A Transdiagnostic, Modular Approach to Treating Pica in Young Girl
Bibliographic record
Abstract
Objective: Pica is the persistent consumption of nonnutritive, nonfood substances. Despite the multitude of adverse complications associated with this condition, there is no gold standard treatment for pica in youth. This case study offers the first empirical investigation into the implementation of an empirically supported modular, transdiagnostic treatment—the MATCH-ADTC: Modular Approach to Therapy for Children with Anxiety, Depression, Trauma, or Conduct Problems—to treat pica and behavior challenges in a 10-year-old, White girl with Triple X Syndrome, autism spectrum disorder, attention-deficit/hyperactivity disorder, and trauma history. Method: We describe our assessment, formulation, and application of the MATCH program to target pica and behavior problems. Pre- and posttreatment symptom ratings (Child Behavior Checklist; CBCL), weekly ratings of pica and behavior problems (Behavior Rating Scale), and client satisfaction with treatment (Client Satisfaction Questionnaire) were collected at pre-, post-, and 6-months after treatment. Results: After 26 sessions, clinically significant improvements were observed in the client’s pica and behavior problems from baseline to posttreatment. Score differences in parent report on the CBCL from pre- to posttreatment indicated decreased levels of symptoms in all subscales reported. Six-month follow-up showed that pica behaviors remained at near-zero rates, and improvements in child behavior were sustained. Conclusions: This case study offers preliminary support for the use of MATCH, a modular, transdiagnostic treatment for treating pica and comorbidities in youth. A detailed treatment approach for clinician use is provided. Implications for Impact Statement This case study offers the first empirical support for a modular and transdiagnostic treatment to treat youth pica and comorbidities. The Modular Approach to Therapy for Children (MATCH) treatment offers a comprehensive program that clinicians can use to tailor treatment. We offer clinicians a treatment plan for youth pica and emphasize the importance of parent involvement in youth treatment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".