Closing the gap between person-oriented theory and methods

Local Effects of Intervention: a Configural Analysis

In standard statistical data analysis, the effects of intervention or prevention efforts are evaluated in terms of variable relations. Results from application of regression-type methods suggest whether, overall, intervention is successful. In this article, we propose using configural frequency analysis (CFA) either in tandem with regression-type methods or by itself. CFA allows one to adopt a person-oriented perspective in which individuals are targeted that can be characterized by particular profiles. The questions asked in CFA concern these individuals instead of variables. In prevention research, one can ask whether, for particular profiles, the preventive measures are successful. In three real-world data examples, CFA is applied and compared to standard log-linear modeling. Examples consider non-randomized (observational) and randomized intervention settings. The results of these analyses suggest that person-oriented CFA and standard variable-oriented methods of analysis respond to different questions. We show that integrating person- and variable-oriented perspectives can help researchers obtain a fuller picture of intervention effectiveness. Extensions of the CFA approach are discussed.

Configural frequency trees

Although variable-oriented analyses are dominant in developmental psychopathology, researchers have championed a person-oriented approach that focuses on the individual as a totality. This view has methodological implications and various person-oriented methods have been developed to test person-oriented hypotheses. Configural frequency analysis (CFA) has been identified as a prime method for a person-oriented analysis of categorical data. CFA searches for configurations in cross-classifications and asks whether the number of observed cases is larger (CFA type) or smaller (CFA antitype) than expected under a probability model. The present study introduces a combination of CFA and model-based recursive partitioning (MOB) to test for type/antitype heterogeneity in the population. MOB CFA is well suited to detect complex moderation processes and can distinguish between subpopulation and population types/antitypes. Model specifications are discussed for first-order CFA and prediction CFA. Results from two simulation studies suggest that MOB CFA is able to detect moderation processes with high accuracy. Two empirical examples are given from school mental health research for illustrative purposes. The first example evaluates heterogeneity in student behavior types/antitypes, the second example focuses on the effect of a teacher classroom management intervention on student behavior. An implementation of the approach is provided in R.

Do Brief Alcohol Interventions Reduce Driving After Drinking Among College Students? A Two-step Meta-analysis of Individual Participant Data

Aims

College students who drink are at an increased risk of driving after drinking and alcohol-involved traffic accidents and deaths. Furthermore, the persistence of driving after drinking over time underscores a need for effective interventions to prevent future drunk driving in adulthood. The present study examined whether brief alcohol interventions (BAIs) for college students reduce driving after drinking.

Methods

A two-step meta-analysis of individual participant data (IPD) was conducted using a combined sample of 6801 college students from 15 randomized controlled trials (38% male, 72% White and 58% first-year students). BAIs included individually delivered Motivational Interviewing with Personalized Feedback (MI + PF), Group Motivational Interviewing (GMI), and stand-alone Personalized Feedback (PF) interventions. Two outcome variables, driving after two+/three+ drinks and driving after four+/five+ drinks, were checked, harmonized and analyzed separately for each study and then combined for meta-analysis and meta-regression analysis.

Results

BAIs lowered the risk of driving after four+/five+ drinks (19% difference in the odds of driving after drinking favoring BAIs vs. control), but not the risk of driving after two+/three+ drinks (9% difference). Subsequent subgroup analysis indicated that the MI + PF intervention was comparatively better than PF or GMI.

Conclusions

BAIs provide a harm reduction approach to college drinking. Hence, it is encouraging that BAIs reduce the risk of driving after heavy drinking among college students. However, there may be opportunities to enhance the intervention content and timing to be more relevant for driving after drinking and improve the outcome assessment and reporting to demonstrate its effect.

Cultural Orientation Trajectories and Substance Use: Findings From a Longitudinal Study of Mexican-Origin Youth

Cultural adaptation may influence Latino youth substance use (SU) development, yet few longitudinal studies have examined cultural change over time and adolescent SU outcomes. Using longitudinal data collected annually across ages 10-16 from 674 Mexican-origin youth (50% female), the authors characterized cultural adaptation patterns for language use (English and Spanish use), values (American values and familism values), and identity (ethnic pride), and examined whether these cultural adaptation patterns were associated with differential SU risk. Youth with increasing bilingualism and high/stable family values had lower SU risk compared to youth who primarily spoke English and endorsed decreasing family values, respectively. Ethnic pride trajectories were not associated with SU. Findings highlight the importance of considering cultural change related to Latino youth SU.

A computational physiology approach to personalized treatment models: the beneficial effects of slow breathing on the human cardiovascular system

Heart rate variability biofeedback intervention involves slow breathing at a rate of ∼6 breaths/min (resonance breathing) to maximize respiratory and baroreflex effects on heart period oscillations. This intervention has wide-ranging clinical benefits and is gaining empirical support as an adjunct therapy for biobehavioral disorders, including asthma and depression. Yet, little is known about the system-level cardiovascular changes that occur during resonance breathing or the extent to which individuals differ in cardiovascular benefit. This study used a computational physiology approach to dynamically model the human cardiovascular system at rest and during resonance breathing. Noninvasive measurements of heart period, beat-to-beat systolic and diastolic blood pressure, and respiration period were obtained from 24 healthy young men and women. A model with respiration as input was parameterized to better understand how the cardiovascular processes that control variability in heart period and blood pressure change from rest to resonance breathing. The cost function used in model calibration corresponded to the difference between the experimental data and model outputs. A good match was observed between the data and model outputs (heart period, blood pressure, and corresponding power spectral densities). Significant improvements in several modeled cardiovascular functions (e.g., blood flow to internal organs, sensitivity of the sympathetic component of the baroreflex, ventricular elastance) were observed during resonance breathing. Individual differences in the magnitude and nature of these dynamic responses suggest that computational physiology may be clinically useful for tailoring heart rate variability biofeedback interventions for the needs of individual patients.

Coping with complexity: Developmental systems and multilevel analyses in developmental psychopathology

Developmental psychopathology is not characterized by adherence to one specific theory but instead serves as an organizational framework in which research is driven by a number of key assumptions. In the developmental psychopathology approach, two primary assumptions emphasize the importance of systems thinking and the utility of multilevel analyses. As will be illustrated here, these emphases are inextricably linked: a systems approach necessitates a multilevel approach, such that a level of organization must bring coherence to a level of mechanisms. Given this assumption, coming to an integrative understanding of the relation between levels is of central importance. One broad framework for this endeavor is relational developmental systems, which has been proposed by certain theorists as a new paradigm for developmental science. The implications of embracing this framework include the potential to connect developmental psychopathology with other approaches that emphasize systems thinking and that take an integrative perspective on the problem of levels of analysis.