Prepared to fake? The relationship between applicants’ job interview preparation and faking

Multiple frameworks and models postulate an effect of job interview preparation on faking. Two studies were conducted to examine if applicants’ interview preparation is correlated with higher faking. Besides analyzing the general extent of preparation, we also distinguished between different preparation categories. In Study 1 (N = 237), a presented preparation video led to higher intentions on image protection but did not increase overall faking intentions. Study 2 (N = 206) focused on past preparation and impression management (IM). The total time spent on preparation was positively correlated with faking. Applicants’ preparation via online videos and professional interview preparation was correlated with higher deceptive and honest IM. Preparation via online videos was additionally correlated with a higher perceived interview difficulty.     

Inhibitory control and set shifting describe different pathways from behavioral inhibition to socially anxious behavior

Individuals with a behaviorally inhibited (BI) temperament are more likely to develop social anxiety. However, the mechanisms by which socially anxious behavior emerges from BI are unclear. Variation in different forms of top‐down control, specifically executive functions (EF), may play distinct roles and characterize differential pathways to social anxiety. Here 291 children were assessed for BI in toddlerhood (ages 2 and 3), parent‐reported inhibitory control and set shifting during middle childhood (age 7), and multidimensional assessment of socially anxious behavior completed during late childhood and early adolescence (ages 9 and 12). Structural equation modeling revealed that early variation in BI predicted the development of socially anxious behavior through either higher levels of parent‐reported inhibitory control or lower levels of parent‐reported set shifting. These data reinforce the notion that top‐down control does not uniformly influence relations between temperament and socially anxious behavior. These data suggest novel approaches to thinking about the role of EFs and social anxiety outcomes as children approach adolescence.     

Effects of containment and closure policies on controlling the COVID‐19 pandemic in East Asia

Growing efforts have been made to pool coronavirus data and control measures from countries and regions to compare the effectiveness of government policies. We examine whether these strategies can explain East Asia’s effective control of the COVID‐19 pandemic based on time‐series data with cross‐correlations between the Stringency Index and number of confirmed cases during the early period of outbreaks. We suggest that multidisciplinary empirical research in healthcare and social sciences, personality, and social psychology is needed for a clear understanding of how cultural values, social norms, and individual predispositions interact with policy to affect life‐saving behavioural changes in different societies.     

EDITORIAL Building bridges with mixed methods research?

Mixed methods refers to the use of both qualitative and quantitative approaches and methods in one study or sequentially in two or more studies. Without a mixed methods approach there is – to our minds ‐ a risk that only part of a phenomenon or experience is being explored. Our own involvement in mixed methods research has grown out of a shared interest in the concept ‘research‐practitioner’. Psychotherapy is a notoriously complex and ever‐developing field, and our growing sense has been that mixed methods research can contribute to a more complete – both broad and deep ‐ sense of knowledge and understanding.     

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.     

Is future self-relevance necessary to increase saving for retirement? A replication study

Insufficient saving for retirement is one consequence of excessive discounting of the future but attempts to mitigate it often involve costly or time-intensive personalized interventions. Marques, Mariano, Lima, and Abrams, by contrast, found that using a generic Future Time Perspective questionnaire to increase future “self-relevance” was an effective method to increase money allocation to retirement when the salience of future aging was also higher. Originally conducted in Portugal, the present study aimed to replicate Marques et al’s findings in the UK context. In the present study (n = 219), participants were shown a website advertising a financial product. The results support Marques and colleagues’ assertion that, alone, a website priming future aging was insufficient to increase retirement savings in a money allocation task. However, in contrast to Marques et al’s original findings, we find no evidence that future self-relevance moderates the effect such that priming future aging becomes effective when individuals have higher future self-relevance. Instead, we find that aging primes are ineffective at increasing retirement saving regardless of whether individuals are high or low in future self-relevance. Possible explanations for this discrepancy in findings, including methodological and cultural differences, are explored as well as directions for future research.