A Counterbalanced Crossover Pilot Study of a Personalized Smartphone Reminder Application for Older Adults with Cognitive Impairment - PMC 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 Neuropsychol Rehabil . Author manuscript; available in PMC: 2026 Apr 17. Published in final edited form as: Neuropsychol Rehabil. 2025 Apr 17;36(1):1–35. doi: 10.1080/09602011.2025.2489125 Search in PMC Search in PubMed View in NLM Catalog Add to search A Counterbalanced Crossover Pilot Study of a Personalized Smartphone Reminder Application for Older Adults with Cognitive Impairment Katherine Hackett Katherine Hackett 1 Department of Psychology and Neuroscience, Temple University; Icahn School of Medicine at Mount Sinai. Find articles by Katherine Hackett 1 , Moira Mckniff Moira Mckniff 2 Department of Psychology and Neuroscience, Temple University Find articles by Moira Mckniff 2 , Sarah Lehman Sarah Lehman 3 Department of Computer and Information Sciences, Temple University; NASA Langley Research Center, Hampton, Virginia. Find articles by Sarah Lehman 3 , Emma Pinsky Emma Pinsky 4 Department of Psychology and Neuroscience, Temple University; Department of Psychology, Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY. Find articles by Emma Pinsky 4 , Chiu C Tan Chiu C Tan 5 Department of Computer and Information Sciences, Temple University Find articles by Chiu C Tan 5 , Marina Kaplan Marina Kaplan 6 Department of Psychology and Neuroscience, Temple University Find articles by Marina Kaplan 6 , Giuliana Vallecorsa Giuliana Vallecorsa 7 Department of Psychology and Neuroscience, Temple University Find articles by Giuliana Vallecorsa 7 , Mijail D Serruya Mijail D Serruya 8 Raphael Center for Neurorestoration, Farber Institute for Neuroscience, Thomas Jefferson University Find articles by Mijail D Serruya 8 , Tania Giovannetti Tania Giovannetti 9 Department of Psychology and Neuroscience, Temple University Find articles by Tania Giovannetti 9 Author information Article notes Copyright and License information 1 Department of Psychology and Neuroscience, Temple University; Icahn School of Medicine at Mount Sinai. 2 Department of Psychology and Neuroscience, Temple University 3 Department of Computer and Information Sciences, Temple University; NASA Langley Research Center, Hampton, Virginia. 4 Department of Psychology and Neuroscience, Temple University; Department of Psychology, Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY. 5 Department of Computer and Information Sciences, Temple University 6 Department of Psychology and Neuroscience, Temple University 7 Department of Psychology and Neuroscience, Temple University 8 Raphael Center for Neurorestoration, Farber Institute for Neuroscience, Thomas Jefferson University 9 Department of Psychology and Neuroscience, Temple University ✉ Corresponding Author: Tania Giovannetti, Ph.D., ABPP-CN, Temple University, Department of Psychology and Neuroscience, Philadelphia, PA, USA, [email protected] Issue date 2026 Jan. PMC Copyright notice PMCID: PMC12353096 NIHMSID: NIHMS2074833 PMID: 40244883 The publisher's version of this article is available at Neuropsychol Rehabil Abstract The SmartPrompt2 iPhone app was designed according to a neuropsychological framework, empirical data, and participant feedback to facilitate the efficient completion of everyday tasks at home by sending personalized prompts to participants’ smartphones. Feasibility, efficacy in the home environment, and usability were examined in ten participants with MCI or mild dementia and their care-partners ( NCT04313582 ). Participants and care-partners identified two individually relevant tasks for the participant to complete for two weeks with the SmartPrompt2 app (SP condition) and for two weeks without the app (Control condition; order counterbalanced). The SmartPrompt2 alerted them to complete their tasks each day at times specified by the participant/care-partner using personalized images, audio, rewards, motivational features and logging features targeting common sources of everyday errors. Care-partners reported significantly higher participant task completion and lower burden during the SP condition versus Control condition. There was no significant difference in participants’ average level of frustration between the two conditions. Usability ratings were high at the end of the study, and all participants requested to keep the app. Larger and longer effectiveness studies are needed, but preliminary data support the feasibility, efficacy and usability of the SmartPrompt2 for improving everyday function in older adults with cognitive impairments. Trial registration NCT04313582 Keywords: everyday action, dementia, mild cognitive impairment, Alzheimer’s disease, memory failure, prompting, assistive technology Introduction Difficulties performing everyday tasks (i.e., functional disability) is a primary reason for the high cost of care for people with dementia ( Alzheimer’s Association, 2016 ; Anderson & Hussey, 2000 ; Kelley et al., 2015 ), as functional difficulties lead to a range of secondary health problems for the person with dementia and their family ( Knapp, 2015 ). Assistive personal digital devices, like smartphones, hold promise as an inexpensive solution to improve daily functioning and reduce the wide range of negative consequences associated with functional disability. Smartphone reminder applications (apps) deliver cues to perform important daily activities (e.g., take medication) and are widely available, but have been limitedly studied in older adults with cognitive impairment ( Schepens Niemiec et al., 2023 ; Scullin et al., 2022 ). More importantly, few apps have been codesigned by neuropsychologists with and for older people with cognitive impairment ( Cole et al., 2022 ). This study investigated the feasibility, efficacy, and usability of a reminder app called the SmartPrompt2, which was iteratively developed for older adults with cognitive impairments to use on their personal smartphone and was informed by neuropsychological theories of everyday task failures ( Boyle et al., 2003 ; Giovannetti et al., 2006 , 2021 ; Huppert et al., 2000 ; McDaniel & Einstein, 2000 ; Oriani et al., 2003 ; Rog et al., 2014 ), laboratory-based pilot testing ( Hackett et al., 2022 ), and principles of codesign (i.e., incorporating input and feedback from patients and care-partners). Digital calendars for daily activity management are of great interest to older adults, who often use digital tools along with paper and pencil– possibly because existing digital programs are not optimized for this population ( Benge et al., 2024 ; Chun & Patterson, 2012 ; Siek et al., 2005 ). Most commercially available reminder/calendar apps involve complex interfaces and provide minimal or no guidance following the initial reminder alert. Older adults with cognitive impairments, who might benefit most from reminder apps, require simple interfaces and explicit instruction to circumvent the multitude of cognitive challenges that preclude successful task recall and completion. For example, a typical reminder alert may be ineffective for someone with dementia because the alert may not capture their attention, and because they may become distracted while moving to a different room to begin the task, may fail to initiate the task due to apathy, may forget that they completed the task, and may quickly lose motivation to use the reminder app over time ( Scullin et al., 2022 ). Development of the SmartPrompt 2 Our team developed a simple smartphone reminder app, called the SmartPrompt, specifically for older adults with cognitive impairment. The original SmartPrompt was initially deployed on a single laboratory smartphone (Android; Samsung Galaxy S2) and was evaluated in a pilot study conducted entirely within the laboratory setting. We used a within-participant, counterbalanced cross-over design requiring participants to remember to retrieve a glass of water at four specific times with or without the aid of the SmartPrompt (order counterbalanced). During the pilot task, a clock and reminder card indicating the target task times were available behind the participant’s chair for checking throughout the session if needed. At the end of the study, participants and care-partners provided feedback via validated usability scales and qualitative free response questions. Results showed that when using the SmartPrompt, participants retrieved significantly more glasses of water, were significantly more likely to retrieve the water at the right time and checked the clock and cue card significantly less frequently. Participants and care-partners learned to use the SmartPrompt with relative ease and provided favorable usability ratings overall along with suggestions for improvement ( Hackett et al., 2022 ). Thus, the SmartPrompt improved task completion and reduced inefficient checking behaviors in a controlled pilot setting following brief training, warranting continued development and evaluation in an extended at-home trial. The SmartPrompt2 was iteratively designed and included all the features of the original SmartPrompt plus key modifications informed by the experimental pilot and participant feedback, aligning with a user centered approach and principles of codesign ( Cole et al., 2022 ; Schulz et al., 2015 ). It was developed for the iPhone family of smartphones using the Swift programming language and Xcode development environment. The iOS platform was chosen due to compatibility issues experienced while trying to target Android devices with the original SmartPrompt; the constraints of the iOS ecosystem allowed our team to reach a wider range of phone operating system versions with fewer application rewrites. The central features of the SmartPrompt were designed to target known cognitive impairments that cause task failure in dementia based on neuropsychological principles. The features are listed and described in Table 1 and illustrated in the app functions in Figure 1 . Prompting begins with a reminder alert designed to target prospective memory failures, which are common in older adults with cognitive impairment ( Kinsella et al., 2018 ). During pilot testing of the original SmartPrompt, we observed that a standard alarm sound was occasionally ignored by participants with dementia. Further, some participants and care-partners commented that the standard alarm sound was confusing or annoying and should be personalized. Therefore, we designed the new SmartPrompt2 to include a highly personalized audio alert to capture attention and increase motivation to compete the task. To maintain some level of experimental control alongside personalization, each participant’s alert included their name (i.e., “cocktail party” effect; Golden et al., 2013 ) and an instruction to look at their phone for more information. Participants and care-partners were encouraged to consider having someone special (e.g., grandchild, spouse) record the alert to increase motivation and arousal. The instruction shown on the screen also was personalized to include custom text and a photo of the participants’ personal object(s) that are used in completing the task, as personal objects are known to elicit richer semantic and episodic memories than generic objects ( Giovannetti et al., 2006 ). Table 1. Features of the Original Smartprompt and the SmartPrompt2 and the Cognitive Impairment Targeted by Each Feature. Feature SmartPrompt (Original) SmartPrompt2 Key Feature Updates Cognitive Target Reminder alert with nudges Standard auditory alarm sound that repeated every 1 minute if ignored; alarm repeated max 3 times Personalized auditory alarm and push notification. The auditory alert included the participant’s first name, instructed them to look at their phone. (e.g., “Hey Joe look at your phone!”), and was recorded by a familiar person. If the participant did not respond to the alert, it was automatically deployed again 15 minutes later as a push notification. Personalized auditory alert with push notification Prospective memory impairment, goal decay, distractibility Choice Initial alarm programmed at pre-defined times; no overt option to defer; participants selected "On my way" button when ready to complete task Participants were given the choice to delay task completion in case they were occupied and were not able to direct their full attention. A slider bar with two options: "Do it Now" in green font or “Do it Later” in red font was displayed. When participants selected "Do it Later" the reminder alert was deployed again 15 minutes later. New feature to improve flexibility and usability Distractibility/multitasking Instructions Standard instruction text without photo Screen showed customized