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Should We Use Behavioural Predictions in Organ Allocation?
Medical predictions, for example, concerning a patient's likelihood of survival, can be used to efficiently allocate scarce resources. Predictions of patient behaviour can also be used-for example, patients on the liver transplant waiting list could receive lower priority based on a high likelihood of non-adherence to their immunosuppressant medication regimen or of drinking excessively. But is this ethically acceptable? In this paper, we will explore arguments for and against behavioural predictions, before providing novel empirical evidence on this question. Firstly, we note that including behavioural predictions would lead to improved transplant outcomes. Fairness could also require prioritising those predicted to engage in healthier behaviours: consistent with using behavioural predictions in other contexts such as psychiatry and substance misuse. Conversely, behavioural predictions may be judged too inaccurate or discriminatory, or it may be thought unfair to deprioritise based on future behaviour. In part two, we performed an online survey of 172 UK adults. When presented with possible factors relevant to liver allocation, most thought predictions of higher medication adherence (78.6%) and lower future alcohol use (76.5%) should be used but not predictions of lower future criminality (24.7%) and higher societal contribution (21.2%). Randomising participants into two groups, 69.8% of participants found deprioritising a patient based on their predicted medication adherence acceptable (91.9% found a nonbehavioural prediction acceptable). We did not identify an ethically relevant difference between behavioural predictions and other medical predictions already used in organ allocation. Our sample of participants also appeared to support behavioural predictions in this context.
Prior Expectations of Volatility Following Psychotherapy for Delusions: A Randomized Clinical Trial.
IMPORTANCE: Persecutory delusions are common, distressing, and difficult to treat. Testing computational neuroscience models of delusions can identify new therapeutic targets. OBJECTIVE: To determine whether change in delusion severity is associated with a corresponding change in volatility priors and brain activation estimated during a belief updating task. DESIGN, SETTING, AND PARTICIPANTS: This randomized clinical trial was conducted from April 9, 2021, to December 5, 2023, within the Vanderbilt University Medical Center Psychiatric Hospital and at a community mental health center in Nashville, Tennessee. Participants were adults (aged between 18 and 65 years) with schizophrenia spectrum or delusional disorder and an active, persistent (≥3 months) persecutory delusion with strong conviction (>50%). Participants were randomly assigned 1:1 to either cognitive behavioral therapy for psychosis (CBTp)-based intervention or befriending therapy. Intention-to-treat analysis was performed from June 1 to October 31, 2024. INTERVENTION: The CBTp was a manualized intervention targeting persecutory delusions. The befriending therapy involved engaging in conversations and activities focused on neutral topics. Both interventions were provided in person, lasted for 8 weeks, and included standard care. Standard care consisted of medication management and ancillary services. MAIN OUTCOMES AND MEASURES: Primary outcomes were volatility priors (ie, prior expectations of volatility) derived from a 3-option probabilistic reversal learning task; persecutory delusion severity measured by the Psychotic Symptom Rating Scales (PSYRATS delusion subscale; score range: 0-16, with the highest score indicating severe preoccupation, distress, conviction, and functioning impact); and brain activation in the striatum and prefrontal cortex measured by blood oxygenation level-dependent signal change. Associations between volatility priors, clinical improvement, and change in neural activation were examined. RESULTS: Sixty-two participants (median [range] age, 31 [19-63] years; 38 males [61%]) were randomly assigned to the CBTp (n = 32) or befriending therapy (n = 30) arms. A subgroup of 35 participants (57%) completed functional magnetic resonance imaging. Volatility priors decreased following treatment (F1,112 = 7.7 [P = .006]; Cohen d = 0.52 [95% CI, 0.15-0.90]), as did delusion severity (F1,112 = 59.7 [P
Efficacy of a 6-month supported online programme (Feeling Safer) for the treatment of persecutory delusions: protocol for a randomised controlled trial.
