Therapeutic processes in group therapy: Intersections between general change mechanisms and motivational stages of change from patient perspective

Intersections between Grawe’s General Psychotherapy and Prochaska’s Transtheoretical Model were investigated in group therapy in a longitudinal design. It was assumed that general change mechanisms have an impact on patients’ stages of change. Specifically, the main hypotheses were that experiential change mechanisms (ECM; clarification of meaning, problem actuation, emotional bond and group cohesion) should be especially relevant for early stages of change (precontemplation and contemplation), whereas behavioral change mechanisms (BCM; resource activation, mastery/coping and task and goals) should be especially relevant for late stages of change (action and maintenance). Therefore, 140 outpatients attending different types of group therapy, with a typical duration of 8 sessions, were investigated. Patients completed the Form for the Evaluation of Therapeutic Processes in Group Therapy (FEPiG), the University of Rhode Island Change Assessment, short version (URICA-S) and several symptomatology measures (BDI-II, BSCL and IIP-32) at two measuring times. Intersections were analysed through correlational analyses, cross-lagged panels and a path-analytic model, supporting the hypotheses. Specifically, results suggested that experiencing ECM at t1 predicted higher levels of reported contemplation at t2. Patients experiencing higher levels of BCM at t1 reported higher levels of action at t2. Clinical implications of the results are discussed.     

Participants' perceptions of smartphone travel surveys

Smartphone travel surveys are becoming of central importance in collecting detailed, accurate data of people’s travel activities. As with their conventional survey counterparts, the quality of data collected through these surveys is adversely affected by participants’ non-response and resulting biases. However, little is known about the factors affecting people’s perceptions and intentions to continue participating in such surveys. Although literature has investigated the associations between individuals’ socio-demographic attributes and their likelihood of survey participation, the impact of their subjective perceptions and attitudes on their survey participation intentions and behaviour is underexplored. Hence, through a model of participants’ perceptions of smartphone travel survey applications (survey apps), this study aims to reveal such impacts and how they affect the participants’ intentions to continue participating in these surveys. In this study, a survey is designed and used to collect data in a smartphone travel survey before the participants are asked about their personal perceptions and attitudes. Partial least squares path modelling (PLS-PM) is applied to analyse the data, as it allows simultaneous estimation of the relationships between multiple latent constructs as well as the indicators of each construct. The results showed a significant, positive impact of the perceived “ease of use” and “usefulness” of the survey app as the technological medium of data collection on the participants’ “satisfaction” and “intention” to continue participating in the corresponding survey. The study also found that participants’ perceived “risk” associated with privacy concerns did not have any significant impact on their intention to continue participating in the survey.     

Modelling the human lane-change execution behaviour through Multilayer Perceptrons and Convolutional Neural Networks

Driving is a highly complex task that involves the execution of multiple cognitive tasks belonging to different levels of abstraction. Traffic emerges from the interaction of a big number of agents implementing those behaviours, but until recent years, modelling it by the interaction of these agents in the so called micro-simulators was a nearly impossible task as their number grows. However, with the growing computing power it is possible to model increasingly large quantities of individual vehicles according to their individual behaviours. These models are usually composed of two sub-models for two well-defined tasks: car-following and lane-change. In the case of lane-change the literature proposes many different models, but few of them use Computational Intelligence (CI) techniques, and much less use personalization for reaching individual granularity. This study explores one of the two aspects of the lane-change called lane-change acceptance, where the driver performs or not a lane-change given his intention and the vehicle environment. We demonstrate how the lane-change acceptance of a specific driver can be learned from his lane change intention and surrounding environment in an urban scenario using CI techniques such as feed-forward Artificial Neural Network (ANN). We work with Multilayer Perceptron (MLP) and Convolutional Neural Networks (CNN) architectures. How they perform one against the other and how the different topologies affect both to the generalization of the problem and the learning process are studied.     

