One size does not fit all in assessment and intervention for people with convictions for sexual offences. Crime scene indicators and risk-related variables have been used to identify distinct clusters of people with convictions for sexual offences, but there is a need for more robust typologies that identify clusters based on psychologically meaningful risk factors that can be targeted in treatment.

To use robust modelling techniques to identify latent profiles of people with convictions for sexual offences based on indicators of dynamic risk.

Adult male participants, who had been convicted for sexual offences and assessed for eligibility for the prison-based Core Sex Offender Treatment Programme delivered by His Majesty's Prison and Probation Service (UK), were randomly allocated to a test (n = 1577: 70.2%) or validation (n = 668: 29.8%) data-set. Exploratory factor analysis (EFA) was used to select measures of dynamic risk from psychological test data. EFA indicated four factors, from which six measures were selected for inclusion in latent profile analysis.

Five latent profiles were identified in the test and validation data-sets. These were labelled low psychological impairment, impulsive, distorted thinker, rape preoccupied and child fantasist. Profiles varied in individual characteristics, offence histories, victim preferences and level of risk.

Our findings should be used to guide assessment and intervention practices that are tailored to distinct psychological profiles consistent with principles of risk, need and responsivity.

The Autism Spectrum Quotient is a popular autism screening tool recommended for identifying potential cases of autism. However, many women with autism demonstrate a different presentation of traits to those currently captured by screening measures and assessment methods, such as the Autism Spectrum Quotient.

Different models of the Autism Spectrum Quotient have been proposed in the literature, utilising different items from the original 50-item scale. Within good-fitting models, the current study aimed to explore whether these items assess autistic traits similarly across men and women.

Seventeen Autism Spectrum Quotient models were identified from the literature. Using the responses of a large sample of adults from the UK general population (5246 women, 1830 men), confirmatory factor analysis was used to evaluate the fit of each model. Measurement invariance with respect to gender, adjusting for age, was explored in the 11 model frameworks that were found to have satisfactory fit to our data.

It emerged that only two items were gender invariant (non-biased), whereas for the remaining items, the probability of endorsement was influenced by gender. In particular, women had a higher probability of endorsing items relating to social skills and communication.

If the items of the Autism Spectrum Quotient indeed reflect autism-related traits, those items should be rephrased to ensure they do not present a gender-related bias. This is vital for ensuring more timely diagnoses and support for all people with autism.

We aimed to establish cut-off scores to stage dementia on the Addenbrooke's Cognitive Examination-III (ACE-III) and the Mini-Addenbrooke's Cognitive Examination (M-ACE) compared with scores traditionally used with the Mini-Mental State Examination (MMSE). Our cross-sectional study recruited 80 patients and carers from secondary care services in the UK.

A score ≤76 on the ACE-III and ≤19 on the M-ACE correlated well with MMSE cut-offs for mild dementia, with a good fit on the receiver operating characteristic analysis for both the ACE-III and M-ACE. The cut-off for moderate dementia had lower sensitivity and specificity. There were low to moderate correlations between the cognitive scales and scales for everyday functioning and behaviour.

Our findings allow an objective interpretation of scores on the ACE-III and the M-ACE relative to the MMSE, which may be helpful for clinical services and research trials.

Current assessment and management models often do not adequately address the many aspects of managing complex brain disorders involving disordered affect, behaviour and cognition (ABC). A more collaborative model of care, where several specialties can jointly assess and manage patients with complex brain disorders, is gaining attention.

In this case report, we present two cases that highlight the benefits of the ‘brain medicine’ clinical model.

The Brain Medicine Clinic employs an integrated clinical model in which psychiatrists and neurologists provide integrated interdisciplinary assessments of patients with complex brain disorders, leading to comprehensive assessment. We describe the clinical model and the trajectories of two patients with complex brain disorders seen in this clinic. In these case descriptions, we explain how the brain medicine clinical approach leads to an improved patient experience.

