Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice J Alzheimers Dis . Author manuscript; available in PMC: 2026 Apr 15. Published in final edited form as: J Alzheimers Dis. 2025 May 1;105(3):825–836. doi: 10.1177/13872877251332659 Search in PMC Search in PubMed View in NLM Catalog Add to search Sharing patient technology preferences with care networks: Stakeholders’ views of the “Let’s Talk Tech” decision aid for dementia care Clara Berridge Clara Berridge 1 School of Social Work, University of Washington, Seattle, WA, USA Find articles by Clara Berridge 1 , Natalie R Turner Natalie R Turner 1 School of Social Work, University of Washington, Seattle, WA, USA Find articles by Natalie R Turner 1 , William B Lober William B Lober 2 Clinical Informatics Research Group, School of Nursing, University of Washington, Seattle, WA, USA Find articles by William B Lober 2 , George Demiris George Demiris 3 Department of Biobehavioral and Health Sciences, School of Nursing and Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Find articles by George Demiris 3 , Jeffrey Kaye Jeffrey Kaye 4 Layton Aging and Alzheimer’s Disease Center and Oregon Center for Aging and Technology, School of Medicine, Oregon Health & Science University, Portland, OR, USA Find articles by Jeffrey Kaye 4 Author information Article notes Copyright and License information 1 School of Social Work, University of Washington, Seattle, WA, USA 2 Clinical Informatics Research Group, School of Nursing, University of Washington, Seattle, WA, USA 3 Department of Biobehavioral and Health Sciences, School of Nursing and Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 4 Layton Aging and Alzheimer’s Disease Center and Oregon Center for Aging and Technology, School of Medicine, Oregon Health & Science University, Portland, OR, USA ✉ Corresponding author: Clara Berridge, School of Social Work, University of Washington, 4101 15th Ave NE, Seattle, WA 98105, USA. [email protected] Issue date 2025 Jun. PMC Copyright notice PMCID: PMC13078615 NIHMSID: NIHMS2150437 PMID: 40313054 The publisher's version of this article is available at J Alzheimers Dis Abstract Background: Let’s Talk Tech (LTT) is a self-administered web intervention for people with memory loss and their care partners that supports decision-making about digital health technologies. In past work, dyads wanted to share LTT preference reports with their larger care networks. Objective: This study aims to understand with whom care dyads want to share their technology preference reports and why, and if and how clinicians want to receive them. Methods: Together, fifteen dyads of people living with mild cognitive impairment (MCI) or early-stage dementia (n = 15) and a care partner (n = 15) completed LTT and two survey questions. Care partners completed independent follow-up interviews, and 32 clinicians at four Alzheimer’s Disease Research Center-affiliated clinics viewed an LTTreport and completed a 10-question survey. We used descriptive statistics for survey responses and thematic analysis for interviews. Results: Two-thirds of care partners (n = 10) wanted to share the report with family members. Half (n = 8) wanted to share it with clinicians to keep them informed about the dyad’s planning and facilitate conversations about technology options. 30 of 32 clinicians reported they would want their patients’ technology preferences reports, with 25 wanting to access it via the electronic health record (EHR). Conclusions: Findings demonstrate potential value to both family dyads and providers of sharing technology preferences beyond the care dyad. Clinicians were highly receptive to accessing technology preference reports in EHRs and to having discussions about technology be a part of advance care planning. Future research should test integration in the EHR and the potential of sharing technology preferences to support person-centered technology choices. Keywords: Alzheimer’s disease, artificial intelligence, assistive technology, caregiving, decision aid, digital health technology, ethics, mild cognitive impairment, patient-centered care, shared decision making Introduction Preparing and empowering care dyads and families to make timely informed decisions about digital health technologies holds great promise for helping them to plan for cognitive changes by supporting the tasks of care at home. There are many reasons to support care partners and people living with dementia (PLWD) to make these decisions in consultation with each other. Care partners can experience stress from having to make care decisions when they do not know or agree with PLWDs’ preferences, 1 , 2 and leaving PLWD out of care decisions may exacerbate their feelings of diminished autonomy and control. 3 Digital health technologies comprise a large and growing portion of initiatives to support dementia care at home because they can provide continuous algorithmic monitoring to detect health changes and safety threats. 4 – 8 There are significant potential benefits of appropriate use of these technologies for costs of care through predicting health events and supporting safety at home, which have driven the dramatic influx of public investment and devices. 9 – 11 With the influx of consumer facing technologies, and more recently artificial intelligence (AI) tools to support care, it is increasingly important to empower care partners and PLWD with person-centered decision-making support and trustworthy information about the risks and benefits of digital health technologies that process data collected in the home to monitor safety. 12 PLWD often want to be involved in decisions about how technology is used to support their care at home. 13 – 19 There is research consensus that enabling involvement to the extent possible is required for ethical, effective use of these technologies. 14 , 15 , 20 – 25 Yet there are no tools to help them or their care partners understand technology options or guide them in balancing a desire for monitoring safety with the PLWD’s dignity and wishes. Let’s Talk Tech (LTT) is the first of its kind education and communication tool that helps families meaningfully engage people living with mild dementia and mild cognitive impairment (MCI) in immediate decision making and planning for technology use. 13 The self-administered intervention is delivered as a web-app and takes about 45 min for two people to complete together. It is the first intervention to provide accessible decision aids for families as they contemplate how to adopt technology tools used in dementia care at home to monitor safety and support quality of life. It does this by: 1) educating dyads about data-diverse technologies used in care; 2) enabling dyadic communication about technology use, and 3) documenting the PLWD/MCI’s preferences for how these technologies should or should not be used, the strength of each preference, and if they would like to be involved in these decisions in the future. It is guided by the value of person-centeredness, ensuring PLWD/MCIs’ voices are heard to enable their choices to be honored. 26 The four categories of technologies featured in LTT are locators, in-home activity sensors, cameras, and AI companions, which were selected based on a multi-survey process described in detail elsewhere. 