photo prompt of the objects needed or the scene where the target task must be completed. A written reminder of the task goal was presented along with the photo, using custom language chosen by the participant/care-partner. Personalized text and photos of individually-relevant objects Semantic knowledge degradation Photo Log and Task List Participant takes photo of completed task which is logged for viewing at any time by the participant or caregiver. Task list was not included Participant is instructed to take a photo of the completed task (e.g., for “take medication” the participant takes a photo of their pillbox) using a simplified camera viewfinder instead of the iPhone camera interface. The photo is logged into the system and may be viewed by the participant or caregiver at any time. Participant is able to re-take photo until they are pleased with the photo quality. The task list showed tasks after the time that they were due. Tasks that were completed/logged were shown in strikethrough text (i.e., crossed out). Tasks that were not completed/logged were listed in plain text. At any time after the task appeared on the list, the participant could tap on the task and receive prompts to complete and log the task from the task list. Simplified camera interface, option to re-take photo, and addition of task list. Episodic memory impairment Progress bar and reward for task completion Points are awarded as photos are collected into the photo log and shown in a horizontal progress bar after each task. After completing the last task, a standard reward was presented. Points are awarded as photos are collected into the photo log and shown in a progress circle after each task. After completing the last task of each day, a custom reward song, which was selected by the participant, was played for 30 seconds. Circular progress bar and personalized reward Apathy Open in a new tab Figure 1: Open in a new tab Function of SmartPrompt2 app features as they unfold over time. The numbered boxes depict sequential steps involved in responding to a task prompt. Alt Text: A series of numbered boxes including a screenshot of the smartphone showing the SmartPrompt2 app features across seven sequential steps, beginning with the initial personalized alert and ending with the personalized reward and progress circle. Reminder nudges (i.e., automatic repetition of the alert if ignored) were retained in the SmartPrompt2 to address distractibility. In the SmartPrompt2 “push” notifications per iOS were set as “persistent” to maintain presence on the home screen (or notification tray) until explicitly addressed or dismissed, thus reducing the likelihood that they would be accidentally missed. Additionally, the Smartprompt2 offered the choice to engage in the target task “now” or “later” – which is more relevant in the home environment where there are more distractions and competing demands compared to laboratory pilot testing. Another important feature retained in the SmartPrompt2 is the Photo Log, which enables participants to log a photo of their completed task for review later. A new Task List feature was added to the SmartPrompt2. As shown in Figure 2 , the Task List included only tasks that were successfully completed or those that were past due each day. Future tasks were not shown in the Task List to prevent participants from doing tasks too soon and to prevent visual overwhelm. After completion of the first task of each day, the task would be shown in the list in strikethrough text. After both daily tasks were completed, both tasks would be listed in strikethrough text. If the participant missed the original alarm and the task had not been completed, it would appear in the task list in regular text. The participant could tap on the regular text to launch the sequence shown in Figure 1 and receive the prompts to perform and log the task. The Photo Log and Task List were designed to address episodic memory failures regarding whether the task had been completed and to prevent mistakenly repeating tasks. Participants and care-partners were instructed that they could log into the SmartPrompt2 and view the Photo Log and/or Task List at any time; thus, minimizing interactions between participants and care-partners regarding whether a task had been completed, which some participants perceived as “nagging” or unpleasant at times (as reported during qualitative feedback in the original pilot). Figure 2: Open in a new tab An example of the SmartPrompt2 Task List feature showing the participant’s first task, which was due at 3:35PM and was completed by the participant. The second task for the day is not shown in the Task List because it was not due until later in the evening. Alt Text: A screenshot of the SmartPrompt2 Task List feature showing the participant’s first task, which was due at 3:35PM, in strikethrough text because it was completed by the participant. The second task for the day is not shown in the Task List because it was not due until later in the evening. The original SmartPrompt included a horizontal progress bar and a standardized reward upon task completion (i.e., Graphics Interchange Format (GIF) of a puppy). The SmartPrompt2 included a personalized reward to increase and maintain participants’ motivation to use the app, as past studies have shown that engagement with traditional reminder apps fades over time ( Scullin et al., 2022 ) and because participants in the pilot study suggested enhanced rewards. Participants were asked to share their favorite song prior to app programming so that a snippet of the song could be played after they logged the last task of each day. Additionally, we updated the horizontal progress bar to a circular progress ring that was displayed after completion of each task based on gamification principles to increase motivation ( Sailer et al., 2013 ). As with the original SmartPrompt, the overall design of the SmartPrompt2 included a very simple interface with large, high-contrast text and “buttons” following evidence of age-related differences in human-computer interaction and cognitive rehabilitation theory ( Chun & Patterson, 2012 ; Dixon et al., 2022 ; Seelye et al., 2012 ; Siek et al., 2005 ). Improvements from the original interface included increasing the size of the text, simplifying the camera buttons, incorporation of a large slider bar to progress to the next step, and adding pictures along with text. These modifications were made to improve usability and reduce unintentional errors based on observations from the pilot study (e.g., accidentally progressing to the next screen before ready due to fine motor difficulties). Finally, the revised SmartPrompt2 included separate “participant,” “care-partner,” and “experimenter” views that enabled access to different features. The “participant” view allowed access to the Photo Log and Task List for only the current day to minimize overload and confusion. The “care-partner” and “experimenter” views included access to all past and current photos and tasks in the Log and Task List. Additionally, the “experimenter” view allowed for new prompts to be added and programed. During the study care-partners did not have access to the “experimenter” view. Current Study of the SmartPrompt2 The present study extended our experimental pilot of the original SmartPrompt by evaluating the new SmartPrompt2 app on participants’ personal smartphones and in their home environment with tasks of their choosing. Feasibility, efficacy, and usability of the SmartPrompt2 were evaluated from both the participant and the care-partner’s perspective. These outcomes were compared with and without the Smartprompt2 in a counterbalanced crossover study design. Efficacy variables included both evaluation of benefits (task completion) as well as negative consequences, such as increased caregiver burden, participant frustration, or other unforeseen adverse effects of the app. We predicted that the simple interface and highly structured prompts embedded in the design of the SmartPrompt2 would lead to relatively seamless deployment in the home following brief training procedures (i.e., high feasibility). We also predicted that efficacy would be demonstrated through reports of greater task completion and less care-partner assistance, but no difference in participant frustration, when completing the target tasks with versus without the SmartPrompt2. Measuring both positive and negative consequences is important, because even if the app markedly increased task completion, it would not be eagerly adopted if it also led to high levels of frustration and care-partner burden. Regarding usability, we predicted high care-partner and participant usability ratings based on positive reviews of the original SmartPrompt ( Hackett et al., 2020 ). Exploratory correlation analyses that examine the participant features associated with SmartPrompt2 efficacy and usability are reported in Supplementary Materials . Methods Participants: Older adults with a self-reported diagnosis of mild dementia or MCI regardless of etiology (e.g., “all-cause dementia”; McKhann et al., 2011 ) were recruited from neurology clinics and the Philadelphia community using informational flyers. In addition to requiring a diagnosis of MCI/mild dementia diagnosis, the following inclusion/exclusion criteria were reviewed over the phone by a member of the study team upon initial contact: 1) age 65 or older; 2) self-reported English language fluency; 3) availability of a study/care-partner; 4) no lifetime history of severe psychiatric disorder (e.g., schizophrenia, bipolar disorder), nervous system infections or disorders other than dementia (e.g., epilepsy, brain tumor, large-vessel stroke, major head trauma), or major intellectual disability; 5) no known current metabolic or systemic disorders (e.g., B12 deficiency, renal failure, cancer); 6) no severe sensory deficits that would preclude viewing a smartphone screen or hearing the smartphone prompt (e.g., blindness, total hearing loss); 7) no severe motor difficulties that would preclude the use of a smartphone (e.g., paralysis of both upper extremities); and 8) own and regularly use an iPhone with iOS 10 or higher. Participants who met inclusion criteria were also classified as having subjective cognitive decline, MCI, or dementia according to cognitive tests administered as part of the study and actuarial criteria described below. Care-partners had to be at least 18 years old, fluent in English, and had to live with or have daily contact with the study participant. Care-partners also had to be cognitively healthy with no diagnosis of dementia or other major health problems that would preclude daily participation in the study over four weeks. When recruited, participants and care-partners were told that entry into the study required them to identify a task or tasks that the participant wanted or needed to perform daily over the course of the 4-week study. Further, they were told that the participant should be having trouble consistently remembering to perform the targeted activities independently. Procedures Overview: This study was conducted with the formal approval of the Temple University Institutional Review Board in accordance with ethical standards for research with human subjects. All participants and care-partners provided written informed consent and were compensated for their time in the study. Additionally, details of the study, including the primary analyses were registered in clinical trials.gov ( NCT04313582 ). The study required participants and care-partners to track the completion of two target tasks and associated behaviors (e.g., frustration, burden) each day during a four-week period as depicted in Figure 3 . Daily diaries were used for self-reported outcomes throughout the four-week study period. For two consecutive weeks the participants used the SmartPrompt2 app to facilitate and log completion of the target task (SmartPrompt [SP] condition), and for the other two consecutive weeks participants performed the target tasks without the SmartPrompt2 (Control condition). Before beginning the study conditions, participants completed an initial session that included informed consent, review of the scientific rationale behind the SmartPrompt2, demographics questions, cognitive tests and clinical questionnaires, and questions to personalize the SmartPrompt2 app for the SP condition (see below). Next, participants were assigned to undergo either the Control condition followed by the SP condition or vice versa. The order of conditions differed for each consecutive participant, such that the condition order was counterbalanced across participants (i.e., half of the participants completed the