Comprehensive Community-Based Intervention and Asthma Outcomes in African American Adolescents
Bibliographic record
Abstract
BACKGROUND: African American adolescents appear to be the most at risk for asthma morbidity and mortality even compared with other minority groups, yet there are few successful interventions for this population that are used to target poorly controlled asthma. METHODS: African American adolescents (age 12–16 years) with moderate-to-severe persistent asthma and ≥1 inpatient hospitalization or ≥2 emergency department visits in 12 months were randomly assigned to Multisystemic Therapy–Health Care or an attention control group (N = 167). Multisystemic Therapy–Health Care is a 6-month home- and community-based treatment that has been shown to improve illness management and health outcomes in high-risk adolescents by addressing the unique barriers for each individual family with cognitive behavioral interventions. The attention control condition was weekly family supportive counseling, which was also provided for 6 months in the home. The primary outcome was lung function (forced expiratory volume in 1 second [FEV1]) measured over 12 months of follow-up. RESULTS: Linear mixed-effects models revealed that compared with adolescents in the comparison group, adolescents in the treatment group had significantly greater improvements in FEV1 secondary outcomes of adherence to controller medication, and the frequency of asthma symptoms. Adolescents in the treatment group had greater reductions in hospitalizations, but there were no differences in reductions in emergency department visits. CONCLUSIONS: A comprehensive family- and community-based treatment significantly improved FEV1, medication adherence, asthma symptom frequency, and inpatient hospitalizations in African American adolescents with poorly controlled asthma. Further evaluation in effectiveness and implementation trials is warranted.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".