Effectiveness of an ACT‐based rehabilitation program for the treatment of chronic fatigue: Results from a 12‐months longitudinal study

Acceptance and Commitment Therapy (ACT) is potentially effective for treating chronic fatigue. Given the paucity of studies on this topic, we aimed to assess long‐term trajectories of primary (fatigue, quality of life and functional abilities) and secondary outcomes (anxious and depressive symptoms) of an ACT‐based rehabilitation program for patients with chronic fatigue. Further, we examined if changes in potential process variables (psychological inflexibility, metacognitive beliefs, and cognitive and behavioral responses to symptoms) during ACT predicted change in all outcomes across follow‐up. One‐hundred ninety‐five workers on sick leave (mean age: 43.61 ± 9.33 years; 80.5% females) with a diagnosis of chronic fatigue were enrolled in a manualized, 3.5‐week intensive return‐to‐work rehabilitation program based on ACT. All completed a battery of questionnaires at pre‐, post‐treatment, 6 and 12 months follow‐up. We found significant longitudinal changes in most primary and secondary outcomes from pre‐ up to 12 months follow‐up. All process variables significantly decreased from pre‐ up to 12 months follow‐up, and pre‐to‐post changes in fear avoidance beliefs were most often associated with a greater change in outcomes across follow‐up. Depressive symptomatology showed a similar trajectory of change to fatigue, meaning that scores were correlated at each time point and tended to converge over time. This suggests that both symptoms influence each other substantially over a year following the treatment. Concluding, results lend support to the effectiveness of an ACT‐based rehabilitation program for patients with chronic fatigue and provide preliminary evidence for the role of process variables and depressive symptomatology on subsequent change in outcomes.     

Mediation,moderation, and context: Understanding complex relations among cognition,affect, and health behaviour

Objective: Researchers have historically treated cognition and affect as separate constructs in motivating health behaviour. We present a framework and empirical evidence for complex relations between cognition and affect in predicting health behaviour.

Main Outcome, Design and Results: First, affect and cognition can mediate each other’s relation to health behaviour. Second, affect and cognition can moderate the other’s impact. Third, context can change the interplay of affect and cognition. Fourth, affect and cognition may be indelibly fused in some psychological constructs (e.g. worry, anticipated regret and reactance). These four propositions in our framework are not mutually exclusive.

Conclusion: Examination of the types of complex relations described here can benefit theory development, empirical testing of theories and intervention design. Doing so will advance the understanding of mechanisms involved in regulation of health behaviours and the effectiveness of interventions to change health behaviours.     

Regression among factor scores

Structural equation models with latent variables are sometimes estimated using an intuitive three-step approach, here denoted factor score regression. Consider a structural equation model composed of an explanatory latent variable and a response latent variable related by a structural parameter of scientific interest. In this simple example estimation of the structural parameter proceeds as follows: First, common factor models areseparately estimated for each latent variable. Second, factor scores areseparately assigned to each latent variable, based on the estimates. Third, ordinary linear regression analysis is performed among the factor scores producing an estimate for the structural parameter. We investigate the asymptotic and finite sample performance of different factor score regression methods for structural equation models with latent variables. It is demonstrated that the conventional approach to factor score regression performs very badly. Revised factor score regression, using Regression factor scores for the explanatory latent variables and Bartlett scores for the response latent variables, produces consistent estimators for all parameters.     

国内外职业承诺研究述评

从职业与事业的区别入手,对国内外职业承诺的概念、常用的几种职业承诺量表、职业承诺形成过程以及相关模型、前因与后果变量等方面的已有研究进行回顾和分析。研究发现,职业承诺与一些重要的效果变量有比较显著的关系,如职业满意度、工作投入、工作绩效等。文章最后指出了目前存在的问题及今后努力研究的方向,如现有的职业承诺概念比较凌乱,测量工具虽然多数是参照国外的重新编制,但其适用范围比较狭窄,因此需要对职业承诺的概念进行重新整合,职业承诺量表也需要对其在信效度指标上进行深入探索     

