Determining clinically meaningful change: minimal clinically important difference for common depression scales in older adults with parkinson’s disease
Bibliographic record
Abstract
BACKGROUND: The Minimal Clinically Important Difference (MCID) is a crucial measure in clinical research, reflecting the smallest change in symptoms that patients perceive as beneficial. While MCID values have been established for various symptoms in Parkinson's disease (PD), they remain underexplored in the context of depression. OBJECTIVE: This study aims to determine MCID values for three commonly used depression scales in PD: The Beck Depression Inventory (BDI-II), the Hospital Anxiety and Depression Scale - Depression subscale (HADS-D), and the 15-item Geriatric Depression Scale (GDS-15). METHODS: A total of 112 individuals with PD and depression (mean age = 70.91 ± 3.12 years) participated in a 10-week cognitive behavioral therapy program. The MCID values were estimated using both distribution-based and anchor-based methods. The Global Rating of Change (GRoC) scale was used as an anchor to assess perceived changes in depressive symptoms. RESULTS: MCID values were refined using the mean difference approach, resulting in the following: -5.79 points for the BDI-II, -3.52 points for the HADS-D, and - 3.05 points for the GDS-15, all with statistical significance (p < 0.001). Using Youden's index, the optimal MCID cut-off values were ≤ -3 points for BDI-II, ≤ -2 points for HADS-D, and ≤ -2 points for GDS-15, with high sensitivity and specificity for each. The MCID values derived from the distribution-based method for the BDI-II, HADS-D, and GDS-15 were 5.57-3.55, 1.11-3.07, and 0.96-2.66 points, respectively. CONCLUSIONS: This study establishes MCID thresholds for commonly used depression scales in PD. These benchmarks are essential for improving clinical decision-making and evaluating the effectiveness of interventions in both clinical and research settings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".