Is it time to discard the Diagnostic and Statistical Manual of Mental Disorders (DSM) in psycho-oncology?

The conceptual basis of psychopathology within cancer survivorship is critical, as the chosen conceptualisation informs assessment and explanatory models, as well as interventions and supportive care approaches. The validity of a chosen conceptualisation of psychopathology is therefore paramount for ensuring cancer survivors receive high-quality and efficacious care and support that can be iteratively improved via coordinated research efforts. In this paper, we discuss the traditional diagnostic approach to conceptualising psychopathology within cancer care, including the diagnostic system the 'Diagnostic and Statistical Manual of Mental Disorders' (DSM) [1], and the significant issues it presents within cancer survivorship. We detail and discuss how an alternate conceptualisation of psychopathology may enhance both research and practice within psycho-oncology. We ultimately pose, and provide our perspective, on the question "Is it Time to Discard the DSM in Psycho-Oncology?"

"Is My Brain Ever Going to Work Fully Again?": Challenges and Needs of Cancer Survivors with Persistent Cancer-Related Cognitive Impairment.

Many cancer survivors experience cognitive impairments that impact memory, concentration, speed of information processing, and decision making. These impairments, collectively known as cancer-related cognitive impairments (CRCIs), are a key domain of unmet needs and can significantly impact a cancer survivor's identity and quality of life. However, there are no purpose-built, multi-domain, needs assessment tools specifically for CRCI. The development of such tools requires an in-depth understanding of cancer survivors' CRCI-specific challenges and associated needs. This study explored the challenges and associated needs of cancer survivors with persistent CRCI. An in-depth qualitative design using semi-structured interviews with (a) cancer survivors with perceived CRCI (n = 32) and (b) oncology health professionals (n = 19) was utilised. A reflexive thematic analysis of the interviews resulted in five overarching themes: (1) executing regular activities, (2) relational difficulties, (3) occupational functioning, (4) psychological distress, and (5) social functioning, as well as an additional informational needs domain. Ultimately, CRCI was found to directly produce a range of challenges that negatively, and persistently, impact cancer survivors' quality of life. Cancer survivors were also found to have a range of needs associated with these challenges. This research should be used to inform future challenges and needs assessment tools as well as treatment and supportive care priority areas directly relating to CRCI.

Research Directions for Leveraging and Supporting the Lived Experience of Mental Illness within Psychology.

This paper explores the lived experience of mental illness within the field of psychology across higher education and the mental health workforce. There is a high prevalence of mental health issues among psychology students and practitioners, and it is critical not only to provide support for these populations, but also to acknowledge the value of leveraging their lived experience within their education and practice. There has been increased interest in and advocacy for the involvement of those with lived experience of mental illness within mental healthcare service provision to improve patient experiences and outcomes. However, there have been limited acknowledgement and research regarding the role of psychologists with personal lived experiences of mental illness, and how to leverage this experience. Further, there are challenges faced by both psychology students and practising psychologists with lived experience that act as barriers to leveraging their unique skills and experiences. Psychology students with lived experience face stigma, inadequate support, and incongruence between the course material and their personal experiences. Similarly, practising psychologists with lived experience encounter stigma and isolation, indicating the need for a culture change that promotes transparency and understanding. The paper calls for research in five key directions to provide evidence that can be used to support and leverage lived experience in psychology.

Do Dimensional Measures of Mental Health Symptoms Predict Level of Alcohol Involvement in the General Population?

Background: There is a limited understanding of what specific mental health symptoms are associated to alcohol involvement. It is important to understand how the severity of different mental health dimensions may differ, and distinguish between, levels of alcohol involvement. Objectives: (a) explore for differences in severity of mental health symptoms between those with lower, and moderate/high alcohol involvement, (b) assess the degree to which mental health dimensions can distinguish between those with lower, and moderate/high alcohol involvement, and (c) examine what mental health dimensions are related to the highest risk of moderate/high alcohol involvement. Results: 400 participants representative of the general population in the USA were recruited online through Prolific and completed the Alcohol, Smoking and Substance Involvement Screening Test and Brief Symptom Inventory. Each of the nine mental health symptom dimensions significantly differed between lower and moderate/high alcohol involvement, with the moderate/high alcohol involvement group reporting greater severity symptoms. The nine symptom dimensions in combination also significantly distinguished lower and moderate/high alcohol involvement, however only somatization offered unique predictive utility. Lastly, global distress was also able to significantly distinguish the alcohol involvement groups, albeit to a lesser accuracy compared to the collection of individual symptom dimensions. Conclusions: These findings suggest that overall mental health distress may be important to understanding alcohol involvement, however individual symptom dimensions can add further explanatory variance. In particular, somatic symptoms may offer unique utility in understanding the relationship between mental health and alcohol involvement.