21 , 27 , 28 Let’s Talk Tech is grounded in the Theory of Dyadic Illness Management, centered on the benefits of shared appraisals and supportive decision making to optimize the health of both members. 29 It enables dyads to talk about what matters to them in decision making and planning for technology use to prepare care partners to make person-centered decisions immediately and if the PLWD loses their capacity to do so. In a pilot study with 29 people living with mild stage Alzheimer’s disease and their care partners, LTT showed excellent feasibility and acceptability 13 and significant improvements on care partner technology comprehension and important dyadic measures such as care partner perception of the PLWD’s technology comprehension, knowledge of the PLWD’s preferences, dyadic alignment, and preparedness to make technology use decisions. 27 Let’s Talk Tech generates a report summarizing the PLWD’s preferences for technology use that the dyad can view or update at any point by logging back in. 13 A theme from post-test paired interviews conducted with both members of the dyad was that they wanted to share their reports with other people in their care networks. They wanted to share with adult children, other family members, and health care providers, as well as future long-term care residences, for reasons of wanting to preempt conflict, show that the PLWD was involved in decisions, and make other members of the care network part of the process. 27 Some had follow-up questions regarding what specific product to purchase and how they would be supported to set up a new device. This finding that dyads wanted to share their reports with others, sometimes to gain support with acquisition and installation, is unsurprising because barriers to technology use exceed those barriers targeted by LTT of technology awareness, understanding, and the ability to communicate preferences. Additional known barriers to adoption of new technologies by older adults that LTT does not target include cost, acquisition, installation, and learning how to use them. 30 Dementia care partners have reported turning to family and friends who have greater technology experience, as well as needing follow-up support for implementation. 31 While there is no robust infrastructure in the U.S. to provide free technology assistance to older adults, many may have untapped resources in their care networks, such as in adult children who could be asked to help or in providers who have perspective on specific devices that other patients have tried. Several questions were raised by the problem of technology access barriers and pilot dyads’ desire to share their technology preference reports with others to overcome those and other issues. First, we need to learn if we can extend the utility of LTT, a shared decision-making dyadic intervention, beyond the dyad to engage other members of their care network who they want looped into these decisions. And importantly, while dyads identify members of their healthcare teams as people who should receive their technology preference reports, we need to know if that information is of value to members of those teams. That is, will providers welcome information about what their patients do and do not want regarding technology used in their care at home? Or will they perceive this as nonactionable information, or information that could come with questions that they are not prepared to answer about technology options? Before conducting the present study to answer these questions and to better understand both dyad goals in sharing and provider interest in receiving this information, we developed electronic sharing of the technology preference report in LTT (hereto, “report”). In addition to developing a viewable summary using PDF format, which can be easily printed or emailed, we also implemented sharing of that report using SMART Health Links. This protocol, which is being proposed as an HL7 standard, allows for secure, verifiable sharing of the summary report under the control of the dyad, using either a QR code or a URL. This functionality allowed us to assess willingness to share preferences, workflow of preference sharing, and content of a preference report. SMART Health Links is part of a larger set of Fast Health Interoperability Resource (FHIR) standards. We can use other elements of the FHIR standard to facilitate exchange of data with electronic health record systems (EHRs). Let’s Talk Tech uses FHIR constructs to internally store and manage data and, while the patient experience does not depend on access to an EHR, we have developed similar systems which allow providers to view summary reports and discrete data from within their EHR workflow, using the related SMART on FHIR standard. With electronic sharing enabled, we asked 15 dyads of care partners and people living with mild dementia or MCI to complete LTT and answer questions about with whom and why they would want to share their reports. We gave them the option to use the new sharing capabilities and interviewed all care partners 1–2 weeks later to learn if they had shared it. We also surveyed clinicians working in NIA Alzheimer’s Disease Research Center-affiliated memory and dementia assessment centers about the value and utility of being on the receiving end of such information. Through this work, we answer the following research questions: With whom do dyads wish to share their report of the PLWD/MCI’s technology preferences and why? Will dyads share their reports immediately within one week of completing LTT, with whom, and how do recipients respond? After reviewing an example report in a mockup of an EHR, how do clinicians who work daily with people with MCI and AD/ADRD feel about receiving this information in the summary report and the value of shared decision-making processes about digital health technologies as part of care planning? Methods Participants Dyads. Inclusion criteria for primary participants (those living with memory loss) were (1) enrollment in the University of Washington Alzheimer’s Disease Research Center (UW ADRC) clinical core with a research diagnosis of MCI or mild dementia due to AD/ADRD; (2) age 55+ years; (3) English speaking; and (4) having an adult co-participant identified as a primary support person willing to participate in the study. Those co-participants (here, care partners [CP]) also had to be English speaking to participate. Between the two members of each dyad at least one had to have access to an Internet-connected device (such as a computer, laptop, tablet or smartphone) that they could use in-person together. Fifty-four percent of dyads we made contact with agreed to participate, for a total of fifteen. Each of these 15 dyads completed LTT and all study procedures between May and July, 2024. The University of Washington Human Subjects Division reviewed the protocol and determined that this research qualified for exempt status. Clinicians. The clinician survey was distributed in the time period July 25 to August 30, 2024 during memory center team meetings and to the email lists of the same clinicians (engaging those who were absent at the team meeting) of memory centers affiliated with an Alzheimer’s Disease Research Center. These included the University of Washington Memory and Brain Wellness Center, the Oregon Health & Science University Layton Aging and Alzheimer’s Disease Research Center, the University of Pennsylvania Penn Memory Center, and the University of Michigan Cognitive Disorders Clinic. 