The Brain Medicine Clinic assessments resulted in a neurobiopsychosocial formulation of symptoms and, consequently, holistic individualised treatment plans for two patients with complex brain disorders. This approach to patients’ conditions emerges from the understanding that there are multifactorial causes of brain disorders at the social, cultural, psychological and biological level.

Integrated interdisciplinary assessments allow for tailored treatment plans for individuals experiencing complex brain disorders, while creating efficiencies for the patient and the healthcare system.

A critical step in research on the epidemiology of post-traumatic stress disorder (PTSD) in low-resource settings is the validation of brief self-reported psychometric tools available in the public domain, such as the Impact Event Scale – Revised (IES-R).

We aimed to investigate the validity of the IES-R in a primary healthcare setting in Harare, Zimbabwe.

We analysed data from a survey of 264 consecutively sampled adults (mean age 38 years; 78% female). We estimated the area under the receiver operating characteristic curve and sensitivity, specificity and likelihood ratios for different cut-off points of the IES-R, against a diagnosis of PTSD made using the Structured Clinical Interview for DSM-IV. We performed factor analysis to evaluate construct validity of the IES-R.

The prevalence of PTSD was 23.9% (95% CI 18.9–29.5). The area under the curve for the IES-R was 0.90. At a cut-off of ≥47, the sensitivity of the IES-R to detect PTSD was 84.1 (95% CI 72.7–92.1) and specificity was 81.1 (95% CI 75.0–86.3). Positive and negative likelihood ratios were 4.45 and 0.20, respectively. Factor analysis revealed a two-factor solution, with both factors showing good internal consistency (Cronbach's factor-1 α = 0.95, factor-2 α = 0.76). In a post hoc analysis, we found the brief six-item IES-6 also performed well, with an area under the curve of 0.87 and optimal cut-off of 15.

The IES-R and IES-6 had good psychometric properties and performed well for indicating possible PTSD, but at higher cut-off points than those recommended in the Global North.

A variety of information sources are used in the best-evidence diagnostic procedure in child and adolescent mental healthcare, including evaluation by referrers and structured assessment questionnaires for parents. However, the incremental value of these information sources is still poorly examined.

To quantify the added and unique predictive value of referral letters, screening, multi-informant assessment and clinicians’ remote evaluations in predicting mental health disorders.

Routine medical record data on 1259 referred children and adolescents were retrospectively extracted. Their referral letters, responses to the Strengths and Difficulties Questionnaire (SDQ), results on closed-ended questions from the Development and Well-Being Assessment (DAWBA) and its clinician-rated version were linked to classifications made after face-to-face intake in psychiatry. Following multiple imputations of missing data, logistic regression analyses were performed with the above four nodes of assessment as predictors and the five childhood disorders common in mental healthcare (anxiety, depression, autism spectrum disorders, attention-deficit hyperactivity disorder, behavioural disorders) as outcomes. Likelihood ratio tests and diagnostic odds ratios were computed.

Each assessment tool significantly predicted the classified outcome. Successive addition of the assessment instruments improved the prediction models, with the exception of behavioural disorder prediction by the clinician-rated DAWBA. With the exception of the SDQ for depressive and behavioural disorders, all instruments showed unique predictive value.

Structured acquisition and integrated use of diverse sources of information supports evidence-based diagnosis in clinical practice. The clinical value of structured assessment at the primary–secondary care interface should now be quantified in prospective studies.

This study investigated the change in suicidal ideation and its risk factors among employees. A longitudinal cohort study was conducted, starting with the baseline online survey in March 2020 (T1), followed by May (T2), and August (T3). The change in suicidal ideation from T2 to T3 and relevant factors associated with suicidal ideation at T3 were examined. Suicidal ideation significantly increased between May and August 2020 among females, younger (under 39 years old), highly educated population, and those without pre-existing mental health conditions. Factors significantly associated with suicidal ideation were younger age, suicidal ideation at T2, and with pre-existing mental health conditions. Loneliness at T2 showed a significant association with suicidal ideation, if adjusting those without pre-existing mental health conditions. National and community support is needed to target people who are likely to be left behind, such as young people and those with pre-existing mental health conditions, in the pandemic.