INTRODUCTION: Persecutory delusions are very common in severe mental health disorders such as schizophrenia. Existing treatments often do not work well enough. We developed a face-to-face theory-driven psychological intervention, called Feeling Safe, that produces very large reductions in persistent persecutory delusions. The challenge now is to make Feeling Safe widely available. So, we developed a 6-month supported online version, called Feeling Safer. The aim is an intervention that patients can easily access and use, reduces persecutory delusions and can be supported by a range of mental health professionals in less contact time than face-to-face therapy. Initial proof of concept testing of Feeling Safer was very encouraging. In a randomised controlled trial, we now plan to test whether Feeling Safer is efficacious for patients and can be successfully delivered by any of three different mental health staff groups (peer-support workers, graduate psychologists and cognitive behavioural therapy (CBT) therapists). We will also test whether Feeling Safer works equally across gender, age, ethnicity and cognitive functioning (moderation) and whether Feeling Safer works via the targeted psychological processes (mediation). METHODS AND ANALYSIS: The study design is a multicentre, single-blind (outcome assessor), parallel, four-arm randomised controlled trial; 484 patients with persistent persecutory delusions will be randomised to one of the four conditions (1:1:1:1): Feeling Safer (added to treatment as usual (TAU)) supported by peer-support workers, or Feeling Safer (added to TAU) supported by graduate mental health workers including assistant psychologists, or Feeling Safer (added to TAU) supported by CBT therapists or TAU. Feeling Safer will be provided for 6 months with a staff member. Assessments will be conducted at 0, 3, 6 and 9 months by research assistants blind to group allocation. The primary outcome is severity of persecutory delusions at 6 months rated with the Psychotic Symptoms Rating Scale-Delusions. The secondary outcomes are other psychiatric symptoms (depression, anxiety, insomnia, agoraphobia and paranoia), psychological well-being, recovery, activity and health-related quality of life. Analysis will be conducted under a treatment policy strategy following the intention-to-treat principle, incorporating data from all participants including those who do not complete treatment. Moderation and mediation will be tested. A within-trial cost-effectiveness analysis will be conducted of Feeling Safer compared with TAU. ETHICS AND DISSEMINATION: The trial has received ethical approval from the NHS Health Research Authority (23/LO/0951). Informed consent will be obtained from all participants. A key output will be an open-access publication in a peer-reviewed journal reporting on the clinical effectiveness of a high-quality supported online programme for the treatment of persecutory delusions that has the potential to be used at scale in mental health services. TRIAL REGISTRATION NUMBER: ISRCTN93974770.
Developing a qualitative and quantitative ambulatory assessment-based feedback system within cognitive behavioural interventions for people with persecutory beliefs.
BACKGROUND: Although the application of self-monitoring (ambulatory assessment) and visual feedback in psychological interventions has yielded promising results, there are currently no reports on using self-monitoring and feedback during a complete therapy. The online m-Path platform provides a tailorable framework for integrating self-monitoring and visual feedback within different psychological interventions. METHODS: Therapy-specific questionnaires and visual feedback were developed within the online m-Path platform as part of the Feeling Safe-NL trial (registration number: ISRCTN25766661) for regular CBT for psychosis (CBTp) and the Feeling Safe Programme combined with peer counselling (the Feeling Safe-NL Programme). The design process involved people with lived experience, psychologists, peer counsellors, researchers, and software developers. The design principles included that the system should be 1) easy to use, 2) suitable for use during a six-month therapy, 3) focussed on positive and goal-aligned outcomes, 4) understandable by patients and professionals, and 5) informing, guiding, and promoting therapy. Design principles were evaluated using compliance data and a patient questionnaire. RESULTS: The system was used by 21 patients, of which nine completed the questionnaires for the full therapy period, 168 days on average. Usability data from patients revealed that the system was easy to use, well-explained, and suitable for use over six months of therapy. The patients also reported that the questions overall positively affected their emotions and that the feedback was insightful. CONCLUSION: The results support the successful application of the design principles to promote the integration of the self-monitoring and visual feedback system within specific CBTp interventions.
A counterweight model for understanding and treating persecutory delusions.
