living burden older adults technology rural 1. Introduction Older people living in rural areas are more vulnerable to health problems due to socioeconomic disadvantages, limited healthcare infrastructure, and lifestyle factors [ 1 ]. Age-related declines in the ability to perform activities of daily living (ADLs) heighten this vulnerability. Reduced or impaired activities of daily living (ADL) lead to loss of independence in older adults living in rural areas, not only diminishing their quality of life but also placing a significant economic burden on the healthcare system [ 2 ]. Studies reveal that each year, approximately 10% of older adults who were able to independently maintain ADL in the previous year become in need of assistance for various reasons [ 4 , 3 ]. It is estimated that approximately 45% of older adults worldwide have difficulty in fulfilling their ADL [ 4 ]. While these rates reveal that difficulties in ADL are an important health problem on a global scale, the conditions in which older adults living in rural areas live further complicate this problem. Distance, transportation, and infrastructure inadequacies in rural areas make access to health services difficult [ 5 ], and when combined with factors such as low income and education levels, disease management becomes very difficult [ 6 ], adversely affecting not only the physical health but also the psychological state of older adults. Indeed, limitations in ADL in older adults living in rural areas can trigger feelings of burdensomeness. This perception develops when a person sees himself/herself as a burden to his/her environment or society [ 7 ], and it has been associated with many negative mental states such as depression, anxiety, loss of self-esteem, and suicidal thoughts [ 9 , 8 , 10 ]. In the face of these psychosocial challenges and loss of independence, new approaches are needed to support older adults living in rural areas to maintain their ADL and reduce feelings of burdensomeness. In this context, technology emerges as a valuable tool that can promote greater independence in daily living and enhance quality of life for older adults in rural settings [ 11 ]. Technology offers important opportunities for older adults, especially as it strengthens social interactions, reduces depression, and supports cognitive skills [ 11 ]. However, these potential impacts remain limited for older adults living in rural areas. Factors such as lack of digital infrastructure, limitations in internet and device access, low levels of digital literacy, and the digital divide negatively affect their access to and use of technology [ 12 , 13 ]. This causes older adults to lag behind in the digitalization process, limiting their ability to benefit from the supportive opportunities offered by technology in a population that is more likely to experience a loss of independence and feelings of burdensomeness due to socioeconomic disadvantages and the digital divide. Thus, barriers to accessing and using technology have negative impacts on older adults’ physical and psychosocial functioning. Most of the existing research has focused on older adults living in urban centers, with only limited information available on the use of technology by older adults living in rural areas and its effects on ADL and feelings of burdensomeness. Since older adults in rural settings often have more limited infrastructure and digital resources, the effects of technology access and usage habits on ADL may differ from those of their peers in urban areas. Therefore, this study was conducted to determine the effects of feelings of burdensomeness and technology use habits on ADL in older adults living in rural areas. 2. Methods 2.1. Study Design and Sample This descriptive correlational study was conducted with 384 older adults living in rural districts and villages of two provinces in the Eastern Black Sea and Central Anatolia regions. The inclusion criteria were older adults aged 65 years or older, capable of understanding and answering the questions, and voluntarily agreeing to participate in the study. Exclusion criteria were older adults living in urban centers and those who were unable to understand and answer the questions due to cognitive or communicative disabilities. Considering the access difficulties and different demographic characteristics of older adults living in rural areas, participants suitable for the population of the study were reached through a purposive sampling method. Thus, it was aimed to obtain valid results with high data quality in accordance with the study objectives [ 15 ]. 2.2. Data Collection Tools Data were collected using the Information Form, Geriatric Feelings of Burdensomeness Scale (GFBS), Barthel Index for Activities of Daily Living (BADLI), and Technology Use Habits Scale (TUHS). Information Form This form was originally developed by the researchers specifically for this study. It consists of nine items questioning the sociodemographic characteristics (age, gender, educational status, marital status, income level), current health conditions (chronic diseases), and technology use (use of a technological device, type of device used, duration of use) of older adults (Suppl. File S1). Geriatric Feelings of Burdensomeness Scale The scale used to assess the feelings of burdensomeness in older individuals was developed by Lutz and Fiske [ 16 ] and adapted into Turkish by Çekiç and Yüksel in 2024 [ 17 ]. It is a 5-point Likert-type scale consisting of 25 items scored from “1- Strongly Disagree” to “5- Strongly Agree.” The minimum and maximum scores that can be obtained from the scale are 25 and 125, respectively. As the scale score increases, the feeling of geriatric burdensomeness increases. The original Cronbach’s alpha internal consistency coefficient of the scale was 0.95 [ 17 ]. In this study, Cronbach’s alpha coefficient was found to be 0.95. Barthel Index for Activities of Daily Living The index was developed by Mahoney and Barthel in 1965 [ 18 ], and its Turkish adaptation’s validity and reliability were studied by Küçükdeveci et al. [ 19 ]. This index was used to determine the independence level of individuals in activities of daily living. Barthel Index scores vary between 0 and 100; 0–20 points indicate complete dependence, 21–61 points indicate heavy dependence, 62–90 points indicate moderate dependence, 91–99 points indicate mild dependence, and 100 points indicate independence. Studies using the Barthel Index take 60 points as the threshold, with scores above 60 indicating independent functioning [ 19 ]. In this study, Cronbach’s alpha coefficient of the scale was calculated as 0.90. Technology Use Habits Scale The Technology Use Habits Scale was developed by Küçükvardar [ 20 ] to assess individuals’ technology use habits. It is a five-point Likert-type scale consisting of 32 items and six factors: use and time, technological invasion, technology adoption, technological obsession, communication cycle, and spiritual/mental variables. The total scores obtained from the scale determine the addiction risk levels; 32–57 points are considered as no addiction risk, 58–83 points as low addiction risk, 84–109 points as moderate addiction risk, 110–135 points as high addiction risk, and 136–160 points as very high addiction risk. In the study in which the scale was developed, the internal consistency coefficient (Cronbach’s alpha) was reported as 0.92 [ 20 ]. In this study, the Cronbach’s alpha coefficient of the scale was found to be 0.96. 2.3. Data Collection Data were collected between December 2024 and February 2025 from older adults living in rural districts and villages of two provinces in the Eastern Black Sea and Central Anatolia regions of Turkey. Face-to-face interviews were conducted with older adults who met the inclusion criteria and volunteered to participate in the study. The data collection process was carried out by the researchers either in participants’ homes or village health centers and village heads’ offices, when they were easily accessible. The interviews lasted an average of 20 minutes. The scale items were read aloud by the researchers to facilitate the participants’ understanding of the questions, and additional explanations were made when necessary. 2.4. Statistical Analysis International Business Machines (IBM) Statistical Package for the Social Sciences (SPSS) version 25.0 (Armonk, NY: IBM Corp., 2022) was used for data analysis. In order to check the applicability of parametric tests, normality of the variables was evaluated by kurtosis and skewness coefficients. Normality was assessed based on the criterion that skewness and kurtosis values fell within the range of ± 2 [George & Mallery, 2010]. An independent sample t-test was used to evaluate whether there was a statistically significant difference between the two groups. A one-way ANOVA test was applied to determine the difference between more than two groups. Pearson correlation analysis was used to examine whether there was a linear relationship between the variables. Factors affecting geriatric feelings of burdensomeness, activities of daily living, and technology use habits were determined by multiple linear regression analysis (enter method). Statistical significance level was accepted as p < 0.05. 3. Results Among older adults, 64.3% were between 65–74 years of age, 52.9% were female, and 36.7% were primary school graduates. 88.3% were married, 72.4% had middle income, and 76% had different chronic diseases. 