The Feasibility and Effectiveness of PASS Plus, A Lay Health Worker Delivered Comprehensive Intervention for Autism Spectrum Disorders: Pilot RCT in a Rural Low and Middle Income Country Setting
Bibliographic record
Abstract
The treatment gap for autism globally is high. Our previous PASS intervention, delivered by community based lay health workers, showed effectiveness. This article reports the development and evaluation of a new "PASS 'Plus'" intervention in a rural population in India. Using formative research methods, we supplemented the PASS intervention with additional (Plus) modules to address autism comorbidities. This is the first time that a rigorous methodology has been used to evaluate autism symptom outcomes in a low and middle-income country setting. 40 parent-child dyads were recruited in a pilot randomized controlled trial against usual care (mean age 65 months (34 boys); n = 19 PASS Plus, n = 21 UC). 89% of intervention families partially or entirely completed the 12-session intervention. Intention to treat analysis showed a reduction in mean scores of autism symptom severity, though the confidence interval contains zero, (adjusted mean difference AMD -2.42 95% CI -7.75, 2.92; ES 0.22); large treatment effects on proximal outcomes of proportion of parent synchronous responses (AMD 0.35; 95% CI 0.18, 0.52; effect size ES 3.97) and proportion of child communication initiations with parent (AMD 0·17; 95% CI 0.03, 0.32; ES 1.02). Confidence intervals for effects on mutual shared attention (AMD 0.10; 95% CI -0.07, 0.27; ES 0.5) and co-morbid symptoms (AMD -9.0; 95% CI -24.26, 6.26; ES 0.32) contained zero. There were significant effects to improve parental mental health. PASS Plus shows good feasibility and adds to the evidence of the effectiveness of task sharing complex autism interventions to lay health workers in India. Autism Res 2019, 12: 328-339 © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This article describes the development of a comprehensive, community-delivered, intervention for young children with autism, which combines a previously developed parent-mediated communication intervention with support for co-morbid problems like challenging behaviors and sensory sensitivities. The unique aspect of this intervention is that it can be delivered by community health workers, addressing the lack of specialists in low resource settings. Our study reports the encouraging findings of a pilot trial evaluating its feasibility and effectiveness.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".