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Record W4379057045 · doi:10.2196/47255

Financial Health of People Living With Dementia and Their Informal Care Partners: Protocol for a Mixed Methods Study

2023· article· en· W4379057045 on OpenAlexvenueno aff
Eli Robert Boone, Heiley Tai, Ali Raich, Amulya Vatsavai, Annie Qin, Kayla Thompson, Mohini Johri, Ruitian Hu, Vishnukamal Golla, Melissa Harris

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesU.S. Department of Veterans Affairs
KeywordsPsychosocialDementiaPopulationHealth careDescriptive statisticsFinanceMedicinePsychologyBusinessDiseaseEnvironmental healthPsychiatryEconomicsEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: There is a growing body of academic literature focusing on the significant financial burdens placed on people living with cancer, but little evidence exists on the impact of rising costs of care in other vulnerable populations. This financial strain, also known as financial toxicity, can impact behavioral, psychosocial, and material domains of life for people diagnosed with chronic conditions and their care partners. New evidence suggests that populations experiencing health disparities, including those with dementia, face limited access to health care, employment discrimination, income inequality, higher burdens of disease, and exacerbating financial toxicity. OBJECTIVE: The three study aims are to (1) adapt a survey to capture financial toxicity in people living with dementia and their care partners; (2) characterize the degree and magnitude of different components of financial toxicity in this population; and (3) empower the voice of this population through imagery and critical reflection on their perceptions and experiences relating to financial toxicity. METHODS: This study uses a mixed methods approach to comprehensively characterize financial toxicity among people living with dementia and their care partners. To address aim 1, we will adapt elements from previously validated and reliable instruments, including the Comprehensive Score for Financial Toxicity and Patient-Reported Outcomes Measurement Information System, to develop a financial toxicity survey specific to dyads of people living with dementia and their care partners. A total of 100 dyads will complete the survey, and data will be analyzed using descriptive statistics and regression models to address aim 2. Aim 3 will be addressed using the process of "photovoice," which is a qualitative, participatory research method that combines photography, verbal narratives, and critical reflection by groups of individuals to capture aspects of their environment and experiences with a certain topic. Quantitative results and qualitative findings will be integrated using a validated, joint display table mixed methods approach called the pillar integration process. RESULTS: This study is ongoing, with quantitative findings and qualitative results anticipated by December 2023. Integrated findings will enhance the understanding of financial toxicity in individuals living with dementia and their care partners by providing a comprehensive baseline assessment. CONCLUSIONS: As one of the first studies on financial toxicity related to dementia care, findings from our mixed methods approach will support the development of new strategies for improving the costs of care. While this work focuses on those living with dementia, this protocol could be replicated for people living with other diseases and serve as a blueprint for future research efforts in this space. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47255.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.421
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.259
GPT teacher head0.541
Teacher spread0.282 · 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 teacher head, not a consensus.

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

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

Citations4
Published2023
Admission routes1
Has abstractyes

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