Direct challenge seldom leads to change in strongly held beliefs such as persecutory delusions. A better route is to develop an alternative belief that can coexist with the delusion. The best such beliefs function as counterweights to the delusion. Over time, the scales shift. The alternative belief becomes more powerful than the delusion. In this paper, we set out such a model of persecutory delusions (or severe paranoia) and describe how it inherently translates theoretical understanding into treatment routes. Severe paranoia occurs when the adaptive cognitive processes of deciding whether to trust become overly weighted to mistrust. An inaccurate threat belief is formed, and the person feels very unsafe. Hence, overcoming the delusion means developing a counterweighting belief. It means building the alternative view that the world is safe enough for the person now and going forward. This, in turn, is done by experiencing safety. However, the pull of paranoia is strong due to multiple factors such as past history, anxious arousal, hallucinations, feelings of vulnerability, use of defenses, withdrawal, worry, difficulties distancing from fears, and a sense of defeat. These factors can prevent the person from feeling safe in even the most benign environments. Therefore, counterweights must be developed for these factors. For instance, feeling vulnerable can be counterweighted by developing self-confidence. Excessive time spent worrying can be counterweighted by devoting more time to thinking about meaningful activities. The counterweight approach provides a non-confrontational, empathic, personalized way to lift the burden of paranoia from a patient with persecutory delusions.
Learning How to Improve the Treatment of Persecutory Delusions: Using a Principal Trajectories Analysis to Examine Differential Effects of Two Psychological Interventions (Feeling Safe, Befriending) in Distinct Groups of Patients.
BACKGROUND: A theory-driven cognitive therapy (Feeling Safe) has produced much better outcomes for patients with persecutory delusions. There are four distinct response classes: very high delusion conviction with large improvement, very high delusion conviction with no response, high delusion conviction with large improvement, and high delusion conviction with modest improvement. Our objective was to apply principal trajectories analysis, a novel statistical method, to original trial data to estimate whether these groups may have responded differently to a different intervention: befriending. DESIGN: One hundred and thirty patients with persistent persecutory delusions were randomised to six months of Feeling Safe or befriending. Baseline assessments were used to assign patients allocated to befriending (who did not receive Feeling Safe) into the four Feeling Safe response classes. The treatment effect, including on potential mediators, was then estimated for these classes. RESULTS: Patients in two treatment response classes (Very high conviction/large improvement, High conviction/large improvement) benefited more from Feeling Safe, patients in one group (Very high conviction/no improvement) benefited more from befriending, and patients in the remaining group (High conviction/moderate improvement) benefited equally from the interventions. Mechanism differences were detected when Feeling Safe was superior to befriending, but not when befriending was superior. CONCLUSIONS: There may be patients with psychosis who benefit more from one type of therapy than another, likely due to different change mechanisms. The application of principal trajectories has generated testable hypotheses and a potential step toward personalised treatment. We recommend an investigation of whether sequential provision of the treatment types could enhance patient outcomes. Keywords: persecutory, delusions, outcome trajectories, psychosis, cognitive therapy.
Moving from exploratory to confirmatory network analysis: An evaluation of structural equation modeling fit indices and cutoff values in network psychometrics.
Network models are well-suited for phenomena detection, and most empirical network studies have been exploratory so far. Yet, due to the close connections between (Gaussian) networks and structural equation modeling (SEM), confirmatory testing and SEM fit indices are readily applicable to network modeling as well. However, no study to date has evaluated how SEM fit indices perform in confirmatory network analysis (CNA), and what criteria should be applied. This study examined the applicability of SEM fit indices and their conventional cutoff values in CNA. We employed a panel graphical autoregressive model for its generalizability to network models in both cross-sectional (Gaussian graphical models) and N = 1 time-series cases (graphical autoregressive models). Using simulations, we analyzed the performance of fit indices to test hypothesized network structures and evaluate stationarity, under varying number of variables (nodes), sample sizes, and measurement waves. Most fit indices performed well, except that Type I incremental fit indices showed high false rejection rates. Conventional SEM cutoffs are largely generalizable to CNA as preliminary assessment criteria when dynamical cutoffs are unavailable. However, we recommend stricter cutoff values (e.g., 0.03/0.04 for the root-mean-square error of approximation [RMSEA] and 0.96/0.97 for incremental fit indices) in hypothesis testing or direct replication studies if researchers aim for more precise testing or exact replications. For detecting network structure non-stationarity, stricter RMSEA cutoffs (0.03/0.04) are advised. This study validates the use of SEM fit criteria for confirmatory network psychometrics and encourages theory-testing and replication studies in network research, providing practical recommendations for using SEM fit indices in confirmatory network testing. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Urban-rural differences in anxiety and depression in the UK, New Zealand, and Norway.
