Redefining unforgiveness: Exploring victims’ experiences in the wake of unforgiven interpersonal transgressions

This study explored victims’ experiences in the aftermath of unforgiven offenses. Semi-structured interviews with 13 individuals discussing two unforgiven offenses revealed considerable variability in the experiences of unforgiveness, suggesting that unforgiveness may be more multifaceted than previously believed. In addition to the negative emotions and rumination previously posited to characterize unforgiveness, novel themes emerged describing unforgiving cognitions (e.g., the offense is unforgiveable) and construals of the offender. Participants varied along each dimension, resulting in a range of outcomes (e.g., forgiveness, lingering personal distress, finding peace without forgiving). Implications for conceptualizing unforgiveness and counseling those who struggle with unforgiven offenses are discussed.     

A Review of Best Practice Recommendations for Text Analysis in R (and a User-Friendly App)

In recent decades, the amount of text available for organizational science research has grown tremendously. Despite the availability of text and advances in text analysis methods, many of these techniques remain largely segmented by discipline. Moreover, there is an increasing number of open-source tools (R, Python) for text analysis, yet these tools are not easily taken advantage of by social science researchers who likely have limited programming knowledge and exposure to computational methods. In this article, we compare quantitative and qualitative text analysis methods used across social sciences. We describe basic terminology and the overlooked, but critically important, steps in pre-processing raw text (e.g., selection of stop words; stemming). Next, we provide an exploratory analysis of open-ended responses from a prototypical survey dataset using topic modeling with R. We provide a list of best practice recommendations for text analysis focused on (1) hypothesis and question formation, (2) design and data collection, (3) data pre-processing, and (4) topic modeling. We also discuss the creation of scale scores for more traditional correlation and regression analyses. All the data are available in an online repository for the interested reader to practice with, along with a reference list for additional reading, an R markdown file, and an open source interactive topic model tool (topicApp; see https://github.com/wesslen/topicApp, https://github.com/wesslen/text-analysis-org-science, https://dataverse.unc.edu/dataset.xhtml?persistentId=doi:10.15139/S3/R4W7ZS).     

Letting Go: Conceptualizing Intervention De‐implementation in Public Health and Social Service Settings

The discontinuation of interventions that should be stopped, or de‐implementation, has emerged as a novel line of inquiry within dissemination and implementation science. As this area grows in human services research, like public health and social work, theory is needed to help guide scientific endeavors. Given the infancy of de‐implementation, this conceptual narrative provides a definition and criteria for determining if an intervention should be de‐implemented. We identify three criteria for identifying interventions appropriate for de‐implementation: (a) interventions that are not effective or harmful, (b) interventions that are not the most effective or efficient to provide, and (c) interventions that are no longer necessary. Detailed, well‐documented examples illustrate each of the criteria. We describe de‐implementation frameworks, but also demonstrate how other existing implementation frameworks might be applied to de‐implementation research as a supplement. Finally, we conclude with a discussion of de‐implementation in the context of other stages of implementation, like sustainability and adoption; next steps for de‐implementation research, especially identifying interventions appropriate for de‐implementation in a systematic manner; and highlight special ethical considerations to advance the field of de‐implementation research.     

State‐Trace Analysis: Dissociable Processes in a Connectionist Network?

Some argue the common practice of inferring multiple processes or systems from a dissociation is flawed (Dunn, 2003). One proposed solution is state‐trace analysis (Bamber, 1979), which involves plotting, across two or more conditions of interest, performance measured by either two dependent variables, or two conditions of the same dependent measure. The resulting analysis is considered to provide evidence that either (a) a single process underlies performance (one function is produced) or (b) there is evidence for more than one process (more than one function is produced). This article reports simulations using the simple recurrent network (SRN; Elman, 1990) in which changes to the learning rate produced state‐trace plots with multiple functions. We also report simulations using a single‐layer error‐correcting network that generate plots with a single function. We argue that the presence of different functions on a state‐trace plot does not necessarily support a dual‐system account, at least as typically defined (e.g. two separate autonomous systems competing to control responding); it can also indicate variation in a single parameter within theories generally considered to be single‐system accounts.     

Choosing Your Words and Pictures Wisely: When Do Individuation Instructions Reduce the Cross‐Race Effect?

Recognition accuracy for faces of an individual's own race typically exceeds recognition accuracy for other‐race faces. The categorization–individuation model (Hugenberg, Young, Bernstein, & Sacco, 2010) attributes this cross‐race effect to motivation to encode distinctive features of own‐race faces but category defining features for other‐race faces. Two experiments using different stimuli tested hypotheses generated from this model with both Black and White participants. For White participants, instructions to individuate reduced the cross‐race effect in both studies but did not eliminate it in Study 1. Black participants did not exhibit the cross‐race effect in either study, but individuation instructions improved both their same‐race and other‐race sensitivity. The present quality of interracial contact moderated the relationship between instructions and other‐race sensitivity for both Black and White participants in Study 1 but not in Study 2. Overall, results provide mixed support for this social categorization model. Copyright © 2015 John Wiley & Sons, Ltd.     

Suicide in bipolar disorder: Risks and management

Bipolar disorders are prevalent, often severe, and disabling illnesses with elevated lethality largely due to suicide. Suicide rates average approximately 1% annually, or perhaps 60 times higher than the international population rate of 0.015% annually. Suicidal acts typically occur early in bipolar disorders and in association with severe depressive or mixed states. The high lethality of suicidal acts in bipolar disorders is suggested by a much lower ratio of attempts:suicide (approximately 3:1) than in the general population (approximately 30:1). Risk factors can help to identify patients at increased suicidal risk, but ongoing clinical assessment is essential to limit risk. Empirical short-term interventions to manage acute suicidal risk include close clinical supervision, rapid hospitalization, and electroconvulsive therapy. Remarkably, however, evidence of the long-term effectiveness of most treatments against suicidal behavior is rare. A notable exception is lithium prophylaxis, which is associated with consistent evidence of major (approximately 80%), sustained relative reductions of risk of suicides and attempts, and lower lethality (increased attempts:suicide ratio). Such benefits are unproved for other treatments commonly used to treat bipolar disorder patients, including anticonvulsants, antipsychotics, antidepressants, and psychosocial interventions. Applying available knowledge systematically, with close and sustained clinical supervision, can enhance management of suicidal risk in bipolar disorders patients.     

"In the storminess": multi-disciplinary approaches to scriptural images representing ethical challenges in the pastor-congregant relationship

In this qualitative study the authors examine the Scriptural images that 10 Lutheran pastors employed in describing the ethical challenges in the pastor-congregant relationship. The analysis of Scriptural images is part of a larger study on pastors' experiences of a mandatory workshop, "Crossing the Boundaries (CTB),"which is required of Evangelical Lutheran Church in Canada (ELCIC) seminarians. The pastors' images were analyzed from the four perspectives of depth psychology, theology, social ethics, and sociology. In commenting on tensions in the pastors' Scriptural images the authors note commonalities among the four theoretical perspectives and discuss implications for practice and future research.