Financial, Legal, and Functional Challenges of Providing Care for People Living With Dementia and Needs for a Digital Platform: Interview Study Among Family Caregivers
Bibliographic record
Abstract
BACKGROUND: Alzheimer disease and Alzheimer disease-related dementia represent complex neuropathologies directly challenging individuals, their families, and communities in the United States. To support persons living with dementia, family or informal caregivers often encounter complex financial, psychological, and physical challenges. A widely used solution such as a consolidated web-based assistance or guidance platform is missing, compounding care challenges. OBJECTIVE: In preparation for designing an internet-based artificial intelligence-driven digital resource platform, a qualitative interview study was conducted to characterize the challenges and needs of family caregivers in the United States. METHODS: A semistructured interview topic guide in English was developed by engaging community partners and research partnerships. Family caregiver participants were purposefully recruited via various means, such as word of mouth, local dementia community service providers, digital recruitment emails, flyers, and social media. Interested individuals were first invited to complete an eligibility screening survey, and eligible individuals were then contacted to arrange a web-based in-depth interview via Zoom (Zoom Video Communications) from January 1, 2022, to May 31, 2022. A follow-up survey was administered in May 2022 to provide an overview of the participants' demographics, socioeconomic characteristics, and caregiving information. Thematic analysis in a framework approach was used to identify and organize themes and the study findings. RESULTS: Following the prescreening of 150 eligible respondents, 20% (30/150) individuals completed both the interviews and follow-up survey, allowing for an in-depth look into the challenges, experiences, and expectations of primary caregivers of people living with dementia. Most participants (20/30, 67%) were primary caregivers of persons with dementia, and 93% (28/30) had provided care for at least a year. Most participants were aged >50 years (25/30, 83%), female (23/30, 77%), White (25/30, 83%), and non-Hispanic (27/30, 90%) and held a bachelor's or graduate degree (22/30, 73%). Collectively, all participants acknowledged challenges in caring for people living with dementia. Thematic analyses elicited the challenges of caregiving related to functional care needs and financial and legal challenges. In addition, participants identified the need for an integrative digital platform where information could be supplied to foster education, share resources, and provide community support, enabling family caregivers to improve the quality of care and reducing caregiver burden. CONCLUSIONS: This study emphasized the difficulties associated with the family caregiver role and the expectations and potential for a supportive web-based platform to mitigate current challenges within the caregiving role.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".