Understanding older people's voice interactions with smart voice assistants: a new modified rule-based natural language processing model with human input.

The COVID-19 pandemic has expedited the integration of Smart Voice Assistants (SVA) among older people. The qualitative data derived from user commands on SVA is pivotal for elucidating the engagement patterns of older individuals with such systems. However, the sheer volume of user-generated voice interaction data presents a formidable challenge for manual coding. Compounding this issue, age-related cognitive decline and alterations in speech patterns further complicate the interpretation of older users' SVA voice interactions. Conventional dictionary-based textual analysis tools, which count word frequencies, are inadequate in capturing the evolving and communicative essence of these interactions that unfold over a series of dialogues and modify with time. To address these challenges, our study introduces a novel, modified rule-based Natural Language Processing (MR-NLP) model augmented with human input. This reproducible approach capitalizes on human-derived insights to establish a lexicon of critical keywords and to formulate rules for the iterative refinement of the NLP model. English speakers, aged 50 or older and residing alone, were enlisted to engage with Amazon Alexa™ via predefined daily routines for a minimum of 30 min daily spanning three months (N = 35, mean age = 77). We amassed time-stamped, textual data comprising participants' user commands and responses from Alexa™. Initially, a subset constituting 20% of the data (1,020 instances) underwent manual coding by human coder, predicated on keywords and commands. Separately, a rule-based Natural Language Processing (NLP) methodology was employed to code the identical subset. Discrepancies arising between human coder and the NLP model programmer were deliberated upon and reconciled to refine the rule-based NLP coding framework for the entire dataset. The modified rule-based NLP approach demonstrated notable enhancements in efficiency and scalability and reduced susceptibility to inadvertent errors in comparison to manual coding. Furthermore, human input was instrumental in augmenting the NLP model, yielding insights germane to the aging adult demographic, such as recurring speech patterns or ambiguities. By disseminating this innovative software solution to the scientific community, we endeavor to advance research and innovation in NLP model formulation, subsequently contributing to the understanding of older people's interactions with SVA and other AI-powered systems.

Reducing Loneliness and Improving Social Support among Older Adults through Different Modalities of Personal Voice Assistants.

This study examines the potential of AI-powered personal voice assistants (PVAs) in reducing loneliness and increasing social support among older adults. With the aging population rapidly expanding, innovative solutions are essential. Prior research has indicated the effectiveness of various interactive communication technologies (ICTs) in mitigating loneliness, but studies focusing on PVAs, particularly considering their modality (audio vs. video), are limited. This research aims to fill this gap by evaluating how voice assistants, in both audio and video formats, influence perceived loneliness and social support. This study examined the impact of voice assistant technology (VAT) interventions, both audio-based (A-VAT) and video-based (V-VAT), on perceived loneliness and social support among 34 older adults living alone. Over three months, participants engaged with Amazon Alexa™ PVA through daily routines for at least 30 min. Using a hybrid natural language processing framework, interactions were analyzed. The results showed reductions in loneliness (Z = -2.99, p < 0.01; pre-study loneliness mean = 1.85, SD = 0.61; post-study loneliness mean = 1.65, SD = 0.57), increases in social support post intervention (Z = -2.23, p < 0.05; pre-study social support mean = 5.44, SD = 1.05; post-study loneliness mean = 5.65, SD = 1.20), and a correlation between increased social support and loneliness reduction when the two conditions are combined (ρ = -0.39, p < 0.05). In addition, V-VAT was more effective than A-VAT in reducing loneliness (U = 85.50, p < 0.05) and increasing social support (U = 95, p < 0.05). However, no significant correlation between changes in perceived social support and changes in perceived loneliness was observed in either intervention condition (V-VAT condition: ρ = -0.24, p = 0.37; A-VAT condition: ρ = -0.46, p = 0.06). This study's findings could significantly contribute to developing targeted interventions for improving the well-being of aging adults, addressing a critical global issue.

Training to use smart tablets to access reliable online health information in older adults' post-pandemic: A focused pilot intervention study.

BACKGROUND: Older adults are becoming more accepting and interested in using digital technologies, but difficulties and barriers remain for accessing reliable health-related information. The purpose of this focused pilot intervention study was to: (1) understand older adults' firsthand experiences and challenges while using smart tablets post-COVID-19 pandemic, and (2) gather suggestions for age-appropriate training materials, preference of training materials, and resources to access reliable online health information. METHODS: A focused pilot intervention study that involved training older adults to use smart tablets followed by focus group of a convenience sample of 13 older adults (65-85 years old; 91.6% female) on their experiences of using smart tablets. RESULTS: Thematic analysis revealed three themes: tablets are convenient to access online information and older adults reported technical, security concerns, emotional and cognitive challenges regarding use of smart tablets. Older adults also requested one-on-one support, assistance, and topic specific learning for future training sessions. CONCLUSIONS: Future studies should focus on providing detailed, clear instructions at an acceptable pace for older adults.