A longitudinal study was conducted with a cohort of full-time employees, starting with the baseline online survey in March 2020 (time point 1), followed by May (time point 2) and August (time point 3). The change in suicidal ideation from time point 2 to 3, and relevant factors associated with suicidal ideation at time point 3, were examined.

Suicidal ideation significantly increased between time points 2 and 3 among women, younger people (aged <39 years), those who were highly educated and those without pre-existing mental health conditions. Factors significantly associated with suicidal ideation were younger age, suicidal ideation at time point 2 and pre-existing mental health conditions. Loneliness at time point 2 showed a significant association with suicidal ideation when adjusting for those without pre-existing mental health conditions.

National and community support is needed to target people who are likely to be left behind, such as young people, those with pre-existing mental health conditions and those experiencing loneliness, in the COVID-19 pandemic.

Cross-sectional studies have found impaired cognitive functioning in patients with bipolar disorder, but long-term longitudinal studies are scarce.

The aims of this study were to examine the 6-year longitudinal course of cognitive functioning in patients with bipolar disorder and healthy controls. Subsets of patients were examined to investigate possible differences in cognitive trajectories.

Patients with bipolar I disorder (n = 44) or bipolar II disorder (n = 28) and healthy controls (n = 59) were tested with a comprehensive cognitive test battery at baseline and retested after 6 years. We conducted repeated measures ANCOVAs with group as a between-subject factor and tested the significance of group and time interaction.

By and large, the change in cognitive functioning between baseline and follow-up did not differ significantly between participants with bipolar disorder and healthy controls. Comparing subsets of patients, for example those with bipolar I and II disorder and those with and without manic episodes during follow-up, did not reveal subgroups more vulnerable to cognitive decline.

Cognitive performance remained stable in patients with bipolar disorder over a 6-year period and evolved similarly to healthy controls. These findings argue against the notion of a general progressive decline in cognitive functioning in bipolar disorder.

The Neuropsychiatric Inventory (NPI) is predicated on the assumption that psychiatric symptoms are manifestations of disease. Biopsychosocial theories suggest behavioural changes viewed as psychiatric may also arise as a result of external behavioural triggers. Knowing the causes of psychiatric symptoms is important since the treatment and management of symptoms relies on this understanding.

This study sought to understand the causes of psychiatric symptoms recorded in care home settings by investigating qualitatively described symptoms in Neuropsychiatric Inventory-Nursing Home (NPI-NH) interviews.

The current study examined the NPI-NH interviews of 725 participants across 50 care homes. The qualitatively described symptoms from each of the 12 subscales of the NPI were extracted: 347 interviews included at least one qualitatively described symptom (n = 651 descriptions). A biopsychosocial algorithm developed following a process of independent researcher coding (n = 3) was applied to the symptom descriptions. This determined whether the description had predominantly psychiatric features, or features that were cognitive or attributable to other causes (i.e. issues with orientation and memory; expressions of need; poor care and communication; or understandable reactions)

Our findings suggest that the majority (over 80%) of descriptions described symptoms with features that could be attributable to cognitive changes and external triggers (such as poor care and communication).

The finding suggest that in its current form the NPI-NH may over attribute the incidence of psychiatric symptoms in care homes by overlooking triggers for behavioural changes. Measures of psychiatric symptoms should determine the causes of behavioural changes in order to guide treatments more effectively.

Cognitive impairment is a core feature of depression and has a negative effect on a person's functioning, in psychosocial and interpersonal areas, and on workforce performance. Cognitive impairment often persists, even with the remittance of mood symptoms. One potential way of improving treatment of cognitive impairment would be to identify variables that predict cognitive change in patients with depression.

