Factors influencing hip protector use among community-dwelling older adults

2010 ◽  
Vol 16 (4) ◽  
pp. 235-239
Author(s):  
S. J. Blalock ◽  
K. B. Demby ◽  
K. L. McCulloch ◽  
J. A. Stevens
2018 ◽  
Vol 21 (1) ◽  
pp. 12-21
Author(s):  
Jae Soon Yoo ◽  
Je Hyun Kim ◽  
Jeongeun Kim ◽  
Hyejin Kim ◽  
Seungyu Oh ◽  
...  

2021 ◽  
Vol 9 ◽  
Author(s):  
Huanhuan Huang ◽  
Zhiyu Chen ◽  
Songmei Cao ◽  
Mingzhao Xiao ◽  
Liling Xie ◽  
...  

Objective: To explore the Chinese community-dwelling intention of older adults to adopt gerontechnology and its influencing factors.Design: A mixed-methods sequential explanatory design with an inductive approach was employed. In phase 1, a self-made questionnaire was administered from August 2018 to December 2019. Multifactor logistic regression was used to analyze the adoption intention and factors influencing the use of gerontechnology. In phase 2, participants completed a semistructured interview to explore the adoption intention of a specific form of gerontechnology, Smart Aged Care Platform, from May to July 2020.Setting: Twelve communities in three districts of Chongqing, China.Participants: Community-dwelling older adults were included.Results: A total of 1,180 older adults completed the quantitative study; two-thirds of them (68.7%) showed adoption intention toward gerontechnology. Nineteen participants (10 users and nine nonusers) completed the qualitative study and four themes were explored. Through a summarized understanding of the qualitative and quantitative data, a conceptual model of influencing factors, namely, predictive, enabling, and need factors, was constructed.Conclusions: This study reveals that most Chinese community-dwelling older adults welcome the emergence of new technologies. However, there was a significant difference in the adoption intention of gerontechnology in Chinese community-dwelling older adults based on their sociodemographic and psychographic characteristics. Our findings extend previous technology acceptance models and theories and contribute to the existing resource base.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jasmine C. Mah ◽  
Susan J. Stevens ◽  
Janice M. Keefe ◽  
Kenneth Rockwood ◽  
Melissa K. Andrew

Abstract Background Older adults want to live at home as long as possible, even in the face of circumstances that limit their autonomy. Home care services reflect this emergent preference, allowing older adults to ‘age in place’ in familiar settings rather than receiving care for chronic health conditions or ageing needs in an institutionalized setting. Numerous social factors, generally studied in isolation, have been associated with home care utilization. Even so, social circumstances are complex and how these factors collectively influence home care use patterns remains unclear. Objectives To provide a broad and comprehensive overview of the social factors influencing home care utilization; and to evaluate the influence of discrete social factors on patterns of home care utilization in community-dwelling older adults in high-income countries. Methods A scoping review was conducted of six electronic databases for records published between 2010 and 2020; additional records were obtained from hand searching review articles, reference lists of included studies and documents from international organisations. A narrative synthesis was presented, complemented by vote counting per social factor, harvest plots and an evaluation of aggregated findings to determine consistency across studies. Results A total of 2,365 records were identified, of which 66 met inclusion criteria. There were 35 discrete social factors grouped into four levels of influence using a socio-ecological model (individual, relationship, community and societal levels) and grouped according to outcome of interest (home care propensity and intensity). Across all studies, social factors consistently showing any association (positive, negative, or equivocal in pattern) with home care propensity were: age, ethnicity/race, self-assessed health, insurance, housing ownership, housing problems, marital status, household income, children, informal caregiving, social networks and urban/rural area. Age, education, personal finances, living arrangements and housing ownership were associated with home care intensity, also with variable patterns in utilization. Additional community and societal level factors were identified as relevant but lacking consistency across the literature; these included rurality, availability of community services, methods of financing home care systems, and cultural determinants. Conclusion This is the first literature review bringing together a wide range of reported social factors that influence home care utilization. It confirms social factors do influence home care utilization in complex interactions, distinguishes level of influences at which these factors affect patterns of use and discusses policy implications for home care reform.


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