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Background The mental health treatment gap—the difference between those with mental health need and those who receive treatment—is high in low- and middle-income countries. Task-shifting has been used to address the shortage of mental health professionals, with a growing body of research demonstrating the effectiveness of mental health interventions delivered through task-shifting. However, very little research has focused on how to embed, support, and sustain task-shifting in government-funded systems with potential for scale up. The goal of the Building and Sustaining Interventions for Children (BASIC) study is to examine implementation policies and practices that predict adoption, fidelity, and sustainment of a mental health intervention in the education sector via teacher delivery and the health sector via community health volunteer delivery. Methods BASIC is a Hybrid Type II Implementation-Effectiveness trial. The study design is a stepped wedge, cluster randomized trial involving 7 sequences of 40 schools and 40 communities surrounding the schools. Enrollment consists of 120 teachers, 120 community health volunteers, up to 80 site leaders, and up to 1280 youth and one of their primary guardians. The evidence-based mental health intervention is a locally adapted version of Trauma-focused Cognitive Behavioral Therapy, called Pamoja Tunaweza. Lay counselors are trained and supervised in Pamoja Tunaweza by local trainers who are experienced in delivering the intervention and who participated in a Train-the-Trainer model of skills transfer. After the first sequence completes implementation, in-depth interviews are conducted with initial implementing sites’ counselors and leaders. Findings are used to inform delivery of implementation facilitation for subsequent sequences’ sites. We use a mixed methods approach including qualitative comparative analysis to identify necessary and sufficient implementation policies and practices that predict 3 implementation outcomes of interest: adoption, fidelity, and sustainment. We also examine child mental health outcomes and cost of the intervention in both the education and health sectors. Discussion The BASIC study will provide knowledge about how implementation of task-shifted mental health care can be supported in government systems that already serve children and adolescents. Knowledge about implementation policies and practices from BASIC can advance the science of implementation in low-resource contexts. Trial registration Trial Registration: ClinicalTrials.gov Identifier: NCT03243396. Registered 9th August 2017, https://clinicaltrials.gov/ct2/show/NCT03243396

Abstract Study Objectives To compare the efficacy of cognitive behavioral therapy for insomnia (CBTi) disorder and a Control condition on reducing insomnia and comorbid symptoms in a sample of active duty military personnel. Methods Randomized clinical trial of 151 active duty US Army personnel at Fort Hood, Texas. Results This study replicated Original (n = 66) findings (CBTi outperformed Control) in a follow-on sample (n = 85) on diary-assessed sleep efficiency (d = 1.04), total sleep time (d = 0.38), sleep latency (d = −0.93), number of awakenings (d = −0.56), wake time after sleep onset (d = −0.91), sleep quality (d = 1.00), and the Insomnia Severity Index (d = −1.36) in active duty soldiers. CBTi also outperformed Control in the combined sample (N = 151) on four of the five subscales of the Multidimensional Fatigue Inventory (d = −0.32 to −0.96) and the mental health subscale on the Veterans RAND 12-Item Health Survey (d = 0.37). Exploratory analyses also showed CBTi outperformed Control on nicotine (d = −0.22) and caffeine (d = −0.47) use reduction. Significant within-group differences were found for both groups on depression, anxiety, and posttraumatic stress disorder symptoms, but there was no group by time interaction for these symptoms or for use of hypnotics or alcohol. Conclusions CBTi was an effective treatment for insomnia and comorbid symptoms including daytime fatigue, general mental health, nicotine, and caffeine use. Clinical Trial Registration Clinicaltrials.gov; Identifier: NCT01549899; “Comparing Internet and In-Person Brief Cognitive Behavioral Therapy of Insomnia”

Background The aim of many physical activity interventions is to develop life-long habits of regular exercise and sports activities in leisure time. Previous studies that assessed tracking (i.e. the stability of a trait over the lifespan) of leisure time exercise behaviour across various parts of the life span have treated it as a uniform construct by summing all types of leisure time exercise activities into a single summary score for the total volume of exercise. This study provides new insight by additionally determining tracking across leisure time exercise activities in six different domains: (1) team-based versus solitary activities, (2) competitive versus non-competitive activities, and (3) externally paced versus internally paced activities. We also assessed which of the domains of exercise activities best predicted total volume of exercise at follow-up. Methods A large dataset ( N  = 43,889) from the Netherlands Twin Register (NTR) was used to analyse the tracking of exercise behaviour over time. Using this dataset, we were able to examine tracking as a function of baseline age (8 to 80 years) and tracking duration (2 to 22-year follow-up), taking into account sex differences, using generalized estimating equations. Results Two-year tracking coefficients are moderate to high for total volume of exercise across ages at baseline, ranging from .38 to .77 with a median of .57. Tracking coefficients tend to decrease as the distance to follow-up increases, down to a median of .38 for the 22-year tracking coefficients. The patterns of tracking were largely domain-independent and were largely similar for solitary, competitive, non-competitive, externally and internally paced activities. With the exception of team-based activities, tracking was seen to increase as a function of baseline age. Cross-domain tracking did not favour any specific domain of exercise activity as the best predictor for total volume of exercise behaviour and this was true at all baseline ages. Conclusion We conclude that exercise behaviour is moderately to highly stable across the life span. In particular in adulthood, where the tracking of exercise mimics that of a classical behavioural trait like personality. This stability reinforces existing evidence that exercise habits are hard to change, but at the same time suggests that successful intervention leading to the adoption of exercise habits will tend to last.