32 clinicians completed the survey, representing a response rate of 64%. Data Dyads completed LTT in their own homes with a researcher present as a ‘fly on the wall’ observer. After viewing their final reports at the end of LTT, dyads answered two survey questions about with whom they would want to share their reports and why. Within 1–2 weeks of LTT completion, we interviewed the CP of each dyad and asked them to elaborate on their interest in sharing the report, and we learned whether either member of the dyad had already shared the report beyond the dyad and how that went. Interviews with care partners averaged 45 min (range: 32 to 60 min) and were conducted via Zoom video or by phone. One study participant inquired before beginning the study about the data privacy and security of the LTT tool, which is detailed in the About section of the tool. The SMART Health Links standard (SHL) is secure in several ways. First, the generated URL itself is hashed into a long, random string, making it virtually impossible to guess, whether used as a string or a QR code. Second, the SHL standard allows the user creating the link to require a passcode and/or set an expiration date. While these server-enforced features make sharing of data more complicated, they may provide some reassurance to users concerned more with privacy than with easy access. LTT links currently do not require a passcode and set the expiration at six months. Third, the SHL creator (user) may revoke and/or recreate the link with new security features at any time. Finally, the link invokes “https” industry-standard Transport Layer Security (TLS) public-private key encryption to ensure authenticity of the server and security of the data request and response. The SHL standard allows users to balance security and accessibility according to their preferences, which we continue to explore. The clinician survey included a de-identified sample patient LTT preference report followed by 10 questions about the potential value of patient LTT preference reports to care team members and how they would want to access them. Survey questions are included in the Appendix . Study data were collected and managed using REDCap electronic data capture tools hosted at the Institute of Translational Health Sciences. 32 , 33 Analysis Frequency counts and descriptive statistics were used to summarize dyads’ responses to sharing LTT reports and clinicians’ survey responses. Interviews were transcribed and coded in Dedoose v. 9.2.12. 34 The first two authors used thematic analysis to identify themes regarding dyads’ interest in sharing their LTT reports. 35 , 36 First, codes related to sharing the LTT summary report were created deductively based on the interview guide (included in the Supplemental Material ). Interviews were then coded by a primary coder. A secondary coder then reviewed the coding decisions. 36 Both coders then read the coded excerpts across interviews and identified themes related to sharing LTT. Results Dyad participant demographics are described in Table 1 . All but two dyads were spousal. Of the two non-spousal dyads, one care partner was a sister, and one was a son. Care partner age ranged from 52 to 88 (M = 71.9; SD = 10.3) and PLWD/MCIs’ age ranged from 59 to 85 (M = 72.3; SD = 7.7). Most dyad participants were white (care partner: 80%, primary participant: 86.7%) and non-Hispanic (care partner: 100%, primary participant: 93.3%). One primary participant was Asian, and one was Native Hawaiian and Other Pacific Islander. Two care partners were Asian, and one care partner opted not to specify. Sixty percent of care partners and 46.7% of primary participants identified as female, with the remaining identifying as male. Care partners reported the primary participant’s cognitive status and 53.3% reported MCI as the diagnosis. The remaining primary participants (46.7%) were reported by the care partner to have AD/ADRD at mild or moderate stage. Table 1. Dyad participant demographics. PLWD/MCI, n = 15 Care partner, n = 15 Demographics (n, %) Age (M, SD) 72.3 (7.7) (Range: 59–85) 71.9 (10.3) (Range: 52–88) Gender Male 8 (53.3) 6 (40.0) Female 7 (46.7) 9 (60.0) Race White 13 (86.7) 12 (80.0) Asian 1 (6.7) 2 (13.3) Native Hawaiian and other Pacific islander 1 (6.7) 0 Chose not to answer 0 1 (6.7) Hispanic/Latinx Ethnicity 1 (6.7) 0 Cognitive Status Mild Cognitive Impairment 8 (53.3) − Alzheimer’s Disease and Related Dementias 7 (46.7) − Open in a new tab M: mean; SD: standard deviation. Reasons to share and with whom: dyad survey Within the final section of LTT, dyads were asked to answer two survey-form questions about with whom they would want to share their summary report and why they would want to share ( Table 2 ). The response options representing possible reasons to share were derived from the pilot study interviews. 27 Most selected that they want to share their report with an adult child or stepchild (n = 11; 73.3%), followed by PCP/My Doctor (n = 6; 40%) and Neurologist (n = 6; 40%). Some dyads explained that they selected providers that they did not necessarily have currently, such as social workers or mental health practitioners, but with whom they would want to share the report. For example, one dyad selected they would share this report with a nurse or social worker even though they did not have any because, “You don’t want to exclude future providers.” This interest in sharing with provider types that they have not yet had was also expressed in care partner interviews. Table 2. Frequencies of who dyads would want to share their Let’s Talk Tech reports beyond the dyad, and their reasons for sharing (closed response options answered by dyad members together), (n = 15). Want to share with: N Reasons to share with anyone: N Adult Child or Stepchild 11 To loop them into these decisions 12 PCP/ Doctor 6 To make them aware for their own information 10 Neurologist 6 To help us all be on the same page about technology use 10 Sibling 4 To get help using technology 9 Power of Attorney 4 To let them know that we discussed technologies together 9 Social Worker 3 To get their advice for finding a technology 8 Mental Health Therapist 3 To get their opinion 7 Case Manager 2 Something else 0 Nurse 2 Niece or Nephew 1 Grandchild 0 Someone else 0 Open in a new tab Dyads could select all that apply, so the total number of responses is greater than 15. As presented in Table 2 , at least half of the dyads endorsed all of the survey’s reasons to share their summary reports with anyone. Eighty percent of dyads (n = 12) selected they would share to loop others into these decisions and 66% (n = 10) would share to make others aware for their own information and to help everyone to be on the same page about technology use. Nine wanted to share the report to help make sure everyone was on