Voice Assistant Reminders for Pain Self-Management Tasks in Aging Adults

Using Voice Assistant Systems to Improve Dietary Recall among Older Adults: Perspectives of Registered Dietitians

Dietary assessments are important clinical tools used by Registered Dietitians (RDs). Current methods pose barriers to accurately assess the nutritional intake of older adults due to age-related increases in risk for cognitive decline and more complex health histories. Our qualitative study explored whether implementing Voice assistant systems (VAS) could improve current dietary recall from the perspective of 20 RDs. RDs believed the implementing VAS in dietary assessments of older adults could potentially improve patient accuracy in reporting food intake, recalling portion sizes, and increasing patient-provider efficiency during clinic visits. RDs reported that low technology literacy in older adults could be a barrier to implementation. Our study provides a better understanding of how VAS can better meet the needs of both older adults and RDs in managing and assessing dietary intake.

What does the literature say about the use of personal voice assistants in older adults? A scoping review

PURPOSE

With ageing, people may experience loss of function which may be compensated for by using technology. This review aims to examine the range and extent of personal voice assistants used for older adults living in the community, their technology readiness level, associated outcomes, and the strength of evidence.

METHODS

This study complies with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. The CINAHL, EMBASE, IEEE Xplore, MEDLINE, APA PsycInfo, Scopus, and Web of Science databases were used to identify studies that explored the use of personal voice assistant technology with older adults living in the community.

RESULTS

The search yielded 499 studies, 22 of which were included for final analysis. Consumer technologies (e.g., Amazon Alexa) were evaluated in 18 studies, while four studies evaluated novel technologies. Most of the studies exploring the use of personal voice assistants with older adults evaluated technology usability and acceptance. Personal voice assistants were most commonly used by older adults for setting up reminders, searching for information, and checking the weather. None of the included studies evaluated the effectiveness of the technologies' ability to improve the management of health conditions or to facilitate the functional capacity of older adults.

CONCLUSIONS

More research is needed to determine the possible impact of using personal voice assistants for older adults living in the community. IMPLICATIONS FOR REHABILITATIONThe TRL for personal voice assistants is high.Personal voice assistants are currently being used by older adults for a range of activities including setting up reminders, searching for information, and checking the weather.Whether personal voice assistants can support older adults' ability to age in place is still unknown.The use of personal voice assistants in older adults is ripe for future enquiry and intervention-based research.

Older adults' intention to use voice assistants: Usability and emotional needs

Population aging is a global problem, and improving the well-being of older adults is an urgent issue. Voice assistants (VAs) offer hands-free voice control and friendly human-computer interaction, making them a significant solution to address the aging problem. Most extant research on VAs is fragmented, and there are relatively few studies conducted from the perspective of emotional needs. This work proposes a comprehensive research model extending the technology acceptance model (TAM) by incorporating the influencing factors subordinate to two research directions: usability and emotional needs. Usability needs include three factors: perceived convenience, security/privacy, and Internet self-efficacy. Emotional needs include humanized interaction, perceived enjoyment, and perceived companionship. A structural equation model (SEM) was used to validate the model empirically with a sample of 425 older users of VAs. The analysis results are quite consistent with the research assumptions, and the findings illustrate that companionship is the most critical factor affecting older adults' intention to adopt VA use, which demonstrates the pivotal role of VAs in meeting the emotional needs of the elderly. The most unexpected observation was seen for the relationship between perceived ease of use and behavioral intention, which was non-significant. This result confirms that when a technology is perceived as very easy to use, perceived ease of use has little to no impact on individuals' intention to use that technology. The novelty of this study lies in the investigation of older adults' behavioral intentions toward using VAs, providing valuable insights for the design and development of VAs tailored for the elderly population. Beyond the academic realm, this research serves as direct inspiration for designers, developers, and policymakers in the fields of assistive technologies and geriatric care. It offers practical insights into creating VAs that effectively address the emotional needs of older adults and enhance their quality of life. Furthermore, elderly individuals are poised to experience significant benefits from the outcomes of this study，the insights garnered from this study empower the elderly to embrace technological advancements that align with their preferences and comfort levels. This study contributes to a more comprehensive understanding of VAs and their potential to enhance the well-being of older adults, while also paving the way for future investigations in this domain. As underscored by this study's emphasis on the significance of emotional needs in technology acceptance, it encourages the adoption of more user-centered design strategies in the development of future VAs.

