Assessing the impact of mental health difficulties on young people’s daily lives: protocol for a scoping umbrella review of measurement instruments
Bibliographic record
Abstract
INTRODUCTION: An important consideration for determining the severity of mental health symptoms is their impact on youth's daily lives. Those wishing to assess 'life impact' face several challenges: First, various measurement instruments are available, including of global functioning, health-related quality of life and well-being. Existing reviews have tended to focus on one of these domains; consequently, a comprehensive overview is lacking. Second, the extent to which such instruments truly capture distinct concepts is unclear. Third, many available scales conflate symptoms and their impact, thus undermining much needed analyses of associations between the two. METHODS AND ANALYSIS: A scoping umbrella review will examine existing reviews of life impact measures for use with children and youth aged 6-24 years in the context of mental health and well-being research. We will systematically search six bibliographic databases (MEDLINE, Embase, APA PsycINFO, CINAHL, Web of Science, and the COSMIN database of systematic reviews of outcome measurement instruments), and conduct systematic record screening, data extraction and charting based on methodological guidance by the Joanna Briggs Institute. Data synthesis will involve the tabulation of scale characteristics, feasibility and measurement properties, and the use of summary statistics to synthesise how these instruments operationalise life impact. The protocol was registered prospectively with the Open Science Framework (osf.io/ers48). ETHICS AND DISSEMINATION: This study will provide a comprehensive road map for researchers and clinicians seeking to assess life impact in youth mental health, providing guidance in navigating available measurement options. We will seek to publish the findings in a leading peer-reviewed journal in the field. Formal research ethics approval will not be required.
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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 | 0.134 | 0.134 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.016 | 0.016 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.085 | 0.021 |
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".