Methodologies Used in Studies of Self-Management Interventions for Urinary Incontinence in Adult Women: An Integrative Review.

BACKGROUND: Urinary incontinence (UI) affects approximately 60% of women in the United States and negatively impacts self-esteem, sexual function, participation in social activities, and quality of life (QOL). Self-management interventions show promise for improving UI symptoms and QOL. Previous reviews of UI self-management studies have focused on outcomes for older women. However, the literature lacks a synthesis of methodologies of these studies. PURPOSE: The purpose of this integrative review was to synthesize and evaluate methodologies used in studies of self-management interventions for UI in adult women. METHODS: Using an integrative review approach, a search of PubMed, CINAHL, and Embase was conducted yielding 1404 results, 23 of which met inclusion criteria. Data abstracted from each article included author(s), year of publication, study design and purpose, sample, country and setting, measures of UI symptoms, and intervention description. RESULTS: Findings showed methodological differences, particularly in design, assessment of UI subtypes, measures of UI symptoms, and intervention components. Multicomponent self-management interventions were used in 18 studies and 1 component used in 5 studies. Education, pelvic floor muscle exercises, and bladder training were the intervention components most frequently used, either alone or in combination; however, intervention components were not consistently aligned with the UI subtypes. Analysis of ethical matters revealed areas for improvement, specifically in reporting privacy and confidentiality and in methods to obtain informed consent. CONCLUSIONS: Results highlight opportunities to improve the rigor of methodologies used in studies of self-management interventions for UI in adult women.

"The constant worry": Urinary incontinence self-management in rural women: A qualitative study.

Urinary incontinence (UI) is experienced by approximately 60% of women in the United States and has a negative impact on self-esteem, sexual function, social participation, and quality of life. Rural women, who are underrepresented in the UI literature, face many health disparities and unique barriers to accessing care. The purpose of this qualitative descriptive study was to explore UI self-management behaviors in rural women with UI, including the contextual factors that influence their approach to self-management. This study recruited rural women, ages 30-60 years, using purposive sampling via social media. Demographic information was collected. A semi-structured interview guide was used to conduct individual, in-depth interviews via Zoom. Interview data were analyzed using qualitative description. Sections of interview text were coded using a priori and emergent codes, grouped into categories, and distilled into themes. A total of 31 participants (mean age = 47.2 years) met inclusion/exclusion criteria, enrolled, and completed the study. Qualitative analysis revealed rural as a cross-cutting theme and five major themes: self-management behaviors, familial influence, medical encounters, talking about UI, and resource scarcity. Participants described the rural environment as having a substantial impact on their approach to UI self-management. Specifically, rural social enmeshment made seeking care for UI in rural communities challenging. Findings shed light on how the rural environment influences various aspects of UI self-management in midlife women. Diverse perspectives in UI self-management are needed to advance knowledge in this field.

Managing Older Adults' Chronic Pain: Higher-Risk Interventions How to help caregivers promote safe pain management.

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. Cite this article as: Arnstein, P., et al. Managing Older Adults' Chronic Pain: Higher-Risk Interventions. Am J Nurs 2023; 123 (4): 56-61.

Managing Older Adults' Chronic Pain: Lower-Risk Interventions Nurses can engage family caregivers in creating, implementing, and evaluating the treatment plan.

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. Cite this article as: Arnstein, P., et al. Managing Older Adults' Chronic Pain: Lower-Risk Interventions. Am J Nurs 2023; 123 (2): 46-52.

Older Adults' Pain Outcomes After mHealth Interventions: Scoping Review.