Control condition first). The SP condition consisted of a single training session, two-week SP test period, and follow-up usability reporting. Care-partners also completed SmartPrompt2 training with the participant and were recruited to track outcomes during the SP and Control conditions. During the SP condition, care-partners also were asked to oversee the functioning of the participant’s smartphone (e.g., charging) and to provide timely reporting of technical problems with the app. The Control condition lasted two weeks to match the SP condition. Figure 3 depicts the overall flow of study procedures; details of the study measures and conditions are provided below. Figure 3: Open in a new tab Flowchart depicting the study procedures. Alt Text: Flowchart depicting how the study procedures unfold over time, beginning with the recruitment and screening step. The flowchart depicts the crossover study design and the counterbalancing of the SmartPrompt and Control conditions. Initial Assessment Informed Consent and Discussion of Study Rationale: The initial assessment began with informed consent and a discussion about the scientific rationale of the SmartPrompt2. The study team reviewed an infographic with participants and care-partners including brief bullet points on: 1) “What is the SmartPrompt?”; 2) “How is the SmartPrompt different from other alarms or calendar apps?”; 3) “How might the SmartPrompt help me?”; and 4) “What is my role as a research participant?” Our intention was to provide educational background, achieve shared understanding of the scientific rationale, promote transparency of research expectations, encourage questions about study participation, and provide context before progressing into the specifics of the technology. This practice is in line with principles of codesign including promoting engagement and ensuring a mutual exchange of knowledge ( Cole et al., 2022 ). Participant Cognitive Testing and Questionnaires: The initial assessment included cognitive testing and questionnaires to characterize participants and explore relations between participant features and SmartPrompt2 outcomes. The Mini-Mental Status Exam (MMSE) was administered as a dementia screener and the Hopkins Reading test was used to estimate premorbid IQ ( Schretlen et al., 2009 ). Participants also completed tests of episodic memory [Hopkins Verbal Learning Tests-Revised ( Brandt, 2017 ), Brief Visuospatial Memory Test-Revised ( Benedict et al., 1996 )]; executive function/attention [Trail Making Test ( Reitan, 1958 ), Digit Span ( Wechsler, 1987 )]; language [Animal Fluency ( Schretlen & Vannorsdall, 2010 ), Boston Naming Test ( Selnes et al., 1988 )]; and processing speed (Pattern/Letter Recognition; Salthouse, 1991 ). Tests were selected for their psychometric properties, association with functional abilities, and availability of demographically-corrected norms ( Schretlen et al., 2010 ). After obtaining demographically adjusted (age, sex, education, premorbid IQ) T-scores for each cognitive test score, an average composite was computed to reflect overall cognitive ability level (T score of 50 = average). The T-score for the episodic memory test (HVLT-R Delayed Free Recall) was examined separately, given the central importance of memory functioning in the study of electronic memory aids. Questionnaires were administered to obtain information on demographics (age, sex, level of education), depression symptoms (Geriatric Depression Scale; Yesavage et al., 1982 ). Several participant factors, including motivation, attitudes regarding computers, computer anxiety, and smartphone proficiency, were evaluated with questionnaires to further characterize the sample and for exploratory, non-parametric correlations with SmartPrompt2 outcomes; ancillary questionnaires are described in the Supplementary Materials . Care-partner Questionnaires: During the initial assessment, the study partner completed questionnaires about the participant’s ability to perform everyday tasks (Functional Activities Questionnaire, FAQ Pfeffer et al., 1982 ) and declines in the participant’s everyday cognitive abilities over the past 10 years (ECog; Measurement of Everyday Cognition; Farias et al., 2008 ). Higher scores on the FAQ and ECog indicate worse functional abilities and greater decline in cognitive abilities, respectively. Target Task Identification and SmartPrompt2 Personalization: Participants and care-partners were provided detailed instructions and guidance to select personalization features for the SmartPrompt2 app. First, using a standardized script, they were instructed to identify two tasks that are important to them and that they have difficulty completing independently. Target tasks had to be done at two different times during the day and had to be done every day. Participants and care-partners were given examples including drink water for hydration, take medication, or meal preparation, and had the opportunity to collaboratively discuss their selection with a study coordinator who could advise on the feasibility of each task choice based on prior experience. The script also was used to inform participants and care-partners to provide digital photos of the target task that clearly depicted the specific household objects needed to complete their target tasks (1 photo per task; e.g., picture of vitamin bottle if using the SmartPrompt2 to remember to take vitamins). They also were instructed to provide an audio file of a recording for the SmartPrompt2 alert. The alert had to include the participant’s name and directions to look at their smartphone (e.g., “Hey Joe, look at your phone.”). Participants/care-partners had the option to record the prompt themselves or have someone close to them record the message (e.g., grandchild). Finally, participants/care-partners were instructed to select a custom audio reward, which could be a self-generated audio file (e.g., encouraging message from family) or their favorite song which the study team converted into a smaller snippet. Participants were informed that the audio reward would play only if both tasks were successfully completed at the end of each day. Control Condition During the two-week Control condition, participants and care-partners were asked to complete a paper daily diary at the end of each day. Participants were instructed not to go back and complete past diary entries that were incomplete, because delayed recall of task completion may be inaccurate and incomplete daily dairies were included as an outcome. Participants’ daily diaries included six total questions; the following three questions were posed for each task (1 and 2) each day: Did you (do task 1/2) today? Response options included “yes,” “no” and “not sure.” Did you (do task 1/2) at the right time (time here)? Response options included “yes,” “no” and “not sure.” When you (completed task 1/2) today, how frustrated did you feel? Response options included “0- not very frustrated,” “1- somewhat frustrated”, and “2- very frustrated.” Care-partners also were asked to complete their own paper daily diary at the end of each day during the two-week Control condition. They were instructed not to consult with the participant about the questions, and if they were not sure of the response, then they were instructed to respond, “not sure.” In contrast to the instructions given to participants, care-partners were told that they could go back and complete questions if they forgot to do so at the end of the day; they were asked to indicate which diary entries were not completed on time. Care-partners were told not to remind the participant to complete their daily diary questions. Care-partners received a text at the end of each day (at a time that they specified) to remind them to complete the daily diary each day. The care-partner’s daily diary included six questions per day; the following questions were posed for each task: Did (name of participant do task 1/2) today? Response options included “0- did not do it,” “1- did it with assistance,” “2- did it alone but with some difficulty,” “3- completed the task without error,” “not sure” Did (name of participant do task 1/2) at the right time (time here)? Response options included “yes,” “no” and “not sure.” When (name of participant completed task 1/2) today, how burdened did you feel? Response options included “0 – no burden (it did not require my attention,” “1-minimal burden (it required minimal attention on my part),” “2- some burden (it required my attention and was somewhat frustrating,” “3- severe burden (it required a great deal of my time and was very stressful).” SmartPrompt (SP) Condition The SP condition included 1) training, 2) testing (two weeks), and 3) usability reporting. The SmartPrompt2 was installed on the participant’s personal iPhone and was programmed to send two alerts to the participant on each day of the two-week testing period. The alerts were sent at the time of the participant’s and care-partner’s choosing. The SmartPrompt2 included a personalized reminder alert, written command, and the multiple features described in Figure 1 and Table 1 . SmartPrompt2 Training: Training took place during a single session according to detailed and standardized procedures that included education and familiarization of the SmartPrompt2 app and two practice runs for the participant followed by additional training for the care-partner. First, the participant and care-partner were shown a 1-minute video of a person using the SmartPrompt2 in a naturalistic setting. Then, a member of the study team reviewed the functions of the SmartPrompt2 step-by-step using a 16-slide presentation with animations. After the slideshow, they were shown the 1-minute video a second time to reinforce learning. Next, participants were asked to complete their first practice run by responding to a “test” SmartPrompt2 alarm. The participant was asked to talk through their actions so that the researcher could correct and redirect incorrect actions consistent with errorless learning principles ( Evans et al., 2000 ). Extensive feedback was provided by the study team during the enactment in accord with a cueing hierarchy. After reaching criterion, the participant was shown additional slides reviewing other SmartPrompt2 features (e.g., what to do if an alert is missed, where to locate the SmartPrompt2 on their phone’s home screen, how to use the Task List to check whether they’ve completed their target tasks). They were also reminded to carry their smartphone with them throughout the study period and to complete the daily diary. Finally, the participant was asked to perform one more practice run - this time using the “snooze” feature (i.e., Do it Later) in response to the practice alert, to enable practice of all features. Both practice runs were repeated until the participant was successful in using the SmartPrompt2 without extensive cues and prompts according to a training criterion (see Supplemental Materials ). At the end of training, participants were offered a range of carrying cases (e.g., belt clip, arm band, etc.) to help them keep the phone close at all times. After the care-partner observed the participant training, they underwent additional training that included information about the care-partner features of the app (e.g., confirming task completion by reviewing the Photo Log and the Task List for the day; see Supplemental Materials ). Care-partners also were reminded to complete the daily diary and were asked to contact the study team in case the smartphone was damaged or lost, or if the phone or SmartPrompt2 app were not functioning. All participants and care-partners were provided with a printed study manual that included the detailed instructions that were reviewed during the training session. Care-partners completed a training quiz to evaluate retention of the training. The quiz included short performance-based components and several open-ended questions to evaluate knowledge of the SmartPrompt2. The training session was not terminated until the care-partner was able to respond correctly to all the quiz items and both the participant and care-partner reported feeling comfortable with the SmartPrompt2 procedures. The time spent training the participant and the care-partner was recorded. SP Testing: The SmartPrompt2 alerts were programmed to begin the day following the training session and continue for two weeks. During the two-week SP condition, the participant was instructed to complete the target tasks twice per day in response to the SP prompts, including logging a photo of the completed tasks. During the SP condition, participants and care-partners also completed a paper daily diary at the end of each day. The questions in the participant’s daily diary were identical to the questions that were included during the Control condition (as explained above). Care-partners’ diaries included the same questions included in the diaries for the Control condition, as well as two additional questions per day: Did (participants’ name) remember how to use the SmartPrompt today? Response options included “No (0)” or “Yes (1)” Were there any technical problems with the SmartPrompt today? Response options included “No (0)” or “Yes (1)”; care-partners were encouraged to describe the technical problems “If Yes, describe:” After the questions, a note on the diary sheet reminded care-partners to ensure that the participant’s smartphone was charged at the end of the day. SP Usability Testing: After completing the SP condition, usability was assessed from the participant and the care-partner using a combination of validated usability questionnaires and internally-developed usability questions. Both the care-partner and the participant completed the Systems Usability Scale (SUS), a well-validated and easy to complete questionnaire ( Bangor et al., 2009 ; Lewis & Sauro, 2009 ). Scores on the SUS of at least 70 indicate adequate usability. Further details on the measures and questions administered to evaluate usability are included below and in Table 4 . Table 4. List and Description of Usability Measures Usability * Outcome Description Range * Care-partner-SUS and Participant-SUS At the end of the SP condition, caregivers completed a modified version of the System Usability Scale, which included 10 items evaluated on a 1 (strongly disagree) to 5 (strongly agree) point scale. After correction (−1 for odd items and −5 for even, reverse-scored items), the total is multiplied by 2.5 to yield a total score ranging from 0 (poor usability) to 100 (excellent usability). 