Mediators and moderators in early intervention research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: The goal of this paper is to provide clarification with regard to the nature of mediator and moderator variables and the statistical methods used to test for the existence of these variables. Particular attention will be devoted to discussing the ways in which the identification of mediator and moderator variables may help to advance the field of early intervention in psychiatry. METHODS: We completed a literature review of the methodological strategies used to test for mediator and moderator variables. RESULTS: Although several tests for mediator variables are currently available, recent evaluations suggest that tests which directly evaluate the indirect effect are superior. With regard to moderator variables, two approaches ('pick-a-point' and regions of significance) are available, and we provide guidelines with regard to how researchers can determine which approach may be most appropriate to use for their specific study. Finally, we discuss how to evaluate the clinical importance of mediator and moderator relationships as well as the methodology to calculate statistical power for tests of mediation and moderation. CONCLUSION: Further exploration of mediator and moderator variables may provide valuable information with regard to interventions provided early in the course of a psychiatric illness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it