Cross-cultural adaptation and psychometric properties of the MMSE and MoCA questionnaires in Tanzanian Swahili for a traumatic brain injury population
Bibliographic record
Abstract
BACKGROUND: Traumatic Brain Injury (TBI) is the most common cause of injury-related death and disability globally, and a common sequelae is cognitive impairment. Addressing post-TBI cognitive deficits is crucial because they affect rehabilitation outcomes, but doing this requires valid and reliable cognitive assessment measures. However, no such instrument has been validated in Tanzania's TBI population. Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) are two commonly used instruments to measure cognitive impairment, and there have been a few studies reporting their use in post-TBI cognitive assessment. Our aim was to report the psychometric properties of the Swahili version of both scales amongst the TBI population in Tanzania. METHODS: A cross-cultural adaptation committee participated in the translation and content validation process for both questionnaires. Our patient sample consisted of 192 adults with TBI who were admitted to Kilimanjaro Christian Medical Center (KCMC) in Tanzania. Confirmatory factor analysis, reliability and external validity were evaluated. RESULTS: MoCA showed adequate factor loadings (values > 0.50 for all items except items 7 & 10) and adequate reliability (values > 0.70). Factor loadings for most of the MMSE items were below 0.5 and internal consistency was medium (< 0.7). Polychoric correlation between MMSE and MoCA was strong, positive and statistically significant (r = 0.68, p = 0.001); correlation with the cognitive subscale of FIM indicated moderately positive relationships - MMSE (r = 0.35, p = 0.001) and MoCA (r = 0.43, p = 0.001). CONCLUSIONS: With the exception of the language and memory items, MoCA is a valid and reliable instrument for cognitive impairment screening in Tanzania's adult TBI population. On the other hand, MMSE does not appear to be an appropriate tool in this patient group, but its positive correlations with MoCA and cFIM indicate similar theoretical concepts. Both instruments require further validation studies to prove their predictive ability for screening cognitive impairment before they are considered suitable for clinical use.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 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".