As the global urban population surpasses 50 %, understanding the impact of urban environments on mental health is crucial. This study examines the relationship between urbanicity and the prevalence of depression and anxiety disorders in the United Kingdom (UK; N = 449,232), New Zealand (N = 33,042), and Norway (N = 13,238). This paper addresses a central limitation of previous research, which relied on dichotomous and varying definitions of urbanicity, by employing a continuous measure of urbanicity consistently across our three samples. Results revealed country-specific patterns: in the UK, a non-linear pattern showed a minimum in semi-urban areas but increased prevalences of anxiety and depression in both urban and rural regions; in New Zealand, only urban living was linked to a higher prevalence of anxiety, while depression rates remained consistent across settings; in Norway, increased mental health problems were associated with rural residency. These relationships were robust across various sensitivity analyses. Overall, the results underscore that there is no universal association between urbanicity and mental health; rather, the urban-rural gradient operates differently across countries. Future research should explore cross-national variation in urban environments toward identifying aspects of urban life that serve as favorable versus detrimental to mental health.
Technology Matters: Online Support and Intervention (OSI) for child anxiety problems - an example of the journey from research to practice.
Childhood anxiety problems are prevalent and impairing, yet many children are unable to access evidence-based treatment (i.e. cognitive behavioural therapy, CBT). Digitally augmented psychological interventions represent one way to help increase access to CBT for children with mental health problems, as these interventions can substantially reduce the amount of therapist time required to deliver the intervention, as well as bringing a range of other potential advantages for therapists and families. Online Support and Intervention (OSI) is an example of a brief digitally augmented, therapist-supported, parent-led CBT intervention for child anxiety problems that is now being commissioned and delivered in child mental health services. This article outlines the journey of OSI from research to implementation into routine clinical practice and highlights key considerations for translating digitally augmented mental health interventions into routine care in child mental health services.
Dorsal raphe nucleus controls motivation-state transitions in monkeys.
The dorsal raphe nucleus (DRN) is an important source of serotonin in the brain, but fundamental aspects of its function remain elusive. Here, we present a combination of minimally invasive recording and disruption studies to show that DRN brings about changes in motivation states. We use recently developed methods for identifying temporal patterns in behavior to show that monkeys change their motivation depending on the availability of rewards in the environment. Distinctive patterns of DRN activity occur when monkeys transition between a high-motivation state occupied when rewards are abundant, to a low-motivation state engendered by reward scarcity. Disrupting DRN diminishes sensitivity to the reward environment and perturbs transitions in motivational states.
Not all verbal labels grease the wheels of odor categories
Language is known to play a crucial role in influencing how humans perceive and categorize sensory stimuli, including odors. This study investigated the impact of linguistic labeling on odor categorization among bilingual participants proficient in Chinese (L1) and English (L2). We hypothesized that L1-like linguistic labels would more robustly propel the learning of new olfactory categories compared to a condition without language, and more familiar labels would better support odor category learning. The analysis focused on comparing learning trajectories and odor categorization performance of four groups, three in which odors were paired with different sets of verbal labels and a control group that categorized odors without any verbal labeling. Following four days of intensive training, the results showed that the groups with verbal labels numerically outperformed the control group, and that the less familiar the labels sounded the more successful categorization became. However, between-group differences did not reach statistical significance. These findings, while not conclusively supporting our hypotheses, provide insights into the complex relationship between linguistic familiarity and odor category formation. The results are nested within Ad Hoc Cognition, highlighting that variations in linguistic familiarity may not induce robust enough contextual changes to differentially affect how odor categories are formed.