the same page about technology use, to get help using technology, and to let others know that they discussed technologies. About half of the dyads wanted to get others’ advice for finding a technology product or to get their opinion. Care partner interviews To allow care partners to reflect on their reasons for sharing or not sharing the report privately from their study partner, care partners were interviewed separately. They were asked with whom they might want to share the report of their partner’s preferences and why. This qualitative data provided more insight into care partners’ reasons for sharing or not sharing this information beyond the dyad, which is important to understand as care partners are the more likely dyad member to do the sharing. Sharing beyond the dyad with family. Most (10/15) care partners expressed wanting to share the LTT summary report with family members during interviews, namely adult children, and described several reasons for this. First, care partners wanted to keep them in the loop and aware of PLWD’s preferences and decisions to use technology. One CP explained why she would want to share the report with her adult sons and their partners, “Then we’d all be kind of on the same page where, okay, this is how dad feels about the technology that’s currently available. And then, if we’re actually utilizing some of those things, let them know at that point, ‘Hey, this is what Dad and I are doing.’ Because I think it is important to keep the family members, particularly when they live close by, which ours do, apprised of what’s going on and where we’re at with things.” Care partners said that sharing the summary would bring other family members more into the conversation on care decisions and reasoned that it was important to share the PLWD/MCI’s preferences with family members who were also involved in caregiving or part of the PLWD/MCI’s care network. One PLWD who completed LTT with her son said they would send the report to her daughter because she “[didn’t] want her to feel not involved.” Care partners reported wanting to ensure family members felt included in the conversation. Sharing the PLWD/MCI’s preferences was also seen as a way to provide clarity on the PLWD/MCI’s preferences and prevent possible future family conflict related to the use of technology. By sharing the LTT summary, care partners could show other family members that the decisions on whether to use technologies were based on the PLWD/MCI’s preferences. As one care partner with a blended family said, “Anything that helps determine his preferences so [his adult children] know if he can’t make choices, they know it’s not just coming from me.” She continued, “maybe if he’s okay with that I think I might share it with my daughter as well, so just because she’s gonna be involved with everybody’s care at some point. So yeah, just so she kind of knows. And that will help her picture me with some of those questions.” A care partner in a dyad with shared children said she could use the report to show that the decisions were coming from their dad and, “it’s not me doing bad things” because “it’s important for them to know it’s not just me.” In other words, summaries could be used to help justify care partners’ decisions on technology use as aligning with a PLWD/MCI’s preferences. Finally, care partners discussed sharing the LTT summary report to get help from both family and providers with specifics on what technology to use. For example, a care partner expressed, “The kids will have a way of monitoring us and holding our feet to the fire – asking did you look into the Air Tag?” Care partners often expressed wanting to share the report to receive guidance on specific technologies products available and help with using technologies. Reasons provided by the five care partners who did not want to share were that it was not yet time to share or they did not want to cause additional worry about the PLWD/MCI’s condition. One care partner said that her partner with MCI’s condition was still very mild and that sharing the report with his adult children might alarm them because they will think their dad’s cognition has declined more than it has. She said that they would likely have more discussions on technology use as his condition progressed before sharing with their children and that she would share the report when they start to consider implementing any of the technologies. Care partners also discussed not wanting to share the LTT report if the featured technologies were not relevant to their situation. One care partner said that they would consider sharing the report if the PLWD lived alone, but she was always either with the care partner or the PLWD’s sister. Another care partner said that it did not feel necessary to share the report because the PLWD’s children do not live nearby, but that “It might be different if they were part of a caregiving circle.” Care partners wanted to share the LTT summary report when they thought the information would be relevant to other members in the family who were involved in caregiving. Experiences sharing with family. Five (of 15) dyads shared the LTT report in the first week after completing LTT. Four shared it with adult children and one shared it with the PLWD’s brother and sister-in-law. Care partners reported that sharing the LTT summary report was useful for opening up or expanding discussions on technology use with other family members. One care partner said, “I think [LTT] lit a fire under me. It’s one thing to think about it. It’s another thing for us to talk about it and then to have the kids’ input. And so I know my kids will not let this [go].” This same care partner went on to read his adult children’s reactions to the summary report, “my daughter starts out ‘this sounds like a great conversation starter.’” Two other care partners said that after sharing the LTT summary report with other family members, the recipients said that it was helpful to receive this information and to know the PLWD/MCI’s preferences. One care partner described how after sharing the summary report with their son, their son said that while the report was helpful, he wanted more information in the report. As a non-participant in the LTT process, he found the summary report “semi-useful but not every answer is actionable” because the specific uses of the featured technologies were not also detailed in the report. While family members who received the LTT summary report considered it helpful, their responses highlight the need for continued and more detailed conversation about future steps and technology use. Sharing with providers. Care partners were asked if they would want to share the report with a member of their partner’s healthcare team, along with their reasons. Eight care partners wanted to share the report with the PLWD/MCI’s providers. They wanted to keep providers updated on their status. A care partner discussed how the PLWD had a strong relationship with her primary care provider, and that the PLWD believed the provider would want to know about her decisions on technology use. Her care partner explained, “I think she was feeling like, with her primary care doctor, [name], she’s been