Television distraction and the performance of introverts and extroverts

An experiment was run to test the effect on reading comprehension of distraction by a television programme, which was presented while reading took place. Respondents, classified in terms of extroversion or introversion, carried out two reading comprehension tests in silence and in the presence of a television drama programme. As predicted, extroverts and introverts both performed better in silence, but there was a significant interaction that showed that extroverts performed better than introverts in the presence of television distraction. The findings are discussed in relation to previous research on this subject.     

Detection of a Cry for Help on the MMPI-2: an analog investigation

We compared Minnesota Multiphasic Personality Inventory (MMPI-2) results from 2 groups of mildly to moderately disturbed psychiatric outpatients (N=60) answering under either Standard or Cry for Help instructions. Results from previously completed intake MMPI-2 protocols were obtained for each participant. The two groups were comparable on intake MMPI-2 variables and demographic characteristics. Analysis of feedback data from the second, experimental observation indicated that the two groups had equivalent self-estimates of understanding of their role and success in simulating their role. Significant differences were found between the two groups on their experimental MMPI-2 protocols. The Cry for Help group had significantly higher scores on F, F-K, Fb, Ds2, and Fp scales as well as significantly lower scorns on the K scale. The Cry for Help group also had significantly higher scores on all clinical scales with the exception of 5, which was not tested. Cutting scores derived by Rogers, Sewell, and Ustad (1995) for the detection of a Cry for Help in outpatients were cross-validated with fairly positive results. Although these results are promising, particularly in light of the shrinkage expected on cross-validation, further research is needed in this area.     

Internet-Based Acceptance and Commitment Therapy: A Transdiagnostic Systematic Review and Meta-Analysis for Mental Health Outcomes

Internet-based acceptance and commitment therapy (iACT) primarily targets the process of psychological flexibility. Its accessibility and low-intensity delivery are applicable across different treatment and prevention scenarios. This transdiagnostic meta-analysis reviews the effectiveness of iACT on anxiety, depression, quality of life, and psychological flexibility across individuals with different psychological and somatic conditions/complaints, or undiagnosed complaints. Seven databases were searched for randomized controlled trials that reported on anxiety, depression, quality of life, and psychological flexibility outcomes from iACT in any adult population. Engagement with iACT was summarized and methodological and population-related variables were investigated as potential moderators of effectiveness. Across 25 studies, small pooled effects were found for all outcomes at post-assessment and maintained at follow-up time-points. Interventions with therapist guidance demonstrated greater effectiveness in improving depression and psychological flexibility outcomes compared to nonguided iACT, and populations defined by a psychological condition or symptoms (e.g., depressed samples) demonstrated greater improvements in anxiety compared to nonclinical or somatic populations (e.g., chronic pain samples or students). Participants completed on average 75.77% of iACT treatments. While we found iACT to be effective in improving and maintaining mental health outcomes across diverse populations, there was limited evidence of reliable, clinically significant effects. PROSPERO registration number: CRD42020140086.     

Defining the Assessment and Treatment Competencies to Deliver Low-Intensity Cognitive Behavior Therapy: A Multi-Center Validation Study

Despite the vastly increased dissemination of the low-intensity (LI) version of cognitive behavior therapy (CBT) for the treatment of anxiety and depression, no valid and reliable indices of the LI-CBT clinical competencies currently exist. This research therefore sought to develop and evaluate two measures: the low-intensity assessment competency scale (LIAC) and the low-intensity treatment competency scale (LITC). Inductive and deductive methods were used to construct the competency scales and detailed rating manuals were prepared. Two studies were then completed. The first study used a quantitative, fully-crossed design and the second a multi-center, quantitative longitudinal design. In study one, novice, qualified, and expert LI-CBT practitioners rated an LI-CBT assessment session (using the LIAC) and an LI-CBT treatment session (using the LITC). Study two used the LIAC and LITC across four training sites to analyze the competencies of LI-CBT practitioners over time, across raters, and in relation to the actor/patients’ feedback concerning helpfulness, the alliance, and willingness to return. Both the LIAC and LITC were found to be single factor scales with good internal, test-retest reliability and reasonable inter-rater reliability. Both measures were sensitive to measuring change in clinical competence. The LIAC had good concurrent, criterion, discriminant, and predictive validity, while the LITC had good concurrent, criterion, and predictive validity, but limited discriminant validity. A score of 18 accurately delineated a minimum level of competence in LI-CBT assessment and treatment practice, with incompetent practice associated with patient disengagement. These observational ratings scales can contribute to the clinical governance of the burgeoning use of LI-CBT interventions for anxiety and depression in routine services and also in the methods of controlled studies.     

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.     

A Two-way Street: Mentor Stress and Depression Influence Relational Satisfaction and Attachment in Youth Mentoring Relationships

Over the past two decades, youth mentoring programs have increased in popularity as an intervention for children exposed to a range of stressful life circumstances. Such programs have been shown to promote positive youth development and reduce risk for emotional and behavioral problems; yet, the effect size of youth gains remains small. The current study examined the influence of college student mentors’ history of early life stress and baseline depressive symptoms on their effectiveness in youth mentoring relationships using 340 randomized mentor–youth pairs from College Mentors for Kids, a well-established mentoring program with chapters across the United States. Hierarchical linear models revealed that mentors with higher levels of depressive symptoms reported lower relationship satisfaction and increased avoidance in the mentoring relationship. In contrast, mentors who experienced higher levels of early life stress had youth who reported greater satisfaction in the mentoring relationship and decreased relational anxiety. These findings are some of the first to examine the impact of mentor characteristics on mentor–youth relationships and highlight the importance of considering factors relevant to psychosocial functioning and emotional distress when recruiting, training, and supporting college student mentors.