The Wellbeing Index for Persons with Dementia—An Observational Study Based on the Group Observational Measurement of Engagement (GOME)
Bibliographic record
Abstract
The Group Observational Measurement of Engagement (GOME) was developed to capture the impact of group recreational activities on the engagement and general wellbeing of persons with dementia. The psychometric properties of the GOME were originally described in a study of group activities conducted at one large Canadian geriatric center. Continuing this work in Israel, this article reports on further psychometric properties of the GOME based on observations of 115 persons with dementia from 10 geriatric units, of which four were senior day center units (in three institutions) and six were nursing units (representing five other institutions). Very good inter-rater reliability between research observers was found. Factor analysis suggests that the GOME's four individual-level outcomes can be combined into one indicator, the Wellbeing Index. Validity, examined via agreement between research observers and group activity leaders who were staff members in the facilities where the group activities were conducted, also showed high levels of positive correlations. The GOME provides a practical tool for assessing wellbeing in the context of group activities. It can be useful in clarifying the relative impact of process variables on participants' general wellbeing.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".