Beyond Consent: Building Trusting Relationships With Diverse Populations in Precision Medicine Research

With the growth of precision medicine research on health data and biospecimens, research institutions will need to build and maintain long-term, trusting relationships with patient-participants. While trust is important for all research relationships, the longitudinal nature of precision medicine research raises particular challenges for facilitating trust when the specifics of future studies are unknown. Based on focus groups with racially and ethnically diverse patients, we describe several factors that influence patient trust and potential institutional approaches to building trustworthiness. Drawing on these findings, we suggest several considerations for research institutions seeking to cultivate long-term, trusting relationships with patients: (1) Address the role of history and experience on trust, (2) engage concerns about potential group harm, (3) address cultural values and communication barriers, and (4) integrate patient values and expectations into oversight and governance structures.     

The life tasks model: Enhancing psychological and spiritual growth in the aged

ABSTRACT

The life tasks model is an active, mutual, and potentially universal approach to the spiritual care of the aged. A life task is a responsibility, once undertaken, that lasts a lifetime. Three tasks are identified. Task 1 is the discovery of hidden learning. The process of discovery draws on implicit learning that comes into awareness. This leads to task 2, testing in which learning brought into awareness is tested by other life experiences. The final task is task 3, integration, in which a more aware and cohesive self is formed. Ideally, this leads to service or vocation. Progress on the life tasks is illustrated by responses in a qualitative study of older adults. Although this model can be applied to self-growth and ministry to all ages, it is well suited to the care of the aged.     

Meta-analysis of the effects of cognitive-behavioral therapy on the core eating disorder maintaining mechanisms: implications for mechanisms of therapeutic change

The original and enhanced cognitive model of eating disorders proposes that cognitive-behavioral therapy (CBT) "works" through modifying dietary restraint and dysfunctional attitudes towards shape and weight. However, evidence supporting the validity of this model is limited. This meta-analysis examined whether CBT can effectively modify these proposed maintaining mechanisms. Randomized controlled trials that compared CBT to control conditions or non-CBT interventions, and reported dietary restraint and shape and weight concern outcomes were searched. Twenty-nine trials were included. CBT was superior to control conditions in reducing shape (g=0.53) and weight (g=0.63) concerns, and dietary restraint (g=0.36). These effects occurred across all diagnoses and treatment formats. Improvements in shape and weight concerns and restraint were also greater in CBT than non-CBT interventions (g's=0.25, 0.24, 0.31, respectively) at post-treatment and follow-up. The magnitude of improvement in binge/purge symptoms was related to the magnitude of improvement in these maintaining mechanisms. Findings demonstrate that CBT has a specific effect in targeting the eating disorder maintaining mechanisms, and offers support to the underlying cognitive model. If changes in these variables during treatment are shown to be causal mechanisms, then these findings show that CBT, relative to non-CBT interventions, is better able to modify these mechanisms.     

等级反应多水平评分者漂移模型的构建

对于评定耗时较长的测验来说,时间因素对评分精确性的影响不容忽视,因此,评分者漂移方面的研究备受关注。研究基于康春花,孙小坚和曾平飞(2016)提出的等级反应多水平侧面模型建构出可用于检测评分者漂移的等级反应多水平评分者漂移模型,并通过模拟研究对模型性能进行验证。结果表明：模型能够精确估计项目和能力参数;且与固定效应模型相比,评分者随机效应模型能更有效地检测出评分者漂移效应,随机效应模型的有效性和稳定性更佳。     

佛教五蕴系统——一种信息加工模型

作为佛教基础教义的“五蕴”是对心理机能尤其是认知过程的高度概括——人类信息加工包括色蕴、受蕴、想蕴、行蕴和识蕴五大机能系统。色蕴对感官信息进行初级加工;受蕴进行信息的情绪编码;随后在想蕴阶段进行高级整合,完成信息的概念语言表征;行蕴则为信息加工提供能量及方向导控;识蕴负责信息储存、监控调节及信息输出,最终形成完整的认知判断。佛教五蕴提供了一种信息加工的新模型。     

改变因症就诊的医疗模式搞好慢性呼吸疾病的防控

本文简单介绍了各种慢性呼吸疾病的特点、重要性、病因和发病机理,重点阐述认真搞好三级预防是有效防控慢性呼吸疾病的基础,而目前我国慢性呼吸疾病医疗服务模式是因症就诊,这种医疗服务模式不利于慢性呼吸疾病的管理和控制,必须尽快改变。