Abstract
We surveyed 491 American Psychological Association division 12 (clinical psychology) members regarding their professional use of clinical and mechanical data combination (CC and MC) in making clinical predictions; 183 (37%) responded. This is the first report of CC and MC utilization frequency known to us. Nearly all respondents used CC in practice (98%), while fewer used MC (31%). Respondents gave reasons why they did not use MC, the most common being that it is conceptually misguided. In addition to computing odds ratios for variable comparisons, we constructed a multivariate regression model to predict use of MC, using a bootstrapping method that returns an estimate of the model's cross-validated validity. This procedure returned the null model: no predictor was powerful enough to replicate upon cross-validation. The extent to which MC was discussed in graduate school significantly mediated nearly all other relationships between variables of interest. Implications of these findings are discussed.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 525-531 |
| Number of pages | 7 |
| Journal | Professional Psychology: Research and Practice |
| Volume | 40 |
| Issue number | 5 |
| DOIs | |
| State | Published - Oct 2009 |
Keywords
- actuarial
- clinical judgment
- mechanical
- prediction
- statistical
- survey
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