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PURPOSE: To investigate the agreement between an online nurse-assisted eye-screening tool and reference tests in older adults receiving home healthcare and to collect user experiences. METHODS: Older adults (65+) receiving home healthcare were included. Home healthcare nurses assisted in administering the eye-screening tool at participants' homes. Approximately 2 weeks later, a researcher administered reference tests at participants' homes. Experiences from participants and home healthcare nurses were collected. Agreement in outcomes (distance and near visual acuity, with the latter being measured using two different optotypes, and macular problems) between the eye-screening tool and reference clinical testing was compared. A difference of less than ±0.15 logMAR was considered acceptable. RESULTS: A total of 40 participants were included. Here, we describe the results for the right eye; results for the left eye were similar. The mean difference between the eye-screening tool and reference tests for distance visual acuity was 0.02 logMAR. The mean difference between the eye-screening tool and reference tests using two different optotypes for near visual acuity was 0.06 and 0.03 logMAR, respectively. The majority of the individual data points were within the ±0.15 logMAR threshold (75%, 51% and 58%, respectively). The agreement between tests for macular problems was 75%. Participants and home healthcare nurses were generally satisfied with the eye-screening tool, although remarks for further improvements were made. CONCLUSIONS: The eye-screening tool is promising for nurse-assisted eye screening in older adults receiving home healthcare, with the mostly satisfactory agreement. After implementing the eye-screening tool in practice, cost-effectiveness needs to be investigated.
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Atenção à Saúde , Humanos , Idoso , Acuidade VisualRESUMO
BACKGROUND: Recently, many studies have been conducted to investigate the effects of exergames on the social well-being of older adults. OBJECTIVE: The aim of this paper is to synthesize existing studies and provide an overall picture on the social effects of exergames on older adults. METHODS: A comprehensive literature search with inclusive criteria was conducted in major social science bibliographic databases. The characteristics of exergames, participants, methodology, as well as outcome measurements were extracted from the relevant studies included in the review. The bibliometric and altmetric outreach of the included studies were also investigated. RESULTS: A total of 10 studies were included in the review, with 8 studies having used the Nintendo Wii platform. Most of the studies recruited healthy older adults from local communities or senior activity centers. Three groups of social-related outcomes have been identified, including emotion-related, behavior-related, and attitude-related outcomes. A metric analysis has shown that the emotion-related and behavior-related outcomes received high attention from both the academic community and social media platforms. CONCLUSIONS: Overall, the majority of exergame studies demonstrated promising results for enhanced social well-being, such as reduction of loneliness, increased social connection, and positive attitudes towards others. The paper also provided implications for health care researchers and exergame designers.
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Terapia por Exercício/efeitos adversos , Comportamento Social , Jogos de Vídeo/psicologia , Idoso , Terapia por Exercício/métodos , Feminino , Humanos , MasculinoRESUMO
BACKGROUND: An increasing aging population has become a pressing problem in many countries. Smart systems and intelligent technologies support aging in place, thereby alleviating the strain on health care systems. OBJECTIVE: This study aims to identify decision-making factors involved in the adoption of smart home sensors (SHS) by older adults in Singapore. METHODS: The study involved 3 phases: as an intervention, SHS were installed in older adults' homes (N=42) for 4 to 5 weeks; in-depth semistructured interviews were conducted with 18 older adults, 2 center managers, 1 family caregiver, and 1 volunteer to understand the factors involved in the decision-making process toward adoption of SHS; and follow-up feedback was collected from 42 older adult participants to understand the reasons for adopting or not adopting SHS. RESULTS: Of the 42 participants, 31 (74%) adopted SHS after the intervention, whereas 11 (26%) did not adopt SHS. The reasons for not adopting SHS ranged from privacy concerns to a lack of family support. Some participants did not fully understand SHS functionality and did not perceive the benefits of using SHS. From the interviews, we found that the decision-making process toward the adoption of SHS technology involved intrinsic factors, such as understanding the technology and perceiving its usefulness and benefits, and more extrinsic factors, such as considering affordability and care support from the community. CONCLUSIONS: We found that training and a strong support ecosystem could empower older adults in their decision to adopt technology. We advise the consideration of human values and involvement of older adults in the design process to build user-centric assistive technology.
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BACKGROUND: The behavior of medication nonadherence is distinguished into primary and secondary nonadherence. Primary nonadherence (PNA) is not as thoroughly studied as secondary nonadherence. OBJECTIVE: To explore and synthesize contributing factors to PNA based on the existing body of literature. METHODS: A search was performed on the PubMed, PsycINFO, CINAHL, and ScienceDirect databases to identify previously published scholarly articles that described the "factors," "reasons," "determinants" or "facilitators" of PNA. The alternate spelling of "nonadherence" was used as well. The effect that the articles had in the research community, as well as across social media, was also explored. RESULTS: 22 studies met the inclusion criteria for this review. The PNA factors that the studies identified were diverse, spanning economic, social, and medical dimensions. A multilevel classification method was applied to categorize the factors into 5 broad groups-patient, medication, health care provider, health care system, and socioeconomic factors. Patient factors were reported the most. Some groups overlapped and shared a dynamic causal relationship where one group influenced the outcome of the other. CONCLUSIONS: Like all nonadherence behaviors, PNA is multifaceted with highly varied contributing factors that are closely associated with one another. Given the multidimensional nature of PNA, future intervention studies should focus on the dynamic relationship between these factor groups for more efficient outcomes. DISCLOSURES: This research was supported by the National Research Foundation Singapore under its National Innovation Challenge on Active and Confident Ageing (Award No. MOH/NIC/CAHIG03/2016) and administered by the Singapore Ministry of Health's National Medical Research Council. This research was also supported by the National Research Foundation within the Prime Minister's Office of Singapore, under its Science of Research, Innovation and Enterprise Programme (SRIE Award No. NRF2014-NRF-SRIE001-019). The authors have no relevant conflicts of interest to disclose.