0 - 100 * Care-partner Overall Rating and Participant Overall Rating A single seven-point adjective rating question regarding the usability of the SmartPrompt from worst imaginable (1) to best imaginable (7) was administered and scored separately from the SUS. 1-7 Care-partner and Participant Net Promoter Score A single 11-point scale to evaluate one's willingness to recommend the SmartPrompt2 to others: On a scale of 0 (not likely to recommend) to 10 (extremely likely to recommend) how likely are you to recommend the SmartPrompt to a friend/family member in the same position as you? 0 - 6 unhappy user; 7-8 unenthusiastic user; 9 - 10 enthusiastic user/promoter. 0 - 10 Participant Feature Ratings Participants were asked to rate four key features of the SmartPrompt2 (custom alarm, nudges, delay option, photo log) as helpful, neutral, or not helpful/distracting. n/a Participant and Care-partner Open-ended Feedback Both care-partners and participants provided free-responses to the questions: "Was there anything you didn't like about the SmartPrompt2" and "What changes would you suggest to make the SmartPrompt2 more useful?" n/a Open in a new tab * Preregistered primary outcome measure NCT04313582 . Abbreviations: SP = SmartPrompt2; SUS = Systems Usability Scale At the end of the study, participants and care-partners also were asked if they wished to keep the SmartPrompt2 app, and if so, they were provided with written instructions on how to independently program alerts for future tasks. Outcome Measures and Analytic Plan All outcome measures are listed in Tables 2 , 3 and 4 . Table 2. List and Description of Feasibility and App Engagement Measures Feasibility * Outcome Description Range Study Completion Number of participants who completed the study. 0 - 10 Adverse Events Number of adverse events reported during the SP condition. no upper limit * Total Training Time Total Training Time refers to the length (in minutes) of the participant's SP training session (from start of training slideshow to completion of practice runs). no upper limit * Care-partner Problem Report Care-partner's responses to the following question in the daily tracking sheet during the SP condition: "Were there any problems with the SmartPrompt today?" (Yes = 1, No = 0). Responses were summed across the 2-week condition. A maximum score of 14 indicated that the participant experienced a technical problem everyday during the SP condition. Care-partners were encouraged to provide notes regarding the specific problem. 0 - 14 Participants' procedural retention of SP Care-partner's responses to the following question in the daily tracking sheet during the SP condition: "Did (participants" name) remember how to use the SP today?" (Yes = 1, No = 0). Responses were summed across the 2-week condition and then divided by the number of completed tracking sheets to compute a percent score that accounted for missing responses. Higher scores reflect better procedural retention of the SP. 0 - 100 App Engagement * Outcome Description Range SP Engagement Engagement with the SP app by selecting "Do it Now" or deferring the initial alert at some point during the day, regardless of whether the task was successfully logged. Engagement was captured directly by the app for each day during the SP condition. A higher score reflects more frequent engagement. 0 - 14 * SP Task Initiation Time Average time to initiate the target task (select "Do it Now") after the SmartPrompt2 initial alert (reported in minutes) Shorter initiation times reflect faster time to initiate the target task. 1 - no upper limit Prompt Deferrals (Do it Later) The total number of times a participant deferred the alarm to a later time by selecting "Do it Later." 0 - 28 Open in a new tab * Preregistered primary outcome measure NCT04313582 . Abbreviations: SP = SmartPrompt2; SUS = Systems Usability Scale Table 3. List and Description of Efficacy Measures Efficacy * Outcome [Care-partner] Description Range * Task Completion Using the daily diary at the end of each day in each condition, care-partners rated the participant’s ability to complete each of the two target tasks on the following scale: failed to complete task = 0; completed the task with assistance= 1; completed the task with some difficulty = 2; completed the task with no difficulty = 3 Care-partners also had the option to report “not sure” in which case the response was treated as missing. An average Task Completion score was computed to account for missing and/or “not sure” responses. Higher scores indicate better task performance. 0 - 3 * Care-partner Burden Using the daily diary at the end of each day in each condition, care-partners rated the level of burden they experienced in assisting the participant with each target task on a scale from 0 (no burden) to 4 (severe burden). An average score was computed in case of missing responses. Higher scores reflect greater burden. 0 - 4 Task Timeliness Using the daily diary at the end of each day in each condition, care-partners rated whether participants completed each target task at the right time using the following response options: Yes = 1; No = 0, or Not Sure. A proportion score was computed to account for not sure/missing responses. Higher proportion scores indicate more tasks were performed at the right time. 0 - 100 Care-partner's Overall Impression of Efficacy After completing the SP condition, care-partners were asked to rate whether they spent more or less time providing care: During the weeks that the participant used the SmartPrompt2 were they able to do the task more independently (did you spend less time supervising/caregiving)? Yes, I spent less time supervising/caregiving; No, I spent the same amount of time supervising/caregiving; No, I spent even more time supervising/caregiving than usual. n/a * Outcome [Participant] Description Range * Task Completion Task Completion was measured differently across the conditions. Participants logged task completion with the SP app during the SP condition and with the daily diary during the Control condition. The SP alerts included instructions to take a photo immediately following task completion using the smartphone camera. If a photo was successfully logged the task was recorded as complete =1 vs. incomplete =0 in the automated SP records (maximum 28 photos). During the Control condition, participants self-reported task completion using the paper daily diary as follows: did not do the target task or not sure = 0 vs. completed the target task = 1. Missing daily diary responses were coded as 0s. The total participant Task Completion score was computed separately for each condition. A perfect score of 28 indicated that the participant completed each of the two target tasks every day during the SP/Control condition. 0 - 28 * Frustration Using the daily diary at the end of each day in each condition, participants recorded task-related frustration using a scale from 0 (not very frustrated) to 2 (very frustrated). An average frustration score was computed to account for missing reports. Higher scores indicate greater frustration. 0 −2 Task Timeliness Using the daily diary at the end of each day in each condition, participants rated whether they completed each target task at the right time using the following response options: Yes = 1, No = 0, or Not Sure. A proportion score was computed in case of not sure/missing responses. Higher proportion scores indicate more tasks were performed at the right time. 0 - 100 Participant's Overall Impression of Efficacy At the end of the SP condition, participants were asked the following questions: 1) During the weeks that you used the SmartPrompt2, did you spend less time checking/asking whether you completed the task? Yes - a lot or somewhat less checking; No - same amount or more checking; and 2) During the weeks that you used the SmartPrompt2 were you able to do the task more independently? Yes, I was more independent; No, I needed the same amount or more help than usual. n/a Open in a new tab * Preregistered primary outcome measure NCT04313582 . Abbreviations: SP = SmartPrompt2; SUS = Systems Usability Scale Feasibility As shown in Table 2 , feasibility was evaluated with five measures. Descriptive statistics were used to examine 1) the number of participants who dropped out of the study and/or 2) experienced adverse events, 3) the time required for participants to be trained on the SmartPrompt2, the number of days care-partners reported that participants 4) experienced technical difficulties with the SmartPrompt2 (Care-partner Problem Report), and 5) whether participants forgot how to use the SmartPrompt2 (Procedural Retention of SP). App Engagement Automated records from the SmartPrompt2 were used to describe the overall level and patterns of engagement with the SmartPrompt2, including any interaction with the SP per day (SP Engagement), average time to respond “Do it Now” to each prompt (i.e., SP Task Initiation Time), and use of the “Do it Later” snooze feature (Prompt Deferrals). Efficacy Efficacy variables were collected from both participants’ and care-partners’ self-report during the SP and Control conditions and are described in Table 3 . Efficacy focused on task completion as well as the ease and timeliness in which tasks were completed. To investigate the hypothesis that the SmartPrompt2 is efficacious at promoting everyday task performance without increasing frustration or burden, paired sample analyses were performed (Wilcoxon Signed-Ranks) comparing task completion/timeliness, care-partner burden and participant frustration during the SP vs. Control conditions. Effect sizes ( r ) were computed and are interpreted as follows: small ≅ .10, medium ≅ .30, large ≥ .50. Usability In addition to validated usability questionnaires and summary data from internally-developed usability questions (see Table 4 ), responses to open-ended questions about limitations and suggested improvements for the SmartPrompt2 were analyzed using principles of thematic analysis ( Braun & Clarke, 2006 ), whereby three members of the research team (TG, KH, MM) collaboratively reviewed all free-response data and identified commonly occurring themes that were non-redundant and aligned with meaningful elements of the app design to inform future improvements. Themes were reviewed separately by two additional members of the research team (MK, GV) and any questions or disagreements were resolved by consensus of the entire qualitative coding team. Exploratory Associations Exploratory Spearman rank order correlations between participant features and outcome measures are reported in Supplementary Materials . Results Participants: 10 participants with a clinical diagnosis of MCI or mild dementia and their care partners (n = 10) were recruited from October 2020 to December 2022 during the study funding period. The initial plan was