Systems use to objectify program evaluation,clinical, and management decisions

The utility of the observational assessment systems at different levels — from local clinical to systemwide management — is outlined. An overview is provided of TSBC information applied to individualized problem identification and programming/monitoring, discharge and competency determinations, and both absolute and comparative program evaluation. The utility of SRIC information for prgoramming/monitoring and for staff training and evaluation is outlined in addition to the applied uses of the information of the assessment systems in combination. Once implemented, the continuous data from the systems allow for empirically based self-corrective improvements in the quality of mental health services while automatically providing a basis for legal documentation and accurate cost/effectiveness comparisons of mental health programs.Preparation of this article and the research and development on which the article is based were supported, in part, by Public Health Service Grants MH-15553 and MH-25464 from the National Institute of Mental Health, and by grants from The Joyce Foundation and the Illinois Department of Mental Health and Developmental Disabilities.Presented at the 87th Annual Meetings of the American Psychological Association, New York City, September 1979, as part of a symposium on New assessment systems for residential treatment, management, research, and evaluation.     

On computing time-to-collision for automation scenarios

Time to collision (TTC) has been a key vehicle safety metric for decades. With the increasing prevalence of advanced driver assistance systems and vehicle automation, TTC and many related metrics are being applied to the analysis of more complicated scenarios, as well as being integrated into automation algorithms. While the TTC metric was originally conceived to be inclusive of generic two-dimensional situations, its applications has been mostly limited to one-dimensional scenarios. This paper derives general equations and algorithms using two-dimensional information. Additionally, methods from computational geometry, a field that didn’t exist when TTC was first used, are employed for the general case of computing TTC between bounding boxes. Parametric equations for lines play a prominent role and offer an elegant way to express the geometry of the scenarios described in this paper. Throughout, the approach is not to derive specific algebraic conditions as in previous efforts. Rather, the focus in on developing general algorithms for computation. The techniques presented are not necessary for traditional car following scenarios; but offer options for more complex situations that trade off analytic solutions for computational flexibility.     

Prospective and Concurrent Affective Dynamics in Self-Injurious Thoughts and Behaviors: An Examination in Young Adult Women

Affective dynamics, assessed using ecological momentary assessment (EMA), provide a nuanced understanding of within-person fluctuations of negative affect (NA) and positive affect (PA) in daily life. NA and PA dynamics have been associated with psychopathology and response to psychological treatments. NA and PA dynamics have been rarely studied concurrently in association with self-injurious thoughts and behaviors (SITB), transdiagnostic difficulties encountered regularly in clinical and community settings. Here we present EMA data from a large, diverse sample of young adult women with high rates of SITB to examine NA and PA dynamics (mean intensity, variability, and inertia). Specifically, we considered the prospective associations between past-year suicidal thoughts and past-year nonsuicidal self-injury and affective dynamics, as well as the concurrent associations between affective dynamics, EMA-reported suicidal thoughts, and EMA-reported urges for nonsuicidal self-injury. Results demonstrate that elevated mean NA and NA variability are robustly associated with all types of SITB assessed prospectively or concurrently. Interestingly, these associations were weakest for past-year nonsuicidal self-injurious behaviors, relative to past-year and concurrent suicidal or nonsuicidal self-injurious thoughts. Past-year suicidal thoughts further predicted increased NA inertia. Decreased PA inertia was associated with past-year nonsuicidal self-injury behavior, as well as concurrent EMA suicidal thoughts. We found no associations (prospective or concurrent) between SITB and mean PA intensity or PA variability. These results highlight the importance of understanding affective processes to develop real-world interventions to prevent nonsuicidal self-injury and suicidal behavior in daily life.     

Quitters would not prosper: Examining the relationship between online assessment performance and assessment attrition behavior

Hiring managers are often hesitant to implement online assessments over concerns that higher‐quality candidates are more likely to quit lengthy assessment batteries than lower‐quality candidates. In this paper, we present the results of two studies that collectively challenge this assumption. In Study 1, data from 327,517 job‐seekers spanning eight hiring contexts showed that assessment performance was negatively associated with subsequent assessment attrition behavior. In Study 2, we replicated this pattern of effects in two additional samples comprising 1,844,604 applicants for hourly associate positions, and 18,937 applicants for nursing positions. Collectively, these findings suggest that some degree of attrition may ultimately benefit, rather than harm, organizations using prehire assessments.     