Neurocognitive Artificial Neural Network Models Are Superior to Linear Models at Accounting for Dimensional Psychopathology.

In recent years, there has been debate about the optimal conceptualisation of psychopathology. Structural models of psychopathology have been developed to counter issues, including comorbidity and poor diagnostic stability prevalent within the traditional nosological approach. Regardless of the conceptualisation of psychological dysfunction, deficits in neurocognitive abilities have been claimed to be an aetiological feature of psychopathology. Explorations of the association between neurocognition and psychopathology have typically taken a linear approach, overlooking the potential interactive dynamics of neurocognitive abilities. Previously, we proposed a multidimensional hypothesis, where within-person interactions between neurocognitive domains are fundamental to understanding the role of neurocognition within psychopathology. In this study, we used previously collected psychopathology data for 400 participants on psychopathological symptoms, substance use, and performance on eight neurocognitive tasks and compared the predictive accuracy of linear models to artificial neural network models. The artificial neural network models were significantly more accurate than the traditional linear models at predicting actual (a) lower-level and (b) high-level dimensional psychopathology. These results provide support for the multidimensional hypothesis: that the study of non-linear interactions and compensatory neurocognitive profiles are integral to understanding the functional associations between neurocognition and of psychopathology.

What Accounts for the Factors of Psychopathology? An Investigation of the Neurocognitive Correlates of Internalising, Externalising, and the p-Factor.

Neurocognitive deficits have been consistently associated with a wide range of psychopathology and are proposed to not only be a consequence of the development of psychopathology but also directly involved in its aetiology. However, there is no clear understanding of what neurocognitive processes are particularly important to mental health. In this paper, we explored the association between neurocognitive abilities and the factors derived from structural models of psychopathology. Four hundred participants from a representative community sample completed measures of symptomology and substance use, as well as 8 neurocognitive tasks. We found a correlated-factors model, with internalising and externalising as the higher-order factors, and a single-factor model with only the p-factor, to be good fits for the data. Tasks that measured the speed of processing were significantly associated with internalising, externalising, and the p-factor, and accounted for significant amounts of unique variance in the factors after accounting for the common variance of the other tasks. Tasks that measured working memory, shifting, and inhibition were not significantly associated with psychopathology factors. Our findings suggest that neurocognitive abilities may not be differentially associated with psychopathology factors, but that speed of processing is a common correlate of the factors. We emphasise the importance of examining neurocognitive abilities and psychopathology on the individual level.

One p-Factor for All? Exploring the Applicability of Structural Models of Psychopathology within Subgroups of a Population.

Structural models of psychopathology have emerged as an alternative to traditional categorical approaches. The bifactor model, which incorporates a general p-factor, has become the preferred structure. The p-factor is claimed to represent a substantive construct or property of the system; however, recent evidence suggests that it may be without substantive meaning. If a universal substantive p, and associated specific factors, is to be developed they not only must be applicable and consistent between populations but also must be applicable and consistent within subgroups of a population. This consistency needs to include not only factor loadings but also factor correlates. We used a simulated data approach to explore the applicability and consistency of four popular models of psychopathology to a range of heterogeneous subgroups and examined the consistency of their neurocognitive correlates. We found that only eight out of sixty-three subgroups fitted any of the models with all significant loadings, no negative loadings, no non-positive-definite identification issues, and no negative variance. All eight of these subgroups fit the correlated factors model, none fit the original bifactor model, four subgroups fit the revised bifactor model, and one subgroup fit the single-factor model. Correlates of the factors also varied substantially between the subgroups fitted to the same model. We discuss the implications of the findings, including the implications for the development of universal substantive factors of psychopathology.

Going "Up" to Move Forward: S-1 Bifactor Models and the Study of Neurocognitive Abilities in Psychopathology.

Recently, structural models of psychopathology, that address the diagnostic stability and comorbidity issues of the traditional nosological approach, have dominated much of the psychopathology literature. Structural approaches have given rise to the p-factor, which is claimed to reflect an individual's propensity toward all common psychopathological symptoms. Neurocognitive abilities are argued to be important to the development and maintenance of a wide range of disorders, and have been suggested as an important driver of the p-factor. However, recent evidence argues against p being an interpretable substantive construct, limiting conclusions that can be drawn from associations between p, the specific factors of a psychopathology model, and neurocognitive abilities. Here, we argue for the use of the S-1 bifactor approach, where the general factor is defined by neurocognitive abilities, to explore the association between neurocognitive performance and a wide range of psychopathological symptoms. We use simulation techniques to give examples of how S-1 bifactor models can be used to examine this relationship, and how the results can be interpreted.