78% used a digital device, and 41.4% used a digital device for 0–30 min (see Table 1 ). Table 1 Sociodemographic characteristics of ruraly elderly individuals and comparison of mean scale scores (n = 384) n % GFBS BADLI TUHS Age Mean ± SD Mean ± SD Mean ± SD 65–74 year A 247 64.3 63.19 ± 17.95 83.09 ± 20.36 66.82 ± 21.81 75–84 year B 112 29.2 71.67 ± 18.22 61.74 ± 26.61 59.91 ± 20.13 85 year and over C 25 6.5 82.84 ± 18.01 33.40 ± 27.89 52.24 ± 24.44 F/p * 18.909/ 0.000 C-B, C-A, B-A 74.976/ 0.000 A-B, A-C, B-C 7.865/ 0.000 A-B, A-C Gender Female 203 52.9 67.67 ± 18.01 75.56 ± 25.48 65.01 ± 23.06 Male 181 47.1 66.13 ± 19.77 71.46 ± 28.37 62.55 ± 20.48 t/p 0.794/0.428 1.493/0.136 1.100/0.272 Education level Illiterate D 109 28.4 70.48 ± 19.35 68.80 ± 27.17 57.59 ± 20.59 Literate E 71 18.5 69.08 ± 20.57 70.98 ± 30.54 63.49 ± 20.92 Primary School F 141 36.7 65.22 ± 17.86 77.23 ± 24.68 63.28 ± 22.08 Secondary School G 33 8.6 63.30 ± 15.89 80.00 ± 23.45 74.93 ± 19.36 High School H 25 6.5 62.68 ± 19.11 71.80 ± 29.82 76.04 ± 20.18 Undergraduate/GraduateI 5 1.3 53.40 ± 12.58 82.00 ± 20.79 87.80 ± 21.89 F/p * 2.239/0.049 1.851/0.102 6.704/ 0.000 G,H,I > D Marital status Single 45 11.7 69.64 ± 18.73 71.88 ± 23.89 64.84 ± 20.65 Married 339 88.3 66.59 ± 18.87 73.86 ± 27.32 63.72 ± 22.08 t/p 1.021/0.308 -0.462/0.644 0.321/0.749 Income level Low J 54 14.1 72.88 ± 19.94 70.27 ± 26.55 60.48 ± 27.75 Middle K 278 72.4 67.45 ± 17.93 73.97 ± 26.51 65.12 ± 20.84 Good L 52 13.5 58.07 ± 19.80 75.28 ± 29.66 60.61 ± 20.21 F/p * 8.883/ 0.000 J-L, K-L 0.539/0.584 1.682/0.187 Other chronic diseases Yes 292 76.0 68.30 ± 18.33 71.64 ± 27.82 64.55 ± 22.34 No 92 24.0 62.65 ± 19.92 79.94 ± 22.87 61.65 ± 20.38 t/p 2.523/ 0.012 -2.598/ 0.010 1.109/0.268 Do you use a digital tool (computer, tablet, cell phone)? Yes 302 78.6 65.07 ± 18.47 79.42 ± 22.89 65.86 ± 21.40 No 82 21.4 73.82 ± 18.77 52.31 ± 29.91 56.47 ± 22.21 t/p -3.790/ 0.000 8.864/ 0.000 3.493/ 0.001 How long do you use digital tools? Not using M 24 6.3 74.66 ± 16.24 54.79 ± 25.81 55.00 ± 17.82 0–30 min N 159 41.4 69.28 ± 18.91 66.22 ± 29.68 56.77 ± 21.07 30–60 min O 111 28.9 62.91 ± 18.37 80.54 ± 21.19 68.65 ± 19.90 60–90 min P 59 15.4 64.72 ± 17.07 84.15 ± 19.83 68.98 ± 19.88 90–120 min R 29 7.6 68.55 ± 22.88 80.00 ± 26.04 79.79 ± 24.78 120 min and above S 2 0.5 54.00 ± 11.31 102.50 ± 3.53 85.00 ± 12.72 F/p * 2.763/ 0.018 9.814/ 0.000 O,P,R > M, O,P > N 10.411/ 0.000 O,R > M, O,P,R > N F, one way ANOVA test; SD, Standard Deviation; t, independent t-test; *, Tukey test. The mean total score of the GFBS was 66.94 ± 18.85, the mean BADLI score was 73.63 ± 26.92, and the mean TUHS score was 63.85 ± 21.89 (see Table 2 ). Table 2 Mean scores of the scales (n = 384) Scales Mean ± SD Min-Max GFBS 66.94 ± 18.85 25–125 BADLI 73.63 ± 26.92 10–100 TUHS 63.85 ± 21.89 32–157 GFBS: Geriatric Feelings of Burdensomeness Scale; BADLI: Barthel Index for Activities of Daily Living; TUHS: Technology Use Habits Scale A weak and negative relationship was found between the GFBS and BADLI scores of older adults (r=-0.484; p < 0.001). In addition, there was a weak and positive correlation between TUHS and BADLI scores (r = 0.192; p 0.001) (see Table 3 ). Table 3 The relationship between the mean scores of the scales (n = 384) GFBS BADLI TUHS GFBS r p 1 BADLI r p -0.484 0.000 1 TUHS r p 0.035 0.498 0.192 0.000 1 GFBS: Geriatric Feelings of Burdensomeness Scale; BADLI: Barthel Index for Activities of Daily Living; TUHS: Technology Use Habits Scale When the sociodemographic characteristics of older adults were compared with the scores of GFBS, BADLI, and TUHS, the mean scores of GFBS and BADLI differed significantly among all age groups (p < 0.05). The mean TUHS scores were higher in the 65–74 age group than in the 75–84 and 85 years and older age groups (p < 0.05). In addition, the TUHS scores of older adults with undergraduate/graduate, high school, and secondary school graduates were statistically significantly higher than those of illiterates (p < 0.05). The mean GFBS scores of older adults with moderate and poor income levels were higher than those with good income levels (p < 0.05). The mean GFBS scores of older adults with another chronic disease and the mean BADLI scores of older adults without another chronic disease were significantly higher (p < 0.05). The mean GFBS scores of older adults who did not use any digital tools were significantly higher than those who did, and the mean BADLI and TUHS scores of older adults who used any digital tools were significantly higher than those who did not (p < 0.05). There was a significant difference between the duration of digital tool use and the mean scores of GFBS, BADLI, and TUHS (p < 0.05). No difference was found between other sociodemographic characteristics and the GFBS, BADLI, and TUHS scores of older adults (see Table 1 ). The results of the multiple linear regression analysis are shown in Table 4 . BADLI and income level are predictors of feelings of burdensomeness among older adults. These two variables accounted for 27.4% of the variance (R = 0.523, R2 = 0.274, F = 23.691, p < 0.001). On the other hand, GFBS, age, and the use of any digital device were predictors of the activities of daily living of older adults. These three variables explained 46.3% of the variance (R = 0.680, R2 = 0.463, F = 54.157, p < 0.001). Finally, the level of technology use habits among older adults was influenced by the duration of digital tool use and educational level. These two variables explained 16.2% of the variance (R = 0.402, R2 = 0.162, F = 14.602, p < 0.001). Table 4 Demographic Predictors of GFBS, BADLI, and TUHS (n = 384) Independent Variable GFBS B (SE, β) BADLI B (SE, β) TUHS B (SE, β) Constant 100.019 (7.140, –) 126.529 (7.529, –) 40.806 (8.216, –) BADLI -0.315 (0.039–0.450) – 0.042 (0.048, 0.052) GFBS – -0.477 (0.058–0.334) – TUHS – 0.105 (0.050, 0.086) – Age 1.875 (1.610, 0.061) -14.347 (1.849 − 0.423) -2.581 (2.020–0.072) Income level -6.411 (1.586 − 0.179) – – Other chronic diseases -2.137 (1.978 − 0.048) 4.034 (2.426, 0.092) – Do you use a digital tool? 0.226 (2.377, 0.005) -13.614 (2.833 − 0.247) -0.114 (2.943 − 0.002) How long do you use the digital tool? 0.946 (0.875, 0.053) 1.535 (1.112, 0.084) 5.370 (1.093, 0.260) Educational level – – 3.517 (0.851, 0.199) Model Statistics F = 23.691, R = 0.523, R²=0.274, adj. R²=0.262, DW = 1.862 F = 54.157, R = 0.680, R²=0.463, adj. R²=0.454, DW = 1.706 F = 14.602, R = 0.402, R²=0.162, adj. R²=0.151, DW = 1.957 Note: GFBS = Geriatric Feelings of Burden Scale; BADLI = Barthel Activities of Daily Living Index; TUHS = Technology Use Habit Scale. B = Unstandardized coefficient, β = Standardized coefficient, DW = Durbin-Watson, adj. R²= Adjusted R-squared. Bold values indicate statistically significant predictors (p < 0.05). 4. Discussion This study aimed to examine the effects of feelings of burdensomeness and technology use habits on activities of daily living in older adults living in rural areas. The study findings demonstrated that sociodemographic factors such as age, education level, income level, presence of chronic diseases, and duration of digital device use had significant effects on feelings of burdensomeness, activities of daily living, and technology use habits. In addition, feelings of burdensomeness had a significant negative relationship with activities of daily living, whereas technology use had a positive relationship with activities of daily living. Multiple regression analyses supported these relationships and showed that feelings of burdensomeness and technology use were significant predictors of activities of daily living. This study found that the rate of ADL dependence increased with increasing age, whereas the use of digital tools decreased the level of dependence. While there is extensive evidence in the literature that age increases functional dependence in older individuals [ 22 , 23 ], there is also a growing number of studies showing that the use of digital tools reduces this dependence [ 24 – 26 ]. The increase in functional dependence rates in older individuals with advancing age is a reflection of natural declines in physical and cognitive capacity [ 27 ]. However, these findings indicate that the level of dependency decreases as digital tool use increases, and that access to and use of technology allows older adults in rural areas to maintain their independence by supporting their daily life activities. Digital technologies can improve the quality of life and functionality of older adults by providing convenience in functions such as health monitoring and communication. Particularly in rural areas, digital tools can mitigate the effects of age-related loss of function by partially overcoming barriers to accessing health services and social support networks. Therefore, promoting digital literacy and technology use against the increasing risk of addiction with age is critical for the sustainability of functional independence of older adults living in rural areas. The findings show that feelings of burdensomeness are negatively associated with activities of daily living in older adults living in rural areas, and these results are in line with previous literature [ 28 , 29 ]. In rural areas, older adults who experience difficulties with ADL cannot receive the help they need in a timely and adequate manner due to limitations in access to health services and inadequate social support networks [ 5 ]. Thus, the loss of independence and self-care skills becomes a psychological stressor, reducing individuals’ energy, motivation, and capacity for social interaction, leading to