Objective This dataset offers empirical support for understanding the number of sexual harassment complaints across various industries and sectors, and for analysing patterns over a decade. The data was manually collected from the annual integrated report or business responsibility report of each company on the BSE100 list. This dataset can be utilised by the Indian Ministry of Women & Child Development and related stakeholders as a foundation for studying the impact of previous interventions and policy changes on complaint reporting rates. Additionally, it can also be used to analyse patterns and trends and give way to revisions to existing legal frameworks and improvements to grievance redressal mechanisms for sexual harassment complaints. Data description Data includes descriptive statistics for all variables and compares complaints received between each year and the subsequent year, with a total of 10 year-to-year comparisons for the period: 2013–2024. The variables are: (1) List of BSE100 Companies, (2) Industry, (3) Sector, (4) Number of sexual harassment complaints received for the periods: 2013–2024, (5) Number of sexual harassment complaints pending during the periods: 2013–2024.

Behavioral scientists are developing new methods and frameworks that leverage mobile health technologies to optimize individual level behavior change. Pervasive sensors and mobile apps allow researchers to passively observe human behaviors “in the wild” 24/7 which supports delivery of personalized interventions in the real-world environment. This is all possible because these technologies contain an incredible array of sensors that allow applications to constantly record user location and can contextualize current environmental conditions through barometers, thermometers, and ambient light sensors and can also capture audio and video of the user and their surroundings through multiple integrated high-definition cameras and microphones. These tools are a game changer in behavioral health research and, not surprisingly, introduce new ethical, regulatory/legal and social implications described in this article.

The goal of evidence-based medicine is ultimately to improve patient outcomes and quality of care. Systematic reviews of the available published evidence are required to identify interventions that lead to improvements in behavior, health, and well-being. Authoritative literature reviews depend on the quality of published research and research reports. The Consolidated Standards for Reporting Trials (CONSORT) Statement (www.consort-statement.org) was developed to improve the design and reporting of interventions involving randomized clinical trials (RCTs) in medical journals. We describe the 22 CONSORT guidelines and explain their application to behavioral medicine research and to evidence-based practice. Additional behavioral medicine-specific guidelines (e.g., treatment adherence) are also presented. Use of these guidelines by clinicians, educators, policymakers, and researchers who design, report, and evaluate or review RCTs will strengthen the research itself and accelerate efforts to apply behavioral medicine research to improve the processes and outcomes of behavioral medicine practice.

Behavior genetics often emphasizes methods over the underlying quality of the psychological information to which the methods are applied. A core aspect of this quality is the demographic diversity of the samples. Building causal genetic models based only on European-ancestry samples compromises their generalizability. Behavior genetics researchers must spend additional time and resources diversifying their samples before emphasizing causation.

The aim of the article is to analyse the structure of consumer behaviour models and their applications to financial behaviour. The paper is theoretical in nature, examining generational breakdowns and selected trends in consumer behaviour. An analysis of the ‚rules‘ significant for types of consumer behaviour is conducted. Despite recently intensified theoretical and empirical analysis of consumer behaviour, a coherent research approach that integrates the issue of consumer behaviour with the specificities of the financial-services market has not yet been developed. Models remain frail, their functionality is still insufficient, and their applicability is constantly being altered by influences on consumer behaviour, including macro and microeconomic factors and the influence of scientific fields such as economics, sociology, psychology, management and anthropology. This article attempts to create a model that takes into account the general factors adopted in models constructed so far, along with the assumption that economic, cultural, social, personal, experiences, and other factors play a role in shaping and stimulating at least five variables: type of consumer from a particular generation (Cy); type of financial products and services (Xy); motivation (My); capacity (Capy); and opportunities (Oy).

When explaining the causes of human behavior, genes are often given a special status. They are thought to relate to an intrinsic human ‘essence’, and essentialist biases have been shown to skew the way in which causation is assessed. Causal reasoning in general is subject to other pre-existing biases, including beliefs about normativity and morality. In this synthesis we show how factors which influence causal reasoning can be mapped to a framework of genetic essentialism, which reveals both the shared and unique factors underpinning biases in causal reasoning and genetic essentialism. This comparison identifies overlooked areas of research which could provide fruitful investigation, such as whether normative assessments of behaviors influence the way that genetic causes are ascribed or endorsed. We also outline the importance of distinguishing reasoning processes regarding genetic causal influences on one’s self versus others, as different cognitive processes and biases are likely to be at play.

Since its earliest days, the field of behavioral medicine has leveraged technology to increase the reach and effectiveness of its interventions. Here, we highlight key areas of opportunity and recommend next steps to further advance intervention development, evaluation, and commercialization with a focus on three technologies: mobile applications (apps), social media, and wearable devices. Ultimately, we argue that future of digital health behavioral science research lies in finding ways to advance more robust academic-industry partnerships. These include academics consciously working towards preparing and training the work force of the twenty first century for digital health, actively working towards advancing methods that can balance the needs for efficiency in industry with the desire for rigor and reproducibility in academia, and the need to advance common practices and procedures that support more ethical practices for promoting healthy behavior.