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Advancing Intervention and Prevention Research for Behavioral Health Problems Through Data Synthesis
Jane L Pearson1, Belinda E Sims2
1National Institute of Mental Health, Rockville, USA. jpearson@nih.gov.
None:
This commentary on the special issue, "Innovations and Applications of Integrative Data Analysis (IDA) and Related Data Harmonization Procedures in Prevention Science" summarizes the utility of data synthesis techniques to elucidate prevention effects in important ways, including effects on low base-rate conditions and effects across multiple small-scale studies of preventive interventions, long-term and crossover effects of preventive interventions, and addressing for whom preventive interventions work, and for how long. In addition, articles tackle methodological challenges by integrating and harmonizing data. Much progress has occurred in the past 5 years. We consider in this commentary the full collection of papers in the special issue, and their ongoing contributions of data synthesis methods for advancing research on the prevention of mental, emotional, and behavioral health problems. We organize our observations by several themes noted across the papers. We also highlight the National Institute of Mental Health's investments that align with many of the efforts summarized here to advance our understanding of prevention research.
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