Travel behavior as a driver of attitude: Car use and car pride in U.S. cities

Individuals attribute social status and personal image to owning and using a car (‘car pride’), which may interact with their travel behavior in complex ways. This study explores the multi-directional relations among car pride, car ownership, and car use for a sample of 1236 adult commuters in New York City, NY and Houston, TX. Applying multivariate structural equation modeling and incorporating instrumental variables, we find evidence of a feedback loop among car pride, car ownership, and car use. Our results suggest that an individual with higher car pride is more likely to own a vehicle, and, enabled with this ownership, use it more frequently. And individuals who use their car more frequently are likely to feel more pride in owning and using their vehicle.This exploration of causal multi-directionality in transportation attitude-behavior relations has important implications for behavioral research, model development, and policy interventions. For researchers, potential bidirectionality must be anticipated from the outset of research design and accounted for appropriately in modeling to address underlying endogeneity. For policymakers, our results suggest that there are multiple intervention points within the reinforcing cycle of attitudes and car consumption. Policies could directly target car ownership and use or could consider influencing behavior through attitude change.     

Demands and capacities versus demands and performance

This article examines the proposed relabeling of “capacities” as “performance” in the Demands and Capacities Model of stuttering in terms of four issues involving the model's demands component, theoretical versatility, genetic potential, and current clinical uses. Although the proposed changes should resolve the measurement issues of concern, it is suggested that this change may not be of sufficient value or significance for a Demands and Performance Model to supplant the Demands and Capacities Model.     

Notes on selective influence, probabilistic causality, and probabilistic dimensionality

The paper provides conceptual clarifications for the issues related to the dependence of jointly distributed systems of random entities on external factors. This includes the theory of selective influence as proposed in Dzhafarov [(2003a). Selective influence through conditional independence. Psychometrika, 68, 7-26] and generalized versions of the notions of probabilistic causality [Suppes, P., & Zanotti, M. (1981). When are probabilistic explanations possible? Synthese, 48, 191-199] and dimensionality in the latent variable models [Levine, M. V. (2003). Dimension in latent variable models. Journal of Mathematical Psychology, 47, 450-466]. One of the basic observations is that any system of random entities whose joint distribution depends on a factor set can be represented by functions of two arguments: a single factor-independent source of randomness and the factor set itself. In the case of random variables (i.e., real-valued random entities endowed with Borel sigma-algebras) the single source of randomness can be chosen to be any random variable with a continuous distribution (e.g., uniformly distributed between 0 and 1).     

组织承诺研究综述

本文通过对组织承诺的文献分析,讨论了组织承诺概念的演变和其结构的发展,并对组织承诺的相关因素进行了评述。分析了组织承诺形成的影响变量和其效标变量,对今后的发展方向进行了展望。     

On the explaining‐away phenomenon in multivariate latent variable models

Many probabilistic models for psychological and educational measurements contain latent variables. Well‐known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the ‘explaining‐away’ phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well‐known latent variable models by using both theoretical and real data examples.     

Bayesian Diagnostics of Hidden Markov Structural Equation Models with Missing Data

Cocaine is a type of drug that functions to increase the availability of the neurotransmitter dopamine in the brain. However, cocaine dependence or abuse is highly related to an increased risk of psychiatric disorders and deficits in cognitive performance, attention, and decision-making abilities. Given the chronic and persistent features of drug addiction, the progression of abstaining from cocaine often evolves across several states, such as addiction to, moderate dependence on, and swearing off cocaine. Hidden Markov models (HMMs) are well suited to the characterization of longitudinal data in terms of a set of unobservable states, and have increasingly been used to uncover the dynamic heterogeneity in progressive diseases or activities. However, the existence of outliers or influential points may misidentify the hidden states and distort the associated inference. In this study, we develop a Bayesian local influence procedure for HMMs with latent variables in the presence of missing data. The proposed model enables us to investigate the dynamic heterogeneity of multivariate longitudinal data, reveal how the interrelationships among latent variables change from one state to another, and simultaneously conduct statistical diagnosis for the given data, model assumptions, and prior inputs. We apply the proposed procedure to analyze a dataset collected by the UCLA center for advancing longitudinal drug abuse research. Several outliers or influential points that seriously influence estimation results are identified and removed. The proposed procedure also discovers the effects of treatment and individuals’ psychological problems on cocaine use behavior and delineates their dynamic changes across the cocaine-addiction states.