Mental Health and Mental Health Services Research

Erratum to: Characteristics of People Who Use Telephone Counseling: Findings from Secondary Analysis of a Population-Based Study

Clinicians’ Attitudes Towards Outcome and Process Monitoring: A Validation of the Outcome Measurement Questionnaire Abstract Valid and reliable instruments to measure monitoring attitudes of clinicians are scarce. The influence of sociodemographics and professional characteristics on monitoring attitudes is largely unknown. First, we investigated the factor structure and reliability of the Outcome Measurement Questionnaire among a sample of Flemish mental health professionals (n = 170). Next, we examined the relationship between clinicians’ sociodemographic and professional characteristics and monitoring attitudes. Construct validity was determined using a confirmatory factor analysis. Internal consistency was ascertained using Cronbach’s alpha. Mean level differences in monitoring attitudes related to clinicians’ gender, work setting, level of education and psychotherapeutic training, were investigated using ANOVAs. The relationships between clinicians’ age, clinical experience and attitudes were calculated using the Pearson correlation coefficient. A model with one general factor and a method factor referring to reverse-worded items best fitted our data. Internal consistency was good. Clinicians with psychotherapeutic training reported more favorable monitoring attitudes than those without such training. Compared to clinicians working in subsidized outpatient services, private practitioners and clinicians from inpatient mental health clinics had more positive attitudes. Results highlight the need for sustained and targeted training, with particular focus on transforming measurement data into meaningful clinical support tools.

Optimal Design and Purposeful Sampling: Complementary Methodologies for Implementation Research Abstract Optimal design has been an under-utilized methodology. However, it has significant real-world applications, particularly in mixed methods implementation research. We review the concept and demonstrate how it can be used to assess the sensitivity of design decisions and balance competing needs. For observational studies, this methodology enables selection of the most informative study units. For experimental studies, it entails selecting and assigning study units to intervention conditions in the most informative manner. We blend optimal design methods with purposeful sampling to show how these two concepts balance competing needs when there are multiple study aims, a common situation in implementation research.

Special Issue Overview: Optimizing Mixed Methods for Implementation Research in Large Systems

Sharing State Mental Health Data for Research: Building Toward Ongoing Learning in Mental Health Care Systems Abstract With the rise of “big data,” the opportunities to use administrative and clinical data to evaluate impact of state level program initiatives are greatly expanded. The National Institute of Mental Health has in recent years supported research studies pooling data across states to address state-relevant questions. This commentary summarizes these activities and describes future platforms that may enhance ongoing work in this area.

Integrating Science and Engineering to Implement Evidence-Based Practices in Health Care Settings Abstract Integrating two distinct and complementary paradigms, science and engineering, may produce more effective outcomes for the implementation of evidence-based practices in health care settings. Science formalizes and tests innovations, whereas engineering customizes and optimizes how the innovation is applied tailoring to accommodate local conditions. Together they may accelerate the creation of an evidence-based healthcare system that works effectively in specific health care settings. We give examples of applying engineering methods for better quality, more efficient, and safer implementation of clinical practices, medical devices, and health services systems. A specific example was applying systems engineering design that orchestrated people, process, data, decision-making, and communication through a technology application to implement evidence-based depression care among low-income patients with diabetes. We recommend that leading journals recognize the fundamental role of engineering in implementation research, to improve understanding of design elements that create a better fit between program elements and local context.

Linking the Legislative Process to the Consequences of Realigning California’s Public Mental Health System Abstract In 1991, California transferred significant responsibility, resources, and accountability for public mental health from the state to its 58 counties. Using purposeful sampling, we conducted in-depth interviews with ten senior state and county leaders to gain insights into the relatively uncharted area of their understanding of this legislation’s intent, development, and long-term consequences. While realignment secured funding for the system and provided incentives and flexibility for counties to move toward providing more community-based care, the decision to base realignment allocations on counties’ historical spending along with minimal payments to address differences helped to institutionalize spending disparities. Results of this study can inform how we develop and implement decentralization policies.

Measures for Predictors of Innovation Adoption Abstract Building on a narrative synthesis of adoption theories by Wisdom et al. (2013), this review identifies 118 measures associated with the 27 adoption predictors in the synthesis. The distribution of measures is uneven across the predictors and predictors vary in modifiability. Multiple dimensions and definitions of predictors further complicate measurement efforts. For state policymakers and researchers, more effective and integrated measurement can advance the adoption of complex innovations such as evidence-based practices.

Characteristics of People Who Use Telephone Counseling: Findings from Secondary Analysis of a Population-Based Study Abstract The characteristics of people who use telephone counseling are not well understood. This secondary analysis used data from a nationally representative community survey of 8,841 Australian adults to compare callers and non-callers to telephone counseling services. Callers have a poorer clinical profile, including a higher risk of suicide, than people who do not use telephone counseling. They also use a variety of other mental health services. Repeat calls are associated with anxiety disorders, receipt of mental health care from general practitioners, and social disadvantage. All callers have a potential need for telephone counseling and further population studies that distinguish between telephone services intended to provide crisis (one-off) and ongoing counseling are warranted.

Long-Term Clinical Outcomes from a Randomized Controlled Trial of Two Implementation Strategies to Promote Collaborative Care Attendance in Community Practices Abstract This randomized controlled implementation study compared the effectiveness of a standard versus enhanced version of the replicating effective programs (REP) implementation strategy to improve the uptake of the life goals-collaborative care model (LG-CC) for bipolar disorder. Seven community-based practices (384 patient participants) were randomized to standard (manual/training) or enhanced REP (customized manual/training/facilitation) to promote LG-CC implementation. Participants from enhanced REP sites had no significant changes in primary outcomes (improved quality of life, reduced functioning or mood symptoms) by 24 months. Further research is needed to determine whether implementation strategies can lead to sustained, improved participant outcomes in addition to program uptake.