No abstract

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

Background Among pediatricians, perceived knowledge of efficacy, tolerability, dosing and side effects of antidepressants represent significant sources of variability in the use of these medications in youth with depressive and anxiety disorders. Importantly, the qualitative factors that relate to varying levels of comfort with antidepressants and willingness to prescribe are poorly understood. Methods Using a mixed-methods approach, in-depth interviews were conducted with community-based and academic medical center-based pediatricians (N=14). Interviews were audio-recorded and iteratively coded; themes were then generated using inductive thematic analysis. The relationship between demographic factors, knowledge of antidepressants, dosing and side effects, as well as prescribing likelihood scores for depressive disorders, anxiety disorders or co-morbid anxiety and depressive disorders, were evaluated using mixed models. Results Pediatricians reported antidepressants to be effective and well-tolerated. However, the likelihood of individual physicians initiating an antidepressant was significantly lower for anxiety disorders relative to depressive disorders with similar functional impairment. Pediatricians considered symptom severity/functional impairment, age and the availability of psychotherapy as they considered prescribing antidepressants to individual patients. Antidepressant choice was related to the physician’s perceived knowledge and comfort with a particular antidepressant, financial factors and the disorder-specific evidence base for that particular medication and consultation with mental health practitioners. Pediatricians noted similar efficacy and tolerability profiles for antidepressants in youth with depressive disorders and anxiety disorders, but tended to utilize “therapy first” approaches for anxiety disorders relative to depressive disorders. Parental and family factors that influenced prescribing of antidepressants by pediatricians included parental ambivalence, family-related dysfunction and impairment secondary to the child’s psychopathology as well as the child’s psychosocial milieu. Conclusions Pediatricians consider patient- and family-specific challenges when choosing prescribing antidepressant medications and are, in general, less likely to prescribe antidepressants for youth with anxiety disorders compared to youth with depressive disorders. The lower likelihood of prescribing antidepressants for anxious youth is not related to perception of the efficacy or tolerability, but rather to a perception that anxiety disorders are less impairing and more appropriately managed with psychotherapy.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

No abstract