Alzheimers Disease Related Dementias
Conditions
Keywords
Alzheimer's Disease, Dementia, Dementia Caregivers, Smart Technology, Assistive Technology
Brief summary
This study aims to assess the effectiveness of the Health App Recommendation Tool (HART), an evidence-based tool that evaluates app features and matches them to the needs, abilities, and preferences of individuals with Alzheimer's disease and related dementias (ADRD) or their caregivers. This novel tool is not an app in and of itself, but rather an assessment tool used to determine how well suited a given app is for a member of the ADRD or caregiver population. Specifically, the objective of this research is to assess the acceptability of the current HART design among target end-users in their individual contexts. The overarching goal of this project is to connect those in the ADRD community with available, usable, and effective digital tools to promote the highest possible level of health and wellness in community settings. To achieve this goal, the study will recruit 15 family caregivers living with their loved ones with ADRD, who will trial HART and provide feedback. Participation will include two data collection sessions (pre-intervention and post-intervention) within a four-week trial period. Participants will be asked to complete the HART, explore the recommended apps, and provide feedback on HART's usability through several brief surveys.
Detailed description
Dementia caregiving is a growing challenge predominantly shouldered by young and middle-aged adults, who often face significant physical and mental health needs. Despite the availability of numerous smart health technologies capable of addressing these needs, caregivers frequently encounter difficulties identifying appropriate health applications due to the overwhelming number of options and lack of clear guidance. Proposed Solution: To bridge this gap, the Health App Recommendation Tool (HART) has been developed as a user-friendly platform designed to connect dementia caregivers with biomedical health apps tailored to their individual requirements. HART operates by gathering targeted information from users regarding their specific needs, accessibility considerations, available supports, and technology literacy through a brief intake survey. A sophisticated matching algorithm then evaluates these user profiles against a library of health apps that have been objectively reviewed, providing a curated list of the most suitable applications for each caregiver. This personalized approach aims to facilitate the adoption and sustained use of health apps, thereby enhancing caregivers' health and quality of life. Preliminary evaluations indicate that HART holds promise in setting a new standard in personalized health technology, offering a practical solution for dementia caregivers navigating the extensive and uncharted landscape of biomedical health applications that address their individual and multifaceted needs. By simplifying the process of finding suitable health technologies, HART not only alleviates the burden on caregivers but also empowers them to manage their own health and caregiving responsibilities more effectively. The ongoing refinement and evaluation of HART are crucial to ensuring its effectiveness and widespread adoption, ultimately contributing to improved health outcomes for dementia caregivers and their care recipients.
Interventions
OTHERHealth App Recommendation Tool (HART)
In 2023, over 11 million family members provided 19.2 billion hours of unpaid care for people with dementia in the U.S. Caregivers face significant physical and emotional challenges, while many individuals with ADRD prefer to stay in their homes. Mobile health apps offer support but often lack user-friendly guidance and are hard to navigate. The Health App Recommendation Tool (HART) bridges this gap by assisting ADRD caregivers in finding suitable health apps. It evaluates users' daily needs and preferences, using end-user informed points of measurement to match them with objectively reviewed apps within the HART App Library. This user-centered tool, shaped by ongoing feedback, simplifies app discovery, ensuring personalized recommendations that enhance caregiving and improve quality of life.
Sponsors
University of Pittsburgh
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SUPPORTIVE_CARE
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
Yes
Inclusion criteria
* Aged between 18 and 65 * Serving as an active caregiver for a loved one with Alzheimer's disease or a related dementia * Have access to smart devices such as smartphones, tablets, or smartwatches
Exclusion criteria
* Individuals with Alzheimer's disease or a related dementia, or with severe cognitive decline, will be excluded * Participants who do not provide caregiving on a routine basis (e.g., part-time or secondary caregivers) will be excluded * Participants who do not own or have access to any smart device will be excluded
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| World Health Organization Quality of Life (WHOQOL-BREF) | Baseline and 4 week follow-up | The WHOQOL-BREF, developed by the World Health Organization, is a measure of perceived quality of life. It includes 26 items across Physical Health, Psychological, Social Relationships, and Environment domains, along with two stand-alone global items assessing overall quality of life and health. Each domain score is transformed to a 0-100 scale, with higher scores indicative of a better quality of life. |
| 36-Item Short Form Health Survey (SF-36) | Baseline and 4 week follow-up | The SF-36 is a widely used measure of health-related quality of life that captures eight dimensions: Physical Functioning, Role Limitations due to Physical Health, Bodily Pain, General Health, Vitality, Social Functioning, Role Limitations due to Emotional Problems, and Mental Health. All items are scored from 0 to 100, with higher scores indicative of better health status. Scale scores are produced by averaging scores across items in that respective scale. |
| Patient Health Questionnaire-4 (PHQ-4) | Baseline and 4 week follow-up | The PHQ-4 is an brief screening tool designed to assess anxiety and depressive symptoms over the past two weeks. It contains four items, each rated from 0 ("not at all") to 3 ("nearly every day"). Subscale scores for anxiety and depression range from 0-6 each, and the total score ranges from 0-12, with higher scores indicating greater psychological distress. Total scores of 0-2 suggest no distress, 3-5 mild, 6-8 moderate, and 9-12 severe distress. |
| Zarit Burden Interview (ZBI) | Baseline and 4 week follow-up | The Zarit Burden Interview assesses the level of burden experienced by informal caregivers. The 22 items are rated on a 5-point Likert scale from 0 ("never") to 4 ("nearly always"), yielding a total score ranging from 0 to 88. Higher scores indicate greater perceived caregiver burden. Typical interpretive ranges classify scores of 0-21 as little or no burden, 21-40 as mild to moderate burden, 41-60 as moderate to severe burden, and 61-88 as severe burden. |
| Global Fatigue Index (GFI) | Baseline and 4 week follow-up | The Global Fatigue Index is composite measure of fatigue severity and impact. It integrates ratings of fatigue intensity, distress, timing, and interference with daily activities, all on a 1-10 scale, and the final frequency question on a scale of 0-4. Higher total scores indicate greater fatigue. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Davis Usability Surveys | 4 week follow-up | The Davis Usability Survey, based on the Technology Acceptance Model (TAM), evaluates several constructs that impact technology adoption: Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Attitudes Towards Use (ATU). Each subscale contians 7, 10, and 6 items respectively rated on a 5-point Likert scale, with higher values indicating more favorable perceptions of usability and acceptance. Subscale scores are calculated by averaging the items within each domain. |
Countries
United States
Contacts
CONTACTJulie M Faieta, PhD, MOT
PRINCIPAL_INVESTIGATORJulie M Faieta, PhD, MOT
University of Pittsburgh
Outcome results
None listed