HOME ASSESSMENT OF PERSON-ENVIRONMENT INTERACTION (HOPE): A CROSS-CULTURAL VALIDATION STUDY
Bibliographic record
Abstract
Aging is frequently associated with impaired mobility. Consequently, the elderly face environmental barriers within their home environment and Aging-in-Place becomes a challenge. Few assessment tools exist to address the issue of home adaptation. HoPE is based on a Person-environment Interaction Model and specifically designed for home adaptation evaluation. Since its original version is in French, this study’s aim was to yield an English version. Based on a back-translation methodology for cross-cultural research, the first steps of the Vallerand’s method were completed: 1) an English experimental version of HoPE was produced by comparing the original version with the translated and back-translated versions by independent translators, 2) this experimental version was submitted to an expert panel to validate the transcultural equivalence using a consensus approach. Comparative data analyses included: 1) highlighting the similarities/differences across the three versions of HoPE (original, translated, back-translated), and 2) reporting the experts agreement/disagreement. Results show that 70% of the experimental version is transculturally equivalent. For the remaining 30%, the experts reached a consensus except for 6 terms for which decision was based on the majority; then, the English version of HoPE was produced. Considering these results and the psychometric properties of its original version (French), this cross-cultural adaptation of HoPE provides clinicians and researchers with a new and valid tool to understand the Person-Environment Interaction in the home setting.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".