seeing her for a long, long time. So, I think she feels well-supported by her, and that’s the person who has recommended she get a Life Alert bracelet. I think [PLWD] was like, ‘oh, well, [PCP’s name] would be excited to see I’m doing these things.’” Care partners also discussed wanting to share the report with providers to get advice on when to implement technologies. One care partner said, “I would hope they would look at this and say, ‘I think you might want to try this technology or that technology,’ depending on what they learn about how things are going with us.” Another care partner expressed wanting to show this to the PLWD’s neurologist during an annual appointment because, “I would hope that he would be able to tell us if, like, for example, is it time to look at some of these things [technologies]…because that would be the expert opinion is how I was thinking about it. If he had, like a counselor of some sort, I would also share it with that person.” Care partners who wanted to share the summary report with a provider thought that it could help move conversations on technology use forward. Let’s Talk Tech reports were viewed as a springboard for deeper, more specific conversations about technology use. Care partners said they could bring this up and then ask providers more specific questions around technologies, such as the specific considerations or ramifications of using different technologies. Care partners suggested that their providers or memory centers where they receive care should refer people to LTT. For example, a care partner explained, “This might be a useful tool a doctor could bring up to you to say you might want to start thinking about these options. And that brings the conversation forward, and even if you might not need it at that time.” Some raised the idea of facilitating sharing reports with providers through their patient portal. As one suggested, “We could share to MyChart – people are used to that – docs want an idea of what’s going on day to day.” Others explained that having the LTT report available in their patient portal would help the care partner access it, along with the link to the LTT web-app for future reference or to update it. Conversely, some care partners believed that providers would not have the time or interest in reviewing the summary. When asked about sharing the report with the PLWD’s provider, a care partner said, I don’t really think so. Just because he goes to [health center name] and they have so much to deal with, I don’t know if they would pay attention to this. Maybe they would, maybe I’m underestimating. I don’t know if they have time. [Nurse practitioner’s name], does she have time? His GP is great, and is who he talks to about his memory issues. [He] definitely doesn’t have time. Another care partner said they were not sure if they would share the report because, “I don’t think they’d want to be bothered by all this.” Care partners who did not want to share with providers questioned whether it was information that the provider would welcome or find useful: “from our standpoint I don’t know how valuable they would take the information.” In the following section, we report clinician views on the value of receiving patient technology preferences. Clinician survey Thirty-two clinicians completed the survey, representing the clinical roles reported in Table 3 . The response rate across the four centers was 64%. To ensure anonymity given the small number of people in certain clinical positions at each memory center, personally identifying information such as race, gender and age or years in position were not asked. Positions represented include neurologist, psychiatrist, neuropsychologist, social worker, nurse practitioner, nurse, speech pathologist, geriatrician, naturopathic physician, and other (case manager). Table 3. Professional roles of survey respondents, (n = 32). Professional Role of Survey Respondent N (n = 32) Neurologist 9 Psychiatrist 5 Neuropsychologist 5 Nurse Practitioner 4 Social Worker 3 Nurse 2 Speech Pathologist 1 Geriatrician 1 Naturopathic Physician 1 Other 1 Open in a new tab Other = 1 Case manager. As shown in Table 4 , the majority (19; 59%) responded that they are sometimes asked by patients and family members about technologies to support care or monitor safety in the home. Most clinicians reported being somewhat unprepared (15), followed by somewhat prepared (12), very unprepared (4), and one very prepared to respond to questions about technologies to support care and monitor safety at home. All participants would probably (18) or definitely (14) refer patients to a tool like LTT that helps them have informed discussions about technologies on their own time, and the majority replied that such discussions should probably (21) or definitely (9) be a part of advance care planning. Most felt that personally knowing their patients’ technology preferences would be somewhat (16) or very (13) helpful for planning patient care. Table 4. Responses to clinician survey (n = 32). Question Response N (%) How frequently do patients or family members ask you questions about technologies to support care or monitor safety at home? Never 0 Rarely 5 Sometimes 19 Often 7 Always 0 How prepared do you feel to respond to their questions about these technologies? Very unprepared 4 Somewhat unprepared 15 Somewhat prepared 12 Very prepared 1 Should discussions about the use of technologies in patients’ care be a part of advance care planning? Definitely no 0 Probably no 2 Probably yes 21 Definitely yes 9 How helpful would it be for planning patient care if you knew their preferences for how they want technology to be used in their care? Very unhelpful 0 Somewhat unhelpful 3 Somewhat helpful 16 Very helpful 13 Open in a new tab Participants selected all of the people who they believe should receive the report by clinical role ( Figure 1 ). The majority (n = 30; 94%) of clinicians reported that they would want to see their patients’ LTT summary report. As depicted in Figure 2 , 78% (n = 25) selected that they would want to access patients’ LTT summary reports in the EHR. More than half (n = 17; 53%) would want patients to share LTT summary reports before the appointment (e.g. uploads to the patient portal, mails or emails to the office) and 8 (25%) selected they would want the report shared during the appointment. Figure 1. Open in a new tab Selection of care team members who should receive the LTT summary report (n = 32). Clinicians could select all that apply, so the total number of responses is greater than 32. Figure 2. Open in a new tab Selection of how clinicians would want to access the LTT summary report (n = 32). Clinicians selected all that apply, so the total number of responses is greater than 32. A few clinicians offered optional comments after completing the survey. A nurse practitioner wrote, I just had a conversation recently where one of the patient’s sons suggested a camera in the patient’s room and the patient’s daughter was hesitant but seemed like she wanted to be open to her brother’s suggestion. This would have been a great tool so we could have had a lengthier discussion about the pros and cons. Instead I just briefly