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Record W4400981306 · doi:10.2196/56878

Ascertaining Out-of-Pocket Costs of Dementia Care: Feasibility Study of a Web-Based Weekly Survey

2024· article· en· W4400981306 on OpenAlexvenueno aff
Walter D Dawson, Nora Mattek, Sarah Gothard, Jeffrey Kaye, Allison Lindauer

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
FundersNational Institute on Aging
KeywordsPreprintDementiaMedicineComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Caring for a family member living with dementia is costly. A major contributor to care demands, and therefore to the costs, are the behavioral symptoms of dementia. Here, we examine the feasibility of ascertaining costs related to caregiving from weekly web-based surveys collected during a telehealth-based behavioral intervention study-Support via Technology: Living and Learning with Advancing Alzheimer Disease. OBJECTIVE: This study aims to determine the feasibility and acceptability of using a web-based weekly survey to capture real-time data on out-of-pocket caregiving expenses and time commitments associated with dementia care. To examine relationships between behavioral symptoms, care partner reactivity, burden, and out-of-pocket dementia care costs. METHODS: Feasibility was measured by accrual, retention, and data completion by participating care partners. Behavioral symptoms, care partner reactivity, and burden were collected before and after the intervention from 13 care partners. Weekly web-based surveys queried Support via Technology: Living and Learning with Advancing Alzheimer Disease care partners about their out-of-pocket costs associated with care-related activities. The surveys included questions on out-of-pocket costs care partners incurred from hospitalizations and emergency department use, primary care provider visits, use of paid in-home care or respite services, use of prescription medications, and use of over-the-counter medications. The surveys also queried the amount of time care partners devoted to these specific care-related activities. RESULTS: Out-of-pocket costs of dementia care were collected via a web-based weekly survey for up to 18 months. In-home assistance was the most frequently reported type of out-of-pocket care expense and the costliest. care partners who paid for in-home assistance or respite reported more behavioral and psychological symptoms of dementia behaviors, higher reactivity, and higher burden than those who did not. CONCLUSIONS: This novel web-based weekly survey-based approach offers lessons for designing and implementing future cost-focused studies and care partner-supportive telehealth-based interventions for Alzheimer disease and related dementias (ADRD). The results correspond with the existing understanding of ADRD in that high family-related out-of-pocket costs are a typical part of the caregiving experience, and those costs likely increase with dementia severity. The results may also offer potential insights to health systems and policy makers as they seek to implement telehealth-based and related interventions that seek to better support people living with ADRD and their family care partners. TRIAL REGISTRATION: ClinicalTrials.gov NCT04335110; https://clinicaltrials.gov/ct2/show/NCT04335110.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.031
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.221
GPT teacher head0.549
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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