BACKGROUND: Pain is prevalent and poorly managed in older adults. Although pain self-management strategies are helpful, adoption and access are limited; thus, technology provides an opportunity for intervention delivery. Mobile health (mHealth) is feasible to use in older adults; however, we have yet to understand the effect of mHealth pain self-management interventions on pain outcomes in older adults. OBJECTIVE: The purpose of this scoping review is to examine the characteristics of mHealth interventions and their efficacy on pain outcomes in older adults with musculoskeletal pain. METHODS: With the assistance of a medical librarian, keywords and subject headings were generated, including but not limited to mobile health application, mHealth, digital, pain, pain management, and older. A search was conducted for papers in journal databases, including PubMed, Embase, CINAHL, Scopus, and IEEE Xplore, between 2000 and 2022. Papers were screened according to predetermined inclusion and exclusion criteria, and reference lists were reviewed for additional paper inclusion. Three authors appraised the methodology of papers independently, then collaboratively to synthesize the evidence. RESULTS: Six publications were included in the scoping review. The design and methodology ranged widely from pilot studies to a comparative effectiveness trial. Older participants in the studies reported a variety of musculoskeletal conditions. Delivery of the mHealth pain self-management interventions incorporated mobile devices, such as a smartphone or tablet. Most mHealth-delivered interventions were multicomponent and incorporated elements of in-person and telephone access to an interventionist. The findings suggested mHealth interventions may reduce pain intensity; however, pain interference and other pain-related conditions did not have a statistically significant reduction. CONCLUSIONS: Research that has explored mHealth for pain self-management is beginning to move beyond feasibility. The few experimental studies conducted in older adults are heterogeneous, and the interventions are mostly multicomponent. It is premature to conclude the interventions' significant effect on pain or pain-related symptoms. As technology continues to integrate into health care, more experimental research is warranted to examine the efficacy of mHealth interventions on a variety of pain outcomes in older adults.

Managing Older Adults' Chronic Pain: Higher-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.].

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.

Glycemic Variability in Patients With Stage II-III Colon Cancer Treated With Surgery and Adjuvant Chemotherapy.

OBJECTIVES: To examine glycemic variability within one month and one year following surgery and throughout adjuvant chemotherapy among patients with stage II-III colon cancer, with and without type 2 diabetes (T2D). SAMPLE & SETTING: 58 patients with stage II-III colon cancer treated with surgery and chemotherapy. METHODS & VARIABLES: A retrospective analysis of electronic health record data over one year showed glycemic variability, measured as standard deviation and coefficient of variation. Chi-square, Fisher's exact, and Mann-Whitney U tests and Spearman's correlation coefficient were calculated. RESULTS: Patients with T2D had higher glycemic variability throughout chemotherapy and within one year following surgery. A significant increase in glycemic variability throughout chemotherapy was observed in patients without T2D. Significant associations between glycemic variability and demographic and clinical characteristics differed by T2D status, standard deviation, and coefficient of variation. IMPLICATIONS FOR NURSING: Nurses need to assess serial blood glucose levels in patients with and without T2D. Teaching patients how to maintain glycemic control during treatment is a priority. Research should include predictive models to identify risk factors for higher glycemic variability and cancer-related symptoms and outcomes.

A Robotic Device to Enhance Nursing Home Provider Telepresence During and After the COVID-19 Pandemic.

The COVID-19 pandemic presented significant challenges to face-to-face communication with people residing in post-acute and long-term care (PALTC) settings. Telemedicine is an alternative, but facility staff may be overburdened with the management of the equipment. Here we introduce the use of a mobile HIPPA-compliant telepresence robot (MTR) to bridge this barrier, which may be beneficial to reimagine options for PALTC in the future.

Reducing Loneliness Among Aging Adults: The Roles of Personal Voice Assistants and Anthropomorphic Interactions.

The perception of feeling lonely is an influential factor in determining quality of life among aging adults. As the US Census Bureau projects that the number of Americans ages 65 and older will double by 2060, reducing loneliness is imperative. Personal voice assistants (PVAs) such as Amazon's Echo offer the ease-of-use of voice control with a friendly, helpful artificial intelligence. This study aimed to understand the influence of a PVA on loneliness reduction among adults of advanced ages, i.e., 75+, and explore anthropomorphism as a potential underlying mechanism. Participants (N = 16) ages 75 or older used an Amazon Echo PVA for 8 weeks in an independent living facility in the Midwest. Surveys were used to collect information about perceived loneliness, and PVA interaction data was recorded and analyzed. Participants consistently exceeded the required daily interactions. As hypothesized, after the first 4 weeks of the intervention, aging adults reported significantly lower loneliness (baseline mean = 2.22, SD = 0.42; week 4 mean = 1.99, SD = 0.45, Z = -2.45, and p = 0.01). Four dominant anthropomorphic themes emerged after thematic analysis of the entire 8 weeks' PVA interaction data (Cohen's Kappa = 0.92): (1) greetings (user-initiated, friendly phrases); (2) comments/questions (user-initiated, second-person pronoun), (3) polite interactions (user-initiated, direct-name friendly requests), (4) reaction (user response to Alexa). Relational greetings predicted loneliness reductions in the first 4 weeks and baseline loneliness predicted relational greetings with the PVA during the entire 8 weeks, suggesting that anthropomorphization of PVAs may play a role in mitigating loneliness in aging 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.