isolation, increased depressive symptoms, and a stronger feeling of burdensomeness [ 30 ]. When individuals cannot meet their own needs, they experience this feeling more intensely by thinking that they create an extra burden on their families. This finding suggests that the feeling of burdensomeness is not only limited to physical dysfunction but is also closely related to other social and health-related variables that negatively affect ADL, such as chronic diseases and low income level. Therefore, especially in economically disadvantaged and chronically ill older adults living in rural areas with chronic diseases, reducing the risk of ADL dependence is critical for the prevention and management of feelings of burdensomeness. In this context, strengthening preventive and curative health services for these risk groups is considered a priority requirement to improve the quality of life of this population. Another important finding of the study shows that technology plays a supportive role in the ADL of older adults living in rural areas. The contribution of digital technologies to the daily functioning of older adults becomes even more evident in rural living conditions. Our data confirms previous studies [ 24 – 26 ] showing that the use of digital tools can reduce the risk of ADL dependence and improve ADL. Digital tools enable older adults to make daily plans, maintain social relationships, and interact more actively with the environment [ 26 ]. Research shows that older adults who use digital technologies communicate more frequently with their social environment, visit family and friends more often, and participate more actively in community-based activities [ 24 , 25 ]. The findings also suggest that technological support contributes not only to individual independence but also to social integration through social participation. This highlights the potential of digital tools to mitigate the isolation caused by physical distance and limited access to services in rural areas. Enhancing older adults’ access to technology and their ability to use it can help them maintain both functional independence and social connections. In conclusion, digital technologies should be regarded not only as facilitators but also as protective resources in later life. 5. Limitations This study has some limitations. First, there are potential limitations in terms of the accuracy and reliability of the responses as the data are based only on the subjective assessments of older adults. In addition, since the study was limited to older adults living in rural areas, the findings may not be generalizable to the elderly population in urban or other geographical areas. 6. Conclusion This study found that sociodemographic factors have significant effects on feelings of burdensomeness, daily living activities, and technology use habits among older adults living in rural areas. Factors such as age, presence of chronic diseases, and income level were found to affect feelings of burdensomeness, while age, digital tool use, and feelings of burdensomeness were found to be determinants of activities of daily living. In addition, the duration of digital tool use and education level were found to affect technology use habits. These findings underscore the importance of interventions that are sensitive to sociodemographic characteristics in maintaining functional independence and reducing feelings of burdensomeness among older adults. Expanding the use of digital tools and improving access to technology can enhance older adults’ ability to perform daily activities, thereby strengthening their independence. Additionally, targeted support programs for those facing economic or health-related challenges may help alleviate feelings of burdensomeness. In conclusion, multidimensional and comprehensive strategies need to be implemented to improve the quality of life of the rural elderly population. In this context, accessible and culturally sensitive educational programs aimed at enhancing digital skills and promoting technological adaptation among rural older adults should be implemented. Declarations Ethical Considerations This study was conducted per the principles outlined in the Declaration of Helsinki [ 21 ]. This study was approved by the Non-Interventional Clinical Research Ethics Committee of Bayburt University (Date: 25.12.2024, Number: 248968). The older adults who agreed to participate in this study were informed about the purpose of the study, the data collection procedure, the confidentiality of the data and their right to withdraw from the study without giving any reason. Verbal and written consent was then obtained before data collection and recording of the interviews began. Finally, the participants’ voice recordings were stored in an encrypted file to which only the researchers of this study had access. The data was not shared with anyone except the researchers of this study and was then destroyed. Consent for publication Not Applicable. Competing interests The authors declare no competing interests. Funding None. Author Contribution Conceptualization: BB, EA. Data curation: BB, EA. Formal analysis: BB, EA. Funding acquisition: BB, EA. Investigation: BB, EA. 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Psychometric properties of the Turkish version of the Geriatric Feelings of Burdensomeness Scale (T-GFBS) in Turkish community-dwelling older adults. Geriatr Nurs. 2024;58:69–75. https://doi.org/10.1016/j.gerinurse.2024.05.011 . Mahoney FI, Barthel DW. Functional evaluation: The Barthel Index: A simple index of independence useful in scoring improvement in the rehabilitation of the chronically ill. Md State Med J. 1965;14:61–5. Küçükdeveci AA, Yavuzer G, Tennant A, Süldür N, Sonel B, Arasil T. Adaptation of the modified Barthel Index for use in physical medicine and rehabilitation in Turkey. Scand J Rehabil Med. 2000;32:87–93. Küçükvardar M. Teknoloji kullanım alışkanlığı ölçeği’nin geliştirilmesi: Geçerlik ve güvenirlik çalışmaları. Sosyal Beşerî Bilimler Araştırmaları Derg. 2020;21(46):40–56. Nashwan AJ, Joy GV. The 2024 Declaration of Helsinki Revision: Relevance to nursing research. J Adv Nurs; 2025. Sánchez-Rodríguez MA, Zacarías-Flores M, Correa-Muñoz E, Mendoza-Núñez VM. Advanced activities of daily living in community-dwelling older adults: A cross-sectional study of the Mexican Health and Aging Study (MHAS 2018). Healthc (Basel). 2023;11(14):2107. https://doi.org/10.3390/healthcare11142107 . Beltz S, Gloystein S, Litschko T, Laag S, van den Berg N. Multivariate analysis of independent determinants of ADL/IADL and quality of life in the elderly. BMC Geriatr. 2022;22(1):894. https://doi.org/10.1186/s12877-022-03469-2 . Kim J, Lee HY, Won CR, Barr T, Merighi JR. Older adults’ technology use and its association with health and depressive symptoms: Findings from the 2011 National Health and Aging Trends Study. Nurs Outlook. 2020;68(5):560–72. https://doi.org/10.1016/j.outlook.2020.06.007 . Tajika A, Nakagomi A, Miyaguni Y, Koga C, Kondo K, Ojima T. Internet use and higher-level functional capacity decline suppression in Japanese older adults with low education: JAGES 2016–2019 longitudinal study. JMIR Aging. 2024;7(1):e53384. https://doi.org/10.2196/53384 . Jeon GS, Choi K. Purposes of internet use and its impacts on physical and psychological health of Korean older adults. Healthc (Basel). 2024;12(2):244. https://doi.org/10.3390/healthcare12020244 . Edemekong PF, Bomgaars D, Sukumaran S, Levy SB. Activities of daily living. StatPearls [Internet]. StatPearls Publishing; 2019. https://www.ncbi.nlm.nih.gov/books/NBK538358/ . Treasure Island (FL). Mournet AM, Bower E, Van Orden KA. Domains of functional impairment and their associations with thwarted belonging and perceived burden in older adults. Clin Gerontol. 2020;43(1):95–103. https://doi.org/10.1080/07317115.2019.1665523 . Ren H, Liu C, Li J, Yang R, Ma F, Zhang M, et al. Self-perceived burden in the young and middle-aged inpatients with stroke: A cross-sectional survey. Rehabil Nurs. 2016;41(2):101–11. https://doi.org/10.1002/rnj.209 . Zhou L, Wang W, Ma X. The bidirectional association between the disability in activities of daily living and depression: A longitudinal study in Chinese middle-aged and older adults. BMC Public Health. 2024;24(1):1884. https://doi.org/10.1186/s12889-024-19421-w . Additional Declarations No competing interests reported. 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Introduction","content":"\u003cp\u003eOlder people living in rural areas are more vulnerable to health problems due to socioeconomic disadvantages, limited healthcare infrastructure, and lifestyle factors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Age-related declines in the ability to perform activities of daily living (ADLs) heighten this vulnerability. Reduced or impaired activities of daily living (ADL) lead to loss of independence in older adults living in rural areas, not only diminishing their quality of life but also placing a significant economic burden on the healthcare system [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Studies reveal that each year, approximately 10% of older adults who were able to independently maintain ADL in the previous year become in need of assistance for various reasons [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It is estimated that approximately 45% of older adults worldwide have difficulty in fulfilling their ADL [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. While these rates reveal that difficulties in ADL are an important health problem on a global scale, the conditions in which older adults living in rural areas live further complicate this problem.