Identifying instruments to quantify financial management skills in adults with acquired cognitive impairments
Bibliographic record
Abstract
INTRODUCTION: Financial management skills-that is, the skills needed to handle personal finances such as banking and paying bills-are essential to a person's autonomy, independence, and community living. To date, no comprehensive review of financial management skills instruments exists, making it difficult for clinicians and researchers to choose relevant instruments. The objectives of this review are to: (a) identify all available instruments containing financial management skill items that have been used with adults with acquired cognitive impairments; (b) categorize the instruments by source (i.e., observation based, self-report, proxy report); and (c) describe observation-based performance instruments by populations, overarching concepts measured, and comprehensiveness of financial management items. Objective (c) focuses on observation-based performance instruments as these measures can aid in situations where the person with cognitive impairment has poor self-awareness or where the proxy has poor knowledge of the person's current abilities. METHOD: Two reviewers completed two systematic searches of five databases. Instruments were categorized by reviewing published literature, copies of the instruments, and/or communication with instrument authors. Comprehensiveness of items was based on nine key domains of financial management skills developed by the authors. RESULTS: A total of 88 discrete instruments were identified. Of these, 44 were categorized as observation-based performance and 44 as self- and/or proxy-reports. Of the 44 observation-based performance instruments, 8 had been developed for acquired brain injury populations and 24 for aging and dementia populations. Only 7 of the observation-based performance instruments had items spanning 6 or more of the 9 financial management skills domains. CONCLUSIONS: The majority of instruments were developed for aging and dementia populations, and few were comprehensive. This review provides foundation for future instrument psychometric and clinimetric reviews. It a necessary first step in providing information to support decision making for clinicians and researchers selecting financial management skills instruments.
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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 | 0.033 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".