mentioned that privacy was something to consider before making the decision. A social worker also endorsed its potential value: “Very helpful tool. In my role as SW I often do not connect with pts/families until they are in moderate stages and families are already implementing this. It would be great if this tool was offered regularly to pts early in their diagnosis.” This comment aligns with dyads’ explanations that they had not yet been connected with a social worker, as well as clinician opinion that social workers are at the top of the list of clinicians who should receive their patient technology preference reports. The issue of limited time during appointments, which was referenced by some care partners, was raised by one clinician in a comment. This neurologist wrote, Given the time-limited nature of appointments and a focus on medical diagnostics and course of treatment, prolonged discussions about the uses of technology are rare in our subspeciality clinic. I discuss certain technologies, particularly door alarms or tracking devices in specific instances where wandering safety is of paramount concern, but this is a far cry from an assessment of a patient’s perspective on other technologies such as virtual companions, cameras or sensors. Finally, a neurologist who was one of the two who thought technology preferences probably should not be a part of advance care planning explained, While I would want to know what a patient’s preferences are regarding use of technology, it may not always influence my decision to recommend it. Sometimes tech is the only good option for monitoring safety in AD/ADRD, especially when the condition is more advanced and there is limited ability to have other people in the home. If a patient stated they would not want to use a certain technology even as their health changes, we might override that if safety becomes an issue. This also becomes more complex if a patient lacks insight into their symptoms or how they might progress over time. Discussion While there is growing recognition for person-centered care and patient empowerment, there is a shortage of tools to actually facilitate such approaches. To our knowledge, Let’s Talk Tech is the first intervention designed for older adults or people living with dementia to enable informed expression and communication of preferences for how technology should be used in one’s care. The Let’s Talk Tech intervention for dyads results in a set of documented preferences for technology use expressed by the person with memory loss. Two-thirds of this study’s care partners said that they would share this report with a member of their family. The five who immediately did share it reported that it was generally well received and served several helpful functions. It served as a conversation starter about technology tools, communicated out a person’s preferences while they were able to express them, and it activated adult children to prompt the dyad to take action steps to implement the preferences for desired use. In some instances, sharing led to further discussion with recipients on technology and non-technology options to promote safety. Sharing with adult children was particularly important to care partners so they could demonstrate that they were acting in accordance with the person’s expressed preferences, echoing our pilot study finding that this might be seen as a way to avoid family conflict over technology choices. About half of the care partners described reasons why they’d like to share the report with one or more of their partner’s providers to keep them in the loop about the dyad’s planning, open conversations about technology options, and to get expert opinions regarding additional considerations and specific products recommendations. While some anticipated this information would be welcome, several believed providers would not have time or interest in learning their partner’s technology use preference. While few clinicians surveyed felt fully prepared to answer their patients’ questions about technologies, all but two wanted to view their patients’ expressed preferences. This suggests that sharing could serve as a springboard in the clinic for having these conversations. Because LTT is completed by dyads on their own time at home, this report sharing approach could enable these conversations in the clinic in a way that accommodates the time constraints of clinical encounters. At the same time, patients or care partners may ask questions that clinicians are not prepared to answer. Overall, clinicians saw value in nearly every clinical role accessing patient reports. While all clinicians but two wanted to receive patient technology preferences, more people endorsed social worker, followed by nurse practitioner, neurologist, occupational therapist, and geriatrician as appropriate recipients of this information than the other categories, though most positions were endorsed by more than half the participants. The roles endorsed by less than half of the clinicians were neuropsychologist and psychologist, followed by naturopathic physician, yet each clinician representing these roles wanted to view their patients’ technology preferences reports. This finding suggests that it may be wise to enable EHR integration to enable access to the entire clinician care team. Additional findings that support this broad access approach via the EHR are that patient interactions with a range of clinical roles is uneven depending on their circumstances, dyads favored sharing with clinicians with whom they have the closest relationships, and most clinicians wanted to view reports in the EHR. It also aligns with the suggestion made by some care partners to make their partner’s LTT report accessible to them in their healthcare provider’s patient portal (i.e. Mychart), along with the link to the LTT web-app for them to be able to find it to update as needed. This could in theory enable the clinicians who want to have a conversation about technology options to have the opportunity to do so. It could also create role confusion if discussions are not documented for the team, potentially also leading to patients receiving conflicting advice by different clinicians. This study finds that clinicians of memory centers are highly receptive to accessing patient technology use preferences in the EHR; however, actual integration, satisfaction, and impact on patient engagement cannot be assessed without deployment in the EHR. This signal of clinician receptivity does not ensure efficacy or workflow compatibility in real-world EHR integration, which will require trials to evaluate. Future studies should also examine if sharing the technology preferences documented in Let’s Talk Tech actually activates the dyads’ larger care networks with the effect of supporting them to use technology how they want to. In the context of a shortage of dyadic interventions for dementia caregivers and absence of education or decision-making tools for caregivers, caregiver empowered decision making will be an important outcome to examine. Limitations This study is responsive to findings from a pilot study with 29 dyads that alerted us to the value to participants of being able to share