\u003c/p\u003e\u003cp\u003eDistance, transportation, and infrastructure inadequacies in rural areas make access to health services difficult [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and when combined with factors such as low income and education levels, disease management becomes very difficult [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], adversely affecting not only the physical health but also the psychological state of older adults. Indeed, limitations in ADL in older adults living in rural areas can trigger feelings of burdensomeness. This perception develops when a person sees himself/herself as a burden to his/her environment or society [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and it has been associated with many negative mental states such as depression, anxiety, loss of self-esteem, and suicidal thoughts [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the face of these psychosocial challenges and loss of independence, new approaches are needed to support older adults living in rural areas to maintain their ADL and reduce feelings of burdensomeness. In this context, technology emerges as a valuable tool that can promote greater independence in daily living and enhance quality of life for older adults in rural settings [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Technology offers important opportunities for older adults, especially as it strengthens social interactions, reduces depression, and supports cognitive skills [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, these potential impacts remain limited for older adults living in rural areas. Factors such as lack of digital infrastructure, limitations in internet and device access, low levels of digital literacy, and the digital divide negatively affect their access to and use of technology [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This causes older adults to lag behind in the digitalization process, limiting their ability to benefit from the supportive opportunities offered by technology in a population that is more likely to experience a loss of independence and feelings of burdensomeness due to socioeconomic disadvantages and the digital divide.\u003c/p\u003e\u003cp\u003eThus, barriers to accessing and using technology have negative impacts on older adults\u0026rsquo; physical and psychosocial functioning. Most of the existing research has focused on older adults living in urban centers, with only limited information available on the use of technology by older adults living in rural areas and its effects on ADL and feelings of burdensomeness. Since older adults in rural settings often have more limited infrastructure and digital resources, the effects of technology access and usage habits on ADL may differ from those of their peers in urban areas. Therefore, this study was conducted to determine the effects of feelings of burdensomeness and technology use habits on ADL in older adults living in rural areas.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study Design and Sample\u003c/h2\u003e\u003cp\u003eThis descriptive correlational study was conducted with 384 older adults living in rural districts and villages of two provinces in the Eastern Black Sea and Central Anatolia regions. The inclusion criteria were older adults aged 65 years or older, capable of understanding and answering the questions, and voluntarily agreeing to participate in the study. Exclusion criteria were older adults living in urban centers and those who were unable to understand and answer the questions due to cognitive or communicative disabilities. Considering the access difficulties and different demographic characteristics of older adults living in rural areas, participants suitable for the population of the study were reached through a purposive sampling method. Thus, it was aimed to obtain valid results with high data quality in accordance with the study objectives [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Data Collection Tools\u003c/h2\u003e\u003cp\u003eData were collected using the Information Form, Geriatric Feelings of Burdensomeness Scale (GFBS), Barthel Index for Activities of Daily Living (BADLI), and Technology Use Habits Scale (TUHS).\u003c/p\u003e\u003cp\u003e\u003cb\u003eInformation Form\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis form was originally developed by the researchers specifically for this study. It consists of nine items questioning the sociodemographic characteristics (age, gender, educational status, marital status, income level), current health conditions (chronic diseases), and technology use (use of a technological device, type of device used, duration of use) of older adults (Suppl. File S1).\u003c/p\u003e\u003cp\u003e\u003cb\u003eGeriatric Feelings of Burdensomeness Scale\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe scale used to assess the feelings of burdensomeness in older individuals was developed by Lutz and Fiske [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and adapted into Turkish by \u0026Ccedil;eki\u0026ccedil; and Y\u0026uuml;ksel in 2024 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It is a 5-point Likert-type scale consisting of 25 items scored from \u0026ldquo;1- Strongly Disagree\u0026rdquo; to \u0026ldquo;5- Strongly Agree.\u0026rdquo; The minimum and maximum scores that can be obtained from the scale are 25 and 125, respectively. As the scale score increases, the feeling of geriatric burdensomeness increases. The original Cronbach\u0026rsquo;s alpha internal consistency coefficient of the scale was 0.95 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In this study, Cronbach\u0026rsquo;s alpha coefficient was found to be 0.95.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBarthel Index for Activities of Daily Living\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe index was developed by Mahoney and Barthel in 1965 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and its Turkish adaptation\u0026rsquo;s validity and reliability were studied by K\u0026uuml;\u0026ccedil;\u0026uuml;kdeveci et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This index was used to determine the independence level of individuals in activities of daily living. Barthel Index scores vary between 0 and 100; 0\u0026ndash;20 points indicate complete dependence, 21\u0026ndash;61 points indicate heavy dependence, 62\u0026ndash;90 points indicate moderate dependence, 91\u0026ndash;99 points indicate mild dependence, and 100 points indicate independence. Studies using the Barthel Index take 60 points as the threshold, with scores above 60 indicating independent functioning [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In this study, Cronbach\u0026rsquo;s alpha coefficient of the scale was calculated as 0.90.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTechnology Use Habits Scale\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe Technology Use Habits Scale was developed by K\u0026uuml;\u0026ccedil;\u0026uuml;kvardar [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] to assess individuals\u0026rsquo; technology use habits. It is a five-point Likert-type scale consisting of 32 items and six factors: use and time, technological invasion, technology adoption, technological obsession, communication cycle, and spiritual/mental variables. The total scores obtained from the scale determine the addiction risk levels; 32\u0026ndash;57 points are considered as no addiction risk, 58\u0026ndash;83 points as low addiction risk, 84\u0026ndash;109 points as moderate addiction risk, 110\u0026ndash;135 points as high addiction risk, and 136\u0026ndash;160 points as very high addiction risk. In the study in which the scale was developed, the internal consistency coefficient (Cronbach\u0026rsquo;s alpha) was reported as 0.92 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In this study, the Cronbach\u0026rsquo;s alpha coefficient of the scale was found to be 0.96.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Data Collection\u003c/h2\u003e\u003cp\u003eData were collected between December 2024 and February 2025 from older adults living in rural districts and villages of two provinces in the Eastern Black Sea and Central Anatolia regions of Turkey. Face-to-face interviews were conducted with older adults who met the inclusion criteria and volunteered to participate in the study. The data collection process was carried out by the researchers either in participants\u0026rsquo; homes or village health centers and village heads\u0026rsquo; offices, when they were easily accessible. The interviews lasted an average of 20 minutes. The scale items were read aloud by the researchers to facilitate the participants\u0026rsquo; understanding of the questions, and additional explanations were made when necessary.