Managing Older Adults' Chronic Pain: Lower-Risk Interventions

This article is part of a series, Supporting Family Caregivers: No Longer Home Alone, published in collaboration with the AARP Public Policy Institute. Results of focus groups, conducted as part of the AARP Public Policy Institute's No Longer Home Alone video project, supported evidence that family caregivers aren't given the information they need to manage the complex care regimens of family members. This series of articles and accompanying videos aims to help nurses provide caregivers with the tools they need to manage their family member's health care at home. This new group of articles provides practical information nurses can share with family caregivers of persons living with pain. To use this series, nurses should read the articles first, so they understand how best to help family caregivers. Then they can refer caregivers to the informational tear sheet-Information for Family Caregivers-and instructional videos, encouraging them to ask questions. For additional information, see Resources for Nurses.

"Ask, 'When You Do This, How Much Pain Are You In?'": Content Preferences for a Conversational Pain Self-Management Software Application

The purpose of the current study was to examine older adults' preferences for conversational pain management content to incorporate in an interactive application (app) for pain self-management. Conversational statements and questions were written as a script to encourage evidence-based pain self-management behaviors. The content was converted from text to female chatbot speech and saved as four groups of MP3 files. A purposive sample of 22 older adults participated in a guided interaction through the MP3 files. One-on-one interviews were conducted to garner participants' conversational content preferences. Overall, participants want the conversational content to increase health care provider engagement in pain management communication. Older adults preferred the inclusion of conversational statements and questions for monitoring the multifaceted dimensions of pain, treatment accountability, guidance for alternative treatments, and undesirable effects from pain treatments. The design of mobile health apps must incorporate the needs and preferences of older adults. [Journal of Gerontological Nursing, 49(1), 11-17.].

Ascertaining Whether an Intelligent Voice Assistant Can Meet Older Adults' Health-Related Needs in the Context of a Geriatrics 5Ms Framework

The Geriatrics 5Ms: Medications, Mind, Mobility, what Matters most and Multicomplexity is a framework to address the complex needs of older adults. Intelligent Voice Assistants (IVAs) are increasingly popular and have potential to support health-related needs of older adults. We utilized previously collected qualitative data on older adults' views of how an IVA may address their health-related needs and ascertained their fit into the Geriatrics 5Ms framework. The codes describing health challenges and potential IVA solutions fit the framework: (1) Medications: difficulty remembering medications.

SOLUTION

reminders. (2) Mind: isolation, anxiety, memory loss.

SOLUTION

companionship, memory aids. (3) Mobility: barriers to exercise.

SOLUTION

incentives, exercise ideas. (4) Matters most: eating healthy foods.

SOLUTION

suggest and order nutritious foods, (5) Multicomplexity; managing multimorbidity.

SOLUTION

symptom tracking and communicating with health care professionals. Incorporating the 5Ms framework into IVA design can aid in addressing health care priorities of older adults.

Voice Assistant Reminders and the Latency of Scheduled Medication Use in Older Adults With Pain: Descriptive Feasibility Study

Background

Pain is difficult to manage in older adults. It has been recommended that pain management in older adults should include both nonpharmacologic and pharmacologic strategies. Unfortunately, nonadherence to pain medication is more prevalent than nonadherence to any other chronic disease treatment. Technology-based reminders have some benefit for medication adherence, but adherence behavior outcomes have mostly been verified by self-reports.

Objective

We aimed to describe objective medication adherence and the latency of medication use after a voice assistant reminder prompted participants to take pain medications for chronic pain.

Methods

A total of 15 older adults created a voice assistant reminder for taking scheduled pain medications. A subsample of 5 participants were randomly selected to participate in a feasibility study, in which a medication event monitoring system for pain medications was used to validate medication adherence as a health outcome. Data on the subsample’s self-assessed pain intensity, pain interference, concerns and necessity beliefs about pain medications, self-confidence in managing pain, and medication implementation adherence were analyzed.

Results

In the 5 participants who used the medication event monitoring system, the overall latency between voice assistant reminder deployment and the medication event (ie, medication bottle cap opening) was 55 minutes. The absolute latency (before or after the reminder) varied among the participants. The shortest average time taken to open the cap after the reminder was 17 minutes, and the longest was 4.5 hours. Of the 168 voice assistant reminders for scheduled pain medications, 25 (14.6%) resulted in the opening of MEMS caps within 5 minutes of the reminder, and 107 (63.7%) resulted in the opening of MEMS caps within 30 minutes of the reminder.

Conclusions

Voice assistant reminders may help cue patients to take scheduled medications, but the timing of medication use may vary. The timing of medication use may influence treatment effectiveness. Tracking the absolute latency time of medication use may be a helpful method for assessing medication adherence. Medication event monitoring may provide additional insight into medication implementation adherence during the implementation of mobile health interventions.