to recruit up to 45 participants, but recruitment was impacted by university closure and social distancing measures during the COVID-19 pandemic. Demographic data are reported in Table 5 . On average, participants were 76 (SD = 5.74) years old with 16 (SD = 3.04) years of education, with average or higher estimated premorbid IQ. The majority of participants identified as White (80%) men (70%), and all (100%) were married and living with their spouse. All (100%) participants selected their spouse to serve as their study partner (care-partner demographics: M age =74, SD = 5.68; M education = 17 years, SD =1.25; 70% White; 70% women). Table 5. Participant Characteristics ID Age Gender Race / Ethnicity * Education (Years) Research Classification ** Estimated IQ MMSE Global Cognitive Function T-Score Episodic Memory T-Score GDS FAQ Ecog 1 70 Man White 13 Dementia 117 17 33.56 28 2 9 2.33 2 79 Man White 11 Dementia 120 21 38.89 32 4 9 2.56 3 83 Man Asian 16 MCI 104 20 48.33 34 3 6 1.08 4 72 Woman White 16 MCI 117 25 47.44 21 2 9 2.08 5 74 Man White 18 MCI 118 29 46.33 53 3 12 2.17 6 68 Woman White 18 MCI 123 29 56.00 35 3 5 1.67 7 78 Man Asian 18 MCI 119 25 41.11 38 0 7 1.75 8 77 Man White 20 MCI 111 26 44.67 41 1 5 1.72 9 85 Man White 20 MCI 135 26 46.78 38 2 2 1.66 10 77 Woman White 12 SCD 112 30 57.11 62 5 4 1.09 Open in a new tab * all participants identified as Not Hispanic or Latino ** all participants reported clinical diagnosis of MCI or dementia MMSE = Mini Mental-status Exam (max = 30); GDS = Geriatric Depression Scale (max = 15); FAQ = Functional Activity Questionnaire; ECOG= Everyday Cognition Scale; SCD= subjective cognitive decline Participants demonstrated a range of cognitive ability levels, with MMSE scores ranging from 17 – 30 and T-scores on the global cognitive composite ranging from 33.56 (borderline impaired) to 57.11 (average). The average episodic memory T-score was 38.2 (SD = 11.8), corresponding to the low average range. Based on the cognitive tests and questionnaires administered for the study, two participants met criteria for dementia and seven were classified as MCI. One participant did not meet criteria for MCI or mild dementia according to our study classification using Jak Bondi criteria ( Jak et al., 2009 ), though they had been diagnosed with MCI by a neurologist and reported subjective cognitive decline (SCD). Participants reported relatively low levels of depression symptoms (GDS M = 2.5; SD = 1.43), and care-partners reported a range of functional disability (FAQ M = 6.8, SD = 2.97) and cognitive decline over the past 10 years (ECog M = 1.81, SD = .49). SmartPrompt2 Personalization Nearly all of the participants selected medications for one of their target tasks, though task times varied widely across participants. Other target task categories included self-care and exercise (e.g., prescribed for a peripheral injury). Sixty percent chose to record the personalized alert in their own voice and all participants selected a specific song as their reward audio. Sixty percent of participants completed the Control condition before the SP condition (AB). See Table 6 for more information about the SmartPrompt2 personalization features. Table 6. SmartPrompt2 Personalization Features for each Participant ID Task 1 Task 2 Prompt Reward Condition Category Time Category Time 1 medications 7:45 medications 18:00 Participant Song AB 2 exercise 20:00 medications 22:30 Someone else Song AB 3 social 14:00 medications 20:30 Someone else Song BA 4 medications 7:30 medications 21:00 Participant Song AB 5 medications 8:30 psychological wellness 16:00 Participant Song AB 6 medications 9:30 medications 17:30 Participant Song BA 7 medications 8:30 chore 20:00 Study partner Song AB 8 medications 14:00 exercise 17:00 Participant Song BA 9 medications 21:00 self-care 23:00 Someone else Song BA 10 hydration 12:00 self-care 20:00 Participant Song AB Open in a new tab Feasibility All (100%) of the study participants completed the four-week study without reporting any adverse events. All participants (100%) completed the SP training during a single session. Training time was missing for two participants due to examiner error. For the remaining 8 participants, the training session lasted 44 minutes on average (range = 30 – 57 min). Four care-partners reported technical difficulties during the SP condition (M Care-partner Problem Report Score = 1.20, SD = 2.49, range 0 – 8, maximum 14). Three care-partners reported technical difficulties on 1 day, and one reported difficulty on 8 days. Technical difficulties were described as failure of the reward song to play with the completed progress bar (54% of difficulties); not hearing the auditory alert even though the visual notification was present on the phone screen (36% of difficulties reported); 9% were not described. According to care-partner reports one participant had difficulty remembering how to use the SP; this participant experienced difficulties on four days within the first five days of the SP condition which then resolved. No other care-partners reported difficulties with participants’ ability to use the SmartPrompt2 (M Procedural Retention = 96.36; SD = 11.50; range 63 – 100). App Engagement During the SP condition, data from the SmartPrompt2 app showed that 90% (n = 9) of participants engaged with the SmartPrompt2 every day during the SP condition. The one participant who did not interact with the app every day missed two days (day 10, day 13). Thus, the average SP Engagement score across participants was 13.8/14 (SD = .63; Mdn = 14; range 12 – 14). On average, participants responded to the initial alerts with “Do it Now” within 14.85 minutes, but there was considerable variability in SP Task Initiation Times across participants (SD = 16.98 min, range = 2.43 – 48.18 min). Fifty percent of participants used the “Do it Later” feature at some point during the SP condition. On average, participants deferred 2.90 alerts (out of 28; SD = 3.87, range 0 – 9). However, once participants initiated the task (i.e., “Do it Now”), they quickly completed the target task, taking about 2 minutes on average to log the photo (M = 2 min, SD = 1.48 min, range = 1 – 5.46 min). Efficacy Care-partner Efficacy Outcomes Care-partners completed most daily diaries (max =14), with no difference in completed entries between the Control (M= 13.8, Mdn = 14, range 13-14) and SP conditions (M= 13.2, Mdn = 14, range 11-14; Z = 1.22, p =.221, r = .27). When reporting Participant Task Completion, “Not sure” responses were infrequent (SP condition = 11 total responses; <4% of all care-partner responses; Control condition = 15 total responses; <6% of all care-partner responses) and did not differ between the conditions (Z = .38, p =.75, r = .10). Analyses of the two preregistered care-partner-reported efficacy outcome measures are included in Table 7 . As predicted, Care-partner Task Completion scores were significantly higher in the SP condition versus the Control condition with a large effect size. Care-partner Burden scores also were significantly lower in the SP condition. Thus, tasks were completed with less difficulty and with less assistance during the SP condition as compared to the Control condition. Table 7. Pre-registered Primary Efficacy Outcome Measures Control Condition SP Condition Wilcoxon Signed Ranks Effect Size Mean Median Range Mean Median Range Z p r Care-partner Outcome Task Completion 2.67 2.76 1.68- 3.00 2.91 3 2.50 - 3.00 2.5 0.012 0.56 Care-partner Burden 0.18 0.08 0-.71 0.09 0 0-.63 2.02 0.043 0.45 Participant Outcome Task Completion 24.4 26 10-28 26.5 27 23-28 0.84 0.339 0.19 Frustration 0.08 0.11 0-.28 0.153 0.11 0 −.42 0.51 0.611 0.11 Open in a new tab a. Participant Outcomes for Task Completion in the Control condition was measured by participant reports in the daily diary whereas Task Completion in the SP condition was measured using the automated records of task completion (photo logged) from the SmartPrompt2 app. There was no difference in the proportion of tasks that caregivers reported were completed on time during the SP condition (M = .79, SD = .19) versus the Control condition (.85 SD = .15; Z = .87, p = .39, r = .27). However, care-partners reported more “Not Sure” responses regarding Task Timeliness compared to responses regarding Task Completion; this was consistent across both conditions (SP condition = 8% of responses; Control condition = 9% of responses). When asked at the end of the SP condition whether the participant was more independent in completing the target tasks during the SP condition, 90% of care-partners responded “Yes, I spent less time supervising/caregiving.” Participant Efficacy Outcomes Consistent with our pre-registration, Task Completion during the SP condition was measured using the SmartPrompt2 app photo log and compared against the daily diary report in the Control condition. Contrary to prediction, there was no difference in Task Completion in the Control condition (as measured with reports in the daily diary) versus the SP condition (as measured by the tasks shown in the SmartPrompt2 photo log; see Table 7 ), though on average, task completion was near ceiling in both conditions and participants completed two more tasks on average in the SP condition. Furthermore, the range was much smaller in the SP Condition, with a markedly higher minimum score. Participants generally reported low levels of frustration when completing the target tasks (“not very frustrated”), and there was no difference in the average level of frustration during the SP vs. Control condition. Although the question regarding Task Timeliness was not a pre-registered outcome measure, participants reported a significantly higher proportion of tasks were completed on time during the SP condition (M= .89, SD = .10) versus the Control condition (M= .79, SD = .11; Z =2.67, p = .008, r =.84). At the end of the SP condition, 70% of participants reported that they spent less time checking and/or asking others whether or not they had completed the target tasks and 90% of participants reported that they were more independent in performing the target tasks with the aid of the SmartPrompt2. Usability Care-partner Impressions The average care-partner SUS was 85/100 (Excellent range; SD = 13.28, range = 60 – 97.5), with two care-partners reporting a SUS below 70/100. Responses to the seven-point, adjective rating (i.e., Overall, I would rate my experience with the SmartPrompt as…) were consistently high with 90% responding “Excellent - 6” and one responding “Best Imaginable - 7”. The average score on the Net Promoter question was 8.7/10 (SD = 1.42, range = 6.7-10), with 60% of care-partners giving a rating of 9.7 or higher, indicating a high likelihood of recommending the SmartPrompt2 to friends or family. All responses to open-ended questions regarding limitations and suggested improvements to the SmartPrompt2 are reported in Table 8 , organized by identified themes. Care-partners provided feedback surrounding difficulties with the interface (specifically the slider function) and the complexity of the photo log feature. Several care-partners suggested incorporating a care-partner version of the app to facilitate remote monitoring of task completion without needing to access the participant’s phone. The most reported suggestion fell within the theme of programming flexibility; care-partners wanted to be able to customize the snooze duration (“Do it Later” reminder), adjust the time of the original alert depending on changes to the participant’s schedule, and/or add additional alerts if needed. Additional creative suggestions were made to enhance the reward feature, including “ A different reward everyday …such as songs, jokes, funny conversations. ” Although the open-ended questions prompted care-partners to comment on limitations and suggested improvements, several care-partners provided positive feedback, particularly around reduced burden (“ Really relieved my anxiety about whether [the participant] took his meds ”; “ I thought it relieved my mind, not having to worry about remembering his tasks ”). Care-partners also provided positive feedback about the custom audio for the prompt and the reward. Table 8. Care-partner and participant responses to open-ended questions about limitations and suggested improvements for the SmartPrompt2 Theme Care-Partner Quotes Participant Quotes LIMITATIONS & SUGGESTED IMPROVEMENTS Interface/HCI "[The participant] was not able to use the slider." "Make the slider a little smoother with more space (expand it vertically or horizontally)" "Slider, Photo Log." [did not like] "I was confused early on, [care-partner] held my hand…More training" Complexity/clarity "The Photo Log was not helpful and was more confusing" "When prompted to take a picture, the [app directions] should be more specific to take a picture of the completed task (not just take any picture). Also, I did not really understand the purpose of the "are you satisfied with the photo"/option to retake the photo prompt." "Reduce the number of steps to perform a task." Alarm prompt "Sometimes I was startled by [the participant's] voice." "My own voice was most of the time unexpected!" "I would prefer a smooth alarm or a text message instead of my recorded reminder." Reward/Motivators "A different reward everyday --14 different things every time, such as songs, jokes, funny conversations. The reward should be a surprise every day." "Make the reward song longer…more music" "Every now and then, the app might ask questions regarding the task how is it going." "Play a bit more of the reward song." Flexibility of programming "After selecting "Do it Later" the later reminders happened too soon/often." "Allow for some flexibility in changing the time of the alarms." "Allow the ability to change the timing of the alerts." "Lack of flexibility; it didn’t work if you were not home at the time that the alarm went off…Flexibility in the time of the alarm; halfway through the [SP condition] my gym reopened and I went back to gym at the time the SmartPrompt2 was programmed to remind me of my meds" "Be able to set the specific time for the reminder after selecting 'Do it later’." "Flexibility in the time for another alert after selecting Do it Later." Some times 15 minutes was too long." "Allow more time between receiving the alert and completing the task and taking the picture." - "The SmartPrompt2 was not adaptable to changes in [participant's] schedule and didn't allow him to customize the alert on an ongoing basis." - "Add the capability to change task time when circumstances warrant it." - "I think it is good for many daily tasks, although other alerts may be added as the need arise, such as weekly scheduled activities such as changing bed sheets and laundry reminders." - "Make it possible to customize it on an ongoing basis." Logistics "I was not able to check at the time when [the participant] was supposed to do his task. I did not look at phone to check, because he has his phone, and he was at the gym in the morning. I would have benefited from a caregiver version of the app on my own phone." "Having to carry my phone with me all the time." "Care-partners should be able to access the Photo Log on their own device." - "A care-partner version of the app." - Technical errors "The reward song stopped playing after the first week." - POSITIVE FEEDBACK General - "I liked everything; I thought it was perfect" - "It is so brilliant what you came up with, my life has changed" Reduced Burden/Reliability "Really relieved my anxiety about whether [the participant] took his meds." "It was very helpful. It helped me to be more organized. The prompt was the best thing for me over the past weeks, which were chaotic. It always went off when it was supposed to" "I thought it relieved my mind, not having to worry about remembering his tasks." - Flexibility - "Liked the ability to snooze, that's a good part of the app." Prompt "The prompt was good feature, particularly the familiar voice." - Reward "I was surprised at how much I enjoyed hearing our grandchild's voice each night." "I love my little song" Open in a new tab Abbreviations: HCI= Human Computer Interaction Participant Impressions The average Participant SUS rating was 86.5/100 (Excellent range; SD = 11.13, range 67.5 - 100). Only 1 participant reported a SUS below 70/100. Responses to the seven-point, adjective ratings were all at or above a 5 (Good) and were distributed as follows: 30% “Best Imaginable– 7”; 50% “Excellent – 6”; 20% “Good– 5”; 0% Neutral – Worst Imaginable (4 rating or below). The average score on the Net Promotor question was 8.7/10 (SD = 1.83, range = 4.2-10), with 40% giving a rating of 9.7 or higher. When asked whether specific features of the SmartPrompt2 were “helpful,” “neutral,” or “unhelpful” none of the participants selected “unhelpful” for any of the features. As shown in Figure 4 , most participants rated each of the SmartPrompt2 features as “helpful.” Finally, when given the choice to keep the SmartPrompt2 app at the end of the study, all participants (100%) requested to do so. Figure 4: Open in a new tab Results of participants’ feature ratings showing the proportion of participants that rated each of the SmartPrompt2 app feature as “helpful.” Alt Text: Results of participants’ feature ratings showing the proportion of participants that rated each of the SmartPrompt2 app feature as “helpful” for the custom alarm (100%), nudges (90%), option to delay (70%), and Photo Log (70%) A complete log of responses to open-ended questions regarding limitations and suggested improvements are listed in Table 6 . There was notable overlap in the identified themes of free-response feedback between participants and care-partners. Participants also suggested increased flexibility in setting the SmartPrompt2 alarm and reminder times. Participants enjoyed the musical reward feature and suggested increasing the length of the song clip. Regarding the prompt, some participants disliked the sound of their own voice and would prefer a different audio prompt. Consistent with care-partner feedback, some participants felt the slider and photo log features were challenging and provided specific feedback to improve the usability of these features. Finally, participants provided a range of unsolicited positive feedback about the app in general (“I liked everything; I thought it was perfect”) , the reliability and organization afforded by the SmartPrompt (“It helped me to be more organized. The prompt was the best thing for me over the past weeks, which were chaotic. It always went off when it was supposed to”) , and specific features (positive impressions of the reward song and snooze feature). Discussion The SmartPrompt2 was designed to target the cognitive failures that preclude successful completion of everyday tasks by older adults with cognitive impairment using a simplified interface informed by participant feedback during pilot testing, iterative development, and principles of cognitive rehabilitation and human-computer interaction. The present study evaluated the feasibility, efficacy, and usability of the SmartPrompt2 during a two-week pilot period compared to a two-week control period using a crossover design. Results showed that participants with MCI or mild dementia learned to independently use the SmartPrompt2 app at home with few technical difficulties. All participants completed the study with no adverse side-effects and reported minimal frustration. Efficacy outcomes indicated that participants completed target tasks more effectively and with less help from their care-partners when using the SmartPrompt2 app as compared to when they did not use the app during the Control weeks. Usability ratings were positive, and all participants requested to keep the SmartPrompt2 app after the study. Results and qualitative feedback from the present study identified strengths and limitations to inform future updates and improved effectiveness and usability of the app in longer studies with larger samples. Efficacy results suggested that the SmartPrompt2 improved participants’ ability to complete the target tasks independently, accurately, and on time, with a large effect size noted in care-partner-reported task completion. There was less evidence from participant-reported efficacy outcomes that the SmartPrompt2 showed a significant effect on whether participants completed the target task, though completion rates were generally high across both conditions, raising concerns of ceiling effects and restricted range. Our results underscore the importance of a control condition, as it is possible that simply requiring participants and care-partners to track activities promoted task completion across both study conditions, particularly given the relatively short study period. Nevertheless, the effect on task performance quality and independence should not be discounted, as it also corresponded with significantly lower care-partner burden during the SP condition. Our findings are consistent with the literature showing that higher care-partner burden is associated with greater time spent helping a person with daily activities ( Frederiksen et al., 2023 ). Reducing care-partner burden can yield tremendous benefits for the relationship between the care-partner and person with MCI/dementia, on the health outcomes and mood of the care-partner, and for reducing cost of care. In fact, care-partners shared that during the SmartPrompt condition, rather than talking to the participant about task completion which often felt like “nagging,” they had more time to have conversations about more interesting and positive topics. It is important that care-partner burden is measured when evaluating new assistive technologies, as it is possible that new assistive devices show efficacy on some outcomes but require time and effort on the part of the care-partner leading to worsening of functioning and quality of life when outcomes are viewed more holistically ( Madara Marasinghe, 2016 ). Similarly, from the perspective of the participant, the benefits of the SmartPrompt2 did not correspond with increased frustration. Thus, improved independence, accuracy, and timeliness of task completion could have longer-term benefits on the participant’s mood and self-efficacy ( Langer et al., 2019 ). Future work is needed to determine efficacy over a longer study period and whether the SmartPrompt2 is effective for participants who do not have a care-partner. It is possible that a longer study period would uncover stronger positive effects of the SmartPrompt2 that were masked by the short-term facilitation of task tracking in the Control condition, or alternatively that the benefits of the SmartPrompt2 could fade over time as reported with other assistive technologies ( Scullin et al., 2022 ). Regarding the role of the care-partner, the SmartPrompt2 was designed for the participant to use independently. The care-partner was enrolled in the current study for the purpose of data collection and learning as much as possible regarding the use and efficacy of the SmartPrompt2 in the home. We acknowledge that the SmartPrompt2 will have very limited utility unless individuals with dementia can use it relatively independently. Future work will use a study design with less care-partner involvement when evaluating the effectiveness of the SmartPrompt2. Regardless, it is encouraging that despite the significant role of the care-partner in task logging, care-partners still reported a significant reduction in subjective feelings of burden and time spent monitoring with the SmartPrompt2. Our results build on the accumulating evidence that smartphone apps are effective at improving everyday function in people with cognitive impairment ( Annese et al., 2023 ; Benge et al., 2020 ; Hackett et al., 2022 ; Scullin et al., 2022 ; Stapleton et al., 2007 ; Svoboda & Richards, 2009 ). The SmartPrompt2 app extends and improves upon prior work by incorporating several important and unique features. First, the SmartPrompt app was deployed onto participants’ personal smartphones, which likely contributed to its feasibility, efficacy, and usability. Principles of cognitive rehabilitation dictate that building on existing skills and habits is tantamount to the success of any intervention, which should be considered when introducing new technology aides ( Annese et al., 2023 ; Benge et al., 2020 ; Sohlberg & Mateer, 2001 ). Participants in our study were all existing smartphone users having experience with the general operations of their personal smartphones, thus needed to learn only the relatively simple functions of the SmartPrompt2, which were intentionally designed to be user-friendly and direct. In fact, exploratory analyses showed that participants with greater proficiency with their smartphone reported less frustration with the SmartPrompt2. Thus, as older adults continue to become more and more proficient with smartphones, apps like the SmartPrompt2 should become even easier to use and consequently more effective. The use of the participant’s personal smartphone also reduced the additional burden of managing an extra mobile device. Although using a research smartphone would have made the app development and deployment much easier because of the greater control afforded by a study smartphone, ultimately, the use of personal phones are essential to increase adoption