their Let’s Talk Tech reports beyond the dyad. 27 There are several significant limitations of the current research. The study has a small sample of 15 dyads that lacks diversity by race, ethnicity, relationship type, and formal education. Eighty-three percent of the participants were white, all identified as either male or female, and highly educated with all participants completing at least some college and 73% (n = 11) having at least a four-year degree. Because the participants were all volunteers in an ADRC cohort, they were also highly service-connected relative to the general population of people with memory loss and their care partners. The majority were spousal dyads. This homogeneity limits our ability to generalize these findings to the larger population of people living with AD/ADRD or MCI and their care partners, including parent/child dyads. Future studies should prioritize engagement of racially diverse samples and non-spousal dyads. Clinicians were all employes of specialized centers for ADRD, so their views may represent those clinics providing leading edge evidence-based assessment and care and may thus be considered to represent best practice. As a limitation, the views expressed by this clinician sample may not be generalizable to those working outside of specialized clinics and may overestimate enthusiasm for receiving technology preferences. Follow-up studies in general healthcare settings are needed to assess broader applicability. Conclusion This multi-stakeholder study describes the potential value of sharing reports of people with memory loss’s preferences for technology use and nonuse documented in a dyadic intervention that centers patient voices for shared decision making. This inquiry is timely in the context of the growing importance of seeking patient preferences with regard to data collected outside the clinic and for AI integration. Most dyads of people living with MCI or AD/ADRD and their care partners valued the opportunity to share technology preference reports from the Let’s Talk Tech (LTT) intervention and reported a range of reasons it might be helpful to share with both other family members and health care providers. This study also finds that clinicians of memory centers are highly receptive to accessing patient technology use preferences in the EHR and that many kinds of clinicians in the care team could find this information useful. Clinicians all reported that they would probably or definitely refer patients to LTT. Most felt that discussions about technology should be a part of advance care planning and that knowing their patients’ preferences would be helpful to planning their patients’ care. These findings indicate that facilitating the engagement of health care professionals and family members on patients’ terms could expand their technology resources significantly. This research illustrates how a dyadic decision aid approach holds promise to activate larger care networks to support desired technology use. Supplementary Material Supplementary material NIHMS2150437-supplement-Supplementary_material.docx (18.8KB, docx) Supplemental material Supplemental material for this article is available online. Acknowledgments The authors thank the Let’s Talk Tech project team at the University of Washington Clinical Informatics Research Group: Amy Chen, Sierramatice Karras, Daniel Lorigan, and Justin McReynolds, as well as Rebecca Brown for reviewing the clinician survey. The Let’s Talk Tech intervention was developed by Berridge. © Clara Berridge 2021. Funding This research was supported by the National Institute on Aging of the National Institutes of Health under Award Number P30AG073105 and with the support of the University of Washington Alzheimer’s Disease Research Center [P30AG066509], the Oregon Alzheimer’s Disease Research Center [P30AG066518] and the Penn Alzheimer’s Disease Research Center [P30AG072979], and the Michigan Alzheimer’s Disease Research Center [P30AG072931]. The REDCap instance used is supported by the Institute of Translational Health Sciences, which is funded by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR002319. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Footnotes Conflicting interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Ethical considerations The University of Washington Human Subjects Division reviewed the protocol and determined that this human subjects research qualifies for exempt status, (STUDY00017087) on March 28, 2024. Consent to participate Respondents gave verbal consent before using Let’s Talk Tech and interviews. All data reported are anonymized. Author contributions/CRediT Clara Berridge: Conceptualization; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing – original draft; Writing – review & editing. Natalie R Turner: Formal analysis; Investigation; Writing – original draft. William B Lober: Conceptualization; Funding acquisition; Methodology; Software; Writing – review & editing. George Demiris: Methodology; Writing – review & editing. Jeffrey Kaye: Methodology; Writing – review & editing. Data availability The survey data supporting the findings of this study are available on request from the corresponding author. The interview data are not publicly available due to privacy or ethical restrictions. References 1. Menne HL, Tucke SS, Whitlatch CJ, et al. Decision-making involvement scale for individuals with dementia and family caregivers. Am J Alzheimers Dis Other Demen 2008; 23: 23–29. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. Reamy AM, Kim K, Zarit SH, et al. Understanding discrepancy in perceptions of values: individuals with mild to moderate dementia and their family caregivers. Gerontologist 2011; 51: 473–483. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 3. Shelton EG, Orsulic-Jeras S, Whitlatch CJ, et al. Does it matter if we disagree? The impact of incongruent care preferences on persons with dementia and their care partners. Gerontologist 2018; 58: 556–566. [ DOI ] [ PubMed ] [ Google Scholar ] 4. Fanning J, Brinkley TE, Campbell LM, et al. Research centers collaborative network workshop on digital health approaches to research in aging. Innov Aging 2024; 8: igae012. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 5. NIA. Notice of Special Interest (NOSI): digital technology for early detection and monitoring of Alzheimer’s disease and related dementias, https://grants.nih.gov/grants/guide/notice-files/NOT-AG-21-048.html.U.S . (2022, January 6). [ Google Scholar ] 6. Department of Health and Human Services (DHHS). National plan to address Alzheimer’s disease: 2021 update, https://aspe.hhs.gov/collaborations-committees-advisory-groups/napa/napa-documents/napa-national-plans#:~:text=National%20Plan%20establishes%20six%20ambitious,Treat%20AD%2FADRD%20by%202025 (2021). [ Google Scholar ] 7. NIA. Approved concepts: leveraging multimodal and generative artificial intelligence to advance the application of social robotics in caregiving. National Institute on Aging, https://www.nia.nih.gov/approved-concepts (2024, May 28, accessed 10 February 2025). 8. National Alzheimer’s Project Act. Public members of the advisory council on Alzheimer’s research, care and services: 2022 recommendations. Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services, https://aspe.hhs.gov/collaborations-committees-advisory-groups/napa/napa-advisory-council (2022). [ Google Scholar ] 9. Abadir PM, Chellappa R, Choudhry N, et al. The promise of AI and technology to improve quality of life and care for older adults. Nat Aging 2023; 3: 629–631. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 10. Piau A, Mattek N, Crissey R, et al. When will my patient fall? Sensor-based in-home walking speed identifies future falls in older adults. J Gerontol A Biol Sci Med Sci 2020; 75: 968–973. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. Wu CY, Dodge HH, Gothard S, et al. Unobtrusive sensing technology detects ecologically valid spatiotemporal patterns of daily routines distinctive to persons with mild cognitive impairment. J Gerontol A Biol Sci Med Sci 2022; 77: 2077–2084. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 12. Martin SE, Tam MT and Robillard JM. Technology in dementia education: an ethical imperative in a digitized world. J Alzheimers Dis 2024; 97: 1105–1109. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 13. Berridge C, Turner NR, Liu L, et al. Advance planning for technology use in dementia care: development, design, and feasibility of a novel self-administered decision-making tool. JMIR Aging 2022; 5: e39335. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. Mahoney DF, Purtilo RB, Webbe FM, et al. In-home monitoring of persons with dementia: ethical guidelines for technology research and development. Alzheimers Dement 2007; 3: 217–226. [ DOI ] [ PubMed ] [ Google Scholar ] 15. Meiland F, Innes A, Mountain G, et al. Technologies to support community-dwelling persons with dementia: a position paper on issues regarding development, usability, effectiveness and cost-effectiveness, deployment, and ethics. JMIR Rehabil Assist Technol 2017; 4: e6376. [ Google Scholar ] 16. Onken LS, Carroll KM, Shoham V, et al. Reenvisioning clinical science: unifying the discipline to improve the public health. Clin Psychol Sci 2014; 2: 22–34. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 17. Thorstensen E. Privacy and future consent in smart homes as assisted living technologies. In: Zhou J and Salvendy G (eds) Human aspects of IT for the aged population. Applications in health, assistance, and entertainment. Cham: Springer International Publishing, 2018, pp.415–433. [ Google Scholar ] 18. Turner NR and Berridge C. How I want technology used in my care: learning from documented choices of people living with dementia using a dyadic decision making tool. Inform Health Soc Care 2023; 48: 387–401. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 19. Whitlatch CJ, Judge K, Zarit SH, et al. Dyadic intervention for family caregivers and care receivers in early-stage dementia. Gerontologist 2006; 46: 688–694. [ DOI ] [ PubMed ] [ Google Scholar ] 20. Alzheimer Europe. 2010 Alzheimer Europe report: the ethical issues linked to the use of assistive technology in dementia care: 1–128, https://www.alzheimer-europe.org/resources/publications/2010-alzheimer-europe-report-ethical-issues-linked-use-assistive-technology?language_content_entity=en (2010, accessed 9 September 2024). 21. Berridge C, Demiris G and Kaye J. Domain experts on dementia-care technologies: mitigating risk in design and implementation. Sci Eng Ethics 2021; 27: 14. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Grigorovich A and Kontos P. Towards responsible implementation of monitoring technologies in institutional care. Gerontologist 2020; 60: 1194–1201. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 23. Lariviere M, Poland F, Woolham J, et al. Placing assistive technology and telecare in everyday practices of people with dementia and their caregivers: findings from an embedded ethnography of a national dementia trial. BMC Geriatr 2021; 21: 121. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 24. Robillard JM, Cleland I, Hoey J, et al. Ethical adoption: a new imperative in the development of technology for dementia. Alzheimers Dement 2018; 14: 1104–1113. [ DOI ] [ PubMed ] [ Google Scholar ] 25. Sriram V, Jenkinson C and Peters M. Informal carers’ experience of assistive technology use in dementia care at home: a systematic review. BMC Geriatr 2019; 19: 160. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 26. U.S. Department of Health and Human Services. Aging in the United States: a strategic framework for a national plan on aging. Report to Congress, https://www.hhs.gov/about/news/2024/05/30/hhs-delivers-strategic-framework-national-plan-aging.html#:~:text=%E2%80%9CThe%20Aging%20in%20the%20United,improve%20their%20health%20and%20wellbeing (2024). 27. Berridge C, Turner NR, Liu L, et al. Preliminary efficacy of let’s talk tech: technology use planning for dementia care dyads. Innov Aging 2023; 7: igad018. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 28. Berridge C, Zhou Y, Lazar A, et al. Control matters in elder care technology: evidence and direction for designing it. In: Proceedings of the 2022 ACM designing interactive systems conference. DIS ‘22, 2022, pp.1831–1848: Association for Computing Machinery. [ Google Scholar ] 29. Lyons KS and Lee CS. The theory of dyadic illness management. J Fam Nurs 2018; 24: 8–28. [ DOI ] [ PubMed ] [ Google Scholar ] 30. Bryant JA and David P. Solving for inclusive technology for older adults. AARP Int J 2020; 13: 62–65. [ Google Scholar ] 31. Mikula CM, Perry C, Boone AE, et al. Dementia caregiver insights on use of assistive technologies. Work Aging Retirement 2024; 10: 14–24. [ Google Scholar ] 32. Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009; 42: 377–381. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 33. Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform 2019; 95: 103208. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 34. Dedoose. Dedoose version 9.2.12, Cloud application for managing, analyzing, and presenting qualitative and mixed method research data, www.dedoose.com (2024). 35. Deterding NM and Waters MC. Flexible coding of in-depth interviews: a twenty-first-century approach. Sociol Methods Res 2021; 50: 708–739. [ Google Scholar ] 36. Nowell LS, Norris JM, White DE, et al. Thematic analysis: striving to meet the trustworthiness criteria. Int J Qual Methods 2017; 16: 1609406917733847. [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Supplementary material NIHMS2150437-supplement-Supplementary_material.docx (18.8KB, docx) Data Availability Statement The survey data supporting the findings of this study are available on request from the corresponding author. The interview data are not publicly available due to privacy or ethical restrictions. ACTIONS View on publisher site PDF (419.8 KB) Cite Collections Permalink PERMALINK Copy RESOURCES Similar articles Cited by other articles Links to NCBI Databases Cite Copy Download .nbib .nbib Format: AMA APA MLA NLM Add to Collections Create a new collection Add to an existing collection Name your collection * Choose a collection Unable to load your collection due to an error Please try again Add Cancel Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top