Psychometric properties of the Knowledge and Attitudes to Mental Health Scales in a Dutch sample (KAMHS-NL): A comprehensive mental health literacy measure in adolescents
Bibliographic record
Abstract
BACKGROUND: Mental health literacy (MHL) is crucial for early recognition of and coping with mental health problems, and for the use and acceptance of mental health services, leading to better health outcomes, especially in adolescence. The prevalence of mental health problems among adolescents is seen as a major public health concern and MHL is an important factor in facilitating positive mental health outcomes. However, the availability of valid measurement instruments for assessing the multifaceted nature of MHL is limited, hindering the ability to make meaningful comparisons across studies. The Knowledge and Attitudes to Mental Health Scales (KAMHS) is a promising comprehensive instrument for measuring adolescents' mental health literacy but its psychometric properties have not been explored in any other contexts than the Welsh. The aim of this study was to translate the KAMHS into Dutch, adapt it in this context, and evaluate its psychometric properties. METHODS: We performed a cross-sectional study with Dutch adolescents between the ages 11-16. We translated the KAHMS and assessed its content validity using cognitive interviewing with n = 16 adolescents. Next, n = 406 adolescents were asked to fill in the translated KAMHS-NL and reference scales, on mental health (SDQ and WHO-5), resilience (BRS), and mental health help-seeking behaviors. We assessed construct validity based on a priori hypotheses regarding convergent and divergent correlations between subscales of KAMHS-NL and the reference scales. Finally, we assessed structural validity via confirmatory factor analysis and exploratory structural equation modeling. RESULTS: The KAMHS-NL showed good content validity and satisfactory construct validity. In total, 28 of the 48 hypotheses regarding convergent and divergent correlations between the KAMHS and reference scales were confirmed. Contrary to our expectations, weak, but significant associations were found between MHL and resilience. The KAMHS showed an acceptable to good internal consistency (McDonald's omega ranging from 0.62 to 0.84). Finally, we could generally confirm the postulated structure of the KAMHS-NL in the Dutch sample with a 5-factor solution (RMSEA = 0.033; CFI = 0.96). CONCLUSIONS: The Dutch version of the KAMHS is a valid measure for detecting differences in MHL levels in adolescents. The KAMHS is a promising instrument for assessing MHL in adolescents in a multifaceted manner in other countries which may facilitate rigorous global MHL research. The instrument therefore deserves further validation research in other settings and comparisons across various cultural contexts.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.002 | 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".