among older adults who are concerned about social stigma associated with assistive devices, privacy, and cost ( Benge et al., 2020 ). We acknowledge that there were a few drawbacks to relying on the participants’ smartphone, including exclusion of participants who did not own or use an iPhone. Our small research team had limited resources to program the SmartPrompt2 for use beyond the Apple operating system (iOS). Future work will aim to expand the SmartPrompt2 to other platforms. Another important feature of the SmartPrompt2 is that it was informed by over a decade of research on everyday functional impairment in dementia from our lab ( Giovannetti et al., 2002 , 2021 ) as well as participant and care-partner feedback ( Hackett et al., 2022 ). The efficacy of the cues that are incorporated in the SmartPrompt have been demonstrated in laboratory studies ( Brennan et al., 2009 ; Giovannetti et al., 2006 , 2015 ; Hackett et al., 2022 ), and the personalization features were informed by pilot testing and feedback from our pilot study ( Hackett et al., 2022 ). Personalization of the alert served to capture attention by incorporating the participant’s first name ( Golden et al., 2013 ) and participants reported satisfaction from hearing their favorite song at the end of the day, which likely promoted adherence and favorable ratings. The SmartPrompt2 was also designed to address some of the most commonly reported barriers to technology use among older adults, including complex interfaces ( Kenigsberg et al., 2019 ), motor/sensory difficulties ( Pijukkana & Sahachaisaeree, 2012 ), and cost ( Nikou, 2015 ). Our positive results underscore the benefit of using cognitive neuroscience principles, empirical data, and feedback from clinical groups and care-partners to build assistive technologies. Our pilot and the current study incorporated principles of codesign, as such we worked to create a non-hierarchical experience for participants and care-partners encouraging collaboration and positive and negative feedback to enable further improvement of the SmartPrompt2 ( Cole et al., 2022 ). Participants and care-partners identified several areas for future improvement. First, several participants and care-partners brought up the lack of flexibility as a limitation. Care-partners expressed a need for the app to be programed to do the target task at different times on different days to adjust for known and unexpected changes in the participant’s daily schedule. To maintain standardization in this efficacy trial, such flexibility was not allowed, which might have negatively impacted the efficacy outcomes. A second area of improvement identified by care-partners was to include a caregiver portal that would enable access to the Photo log remotely without having to access the participant’s smartphone. Additional resources would enable building a remote web-based caregiver portal for future iterations of the SmartPrompt. We acknowledge our study had limitations, including the small sample size and potential biases because participants and the study team were not blind to study condition when conducting the study. The Control condition was included to evaluate the influence of task tracking on behavior, and because task completion was generally high in both the Control and SP conditions, it is likely that task tracking positively influenced completion of the target tasks. We also acknowledge that further modifications to the SmartPrompt2 will be necessary for scalability. For example, although participants were able to successfully use the SmartPrompt2 after a relatively brief training session, the training was delivered by a member of the research team and included several practice trials with immediate feedback. Although we suspect that the training and practice session was crucial for the success of this trial, the study was not designed to test whether the training and practice was essential. Future versions of the SmartPrompt2 app will include automated training and training trials that are directly embedded into the app for scalability. Automated training should include guided practice with feedback. Booster training sessions could be implemented based on participant’s use of the SmartPrompt2 app. For example, if the participant fails to respond to alerts over a period, they could receive an alert to complete another training session. Additionally, the need for personalization features should be directly evaluated in future work. If, as we suspect, personalization is determined to be essential for prompt effectiveness, then app personalization could be automated with inclusion of a set-up assistant (wizard). Further modifications could expand the functions of the SmartPromt2 to include more detailed task instructions, as some participants might benefit from more explicit instructions and a demonstration video on how to complete a targeted activity ( Bettcher et al., 2011 ). Chat groups or data sharing features with other SmartPrompt2 users could be added for encouragement and socialization or serve as accountability partners to boost adherence and app engagement. Further research is needed in larger and longer trials. However, the results of this small efficacy trial demonstrate the promise of the SmartPrompt2 and the principles that informed the design of the SmartPrompt2 for improving everyday function in older adults with cognitive impairment and reducing burden in their care-partners. Although further study is needed, it is reasonable to expect that the principles that informed the design of the SmartPrompt2 would generalize to a wide range of clinical populations with cognitive impairment, including individuals with traumatic brain injury, stroke, psychiatric disorders, and others. We also intend to enable greater flexibility in selection of the SmartPrompt2 features for streamlining the app for people with greater cognitive impairment or different daily needs (e.g., the Photo Log could be omitted if it were too complex or not useful in a particular context). Our goal is to ultimately make the SmartPrompt2 app widely available with automated set up and training; however, the SmartPrompt2 also may be effectively used as part of cognitive rehabilitation programs where individuals would receive training and support in incorporating the app into their daily life. Smartphones are ubiquitous, with widespread use across people of all demographics across the world and great computing power and sophistication. The SmartPrompt2 harnesses the advantages of personal digital devices to improve the lives of people with cognitive impairment and their care-partners. As our team further develops the SmartPrompt2 in larger trials with automated training and personalization for widespread dissemination, our results demonstrate the utility of design principles informed by co-design and neuropsychological theory, including personalization, customized prompts, task logging, and personally meaningful rewards. These principles should be incorporated into the design of a variety of digital technologies, including apps used for medical records, hospitals, or insurance companies, to promote independence in daily activities in adults with cognitive impairment and mild dementia. Supplementary Material Supp 1 NIHMS2074833-supplement-Supp_1.docx (37.2KB, docx) Supp 2 NIHMS2074833-supplement-Supp_2.pdf (1.4MB, pdf) Supp 3 NIHMS2074833-supplement-Supp_3.pdf (5.1MB, pdf) Funding Details: This work was supported by the National Institute on Aging under Grants R21AG060422 and R01AG062503. KH’s time was supported by the National Institute on Aging under Grant F31AG069444 and T32AG066598 Footnotes Disclosure statement: There are no relevant financial or non-financial competing interests to report. Contributor Information Katherine Hackett, Department of Psychology and Neuroscience, Temple University; Icahn School of Medicine at Mount Sinai.. Moira Mckniff, Department of Psychology and Neuroscience, Temple University. Sarah Lehman, Department of Computer and Information Sciences, Temple University; NASA Langley Research Center, Hampton, Virginia.. Emma Pinsky, Department of Psychology and Neuroscience, Temple University; Department of Psychology, Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY.. Chiu C. Tan, Department of Computer and Information Sciences, Temple University Marina Kaplan, Department of Psychology and Neuroscience, Temple University. Giuliana Vallecorsa, Department of Psychology and Neuroscience, Temple University. Mijail D. Serruya, Raphael Center for Neurorestoration, Farber Institute for Neuroscience, Thomas Jefferson University Tania Giovannetti, Department of Psychology and Neuroscience, Temple University. Data availability statement: Data are available upon request from the authors. After publication, all data will be publicly available at ClinicalTrials.gov ( https://clinicaltrials.gov/study/NCT04313582 ) and here ( https://osf.io/x9qwb/?view_only=121f70bf49334c259d71abed46eddb14 ) References Alzheimer’s Association. (2016). 2016 Alzheimer’s disease facts and figures. Alzheimer’s & Dementia, 12(4), 459–509. 10.1016/j.jalz.2016.03.001 [ DOI ] [ PubMed ] [ Google Scholar ] Anderson GF, & Hussey PS (2000). Population aging: A comparison among industrialized countries. Health Affairs (Project Hope), 19(3), 191–203. 10.1377/hlthaff.19.3.191 [ DOI ] [ PubMed ] [ Google Scholar ] Annese J, Klaming R, Haase Alasantro L, & Feinstein JS (2023). A case of severe anterograde amnesia in the era of smartphone technology. Journal of Clinical and Experimental Neuropsychology, 45(5), 498–512. 10.1080/13803395.2023.2254911 [ DOI ] [ PubMed ] [ Google Scholar ] Bangor A, Kortum P, & Miller J (2009). Determining What Individual SUS Scores Mean: Adding an Adjective Rating Scale. Journal of Usability Studies, 4(3), 114–123. [ Google Scholar ] Benedict RHB, Schretlen D, Groninger L, Dobraski M, & Shpritz B (1996). Revision of the Brief Visuospatial Memory Test: Studies of normal performance, reliability, and validity. Psychological Assessment, 8(2), 145–153. 10.1037/1040-3590.8.2.145 [ DOI ] [ Google Scholar ] Benge JF, Aguirre A, Scullin MK, Kiselica A, Hilsabeck RC, Paydarfar D, Thomaz E, & Douglas M (2024). Digital Methods for Performing Daily Tasks Among Older Adults: An Initial Report of Frequency of Use and Perceived Utility. Experimental Aging Research, 50(2), 133–154. 10.1080/0361073X.2023.2172950 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Benge JF, Dinh KL, Logue E, Phenis R, Dasse MN, & Scullin MK (2020). The smartphone in the memory clinic: A study of patient and care partner’s utilisation habits. Neuropsychological Rehabilitation, 30(1), 101–115. 10.1080/09602011.2018.1459307 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Bettcher BM, Giovannetti T, Libon DJ, Eppig J, Wambach D, & Klobusicky E (2011). Improving everyday error detection, one picture at a time: A performance-based study of everyday task training. Neuropsychology, 25(6), 771–783. 10.1037/a0024107 [ DOI ] [ PubMed ] [ Google Scholar ] Boyle PA, Malloy PF, Salloway S, Cahn-Weiner DA, Cohen R, & Cummings JL (2003). Executive dysfunction and apathy predict functional impairment in Alzheimer disease. The American Journal of Geriatric Psychiatry, 11(2), 214–221. 10.1097/00019442-200303000-00012 [ DOI ] [ PubMed ] [ Google Scholar ] Brandt J. (2017). Hopkins Verbal Learning Test [dataset]. 10.1037/t49859-000 [ DOI ] [ Google Scholar ] Braun V, & Clarke V (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. 10.1191/1478088706qp063oa [ DOI ] [ Google Scholar ] Brennan L, Giovannetti T, Libon DJ, Bettcher BM, & Duey K (2009). The impact of goal cues on everyday action performance in dementia. Neuropsychological Rehabilitation, 19(4), 562–582. 10.1080/09602010802405623 [ DOI ] [ PubMed ] [ Google Scholar ] Chun YJ, & Patterson PE (2012). A usability gap between older adults and younger adults on interface design of an Internet-based telemedicine system. Work (Reading, Mass.), 41 Suppl 1, 349–352. 10.3233/WOR-2012-0180-349 [ DOI ] [ PubMed ] [ Google Scholar ] Cole AC, Adapa K, Khasawneh A, Richardson DR, & Mazur L (2022). Codesign approaches involving older adults in the development of electronic healthcare tools: A systematic review. BMJ Open, 12(7), e058390. 10.1136/bmjopen-2021-058390 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Dixon E, Michaels R, Xiao X, Zhong Y, Clary P, Narayanan A, Brewer RN, & Lazar A (2022). Mobile Phone Use by People with Mild to Moderate Dementia: Uncovering Challenges and Identifying Opportunities: Mobile Phone Use by People with Mild to Moderate Dementia. Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility, 1–16. 