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

Aging adults are impacted by pain. Technology can assist older adults with pain self-management while allowing for independence. The current usability study explored the use of voice assistant reminders for two pain self-management tasks in aging adults. Fifteen community-dwelling older adults with chronic pain and an average age of 65 years used the voice assistant for 4 weeks. Participants had moderate scores for pain severity (mean = 4.6 [SD = 2.3]) and pain interference (mean = 4 [SD = 2.6]). Voice assistant usability was above average (78 of 100). Median time to set up the Google Home Assistant profile was 5 minutes (SD = 7.5), with a median of asking for help two times. Pain self-management task reminders from the voice assistant were perceived as consistent, easy to set up, and helpful for accountability. Voice assistant reminders may be an option to help encourage a variety of pain self-management tasks in aging adults. [Journal of Gerontological Nursing, 46(10), 27-33.].

Virtual Reality for Therapeutic Recreation in Dementia Hospice Care: A Feasibility Study.

OBJECTIVES: To explore acceptability, tolerability, and subjective experience of virtual reality (VR) as therapeutic recreation for hospice patients living with dementia (hPLWD). DESIGN: Descriptive study setting. COMMUNITY HOSPICE AGENCY PARTICIPANTS: A convenience sample of n = 25 hPLWD cared for by a local hospice agency. INTERVENTION: Participants viewed a beach scene using VR headset for ≤30 minutes. MEASUREMENTS: Tolerability was measured with Pain Assessment IN Advanced Dementia (PAINAD)scores at baseline, every 5 minutes during VR use, and 5 minutes after headset removal. Additionally, follow-up phone calls to caregivers several hours after the intervention were performed to inquire regarding any noted adverse effect after the intervention. The subjective experience was measured with qualitative semistructured interviews with the hPLWD regarding enjoyment for the VR. Descriptive statistics were performed on all collected data. RESULTS: The VR was stopped early in 2 of the participants due to a ≥2-point increase in PAINAD score. Baseline behavioral and psychological symptoms of dementia (BPSD) were reported to have worsened in 2 (8%) of the participants at follow-up. There was no significant difference between dementia type and usage time or dementia severity and usage time. Of the 25 participants, 14 (56%) reported enjoying VR and 12 (48%) would do it again. CONCLUSION: Virtual reality use was generally safe and enjoyable in hPLWD. Virtual reality can provide meaningful activity and enhance quality of life for hPLWD at the end of life. In the future, VR may be a useful intervention for BPSD in hPLWD.

Ease of Use and Usefulness of Medication Reminder Apps among Rural Aging Adults.

Older adults manage multiple medications for chronic disease and those living in rural areas are impacted by health care disparities due to health provider shortages and fewer pharmacies. The use of downloadable medication reminder apps on smartphones may serve as a strategy for medication self-management of chronic diseases. In this feasibility study, thirteen rural older adult participants downloaded Medisafe® and used the app to manage their daily medications. The community-dwelling aging adults in this pilot perceived the Medisafe® as not difficult to use, useful for medication tracking and providing reminders for the self-management of multiple medications.

Self-Reported Pain Interference and Analgesic Characteristics in Rural Older Adults.

BACKGROUND: Pain impacts the lives of millions of community-dwelling older adults. An important characteristic of pain is "pain interference" which describes the influence of pain on function. A description of pain interference is limited in rural settings where the number of older adults is expected to increase, and health disparities exist. AIMS: The purpose of this study was to describe pain interference and analgesic medication use, highlighting those that may be potentially inappropriate in a sample of rural community-dwelling older adults. DESIGN: This secondary analysis was from a cross sectional study. SAMPLE AND SETTINGS: Data were analyzed from a sample of 138 rural community-dwelling older adults. METHODS: Statistical analyses were performed on demographics, health characteristics, pain interference, and potentially inappropriate analgesic medication data. RESULTS: Pain interference with work activity was reported by 76% of older adults overall, with 23% reporting moderate and 4% extreme interference, and 41% reported sleep difficulty due to pain. Higher pain interference was significantly associated with higher body mass index, more health providers, and the daily use of non-steroidal anti-inflammatory drugs (NSAIDs). Older women experienced more sleep difficulties due to pain. Over-the-counter analgesics were used most frequently by rural older adults to manage pain. Of most risk was the daily use of NSAIDs, in which only 30% used medications to protect the gastrointestinal system. CONCLUSIONS: Older adults in rural settings experience pain interference and participate in independent-medicating behaviors that may impact safety.