Support for distracted driving laws: An analysis of adolescent drivers from the Traffic Safety Culture Index from 2011 to 2017

IntroductionAdolescent drivers are often the focus of traffic safety legislation as they are at increased risk for crash-related injury and death. However, the degree to which adolescents support distracted driving laws and factors contributing to their support are relatively unknown. Using a large, nationally weighted sample of adolescent drivers in the United States, we assessed if perceived threat from other road users’ engagement in distracted driving, personal engagement in distracted driving behaviors, and the presence of state distracted driving laws was associated with support for distracted driving laws.MethodsThe sample included 3565 adolescents (aged 16–18) who participated in the Traffic Safety Culture Index survey from 2011 to 2017. A modified Poisson regression model with robust errors was fit to the weighted data to examine support for distracted driving laws. Models included age, gender, year, state distracted driving laws, personal engagement in distracted driving behavior, and perceived threat from other road users’ engaging in distracted driving.ResultsApproximately 87% of adolescents supported a law against texting and emailing compared to 66% who supported a universal handheld cellphone law. Support for distracted driving legislation was associated with greater perceived threat of other road users engaging in distracted driving while accounting for personal engagement in distracted driving, state distracted driving laws, and developmental covariates.DiscussionGreater understanding of the factors behind legislative support is needed. Public health interventions focused on effectively translating the risks of cellphone use while driving and effective policy will further improve the traffic safety culture.     

The social dynamics involved in recovery and return to sport following a sport-related concussion: A study of three athlete-teammate-coach triads

An athlete's connection to their team and team members is an important part of their sport experience. However, researchers currently know little about the nature of these social dynamics with respect to concussed athletes. Our study explored athletes' recovery and reintegration into the team environment following a sport-related concussion. We conducted semi-structured interviews with each member of three athlete-teammate-coach triads (N = 9). We analysed the data using thematic narrative analysis and present the results as three stories that focused on each athlete's experience. For Cassie, we found two major plot points in her story: the transition in her role (and shift in identity) from athlete to student assistant coach/team manager and, once recovered, back to an athlete on the team. For Jess, we found that the main plot in her story was “pressure”. Specifically, the interplay between internal (placed on herself) and external (perceived from teammates and coaches) pressures to return to sport. In the third and final story, the main plot point was the tensions that arose from Jaden's preferences for social support and the type of support that his teammates and coaches believed he needed during his recovery. Our results highlight the interplay between athlete's personal and social identities, feelings of pressure to return and readiness, and the challenges of providing the right amount and type of social support. This research contributes to our limited understanding of the social dynamics involved in athletes' return to sport following a concussion.     

EDITORIAL Building bridges with mixed methods research?

Mixed methods refers to the use of both qualitative and quantitative approaches and methods in one study or sequentially in two or more studies. Without a mixed methods approach there is – to our minds ‐ a risk that only part of a phenomenon or experience is being explored. Our own involvement in mixed methods research has grown out of a shared interest in the concept ‘research‐practitioner’. Psychotherapy is a notoriously complex and ever‐developing field, and our growing sense has been that mixed methods research can contribute to a more complete – both broad and deep ‐ sense of knowledge and understanding.     

情感计算技术如何推动犯罪风险评估工具的发展？

摘 要 随着近年来人工智能深度学习技术的发展,情感计算与人格计算技术日渐成熟,在许多实际应用场景中取得了良好的表现,当前人工智能情感计算技术应用于犯罪风险评估领域,能够有效解决目前主流的风险评估工具难以解决的个体内差异性的预测因子评估问题以及被测评参与者因社会赞许性而导致结果失真的问题。本文在详细阐述目前主流评估工具的局限性基础上,详细阐述了以情感计算技术为支撑的动态风险评估工具的设计思路、目前已有的技术方案以及设计细节的理论依据,在此基础上最后提出以人工智能技术为支撑的新型评估工具的未来发展方向。     

多级评分认知诊断模型述评

认知诊断评估旨在探讨个体内部的知识掌握结构,并提供关于学生优缺点的详细诊断信息,以促进个体的全面发展。当前研究者已开发了大量0-1评分的认知诊断模型,但对于多级评分认知诊断模型的研究还比较少。本文对已有的多级评分认知诊断模型进行了归纳,介绍了模型的假设,计量特征以及适用范围,为实际应用者和研究者在多级评分认知诊断模型的比较和选用上提供借鉴和参考。最后,对未来关于多级评分诊断模型的研究方向进行了展望。