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Statistical Analysis\u003c/h2\u003e\u003cp\u003eInternational Business Machines (IBM) Statistical Package for the Social Sciences (SPSS) version 25.0 (Armonk, NY: IBM Corp., 2022) was used for data analysis. In order to check the applicability of parametric tests, normality of the variables was evaluated by kurtosis and skewness coefficients. Normality was assessed based on the criterion that skewness and kurtosis values fell within the range of \u0026plusmn;\u0026thinsp;2 [George \u0026amp; Mallery, 2010]. An independent sample t-test was used to evaluate whether there was a statistically significant difference between the two groups. A one-way ANOVA test was applied to determine the difference between more than two groups. Pearson correlation analysis was used to examine whether there was a linear relationship between the variables. Factors affecting geriatric feelings of burdensomeness, activities of daily living, and technology use habits were determined by multiple linear regression analysis (enter method). Statistical significance level was accepted as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eAmong older adults, 64.3% were between 65\u0026ndash;74 years of age, 52.9% were female, and 36.7% were primary school graduates. 88.3% were married, 72.4% had middle income, and 76% had different chronic diseases. 78% used a digital device, and 41.4% used a digital device for 0\u0026ndash;30 min (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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 ruraly elderly individuals and comparison of mean scale scores (n\u0026thinsp;=\u0026thinsp;384)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGFBS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBADLI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTUHS\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e65\u0026ndash;74 year\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63.19\u0026thinsp;\u0026plusmn;\u0026thinsp;17.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e83.09\u0026thinsp;\u0026plusmn;\u0026thinsp;20.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e66.82\u0026thinsp;\u0026plusmn;\u0026thinsp;21.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e75\u0026ndash;84 year\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71.67\u0026thinsp;\u0026plusmn;\u0026thinsp;18.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61.74\u0026thinsp;\u0026plusmn;\u0026thinsp;26.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59.91\u0026thinsp;\u0026plusmn;\u0026thinsp;20.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e85 year and over\u003csup\u003eC\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e82.84\u0026thinsp;\u0026plusmn;\u0026thinsp;18.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33.40\u0026thinsp;\u0026plusmn;\u0026thinsp;27.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e52.24\u0026thinsp;\u0026plusmn;\u0026thinsp;24.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF/p\u003c/p\u003e\u003cp\u003e*\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\u003cp\u003e18.909/\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003cp\u003eC-B, C-A, B-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e74.976/\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA-B, A-C, B-C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.865/\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA-B, A-C\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67.67\u0026thinsp;\u0026plusmn;\u0026thinsp;18.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75.56\u0026thinsp;\u0026plusmn;\u0026thinsp;25.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e65.01\u0026thinsp;\u0026plusmn;\u0026thinsp;23.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66.13\u0026thinsp;\u0026plusmn;\u0026thinsp;19.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71.46\u0026thinsp;\u0026plusmn;\u0026thinsp;28.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e62.55\u0026thinsp;\u0026plusmn;\u0026thinsp;20.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003et/p\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\u003cp\u003e0.794/0.428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.493/0.136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.100/0.272\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIlliterate\u003csup\u003eD\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70.48\u0026thinsp;\u0026plusmn;\u0026thinsp;19.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e68.80\u0026thinsp;\u0026plusmn;\u0026thinsp;27.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e57.59\u0026thinsp;\u0026plusmn;\u0026thinsp;20.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiterate\u003csup\u003eE\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69.08\u0026thinsp;\u0026plusmn;\u0026thinsp;20.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70.98\u0026thinsp;\u0026plusmn;\u0026thinsp;30.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e63.49\u0026thinsp;\u0026plusmn;\u0026thinsp;20.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary School\u003csup\u003eF\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65.22\u0026thinsp;\u0026plusmn;\u0026thinsp;17.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e77.23\u0026thinsp;\u0026plusmn;\u0026thinsp;24.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e63.28\u0026thinsp;\u0026plusmn;\u0026thinsp;22.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary School\u003csup\u003eG\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63.30\u0026thinsp;\u0026plusmn;\u0026thinsp;15.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80.00\u0026thinsp;\u0026plusmn;\u0026thinsp;23.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e74.93\u0026thinsp;\u0026plusmn;\u0026thinsp;19.36\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh School\u003csup\u003eH\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.68\u0026thinsp;\u0026plusmn;\u0026thinsp;19.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71.80\u0026thinsp;\u0026plusmn;\u0026thinsp;29.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e76.04\u0026thinsp;\u0026plusmn;\u0026thinsp;20.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndergraduate/GraduateI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53.40\u0026thinsp;\u0026plusmn;\u0026thinsp;12.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e82.00\u0026thinsp;\u0026plusmn;\u0026thinsp;20.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e87.80\u0026thinsp;\u0026plusmn;\u0026thinsp;21.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF/p\u003c/p\u003e\u003cp\u003e*\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\u003cp\u003e2.239/0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.851/0.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.704/\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003cp\u003eG,H,I\u0026thinsp;\u0026gt;\u0026thinsp;D\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69.64\u0026thinsp;\u0026plusmn;\u0026thinsp;18.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71.88\u0026thinsp;\u0026plusmn;\u0026thinsp;23.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e64.84\u0026thinsp;\u0026plusmn;\u0026thinsp;20.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66.59\u0026thinsp;\u0026plusmn;\u0026thinsp;18.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e73.86\u0026thinsp;\u0026plusmn;\u0026thinsp;27.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e63.72\u0026thinsp;\u0026plusmn;\u0026thinsp;22.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003et/p\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\u003cp\u003e1.021/0.308\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.462/0.644\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.321/0.749\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIncome level\u003c/b\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow\u003csup\u003eJ\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72.88\u0026thinsp;\u0026plusmn;\u0026thinsp;19.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70.27\u0026thinsp;\u0026plusmn;\u0026thinsp;26.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e60.48\u0026thinsp;\u0026plusmn;\u0026thinsp;27.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle \u003csup\u003eK\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67.45\u0026thinsp;\u0026plusmn;\u0026thinsp;17.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e73.97\u0026thinsp;\u0026plusmn;\u0026thinsp;26.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e65.12\u0026thinsp;\u0026plusmn;\u0026thinsp;20.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGood\u003csup\u003eL\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58.07\u0026thinsp;\u0026plusmn;\u0026thinsp;19.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75.28\u0026thinsp;\u0026plusmn;\u0026thinsp;29.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e60.61\u0026thinsp;\u0026plusmn;\u0026thinsp;20.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF/p\u003c/p\u003e\u003cp\u003e*\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\u003cp\u003e8.883/\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003cp\u003eJ-L, K-L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.539/0.584\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.682/0.187\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOther chronic diseases\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e292\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.30\u0026thinsp;\u0026plusmn;\u0026thinsp;18.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71.64\u0026thinsp;\u0026plusmn;\u0026thinsp;27.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e64.55\u0026thinsp;\u0026plusmn;\u0026thinsp;22.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.65\u0026thinsp;\u0026plusmn;\u0026thinsp;19.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79.94\u0026thinsp;\u0026plusmn;\u0026thinsp;22.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e61.65\u0026thinsp;\u0026plusmn;\u0026thinsp;20.