How the use of mobile fitness technology influences older adults’ physical and psychological well-being

Psychological big data is observed based on behavior or habitual features of people for determining the influencing factors. The influencing factor information is used for analysis in treatment, recommendation, and diagnosis of psychological disorders, depression, etc. Identifying the influencing factors is challenging due to irregular behaviors and responses from young people. However, for organizing the quality of observation, this article introduces a behavioral pattern recognition method (BPRM) with associating quality (AQ) identification. This method observes the different day-to-day behaviors of young people and recurrently associates them. The observations are aided through conventional wireless networks for swift interconnection and information sharing. The association is organized based on the transfer learning state processing model. Based on the state processing, the behavior-based psychological data are classified as abnormal and normal. If the association throughout the state changes remains the same, then it is organized or else the new data are identified as an influencing factor. The state changes are validated using random observation intervals that result in series data associations. Based on the actual data extraction, the proposed method improves the prediction accuracy and reduces false rate and processing time, whereas it improves the organization precision.

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“…e test is also used to nd out the depression rate, fear rate, and personality rate of college students [3].…”

Section: Introductionmentioning

confidence: 99%

“…is increases the accuracy rate in the behavior detection process, which enhances the performance of the system [3,5].…”

Section: Introductionmentioning

confidence: 99%

Prediction and Influencing Factors of Big Data on College Students’ Positive Psychological Quality under Mobile Wireless Network

Jiang

Zhang

2022

Mobile Information Systems

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“…Therefore, scale items for construct opportunity and motivation enhancing were adopted from Liao (2006) and Bag et al (2021). Moving further into psychological well-being and empowerment constructs, scale items were adopted from Appelbaum et al (2000), Rahi (2021), Spreitzer (1995) and Suh and Li (2022). Transformational leadership items were adopted from Scuotto et al (2022) and Nguyen et al (2022).…”

Section: Methodsmentioning

confidence: 99%

Fostering employee work engagement and sustainable employment during COVID-19 crisis through HR practices, employee psychological well-being and psychological empowerment

Rahi

2023

ICT

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Purpose This study aims to investigate employee behavior toward work engagement with an integrative research framework that combines human resource practices, employee psychological empowerment and well-being. Moreover, the moderating effect of transformational leadership is tested between employee engagement at workplace during crisis such as COVID-19 and sustainable employment. Design/methodology/approach This study empirically investigates research framework with 353 responses retrieved from employees working in private sector organizations. The data were collected through structured, closed-ended questionnaires. For inferential analysis, structural equation modeling approach has been used. To test the predictive power of the research framework, blindfolding procedure Q2 is incorporated. Findings Statistical findings indicate that HR compensation, HR training, opportunity enhancing, motivation enhancing, psychological well-being and empowerment have explained substantial variance (R2 = 67.5%) in employee work engagement during crisis. Concerning with sustainable employment, the transformational leadership and work engagement have shown significant variance (R2 = 20.6%) in determining sustainable employment. Moving further psychological empowerment has revealed maximum effect size (f2) to determine employee engagement behavior at work place during pandemic crisis. The blindfolding procedure Q2 has exhibited substantial power to predict employee work engagement and sustainable employment during crisis such as COVID-19 pandemic. Practical implications This study has several contributions to theory and practice. Theoretically, this study develops an integrative research framework with the help of human resource practices and employee psychological factors such as employee well-being and empowerment. Therefore, practically, this research suggests that factors such as opportunity enhancing, transformational leadership and employee psychological empowerment need managerial attention to increase employee engagement at workplace and sustainable employment during pandemic crisis. Social implications With the growing concerns of layoff during pandemic crisis, employees have shown lack of interest at workplace because of psychological fears. Nevertheless, this study has established that policymakers could enhance employee engagement at workplace and sustainable employment during crisis by redesigning HR practices and improving employee psychological well-being and empowerment. In addition to that, employee psychological well-being and empowerment are considered healthy factors for human beings and nurture society at large. Originality/value This research is original as it establishes an integrative research framework grounded in HR practices, employee psychological empowerment and employee psychological well-being to investigate employee behavior at work place during crisis such as pandemic. In addition to that, this study has enriched leadership literature by examining the moderating effect of transformational leadership between employee work engagement and sustainable employment.

