Informatics for Health & Social Care最新文献

Tailored physical activity (PA) programs using digital health technologies in the home can promote family caregivers' (FCGs) physical function and psychological wellbeing. However, there is a gap in research for digital health PA interventions targeting older FCGs of persons with HF (HF-FCGs). The burden of caregiving for persons with HF may displace the FCG's self-care, including PA. Therefore, we examined older HF-FCGs' perceptions and attitudes toward three technology components (video-conferencing, fitness tracker, text messaging) that would be most useful in delivering a digital health PA program. Interviews were conducted with 13 HF-FCGs (≥65 years old) between January and April 2021. Directed content analysis was used and the analysis was guided by the adapted unified theory of acceptance and use of technology (UTAUT) model. In addition to HF-FCGs' perceptions and attitudes toward each technology component in each construct of the adapted UTAUT model (ease of use, usefulness, facilitating conditions), three additional factors were associated with intention to use technology. These were: (1) HF patients' positive experience, (2) digital skills, and (3) quality of internet connectivity. The findings provide digital health requirements for design and modification of a technology-supported PA program that engages older FCGs who care for persons with HF.

Participants: Four electronic databases were searched on March 6, 2020 including Scopus, PubMed, ISI, and Embase.

Methods: Our search consisted of concepts of "self-care," "elderly" and "Mobile device." English journal papers and, RCTs conducted for individuals older than 60 in the last 10 years were included. A narrative approach was used to synthesize the data due to the heterogeneous nature of the data.

Results: Initially, 3047 studies were obtained and finally 19 studies were identified for deep analysis. 13 outcomes were identified in m-health interventions to help older adults' self-care. Each outcome has at least one or more positive results. The psychological status and clinical outcome measures were all significantly improved.

Conclusion: According to the findings, it is not possible to draw a definite positive decision about the effectiveness of interventions on older adults because the measures are very diverse and have been measured with different tools. However, it might be declared that m-health interventions have one or more positive results and can be used along with other interventions to improve the health of older adults.

To compare responses to 40 common prenatal questions from Amazon's virtual assistant, Alexa, one year apart during the COVID pandemic. Participants: Two researchers replicated a prenatal query using unique Alexa devices. A conceptual content analysis was conducted where the researchers independently queried Alexa the identical questions from their 2020 study during the same one-week timeframe, between May 20, 2021 and May 27, 2021. Alexa's responses were compared to the 2020 study and the American College of Obstetricians and Gynecologists data and verified by one of the researchers, a Certified Nurse Midwife. Alexa provided accurate responses to 26 (65%) of the questions, an increase by 55 percentage points from 2020. Alexa was able to recite the symptoms of COVID-19 illness but was unable to provide a response to the two other COVID-specific questions. Compared to the 2020 query, Alexa provided more reputable sources for the responses including the CDC, WHO, NIH, and Mayo Clinic. Alexa's ability to provide more accurate, evidence-based responses was remarkably improved in 2021. Mobile health tools, like Amazon Alexa, are highly utilized by the public, particularly with limited healthcare access during the COVID-19 pandemic. Technology-based platforms should provide credible, evidence-based content.

To improve medication safety for residents in long-term care facilities (LTCFs), electronic medication administration records (eMARs) are widely adopted in Macao. This study aimed to (1) develop a logic model for adopting eMAR in LTCFs and (2) explore the contextual factors relevant to the implementation. Semi-structured interviews were conducted with key stakeholders (managers, doctors, nurses, pharmacy staff and other frontline workers) experienced with eMAR in LTCFs in Macao between February and March 2021. Purposive sampling was used for recruitment and thematic analysis followed the theoretical framework of the logic model. All 57 participants were positive about eMAR. Financial and nonfinancial resources were critical to adopting eMAR. eMAR was mostly used for its functions in documentation, e-prescribing and monitoring. Immediate output included simplified working process, reduced errors, closer monitoring of residents' conditions, and timely communication among staff. The outcomes mainly related to efficiency, safety and quality of care, workload redundancy, and data unification. Key influencing factors included eMAR flexibility, stability, and technical support. Adopting eMARs is highly consuming and the benefits in improving quality of care can only be realized with appropriate implementation, precise execution, regular evaluation and responsive adjustment. The proposed logic model framework serves as a roadmap for LTCFs, both current and future users of eMAR.

Using diabetes mobile apps for self-management of diabetes is one of the emerging strategies for controlling blood sugar levels and maintaining the wellness of patients with diabetes. This study aims to develop a strategy for thematically extracting user comments from diabetes mobile apps to understand the concern of patients with diabetes. Hence, 2678 user comments obtained from the Google Play Store are thematically analyzed with Non-negative Matrix Factorization (NMF) to identify the themes for describing positive, neutral, and negative sentiments. These themes are used as the ground truth for developing a 10-fold cross-validation ensemble Multilayer Artificial Neural Network (ANN) model following the Bag of Word (BOW) analysis of lemmatized user comments. The result shows that a total of 41.24% of positive sentimental users identified the diabetes mobile apps as Effective for Blood Sugar Monitoring (EBSM), 32.36% with neutral sentiments are mostly impressed by the Information Quality (IQ), whereas 40.81% of unhappy users are worried about the Poor Information Quality (PIQ). The prediction accuracy of the ANN model is 89%-97%, which is 5%-48% better than other predominant algorithms. It can be concluded from this study that diabetes mobile apps with a simple user interface, effective data storage and security, medication adherence, and doctor appointment scheduling are preferred by patients with diabetes.

