ADAPTATION OF THE COGNITIVE RESERVE INDEX QUESTIONNAIRE, PRELIMINARY RESULTS
Bibliographic record
Abstract
Introduction: The concept of “cognitive reserve” has been used to explain the observation where two individuals with similar neuropathology experience different outcomes either through coping or compensational mechanisms (Stern, 2002). Intellectual and work involvement are considered the main aspects of cognitive reserve – the ability to overcome a neuropathology by using previously developed cognitive or compensational processes (Stern, 2009). However, even though the subject of “cognitive reserve” has become more and more relevant, available tools for measuring it are sparse. The main objective of this study was to conduct the first stage in adapting Cognitive Reserve Index Questionnaire, CRIq (Nucci, Mapelli, & Mondini, 2012). Methods: 29 participants aged from 65 to 80 (M = 72,48, SD = 4,7, 28% male) participated in the study. None of the participants were diagnosed with a neurodegenerative disease, participants with previous head trauma were excluded from the data analysis. Before administering, the CRIq was translated to Latvian and back by two bilingual translators. The questionnaire consists of three sections – the first section comprises years of education, the second secion accounts for working activity (years and level of professional occupation) and the third section comprises information on leisure time (years of frequent leisure activities, e.g. reading, traveling, taking care of a pet etc.). In order to assess the cognitive processes, Montreal Cognitive Assessment (Nasreddine et al., 2005) and Memory Ten-word test (Luria, 1976) were used. Results: The total CRI score correlated strongly with all the three subscores (r = 0,616, 0,758, 0,483, p < 0,05, for the correlations with CRI-Education, CRI-Working Activity and CRI-Leisure Time respectively). There were no significant correlations across any of the CRI subscores and MoCA test and Memory Ten-word test results. Significant differences across gender were found in CRI-Education (t = 2,423, p < 0,05) and the total CRI score (t = 2,981, p < 0,05). Conclusions: Overall, this study will provide an instrument for measuring cognitive reserve in Latvia; however, even in the first stage of adaptation, a question regarding the necessary changes for adapting this instrument. Even though the internal consistency of the CRIq was satisfactory, there were no correlations with the measures of cognitive processes. These results raise the question regarding such limitations of this research as the small sample as well as not taking into the consideration the aspect of bilingualism.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".