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“…There are several different kinds of features implemented in digital wellness technologies to support PA; these features can be found in devices, applications, and services. Commonly used ones include PA tracking features (e.g., Mendiola et al, 2015;Wang & Collins, 2021), data management features (e.g., James et al, 2019;Suh & Li, 2022), goal-setting features (e.g., Gordon et al, 2019;Kirwan et al, 2013), and some novel solutions even include digital coaching features (e.g., Kari & Rinne, 2018;Kettunen et al, 2020). Besides these utility related features, social support features (e.g., Suh & Li, 2022;Sullivan & Lachman, 2017) are common, as well as gamification (Kari, Piippo, et al, 2016;Koivisto & Hamari, 2019) and exergaming features (e.g., Kari, 2014;Loos & Zonneveld, 2016), which are typically implemented to make PA more enjoyable.…”

Section: Digital Wellness Technologies In Promoting Pa Among Older Ad...mentioning

confidence: 99%

“…Commonly used ones include PA tracking features (e.g., Mendiola et al, 2015;Wang & Collins, 2021), data management features (e.g., James et al, 2019;Suh & Li, 2022), goal-setting features (e.g., Gordon et al, 2019;Kirwan et al, 2013), and some novel solutions even include digital coaching features (e.g., Kari & Rinne, 2018;Kettunen et al, 2020). Besides these utility related features, social support features (e.g., Suh & Li, 2022;Sullivan & Lachman, 2017) are common, as well as gamification (Kari, Piippo, et al, 2016;Koivisto & Hamari, 2019) and exergaming features (e.g., Kari, 2014;Loos & Zonneveld, 2016), which are typically implemented to make PA more enjoyable. However, technology features alone are not enough for continued digital wellness technology use among older adults, and a successful integration of the used technology as part of the user's daily life is influenced more by the perceived added value to life (Moore et al, 2021).…”

Section: Digital Wellness Technologies In Promoting Pa Among Older Ad...mentioning

confidence: 99%

Physical Activity Tracker Application in Promoting Physical Activity Behavior among Older Adults: A 24-month Follow-Up Study

Kari

Makkonen

Carlsson³

2022

J Aging Health

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Objectives To investigate whether and how PA tracker application use supports PA behavior among older adults during the first 24 months of use. Methods: The changes in PA levels (i.e., time spent in different PA intensities) and between PA categories (i.e., low, moderate, or high based on total PA) were examined between three different time points: before taking the application into use (t0), after 12 months of use (t1), and after 24 months of use (t2). The data was collected by using the International Physical Activity Questionnaire modified for the elderly (IPAQ-E). Results: A statistically significant increase was observed in walking (χ2 (2) = 29.741, p < .001), moderate PA (χ2 (2) = 6.327, p = .042), and total PA levels (χ2 (2) = 11.489, p = .003). The increase was observed between t0 and t1 as well as between t0 and t2. The overall changes between PA categories were statistically significant between t0 and t1 (χ2 (3) = 15.789, p = .001) as well as between t0 and t2 (χ2 (3) = 14.745, p = .002). There were more increasingly active (moved to a higher PA category) than decreasingly active (moved to a lower PA category) participants. Discussion: Overall, the results indicate that PA tracker application use can promote PA behavior among older adults. Stakeholders that work with PA programs and PA promotion, as well as individual users, can utilize digital wellness technologies in supporting PA promotion, especially in exceptional times, like the COVID-19 pandemic, when health care restrictions prevent general gatherings.

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How the use of mobile fitness technology influences older adults’ physical and psychological well-being

Cited by 19 publications

References 53 publications

Prediction and Influencing Factors of Big Data on College Students’ Positive Psychological Quality under Mobile Wireless Network

Prediction and Influencing Factors of Big Data on College Students’ Positive Psychological Quality under Mobile Wireless Network

Fostering employee work engagement and sustainable employment during COVID-19 crisis through HR practices, employee psychological well-being and psychological empowerment

Physical Activity Tracker Application in Promoting Physical Activity Behavior among Older Adults: A 24-month Follow-Up Study

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