A Conceptual Model of Long-Term Weight Loss Maintenance: The Importance of Cognitive, Empirical and Computational Approaches.

Living with obesity is related to numerous negative health outcomes, including various cancers, type II diabetes, and cardiovascular disease. Although much is known about the factors associated with obesity, and a range of weight loss interventions have been established, changing health-related behaviours to positively affect obesity outcomes has proven difficult. In this paper, we first draw together major factors that have emerged within the literature on weight loss to describe a new conceptual framework of long-term weight loss maintenance. Key to this framework is the suggestion that increased positive social support influences a reduction in psychosocial stress, and that this has the effect of promoting better executive functioning which in turn facilitates the development of healthy habits and the breaking of unhealthy habits, leading to improved ongoing maintenance of weight loss. We then outline how the use of computational approaches are an essential next step, to more rigorously test conceptual frameworks, such as the one we propose, and the benefits that a mixture of conceptual, empirical and computational approaches offer to the field of health psychology.

Active Learning in Research Methods Classes Is Associated with Higher Knowledge and Confidence, Though not Evaluations or Satisfaction.

Research methods and statistics are regarded as difficult subjects to teach, fueling investigations into techniques that increase student engagement. Students enjoy active learning opportunities like hands-on demonstrations, authentic research participation, and working with real data. However, enhanced enjoyment does not always correspond with enhanced learning and performance. In this study, we developed a workshop activity in which students participated in a computer-based experiment and used class-generated data to run a range of statistical procedures. To enable evaluation, we developed a parallel, didactic/canned workshop, which was identical to the activity-based version, except that students were told about the experiment and used a pre-existing/canned dataset to perform their analyses. Tutorial groups were randomized to one of the two workshop versions, and 39 students completed a post-workshop evaluation questionnaire. A series of generalized linear mixed models suggested that, compared to the students in the didactic/canned condition, students exposed to the activity-based workshop displayed significantly greater knowledge of the methodological and statistical issues addressed in class, and were more confident about their ability to use this knowledge in the future. However, overall evaluations and satisfaction between the two groups were not reliably different. Implications of these findings and suggestions for future research are discussed.

Introducing StatHand: A Cross-Platform Mobile Application to Support Students' Statistical Decision Making.

Although essential to professional competence in psychology, quantitative research methods are a known area of weakness for many undergraduate psychology students. Students find selecting appropriate statistical tests and procedures for different types of research questions, hypotheses and data types particularly challenging, and these skills are not often practiced in class. Decision trees (a type of graphic organizer) are known to facilitate this decision making process, but extant trees have a number of limitations. Furthermore, emerging research suggests that mobile technologies offer many possibilities for facilitating learning. It is within this context that we have developed StatHand, a free cross-platform application designed to support students' statistical decision making. Developed with the support of the Australian Government Office for Learning and Teaching, StatHand guides users through a series of simple, annotated questions to help them identify a statistical test or procedure appropriate to their circumstances. It further offers the guidance necessary to run these tests and procedures, then interpret and report their results. In this Technology Report we will overview the rationale behind StatHand, before describing the feature set of the application. We will then provide guidelines for integrating StatHand into the research methods curriculum, before concluding by outlining our road map for the ongoing development and evaluation of StatHand.

The impact of transcranial direct current stimulation on inhibitory control in young adults.

BACKGROUND: There is increasing evidence that the dorso-lateral prefrontal cortex (DLPFC), a brain region related to reward and motivational processes, is involved in effective response inhibition and that decreased activity in this region coincides with reduced inhibitory capacity. Using transcranial direct current stimulation (tDCS) to manipulate cortical activation, this study examined whether cross-hemispheric tDCS over the DLPFC affected performance on an inhibitory control task. METHODS: Neurologically intact participants performed a modified Stroop color-word matching task before and after completing one of two tDCS conditions; (1) anodal stimulation over the left DLPFC or (2) sham tDCS. RESULTS: There was a statistically significant effect of tDCS condition on Stroop reaction time (RT) pre-post tDCS change scores. Participants who received anodal stimulation over the left DLPFC demonstrated statistically significant faster RT change scores on the Stroop items compared to participants in the sham condition. Although errors on Stroop incongruent items decreased before and after receiving the tDCS treatment, there were no significant differences in errors on Stroop items between the anodal stimulation over left DLPFC and sham tDCS conditions. Anodal tDCS, which is known to elevate neural excitation, may have enhanced activation levels in the left DLPFC and minimized impairment of inhibitory control, resulting in better task performance. CONCLUSIONS: Current findings provide preliminary evidence that increased excitation of the left DLPFC improves inhibitory control and are a step toward understanding the potential of tDCS for moderating deficits in inhibitory control.