FANTASTIC‐D: A lifestyle questionnaire for people with dementia living at home
Bibliographic record
Abstract
Abstract Background The neglect of certain lifestyle factors entails a risk for negative outcomes (e.g., reduced quality of life, cardiovascular diseases, increased mortality) for people with dementia. Internationally, short overview instruments for identifying lifestyle risk factors in people with dementia to positively influence the course of the disease are lacking. The FANTASTIC questionnaire, originally developed in Canada, provides a short but comprehensive assessment of physical and psychosocial lifestyle risk factors. The aim of this study was to translate the FANTASTIC lifestyle questionnaire into German, to adapt it for people with dementia and to pretest the questionnaire regarding completeness, comprehensibility and face validity. Method In accordance with the principles of the ISPOR society, the literature and expert knowledge, the FANTASTIC questionnaire was forward‐backward‐translated, adapted to people with dementia and checked by means of two pre‐tests (expert review, cognitive interviews). Three experts participated in the expert review (including three members of the research team) and gave feedback on the retranslated questionnaire, ensuring face validity. Cognitive individual interviews were then conducted with five people with mild dementia living at home. A qualitative content analysis was performed using a concept‐driven coding frame. Result Evaluation of the expert review resulted in the following changes: usage of question words, addition of synonyms/examples for better understanding, development of a new dementia‐specific domain, and creation of answer cards (A4 landscape format) to make data collection easier for people with dementia. Analysis of cognitive interviews showed that people with dementia had problems with certain terms in the questions (e.g., emotional support), and with individual answer options (e.g., not weekly). The incomprehensible terms were either replaced by more understandable synonyms (e.g., "mental support" instead of "emotional support") or were explained with additional synonyms/examples in brackets after the questions. Unclear answer options were made more explicit (e.g., "1‐3 times per month" instead of "not weekly"). Furthermore, an interviewer manual was developed. Conclusion The FANTASTIC‐D is now available to assess lifestyle risk factors for German‐speaking people with dementia living at home. The next step in the study will be to test further psychometric properties and to establish the English version of FANTASTIC‐D.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".