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003et/p\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\u003cp\u003e2.523/\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.598/\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.109/0.268\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDo you use a digital tool (computer, tablet, cell phone)?\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e302\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65.07\u0026thinsp;\u0026plusmn;\u0026thinsp;18.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79.42\u0026thinsp;\u0026plusmn;\u0026thinsp;22.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e65.86\u0026thinsp;\u0026plusmn;\u0026thinsp;21.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73.82\u0026thinsp;\u0026plusmn;\u0026thinsp;18.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e52.31\u0026thinsp;\u0026plusmn;\u0026thinsp;29.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e56.47\u0026thinsp;\u0026plusmn;\u0026thinsp;22.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003et/p\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\u003cp\u003e-3.790/\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.864/\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.493/\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHow long do you use digital tools?\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot using\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e74.66\u0026thinsp;\u0026plusmn;\u0026thinsp;16.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54.79\u0026thinsp;\u0026plusmn;\u0026thinsp;25.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e55.00\u0026thinsp;\u0026plusmn;\u0026thinsp;17.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u0026ndash;30 min\u003csup\u003eN\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69.28\u0026thinsp;\u0026plusmn;\u0026thinsp;18.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66.22\u0026thinsp;\u0026plusmn;\u0026thinsp;29.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e56.77\u0026thinsp;\u0026plusmn;\u0026thinsp;21.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u0026ndash;60 min\u003csup\u003eO\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.91\u0026thinsp;\u0026plusmn;\u0026thinsp;18.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80.54\u0026thinsp;\u0026plusmn;\u0026thinsp;21.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e68.65\u0026thinsp;\u0026plusmn;\u0026thinsp;19.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60\u0026ndash;90 min\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64.72\u0026thinsp;\u0026plusmn;\u0026thinsp;17.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e84.15\u0026thinsp;\u0026plusmn;\u0026thinsp;19.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e68.98\u0026thinsp;\u0026plusmn;\u0026thinsp;19.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e90\u0026ndash;120 min\u003csup\u003eR\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.55\u0026thinsp;\u0026plusmn;\u0026thinsp;22.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80.00\u0026thinsp;\u0026plusmn;\u0026thinsp;26.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e79.79\u0026thinsp;\u0026plusmn;\u0026thinsp;24.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e120 min and above\u003csup\u003eS\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54.00\u0026thinsp;\u0026plusmn;\u0026thinsp;11.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e102.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e85.00\u0026thinsp;\u0026plusmn;\u0026thinsp;12.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF/p\u003c/p\u003e\u003cp\u003e*\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\u003cp\u003e2.763/\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.814/\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003cp\u003eO,P,R\u0026thinsp;\u0026gt;\u0026thinsp;M, O,P\u0026thinsp;\u0026gt;\u0026thinsp;N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.411/\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003cp\u003eO,R\u0026thinsp;\u0026gt;\u0026thinsp;M, O,P,R\u0026thinsp;\u0026gt;\u0026thinsp;N\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eF, one way ANOVA test; SD, Standard Deviation; t, independent t-test; *, Tukey test.\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 mean total score of the GFBS was 66.94\u0026thinsp;\u0026plusmn;\u0026thinsp;18.85, the mean BADLI score was 73.63\u0026thinsp;\u0026plusmn;\u0026thinsp;26.92, and the mean TUHS score was 63.85\u0026thinsp;\u0026plusmn;\u0026thinsp;21.89 (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003eMean scores of the scales (n\u0026thinsp;=\u0026thinsp;384)\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScales\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMin-Max\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGFBS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.94\u0026thinsp;\u0026plusmn;\u0026thinsp;18.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25\u0026ndash;125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBADLI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73.63\u0026thinsp;\u0026plusmn;\u0026thinsp;26.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u0026ndash;100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTUHS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63.85\u0026thinsp;\u0026plusmn;\u0026thinsp;21.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32\u0026ndash;157\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eGFBS: Geriatric Feelings of Burdensomeness Scale; BADLI: Barthel Index for Activities of Daily Living; TUHS: Technology Use Habits Scale\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eA weak and negative relationship was found between the GFBS and BADLI scores of older adults (r=-0.484; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In addition, there was a weak and positive correlation between TUHS and BADLI scores (r\u0026thinsp;=\u0026thinsp;0.192; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No correlation was found between the GFBS and TUHS scores (r\u0026thinsp;=\u0026thinsp;0.035; p\u0026thinsp;\u0026gt;\u0026thinsp;0.001) (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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\u003eThe relationship between the mean scores of the scales (n\u0026thinsp;=\u0026thinsp;384)\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=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGFBS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBADLI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTUHS\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGFBS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBADLI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.484\u003c/p\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTUHS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003cp\u003e0.498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.192\u003c/p\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eGFBS: Geriatric Feelings of Burdensomeness Scale; BADLI: Barthel Index for Activities of Daily Living; TUHS: Technology Use Habits Scale\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhen the sociodemographic characteristics of older adults were compared with the scores of GFBS, BADLI, and TUHS, the mean scores of GFBS and BADLI differed significantly among all age groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mean TUHS scores were higher in the 65\u0026ndash;74 age group than in the 75\u0026ndash;84 and 85 years and older age groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In addition, the TUHS scores of older adults with undergraduate/graduate, high school, and secondary school graduates were statistically significantly higher than those of illiterates (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mean GFBS scores of older adults with moderate and poor income levels were higher than those with good income levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mean GFBS scores of older adults with another chronic disease and the mean BADLI scores of older adults without another chronic disease were significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mean GFBS scores of older adults who did not use any digital tools were significantly higher than those who did, and the mean BADLI and TUHS scores of older adults who used any digital tools were significantly higher than those who did not (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). There was a significant difference between the duration of digital tool use and the mean scores of GFBS, BADLI, and TUHS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No difference was found between other sociodemographic characteristics and the GFBS, BADLI, and TUHS scores of older adults (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results of the multiple linear regression analysis are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. BADLI and income level are predictors of feelings of burdensomeness among older adults. These two variables accounted for 27.4% of the variance (R\u0026thinsp;=\u0026thinsp;0.523, R2\u0026thinsp;=\u0026thinsp;0.274, F\u0026thinsp;=\u0026thinsp;23.691, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). On the other hand, GFBS, age, and the use of any digital device were predictors of the activities of daily living of older adults. These three variables explained 46.3% of the variance (R\u0026thinsp;=\u0026thinsp;0.680, R2\u0026thinsp;=\u0026thinsp;0.463, F\u0026thinsp;=\u0026thinsp;54.157, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Finally, the level of technology use habits among older adults was influenced by the duration of digital tool use and educational level. These two variables explained 16.2% of the variance (R\u0026thinsp;=\u0026thinsp;0.402, R2\u0026thinsp;=\u0026thinsp;0.162, F\u0026thinsp;=\u0026thinsp;14.602, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic Predictors of GFBS, BADLI, and TUHS (n\u0026thinsp;=\u0026thinsp;384)\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndependent Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGFBS\u003c/p\u003e\u003cp\u003eB (SE, β)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBADLI\u003c/p\u003e\u003cp\u003eB (SE, β)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTUHS\u003c/p\u003e\u003cp\u003eB (SE, β)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100.019 (7.140, \u0026ndash;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e126.529 (7.529, \u0026ndash;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40.806 (8.216, \u0026ndash;)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBADLI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-0.315 (0.039\u0026ndash;0.450)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.042 (0.048, 0.052)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGFBS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e-0.477 (0.058\u0026ndash;0.334)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTUHS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.105 (0.050, 0.086)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.875 (1.610, 0.061)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e-14.347 (1.849\u0026thinsp;\u0026minus;\u0026thinsp;0.423)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-2.581 (2.020\u0026ndash;0.072)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-6.411 (1.586\u0026thinsp;\u0026minus;\u0026thinsp;0.179)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther chronic diseases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.137 (1.978\u0026thinsp;\u0026minus;\u0026thinsp;0.048)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.034 (2.426, 0.092)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDo you use a digital tool?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.226 (2.377, 0.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e-13.614 (2.833\u0026thinsp;\u0026minus;\u0026thinsp;0.247)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.114 (2.943\u0026thinsp;\u0026minus;\u0026thinsp;0.002)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHow long do you use the digital tool?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.946 (0.875, 0.053)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.535 (1.112, 0.084)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e5.370 (1.093, 0.260)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducational level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e3.517 (0.851, 0.199)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel Statistics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eF\u0026thinsp;=\u0026thinsp;23.691, R\u0026thinsp;=\u0026thinsp;0.523, R\u0026sup2;=0.274, adj. R\u0026sup2;=0.262, DW\u0026thinsp;=\u0026thinsp;1.862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u0026thinsp;=\u0026thinsp;54.157, R\u0026thinsp;=\u0026thinsp;0.680, R\u0026sup2;=0.463, adj. R\u0026sup2;=0.454, DW\u0026thinsp;=\u0026thinsp;1.706\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u0026thinsp;=\u0026thinsp;14.602, R\u0026thinsp;=\u0026thinsp;0.402, R\u0026sup2;=0.162, adj. R\u0026sup2;=0.151, DW\u0026thinsp;=\u0026thinsp;1.957\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: GFBS\u0026thinsp;=\u0026thinsp;Geriatric Feelings of Burden Scale; BADLI\u0026thinsp;=\u0026thinsp;Barthel Activities of Daily Living Index; TUHS\u0026thinsp;=\u0026thinsp;Technology Use Habit Scale. B\u0026thinsp;=\u0026thinsp;Unstandardized coefficient, β\u0026thinsp;=\u0026thinsp;Standardized coefficient, DW\u0026thinsp;=\u0026thinsp;Durbin-Watson, adj. R\u0026sup2;= Adjusted R-squared. Bold values indicate statistically significant predictors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study aimed to examine the effects of feelings of burdensomeness and technology use habits on activities of daily living in older adults living in rural areas. The study findings demonstrated that sociodemographic factors such as age, education level, income level, presence of chronic diseases, and duration of digital device use had significant effects on feelings of burdensomeness, activities of daily living, and technology use habits. In addition, feelings of burdensomeness had a significant negative relationship with activities of daily living, whereas technology use had a positive relationship with activities of daily living. Multiple regression analyses supported these relationships and showed that feelings of burdensomeness and technology use were significant predictors of activities of daily living.\u003c/p\u003e\u003cp\u003eThis study found that the rate of ADL dependence increased with increasing age, whereas the use of digital tools decreased the level of dependence. While there is extensive evidence in the literature that age increases functional dependence in older individuals [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], there is also a growing number of studies showing that the use of digital tools reduces this dependence [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The increase in functional dependence rates in older individuals with advancing age is a reflection of natural declines in physical and cognitive capacity [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, these findings indicate that the level of dependency decreases as digital tool use increases, and that access to and use of technology allows older adults in rural areas to maintain their independence by supporting their daily life activities. Digital technologies can improve the quality of life and functionality of older adults by providing convenience in functions such as health monitoring and communication. Particularly in rural areas, digital tools can mitigate the effects of age-related loss of function by partially overcoming barriers to accessing health services and social support networks. Therefore, promoting digital literacy and technology use against the increasing risk of addiction with age is critical for the sustainability of functional independence of older adults living in rural areas.\u003c/p\u003e\u003cp\u003eThe findings show that feelings of burdensomeness are negatively associated with activities of daily living in older adults living in rural areas, and these results are in line with previous literature [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In rural areas, older adults who experience difficulties with ADL cannot receive the help they need in a timely and adequate manner due to limitations in access to health services and inadequate social support networks [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Thus, the loss of independence and self-care skills becomes a psychological stressor, reducing individuals\u0026rsquo; energy, motivation, and capacity for social interaction, leading to isolation, increased depressive symptoms, and a stronger feeling of burdensomeness [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. When individuals cannot meet their own needs, they experience this feeling more intensely by thinking that they create an extra burden on their families. This finding suggests that the feeling of burdensomeness is not only limited to physical dysfunction but is also closely related to other social and health-related variables that negatively affect ADL, such as chronic diseases and low income level. Therefore, especially in economically disadvantaged and chronically ill older adults living in rural areas with chronic diseases, reducing the risk of ADL dependence is critical for the prevention and management of feelings of burdensomeness. In this context, strengthening preventive and curative health services for these risk groups is considered a priority requirement to improve the quality of life of this population.\u003c/p\u003e\u003cp\u003eAnother important finding of the study shows that technology plays a supportive role in the ADL of older adults living in rural areas. The contribution of digital technologies to the daily functioning of older adults becomes even more evident in rural living conditions. Our data confirms previous studies [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] showing that the use of digital tools can reduce the risk of ADL dependence and improve ADL. Digital tools enable older adults to make daily plans, maintain social relationships, and interact more actively with the environment [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Research shows that older adults who use digital technologies communicate more frequently with their social environment, visit family and friends more often, and participate more actively in community-based activities [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The findings also suggest that technological support contributes not only to individual independence but also to social integration through social participation. This highlights the potential of digital tools to mitigate the isolation caused by physical distance and limited access to services in rural areas. Enhancing older adults\u0026rsquo; access to technology and their ability to use it can help them maintain both functional independence and social connections. In conclusion, digital technologies should be regarded not only as facilitators but also as protective resources in later life.