10.1145/3517428.3544809 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Evans JJ, Wilson BA, Schuri U, Andrade J, Baddeley A, Bruna O, Canavan T, Del Sala S, Green R, Laaksonen R, Lorenzi L, & Taussik I (2000). A Comparison of “‘Errorless’” and “ ‘Trial-and-error’” Learning Methods for Teaching Individuals with Acquired Memory Deficits. Neuropsychological Rehabilitation, 10(1), 67–101. 10.1080/096020100389309 [ DOI ] [ Google Scholar ] Farias ST, Mungas D, Reed BR, Cahn-Weiner D, Jagust W, Baynes K, & DeCarli C (2008). The measurement of everyday cognition (ECog): Scale development and psychometric properties. Neuropsychology, 22(4), 531–544. 10.1037/0894-4105.22.4.531 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Frederiksen KS, Lanctôt KL, Weidner W, Hahn-Pedersen JH, & Mattke S (2023). A Literature Review on the Burden of Alzheimer’s Disease on Care Partners. Journal of Alzheimer’s Disease, 96(3), 947–966. 10.3233/JAD-230487 [ DOI ] [ PubMed ] [ Google Scholar ] Giovannetti T, Libon DJ, Buxbaum LJ, & Schwartz MF (2002). Naturalistic action impairments in dementia. Neuropsychologia, 40(8), 1220–1232. 10.1016/S0028-3932(01)00229-9 [ DOI ] [ PubMed ] [ Google Scholar ] Giovannetti T, Mis R, Hackett K, Simone SM, & Ungrady MB (2021). The goal-control model: An integrated neuropsychological framework to explain impaired performance of everyday activities. Neuropsychology, 35(1), 3–18. 10.1037/neu0000714 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Giovannetti T, Seligman SC, Britnell P, Brennan L, & Libon DJ (2015). Differential effects of goal cues on everyday action errors in Alzheimer’s disease versus Parkinson’s disease dementia. Neuropsychology, 29(4), 592–602. 10.1037/neu0000167 [ DOI ] [ PubMed ] [ Google Scholar ] Giovannetti T, Sestito N, Libon DJ, Schmidt KS, Gallo JL, Gambino M, & Chrysikou EG (2006). The influence of personal familiarity on object naming, knowledge, and use in dementia. Archives of Clinical Neuropsychology, 21(7), 607–614. 10.1016/j.acn.2006.05.005 [ DOI ] [ PubMed ] [ Google Scholar ] Golden H, Agustus J, Goll J, Yong K, Downey L, Crutch S, & Warren J (2013). O3–04–03: The cocktail party effect in Alzheimer’s disease. Alzheimer’s & Dementia, 9(4S_Part_13), P524–P525. 10.1016/j.jalz.2013.04.256 [ DOI ] [ Google Scholar ] Hackett K, Lehman S, Divers R, Ambrogi M, Gomes L, Tan CC, & Giovannetti T (2022). Remind Me To Remember: A pilot study of a novel smartphone reminder application for older adults with dementia and mild cognitive impairment. Neuropsychological Rehabilitation, 32(1), 22–50. 10.1080/09602011.2020.1794909 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Hackett K, Mis R, Drabick DAG, & Giovannetti T (2020). Informant Reporting in Mild Cognitive Impairment: Sources of Discrepancy on the Functional Activities Questionnaire. Journal of the International Neuropsychological Society, 26(5), 503–514. 10.1017/S1355617719001449 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Huppert FA, Johnson T, & Nickson J (2000). High prevalence of prospective memory impairment in the elderly and in early-stage dementia: Findings from a population-based study. Applied Cognitive Psychology, 14(7), S63–S81. 10.1002/acp.771 [ DOI ] [ Google Scholar ] Jak AJ, Bondi MW, Delano-Wood L, Wierenga C, Corey-Bloom J, Salmon DP, & Delis DC (2009). Quantification of Five Neuropsychological Approaches to Defining Mild Cognitive Impairment. The American Journal of Geriatric Psychiatry, 17(5), 368–375. 10.1097/JGP.0b013e31819431d5 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Jay GM, & Willis SL (1992). Influence of Direct Computer Experience on Older Adults’ Attitudes Toward Computers. Journal of Gerontology, 47(4), P250–P257. 10.1093/geronj/47.4.P250 [ DOI ] [ PubMed ] [ Google Scholar ] Kelley AS, McGarry K, Gorges R, & Skinner JS (2015). The Burden of Health Care Costs for Patients With Dementia in the Last 5 Years of Life. Annals of Internal Medicine, 163(10), 729–736. 10.7326/M15-0381 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Kenigsberg P-A, Aquino J-P, Bérard A, Brémond F, Charras K, Dening T, Droës R-M, Gzil F, Hicks B, Innes A, Nguyen S-M, Nygård L, Pino M, Sacco G, Salmon E, Van Der Roest H, Villet H, Villez M, Robert P, & Manera V (2019). Assistive Technologies to Address Capabilities of People with Dementia: From Research to Practice. Dementia, 18(4), 1568–1595. 10.1177/1471301217714093 [ DOI ] [ PubMed ] [ Google Scholar ] Kinsella GJ, Pike KE, Cavuoto MG, & Lee SD (2018). Mild cognitive impairment and prospective memory: Translating the evidence into neuropsychological practice. The Clinical Neuropsychologist, 32(5), 960–980. 10.1080/13854046.2018.1468926 [ DOI ] [ PubMed ] [ Google Scholar ] Knapp M. (2015). The cost-effectiveness challenge: Is it worth it? Alzheimer’s Research & Therapy, 7(1), 10. 10.1186/s13195-015-0095-4 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Langer K, O’Shea DM, De Wit L, DeFeis B, Mejia A, Amofa P, Chandler M, Locke DEC, Fields J, Phatak V, Dean PM, & Smith G (2019). Self-Efficacy Mediates the Association Between Physical Function and Perceived Quality of Life in Individuals with Mild Cognitive Impairment. Journal of Alzheimer’s Disease, 68(4), 1511–1519. 10.3233/JAD-181020 [ DOI ] [ PubMed ] [ Google Scholar ] Lewis JR, & Sauro J (2009). The Factor Structure of the System Usability Scale. In Kurosu M (Ed.), Human Centered Design (Vol. 5619, pp. 94–103). Springer Berlin Heidelberg. 10.1007/978-3-642-02806-9_12 [ DOI ] [ Google Scholar ] Loyd BH, & Gressard C (1984). Reliability and Factorial Validity of Computer Attitude Scales. Educational and Psychological Measurement, 44(2), 501–505. 10.1177/0013164484442033 [ DOI ] [ Google Scholar ] Madara Marasinghe K. (2016). Assistive technologies in reducing caregiver burden among informal caregivers of older adults: A systematic review. Disability and Rehabilitation: Assistive Technology, 11(5), 353–360. 10.3109/17483107.2015.1087061 [ DOI ] [ PubMed ] [ Google Scholar ] McConnaughy EA, Prochaska JO, & Velicer WF (1983). Stages of change in psychotherapy: Measurement and sample profiles. Psychotherapy: Theory, Research & Practice, 20(3), 368–375. 10.1037/h0090198 [ DOI ] [ Google Scholar ] McDaniel MA, & Einstein GO (2000). Strategic and automatic processes in prospective memory retrieval: A multiprocess framework. Applied Cognitive Psychology, 14(7), S127–S144. 10.1002/acp.775 [ DOI ] [ Google Scholar ] McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, & Phelps CH (2011). The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7(3), 263–269. 10.1016/j.jalz.2011.03.005 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Nikou S. (2015). Mobile technology and forgotten consumers: The young-elderly. International Journal of Consumer Studies, 39(4), 294–304. 10.1111/ijcs.12187 [ DOI ] [ Google Scholar ] Pfeffer RI, Kurosaki TT, Harrah CH, Chance JM, & Filos S (1982). Measurement of Functional Activities in Older Adults in the Community. Journal of Gerontology, 37(3), 323–329. 10.1093/geronj/37.3.323 [ DOI ] [ PubMed ] [ Google Scholar ] Oriani M, Moniz-Cook E, Binetti G, Zanieri G, Frisoni GB, Geroldi C, Vreese LPD, & Zanetti O (2003). An electronic memory aid to support prospective memory in patientsin the early stages of Alzheimer’s disease: A pilot study. Aging & Mental Health, 7(1), 22–27. 10.1080/1360786021000045863 [ DOI ] [ PubMed ] [ Google Scholar ] Pijukkana K, & Sahachaisaeree N (2012). Graphical Design and Functional Perception on Technology-Driven Products: Case Study on Mobile Usage of the Elderly. Procedia - Social and Behavioral Sciences, 42, 264–270. 10.1016/j.sbspro.2012.04.190 [ DOI ] [ Google Scholar ] Reitan RM (1958). Validity of the Trail Making Test as an Indicator of Organic Brain Damage. Perceptual and Motor Skills, 8(3), 271–276. 10.2466/pms.1958.8.3.271 [ DOI ] [ Google Scholar ] Rog LA, Park LQ, Harvey DJ, Huang C-J, Mackin S, & Farias ST (2014). The independent contributions of cognitive impairment and neuropsychiatric symptoms to everyday function in older adults. The Clinical Neuropsychologist, 28(2), 215–236. 10.1080/13854046.2013.876101 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Roque NA, & Boot WR (2018). A New Tool for Assessing Mobile Device Proficiency in Older Adults: The Mobile Device Proficiency Questionnaire. Journal of Applied Gerontology, 37(2), 131–156. 10.1177/0733464816642582 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Sailer M, Hense J, Mandl H, & Klevers M (2013). Psychological perspectives on motivation through gamification. Interaction Design and Architecture(s) - IxD&A, 19, 28–37. 10.55612/s-5002-019-002 [ DOI ] [ Google Scholar ] Salthouse TA (1991). Mediation of Adult Age Differences in Cognition by Reductions in Working Memory and Speed of Processing. Psychological Science, 2(3), 179–183. 10.1111/j.1467-9280.1991.tb00127.x [ DOI ] [ Google Scholar ] Schepens Niemiec SL, Lee E, Saunders R, Wagas R, & Wu S (2023). Technology for activity participation in older people with mild cognitive impairment or dementia: Expert perspectives and a scoping review. Disability and Rehabilitation. Assistive Technology, 18(8), 1555–1576. 10.1080/17483107.2022.2116114 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Schretlen DJ, Testa SM, & Pearlson GD (2010). Calibrated Neuropsychological Normative System. Psychological Assessment Resources. [ Google Scholar ] Schretlen DJ, Winicki JM, Meyer SM, Testa SM, Pearlson GD, & Gordon B (2009). Development, Psychometric Properties, and Validity of the Hopkins Adult Reading Test (HART). The Clinical Neuropsychologist, 23(6), 926–943. 10.1080/13854040802603684 [ DOI ] [ PubMed ] [ Google Scholar ] Schretlen D, & Vannorsdall TD (2010). Calibrated ideational fluency assessment (CIFA) professional manual. Psychological Assessment Resources. [ Google Scholar ] Schulz R, Wahl H, Matthews JT, De Vito Dabbs A, Beach SR, & Czaja SJ (2015). Advancing the Aging and Technology Agenda in Gerontology. The Gerontologist, 55(5). 10.1093/geront/gnu071 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Scullin MK, Jones WE, Phenis R, Beevers S, Rosen S, Dinh K, Kiselica A, Keefe FJ, & Benge JF (2022). Using smartphone technology to improve prospective memory functioning: A randomized controlled trial. Journal of the American Geriatrics Society, 70(2), 459–469. 10.1111/jgs.17551 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Seelye AM, Schmitter-Edgecombe M, Das B, & Cook DJ (2012). Application of Cognitive Rehabilitation Theory to the Development of Smart Prompting Technologies. IEEE Reviews in Biomedical Engineering, 5, 29–44. 10.1109/RBME.2012.2196691 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Selnes OA, Carson K, Rovner B, & Giordon B (1988). Language in Alzheimer’s disease. Neurology, 38(12), 1899–1899. 10.1212/WNL.38.12.1899 [ DOI ] [ PubMed ] [ Google Scholar ] Siek KA, Rogers Y, & Connelly KH (2005). Fat Finger Worries: How Older and Younger Users Physically Interact with PDAs. In Costabile MF & Paternò F (Eds.), Human-Computer Interaction—INTERACT 2005 (pp. 267–280). Springer. 10.1007/11555261_24 [ DOI ] [ Google Scholar ] Sohlberg MM, & Mateer CA (Eds.). (2001). Cognitive rehabilitation: An integrative neuropsychological approach. Guilford Press. [ Google Scholar ] Stapleton S, Adams M, & Atterton L (2007). A mobile phone as a memory aid for individuals with traumatic brain injury: A preliminary investigation. Brain Injury, 21(4), 401–411. 10.1080/02699050701252030 [ DOI ] [ PubMed ] [ Google Scholar ] Svoboda E, & Richards B (2009). Compensating for anterograde amnesia: A new training method that capitalizes on emerging smartphone technologies. Journal of the International Neuropsychological Society, 15(4), 629–638. 10.1017/S1355617709090791 [ DOI ] [ PubMed ] [ Google Scholar ] Wechsler D. (1987). Wechsler memory scale-revised. Psychological Corporation. [ Google Scholar ] Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, & Leirer VO (1982). Development and validation of a geriatric depression screening scale: A preliminary report. Journal of Psychiatric Research, 17(1), 37–49. 10.1016/0022-3956(82)90033-4 [ DOI ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Supp 1 NIHMS2074833-supplement-Supp_1.docx (37.2KB, docx) Supp 2 NIHMS2074833-supplement-Supp_2.pdf (1.4MB, pdf) Supp 3 NIHMS2074833-supplement-Supp_3.pdf (5.1MB, pdf) Data Availability Statement Data are available upon request from the authors. After publication, all data will be publicly available at ClinicalTrials.gov ( https://clinicaltrials.gov/study/NCT04313582 ) and here ( https://osf.io/x9qwb/?view_only=121f70bf49334c259d71abed46eddb14 ) ACTIONS View on publisher site PDF (1.1 MB) 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