Gerontological Counseling Trends in Adultspan Journal: 1999–2019

Using quantitative content analysis, we categorized 76 out of 154 articles (49.35%) published in Adultspan Journal from 1999 to 2019 as focused on gerontological counseling. This study explored publication trends for these articles and compared results with a larger study (Fullen et al., 2019) on publication trends for gerontological counseling across all counseling‐related journals.     

A systematic review of the effectiveness of machine learning for predicting psychosocial outcomes in acquired brain injury: Which algorithms are used and why?

Clinicians working in the field of acquired brain injury (ABI, an injury to the brain sustained after birth) are challenged to develop suitable care pathways for an individual client’s needs. Being able to predict psychosocial outcomes after ABI would enable clinicians and service providers to make advance decisions and better tailor care plans. Machine learning (ML, a predictive method from the field of artificial intelligence) is increasingly used for predicting ABI outcomes. This review aimed to examine the efficacy of using ML to make psychosocial predictions in ABI, evaluate the methodological quality of studies, and understand researchers’ rationale for their choice of ML algorithms. Nine studies were reviewed from five databases, predicting a range of psychosocial outcomes from stroke, traumatic brain injury, and concussion. Eleven types of ML were employed with a total of 75 ML models. Every model was evaluated as having high risk of bias, unable to provide adequate evidence for predictive performance due to poor methodological quality. Overall, there was limited rationale for the choice of ML algorithms and poor evaluation of the methodological limitations by study authors. Considerations for overcoming methodological shortcomings are discussed, along with suggestions for assessing the suitability of data and suitability of ML algorithms for different ABI research questions.     

The Nature of Client Agency Prior to Therapy: A Qualitative Study on Clients’ Narratives

Client agency is considered a crucial contributor to good treatment outcome. Recent studies, however, differ strongly in how they conceptualise and investigate agency. The current study explores the nature of client agency in ten clients’ pre-treatment interviews. Applying Consensual Qualitative Research, we constructed three overarching categories, subdivided into 14 sub-categories capturing both between- and within-person differences in agency before therapy. We found that all participants oscillated between the experience of a lack of grip on problems on the one hand and noticing their involvement in the problem and taking action on the other. These results present a dynamic conceptualisation of client agency. This allows us to ask pertinent questions for both future research and clinical practice.     

Self-Compassion and Need Frustration Moderate the Effects of Upward Appearance Comparisons on Body Image Discrepancies

Abstract

Drawing from diverse theoretical frameworks, we examined predictors of discrepancy between current and ideal body image in a sample of 396 Greek adolescents. The participants completed assessments of the frequency of comparing oneself with someone of perceived better appearance, appearance evaluations, frustration of basic psychological needs, and appearance self-compassion. We found that upward appearance comparisons negatively predicted appearance evaluation, which in turn was a negative predictor of body image discrepancy. Moderated mediation analyses showed that appearance self-compassion buffered, whereas psychological need frustration augmented the negative effects of upward comparisons on appearance evaluation. Our findings contribute to the growing literature on body image discrepancies in adolescence by examining moderating factors that amplify or buffer such discrepancies, hence identifying viable intervention pathways.     

Moral Values Reveal the Causality Implicit in Verb Meaning

Prior work has found that moral values that build and bind groups—that is, the binding values of ingroup loyalty, respect for authority, and preservation of purity—are linked to blaming people who have been harmed. The present research investigated whether people's endorsement of binding values predicts their assignment of the causal locus of harmful events to the victims of the events. We used an implicit causality task from psycholinguistics in which participants read a sentence in the form “SUBJECT verbed OBJECT because…” where male and female proper names occupy the SUBJECT and OBJECT position. The participants were asked to predict the pronoun that follows “because”—the referent to the subject or object—which indicates their intuition about the likely cause of the event. We also collected explicit judgments of causal contributions and measured participants' moral values to investigate the relationship between moral values and the causal interpretation of events. Using two verb sets and two independent replications (N = 459, 249, 788), we found that greater endorsement of binding values was associated with a higher likelihood of selecting the object as the cause for harmful events in the implicit causality task, a result consistent with, and supportive of, previous moral psychological work on victim blaming. Endorsement of binding values also predicted explicit causal attributions to victims. Overall, these findings indicate that moral values that support the group rather than the individual reliably predict that people shift the causal locus of harmful events to those affected by the harms.     

A Process Model of Causal Reasoning

How do we make causal judgments? Many studies have demonstrated that people are capable causal reasoners, achieving success on tasks from reasoning to categorization to interventions. However, less is known about the mental processes used to achieve such sophisticated judgments. We propose a new process model—the mutation sampler—that models causal judgments as based on a sample of possible states of the causal system generated using the Metropolis–Hastings sampling algorithm. Across a diverse array of tasks and conditions encompassing over 1,700 participants, we found that our model provided a consistently closer fit to participant judgments than standard causal graphical models. In particular, we found that the biases introduced by mutation sampling accounted for people's consistent, predictable errors that the normative model by definition could not. Moreover, using a novel experimental methodology, we found that those biases appeared in the samples that participants explicitly judged to be representative of a causal system. We conclude by advocating sampling methods as plausible process-level accounts of the computations specified by the causal graphical model framework and highlight opportunities for future research to identify not just what reasoners compute when drawing causal inferences, but also how they compute it.     

Counseling Military Populations: A Content Analysis of Counseling Journals From 1998 to 2018

Mental health scholarship of military populations is largely guided by researchers in psychiatry and psychology. Recent advocacy efforts have created increased opportunities for professional counselors to serve military clients, but the research within the profession has yet to be explored. A content analysis of 23 professional counseling journals from June 1998 to June 2018 was conducted to determine military population research trends. Findings indicated that counselors are researching topics similar to those of other mental health fields, such as posttraumatic stress, but are contributing to those topics conceptually rather than empirically. Topical areas in which counselors do produce more empirical studies include career counseling, and these studies relied on college student veteran populations. Suggestions for incorporating the philosophical principles of counseling into future research are provided to inform the trajectory of military scholarship in the profession.