Social isolation and loneliness are associated with negative health outcomes, physical as well as cognitive. Information and communication technology (ICT) can be effective tools for preventing and tackling social isolation and loneliness among older people. Our objective was to evaluate the feasibility of the Fik@ room, a web platform for social interaction designed for older people. A mixed methods design was applied, where both quantitative and qualitative data were collected during a 12-week period (n = 28, Md age 74). Experiences of loneliness were reduced using the Fik@ room. The results highlight the feasibility issues surrounding the recruitment process, adoption, pattern of use, usability, support service, and technical infrastructure. In particular, the importance of offering ICT solutions with few technical issues, and to provide easily accessible and appropriate support. The Fik@ room is a feasible tool for older people to develop new friendships, reduce loneliness, and grow their social networks. However, it is not a communication option that fits all. The results offer a compilation of feasibility issues that can serve as an inspirational guide in the design and implementation of similar technologies.

This study aimed to explore the effects of health technologies on the promotion of health through physical activities of older persons. Following PRISMA guidelines, a systematic review of relevant articles published prior to 2020 was conducted from selected indices such as COCHRANE, PubMed, Science Direct, Proquest, including the use of hand search procedure. Twenty-seven articles were analyzed with significant findings influential to older people nursing: types of health technologies used for promoting physical activity; effects of technology use in promoting physical activity of older person care; and aspects that need to be considered in technology use among older persons. Characteristics of technologies were accuracy, usefulness, reliability, comfort, safety, and relevancy. Most technologies promoting physical activities for older people were wearable technologies that use artificial intelligence. Altogether, these technologies influenced overall healthcare behaviors of older persons. With healthcare technology efficiencies, proficiencies, and dependencies, technology-based healthcare have served older people well. Most technologies for older people care, such as wearables, reliably produce characteristics enhancing dependency and accuracy of bio-behavioral information influencing physical activities of older persons. Health technologies foster the values of physical activities among older persons thereby promoting healthy living.

About 40 000 individuals depend on assisted living in long-term care facilities in Norway. Around 80% of these have a cognitive impairment or suffer from dementia. This actualizes the need for activities that are tailored to individual needs. For some users, technology-assisted participation in communal activities can be an alternative approach to increasing their quality of life. To gain insight about the experiences of residents and healthcare professionals in long-term care facilities when interacting with the social robot Pepper. This is a qualitative pilot study. After a series of interventions with the robot in a long-term care facility, data were collected through individual interviews with healthcare professional and residents. These were analyzed through a qualitative content analysis. A thematic analysis identified three major themes: 1) Activity, joy and ambivalence, 2) challenges when introducing social robots in contexts of care and 3) thoughts about the future. Although employees and residents report that they enjoyed interactions with the social robot, highlighting opportunities for novel types of activities and action that differed from the daily routine, the subjects articulated several concerns and challenges. Developments in intelligent social robots is still in its infancy, despite much hype.

Use of mobile health applications (mHealth apps) is becoming increasingly popular for the management of chronic illnesses, but mHealth-based intervention studies often have limitations associated with subject recruitment and retention. In this synopsis, we focus on targeted aspects of mHealth-based intervention studies, specifically: (i) subject recruitment, (ii) cohort sizes, and (iii) retention rates. We used the Google Scholar (meta-search) and Galileo search engines to identify sample articles focusing on mHealth apps and interventions published between 2010 and 2020 and selected 21 papers for detailed review. Most studies recruited relatively small cohorts (minimum: 20, maximum: 510). Retention rates had high variance with only five studies managing >80% subject retention throughout the study duration, 10.4% being the lowest. Eighty-five percent of the studies expressed concerns regarding study duration, app usage, and lack of proper implementation. The use of mHealth interventions generally yielded positive outcomes, but most studies discussed facing challenges associated with recruitment and retention. There is a clear need to identify strategies for recruiting larger cohorts and improving retention rates, and ultimately increasing the reliability of mHealth app-based intervention studies. We advise that potential underutilized opportunities lie at the intersection of mHealth and social media to address the limitations identified in the synopsis.

Fitness application service providers are offering rewards, such as points to users as incentives for service use. However, it is questionable whether this reward offering is an effective measure for persuading consumers to use fitness applications continuously. This study examines how reward affects continued use of fitness applications. An online survey was conducted on 268 people who actually used the fitness application. Respondents were divided into two groups at random, an extrinsic reward group and a non-extrinsic reward group, to check the effects of the rewards. Structural equation modeling was used for data analysis. Factors influencing a user's continuous intention to use fitness applications will vary depending on whether rewards are provided. For the extrinsic reward group, perceived enjoyment and perceived privacy protection were significant variables to continue use of a fitness application. However, for the non-extrinsic reward group, monetary value was a significant variable. For continuous use of a fitness application, if rewards are provided, it is necessary to emphasize intrinsic factors such as fun rather than extrinsic factors such as savings and cost. On the other hand, without rewards, it is necessary to highlight extrinsic factors rather than intrinsic factors.