Research on Day Treatment Programs for Preschoolers With Disruptive Behavior Disorders
Bibliographic record
Abstract
OBJECTIVE: This review examined the literature on psychosocial treatments for preschoolers with disruptive behavior disorders to delineate ways in which interventions developed in research settings can be used to enhance existing clinical preschool day treatment programs. METHODS: A PsycINFO search was performed by using the keywords "day treatment," "behavior problems," "disruptive behavior disorder," and "oppositional defiant disorder" to find articles published between 1974 and 2004 on randomized controlled trials of psychosocial interventions for preschoolers (ages two to five years). No randomized controlled trials of multimodal day treatment programs were found. Therefore, studies on multimodal day treatment were selected on the basis of whether they presented quantitative outcome data. RESULTS AND CONCLUSIONS: Little research was available on the effectiveness of day treatment programs, despite the programs' prevalence as a treatment modality for disruptive preschoolers. In contrast, many interventions in the disruptive behavior disorder research have not made their way into clinical practice. Preschool day treatment programs may be enhanced by improving access to care, emphasizing social problem-solving skills, and using strategies to engage families in treatment. Research studies on existing day treatment programs are needed to clarify the role of these programs in child psychiatry clinics and to shed light on optimal methods of service delivery.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| 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) | 0.005 | 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".