\u003c/p\u003e"},{"header":"5. Limitations","content":"\u003cp\u003eThis study has some limitations. First, there are potential limitations in terms of the accuracy and reliability of the responses as the data are based only on the subjective assessments of older adults. In addition, since the study was limited to older adults living in rural areas, the findings may not be generalizable to the elderly population in urban or other geographical areas.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study found that sociodemographic factors have significant effects on feelings of burdensomeness, daily living activities, and technology use habits among older adults living in rural areas. Factors such as age, presence of chronic diseases, and income level were found to affect feelings of burdensomeness, while age, digital tool use, and feelings of burdensomeness were found to be determinants of activities of daily living. In addition, the duration of digital tool use and education level were found to affect technology use habits. These findings underscore the importance of interventions that are sensitive to sociodemographic characteristics in maintaining functional independence and reducing feelings of burdensomeness among older adults. Expanding the use of digital tools and improving access to technology can enhance older adults\u0026rsquo; ability to perform daily activities, thereby strengthening their independence. Additionally, targeted support programs for those facing economic or health-related challenges may help alleviate feelings of burdensomeness. In conclusion, multidimensional and comprehensive strategies need to be implemented to improve the quality of life of the rural elderly population. In this context, accessible and culturally sensitive educational programs aimed at enhancing digital skills and promoting technological adaptation among rural older adults should be implemented.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cb\u003eEthical Considerations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study was conducted per the principles outlined in the Declaration of Helsinki [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This study was approved by the Non-Interventional Clinical Research Ethics Committee of Bayburt University (Date: 25.12.2024, Number: 248968). The older adults who agreed to participate in this study were informed about the purpose of the study, the data collection procedure, the confidentiality of the data and their right to withdraw from the study without giving any reason. Verbal and written consent was then obtained before data collection and recording of the interviews began. Finally, the participants\u0026rsquo; voice recordings were stored in an encrypted file to which only the researchers of this study had access. The data was not shared with anyone except the researchers of this study and was then destroyed.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot Applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eNone.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: BB, EA. Data curation: BB, EA. Formal analysis: BB, EA. Funding acquisition: BB, EA. Investigation: BB, EA. Methodology: BB, EA. Project administration: BB. Resources: BB, EA. Software: BB, EA. Supervision: BB. Validation: BB, EA. Visualization: BB, EA. Writing \u0026ndash; original draft: BB, EA. Writing \u0026ndash; review and editing: BB, EA.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhang M, Yang XJ, Zhu HM, Tang Z, Li BY, Zhao DD. Epidemiological study of elderly constipation in Beijing. World J Gastroenterol. 2015;21(47):13368\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3748/wjg.v21.i47.13368\u003c/span\u003e\u003cspan address=\"10.3748/wjg.v21.i47.13368\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKankaya H, Karadakovan A. Yaşlı bireylerde g\u0026uuml;nl\u0026uuml;k yaşam aktivite d\u0026uuml;zeylerinin yaşam kalitesi ve yaşam doyumuna etkisi. 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BMC Public Health. 2024;24(1):1884. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12889-024-19421-w\u003c/span\u003e\u003cspan address=\"10.1186/s12889-024-19421-w\" targettype=\"DOI\" 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":true,"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":"Activities of daily living, burden, older adults, technology, rural","lastPublishedDoi":"10.21203/rs.3.rs-7293124/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7293124/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis study aims to examine feelings of burdensomeness and technology use habits and the effects of these factors on activities of daily living in older adults living in rural areas.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis correlational study was conducted with 384 older adults living in rural areas in two different regions of Turkey. Information Form, Geriatric Feelings of Burdensomeness Scale, Barthel Index for Activities of Daily Living and Technology Use Habits Scale were used as data collection tools.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThis study found significant negative and positive relationships, respectively, between feelings of burdensomeness and dependence on activities of daily living (r = -0.484, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and between technology use habits and independence in activities of daily living (r\u0026thinsp;=\u0026thinsp;0.192, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Scale mean scores differed significantly according to sociodemographic variables (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). According to the multiple regression analysis, the variables that most strongly predicted dependence on activities of daily living were feelings of burdensomeness, age, and use of digital devices, and the model explained 46.3% of the variance (R\u0026sup2; = 0.463, F\u0026thinsp;=\u0026thinsp;54.157, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The study results indicate that the sense of perceived burdensomeness in older adults in rural areas is associated with a loss of independence in daily living activities. Additionally, technology use habits were found to have a positive effect on independence in daily activities. Age, perceived burdensomeness, and digital device usage emerged as important factors influencing the level of dependence.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eOlder adults living in rural areas may experience loss of independence due to limitations in daily living activities and a heightened sense of perceived burdensomeness. Nurses can support these individuals by promoting technology use, enhancing digital literacy, and developing interventions tailored to rural infrastructure conditions to help them maintain greater independence in their daily activities. This approach may reduce feelings of burdensomeness while improving psychosocial well-being and overall quality of life.\u003c/p\u003e\u003ch2\u003eClinical trial number:\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e","manuscriptTitle":"The Role of Feelings of Burdensomeness and Technology Use in The Daily Activities of Older Adults Living in Rural Areas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-29 18:15:08","doi":"10.21203/rs.3.rs-7293124/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-03T09:55:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-07T13:10:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-07T09:29:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-25T00:30:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"125998194272220125481232286817894764227","date":"2025-09-22T02:58:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-18T23:00:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316293942073770693114947919183791548452","date":"2025-09-18T21:20:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196261633345165735884880884571552693995","date":"2025-09-18T18:54:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152919120887705731163446372583197172002","date":"2025-09-18T10:46:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"64454595451527694402410549263253214477","date":"2025-09-18T06:59:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-18T04:20:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-15T13:56:25+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-25T17:35:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-21T18:25:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-08-21T18:22:31+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":"f2f36cf4-1ce9-4616-a5af-e2488c820cfb","owner":[],"postedDate":"September 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T16:10:15+00:00","versionOfRecord":{"articleIdentity":"rs-7293124","link":"https://doi.org/10.1186/s12877-026-07073-x","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2026-01-31 15:58:16","publishedOnDateReadable":"January 31st, 2026"},"versionCreatedAt":"2025-09-29 18:15:08","video":"","vorDoi":"10.1186/s12877-026-07073-x","vorDoiUrl":"https://doi.org/10.1186/s12877-026-07073-x","workflowStages":[]},"version":"v1","identity":"rs-7293124","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7293124","identity":"rs-7293124","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}