Fairness at the collective level: a meta-analytic examination of the consequences and boundary conditions of organizational justice climate

This article uses meta-analytic methods (k = 38) to examine the relationship between organizational justice climate and unit-level effectiveness. Overall, our results suggest that the relationship between justice and effectiveness is significant (ρ = .40) when both constructs are construed at the collective level. Our results also indicate that distributive justice climate was most strongly linked with unit-level performance (e.g., productivity, customer satisfaction), whereas interactional justice was most strongly related to unit-level processes (e.g., organizational citizenship behavior, cohesion). We also show that a number of factors moderate this relationship, including justice climate strength, the level of referent in the justice measure, the hierarchical level of the unit, and how criteria are classified. We elaborate on these findings and attempt to provide a clearer direction for future research in this area.     

A randomized wait-list controlled analysis of the implementation integrity of team-initiated problem solving processes

Members of Positive Behavior Interventions and Supports (PBIS) teams from 34 elementary schools participated in a Team-Initiated Problem Solving (TIPS) Workshop and follow-up technical assistance. Within the context of a randomized wait-list controlled trial, team members who were the first recipients of the TIPS intervention demonstrated greater implementation integrity in using the problem-solving processes during their team meetings than did members of PBIS Teams in the Wait-List Control group. The success of TIPS at improving implementation integrity of the problem-solving processes is encouraging and suggests the value of conducting additional research focused on determining whether there is a functional relation between use of these problem-solving processes and actual resolution of targeted student academic and social problems.     

Practical Implementation Science: Developing and Piloting the Quality Implementation Tool

According to the Interactive Systems Framework for Dissemination and Implementation, implementation is a major mechanism and concern in bridging research and practice. The growing number of implementation frameworks need to be synthesized and translated so that the science and practice of quality implementation can be furthered. In this article, we: (1) use the synthesis of frameworks developed by Meyers et al. (Am J Commun Psychol, 2012) and translate the results into a practical implementation science tool to use for improving quality of implementation (i.e., the Quality Implementation Tool; QIT), and (2) present some of the benefits and limitations of the tool by describing how the QIT was implemented in two different pilot projects. We discuss how the QIT can be used to guide collaborative planning, monitoring, and evaluation of how an innovation is implemented.     

Developmental pattern of digit span in Spanish population

This study examined in a Spanish population the developmental pattern of digit span, as an index of one of the components of Baddeley's working memory--the phonological loop. A verbal digit span was administered to 570 participants ranging from 5 to 17 years old. The results indicated that the digit memory span increases until age 17 as opposed to Anglo-Saxon data--where it is established that this span reaches a peak by age 15. Additionally, these results were compared to the performance in the same task of healthy elderly, Alzheimer disease patients, and Frontotemporal dementia patients, examined in a previous study. The analysis shows that the phonological loop is affected by age and not so much by dementias.     

Exploring programmatic moderators of the effectiveness of marriage and relationship education programs: a meta-analytic study

This study uses meta-analytic methods to explore programmatic moderators or common factors of the effectiveness of marriage and relationship education (MRE) programs. We coded 148 evaluation reports for potential programmatic factors that were associated with stronger intervention effects, although the range of factors we could code was limited by the lack of details in the reports. Overall, we found a positive effect for program dosage: moderate-dosage programs (9-20 contact hours) were associated with stronger effects compared to low-dosage programs (1-8 contact hours). A programmatic emphasis on communication skills was associated with stronger effects on couple communication outcomes, but this difference did not reach statistical significance for the relationship quality/satisfaction outcome. There was no evidence that institutionalized MRE programs (formal manuals, ongoing presence, formal instructor training, multiple evaluations) were associated with stronger effects. Similarly, there was little evidence of differences in program setting (university/laboratory vs. religious). We discuss possible explanations for these findings and implications for program design and evaluation.     

Minimizing sleep deprivation effects in healthy adults by differential outcomes

Sleep deprivation reduces vigilance or arousal levels, affecting the efficiency of certain cognitive functions such as learning and memory. Here we assessed whether the differential outcomes procedure (DOP), a learning procedure that has proved useful to ameliorate episodic memory deficits, can also improve memory performance in sleep-deprived participants. Photographs were presented as sample faces. A probe face was then presented for recognition after either short or long delays. In the differential outcomes condition a unique reinforcer followed correct responses. In the non-differential outcomes condition reinforcers were provided in a random manner. The results indicated that the DOP prevented the recognition memory to decrement during the long delay in the control group, replicating previous findings. The sleep-deprived group showed DOP benefits mainly with the short delay, when working memory could be affected by low arousal. These findings confirm that the DOP can overcome impaired recognition memory due to sleep deprivation conditions.     

Neurogenesis interferes with the retrieval of remote memories: Forgetting in neurocomputational terms

In contrast to models and theories that relate adult neurogenesis with the processes of learning and memory, almost no solid hypotheses have been formulated that involve a possible neurocomputational influence of adult neurogenesis on forgetting. Based on data from a previous study that implemented a simple but complete model of the main hippocampal circuitry (Weisz & Argibay, 2009), we now test this model under different situations to better study the case of remote memories. The results of this work show that following neurogenesis, the new, ongoing memories in the hippocampus are better retained than when no neurogenesis occurs at all, while the older memories are affected (to a lesser extent) by a special type of interference that is different from interference that occurs with an increasing number of memories per se. This work adds a new point of analysis in support of the interference view that might lead to the forgetting of memories in the hippocampus as they are transferred to neocortex for long-term storage, consistent with the Complementary Learning Systems models of system-level consolidation. Attention should be directed to the specific causes of interference; the results of this work signal a type of distortion of remote memories that is produced by the birth and the growth of new processing units, which results in a subtly impoverished retrieval as new neurons become active. The proposals of this model fit well with some empirical findings that are related to the issue. In the future, as new evidence emerges, we believe that this biological process, which is largely related to learning and memory, will also help to shape our ideas about normal forgetting and its possible contributions to system consolidation.     

A generalized least squares regression approach for computing effect sizes in single-case research: application examples

A new method for deriving effect sizes from single-case designs is proposed. The strategy is applicable to small-sample time-series data with autoregressive errors. The method uses Generalized Least Squares (GLS) to model the autocorrelation of the data and estimate regression parameters to produce an effect size that represents the magnitude of treatment effect from baseline to treatment phases in standard deviation units. In this paper, the method is applied to two published examples using common single case designs (i.e., withdrawal and multiple-baseline). The results from these studies are described, and the method is compared to ten desirable criteria for single-case effect sizes. Based on the results of this application, we conclude with observations about the use of GLS as a support to visual analysis, provide recommendations for future research, and describe implications for practice.