To systematically examine findings from studies that investigate baseline variables and how they predict, or correlate with, cognitive change in mood disorders, and to examine methodological issues from these studies.

Studies that directly measured associations between at least one baseline variable and change in cognitive outcome in patients with current major depressive episode were identified using PubMed and Web of Science databases. Narrative review technique was used because of the heterogeneity of patient samples, outcome measures and study procedures. The review was registered on PROSPERO with registration number CRD42020150975.

Twenty-four studies met the inclusion criteria. Evidence from the present review for prediction of cognitive change from baseline variables was limited for demographic factors, with some preliminary evidence for depression, cognitive and biological factors. Identification of patterns across studies was difficult because of methodological variability across studies.

Findings from the present review suggest there may be some baseline variables that are useful in predicting cognitive change in mood disorders. This is an area warranting further research focus.

Depression is characterised by negative views of the self. Antidepressant treatment may remediate negative self-schema through increasing processing of positive information about the self. Changes in affective processing during social interactions may increase expression of prosocial behaviours, improving interpersonal communications.

To examine whether acute administration of citalopram is associated with an increase in positive affective learning biases about the self and prosocial behaviour.

Healthy volunteers (n = 41) were randomised to either an acute 20 mg dose of citalopram or matched placebo in a between-subjects double-blind design. Participants completed computer-based cognitive tasks designed to measure referential affective processing, social cognition and expression of prosocial behaviours.

Participants administered citalopram made more cooperative choices than those administered placebo in a prisoner's dilemma task (β = 20%, 95% CI: 2%, 37%). Exploratory analyses indicated that participants administered citalopram showed a positive bias when learning social evaluations about a friend (β = 4.06, 95% CI: 0.88, 7.24), but not about the self or a stranger. Similarly, exploratory analyses found evidence of increased recall of positive words and reduced recall of negative words about others (β = 2.41, 95% CI: 0.89, 3.93), but not the self, in the citalopram group.

Participants administered citalopram showed greater prosocial behaviours, increased positive recall and increased positive learning of social evaluations towards others. The increase in positive affective bias and prosocial behaviours towards others may, at least partially, be a mechanism of antidepressant effect. However, we found no evidence that citalopram influenced self-referential processing.

Cognitive impairment is strongly linked with persistent disability in people with mood disorders, but the factors that explain cognitive impairment in this population are unclear.

To estimate the total effect of (a) bipolar disorder and (b) major depression on cognitive function, and the magnitude of the effect that is explained by potentially modifiable intermediate factors.

Cross-sectional study using baseline data from the UK Biobank cohort. Participants were categorised as having bipolar disorder (n = 2709), major depression (n = 50 975) or no mood disorder (n = 102 931 and n = 105 284). The outcomes were computerised tests of reasoning, reaction time and memory. The potential mediators were cardiometabolic disease and psychotropic medication. Analyses were informed by graphical methods and controlled for confounding using regression, propensity score-based methods and G-computation.

Group differences of small magnitude were found on a visuospatial memory test. Z-score differences for the bipolar disorder group were in the range −0.23 to −0.17 (95% CI −0.39 to −0.03) across different estimation methods, and for the major depression group they were approximately −0.07 (95% CI −0.10 to −0.03). One-quarter of the effect was mediated via psychotropic medication in the bipolar disorder group (−0.05; 95% CI −0.09 to −0.01). No evidence was found for mediation via cardiometabolic disease.

In a large community-based sample in middle to early old age, bipolar disorder and depression were associated with lower visuospatial memory performance, in part potentially due to psychotropic medication use. Mood disorders and their treatments will have increasing importance for population cognitive health as the proportion of older adults continues to grow.

I.J.D. is a UK Biobank participant. J.P.P. is a member of the UK Biobank Steering Committee.