A significant rise in mental health disorders was expected during the COVID-19 pandemic. However, referrals to mental health services dropped for several months before rising to pre-pandemic levels.

To identify trajectories of incidence and risk factors for common mental disorders among the general population during 14 months of the COVID-19 pandemic, to inform potential mental health service needs.

A cohort of 33 703 adults in England in the University College London COVID-19 Social Study provided data from March 2020 to May 2021. Growth mixture modelling was used to identify trajectories based on the probability of participants reporting symptoms of depression (Patient Health Questionnaire-9) or anxiety (Generalised Anxiety Disorder-7) in the clinical range, for each month. Sociodemographic and personality-related characteristics associated with each trajectory class were explored.

Five trajectory classes were identified for depression and anxiety. Participants in the largest class (62%) were very unlikely to report clinically significant symptom levels. Other trajectories represented participants with a high likelihood of clinically significant symptoms throughout, early clinically significant symptoms that reduced over time, clinically significant symptoms that emerged as the pandemic unfolded and a moderate likelihood of clinically significant symptoms throughout. Females, younger adults, carers, those with existing mental health diagnoses, those that socialised frequently pre-pandemic and those with higher neuroticism scores were more likely to experience depression or anxiety.

Nearly 40% of participants followed trajectories indicating risk of clinically significant symptoms of depression or anxiety. The identified risk factors could inform public health interventions to target individuals at risk in future health emergencies.

Although the COVID-19 pandemic has affected depression, evidence of the role of pre-pandemic history of depression remains limited.

We investigated how long-term trajectories of depressive symptomatology before the COVID-19 pandemic were related to depression during the pandemic, over and above the latest pre-pandemic depression status. Furthermore, we examined whether those experiencing depression closer to the pandemic were at higher risk during the pandemic.

Employing data from waves 4–9 of the English Longitudinal Study of Ageing (2008–2009 to 2018–2019), we used group-based trajectory modelling on 3925 English older adults aged 50+ years to identify distinctive trajectories of elevated depressive symptoms (EDS). Fully adjusted logistic models were then used to examine the associations between trajectories and depression during the COVID-19 pandemic (June–July and November–December 2020).

We identified four classes of pre-pandemic trajectories of EDS. About 5% were classed as ‘enduring EDS’, 8% as ‘increasing EDS’, 10% as ‘decreasing EDS’ and 77% as ‘absence of EDS’. Compared with respondents with absence of EDS, those with EDS history were more likely to have depression during the COVID-19 pandemic, particularly those with enduring or increasing EDS in the previous 10 years. Moreover, the frequency of EDS was more crucial in predicting the risks of depression during the pandemic than the timing of the latest episode.

Trajectories of depressive symptomatology are an important risk factor for older adults’ mental health, particularly in the context of crisis. Older people with enduring or increasing EDS should receive particular attention from policy makers when provisioning post-pandemic well-being support.

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.

There are numerous challenges in the recruitment and retention of the medical workforce in psychiatry. This mixed-methods study examined the role of psychiatry clinical attachments for international medical graduates (IMGs) to enhance recruitment and retention. An online survey was launched to capture views and perceptions of IMGs about clinical attachments. The quantitative and qualitative responses were analysed to elicit findings.

In total, 92 responses were received, with respondents commonly from India, Pakistan and Egypt. Respondents were mostly aged 25–34, with ≥3 years of psychiatry experience. Over 80% expressed strong interest in completing a psychiatry clinical attachment and believed it would support career progression. Qualitative data indicated that IMGs hoped to gain clinical experience and understanding of the National Health Service (NHS). They wished for a clearer, simpler process for clinical attachments.

Clinical attachment can be mutually beneficial, providing IMGs with opportunity to confidently start their psychiatry career in the UK and enhance medical recruitment in mental health services across the NHS.

A core element of the Strengthening Responses to Dementia in Developing Countries (STRiDE) programme was to generate novel data on the prevalence, cost and impact of dementia in low- and middle-income countries, to build better health policy. Indonesia and South Africa are two middle-income countries in need of such data.

To present the STRiDE methodology and generate estimates of dementia prevalence in Indonesia and South Africa.

We conducted community-based, single-phase, cross-sectional studies in Indonesia and South Africa, randomly sampling participants aged 65 years or older in each country. Dementia prevalence rates for each country were generated by using the 10/66 short schedule and applying its diagnostic algorithm. Weighted estimates were calculated with national sociodemographic data.

Data were collected between September and December 2021 in 2110 people in Indonesia and 408 people in South Africa. The adjusted weighted dementia prevalence was 27.9% (95% CI 25.2–28.9) in Indonesia and 12.5% (95% CI 9.5–16.0) in South Africa. Our results indicate that there could be >4.2 million people in Indonesia and >450 000 people in South Africa who have dementia. Only five participants (0.2%) in Indonesia and two (0.5%) in South Africa had been previously diagnosed with dementia.

Despite prevalence estimates being high, formal diagnosis rates of dementia were very low across both countries (<1%). Further STRiDE investigations will provide indications of the impact and costs of dementia in these countries, but our results provide evidence that dementia needs to be prioritised within national health and social care policy agendas.

Cognitive stimulation therapy (CST) is the only non-pharmacological, treatment for dementia recommended by the UK National Institute for Health and Care Excellence, following multiple international trials demonstrating beneficial cognitive outcomes in people with mild-to-moderate dementia. However, there is limited understanding of whether treatment prognosis is influenced by sociodemographic and clinical variables (such as dementia subtype and gender), information which could inform clinical decision-making.

We describe the protocol for a systematic review and individual patient data meta-analysis assessing the prognostic factors related to CST. In publishing this protocol, we hope to increase the transparency of our work, and keep healthcare professionals aware of the latest evidence for effective CST.

A systematic review will be conducted with searches of the bibliographic databases Medline, EMBASE and PsycINFO, from inception to 7 February 2023. Studies will be included if they are clinical trials of CST, use the Alzheimer's Disease Assessment Scale – Cognitive Subscale (gold-standard measure of cognition in dementia in clinical trials) and include participants with mild-to-moderate dementia. Following harmonisation of the data-set, mixed-effect models will be constructed to explore the relationship between the prognostic indicators and change scores post-treatment.

This is the first individual patient data meta-analyses on CST, and has the potential to significantly optimise patient care. Previous analyses suggest people with advanced dementia could benefit more from CST treatment. Given that CST is currently used post-diagnosis in people with mild-to-moderate dementia, the implications of confirming this finding, among identifying other prognostic indicators, are profound.

In the connected world, although societies are not directly involved in a military conflict, they are exposed to media reports of violence.

We assessed the effects of such exposures on mental health in Germany during the military conflict in Ukraine.

We used the German population-based cohort for digital health research, DigiHero, launching a survey on the eighth day of the Russo-Ukrainian war. Of the 27 509 cohort participants from the general population, 19 444 (70.7%) responded within 17 days. We measured mental health and fear of the impact of war compared with other fears (natural disasters or health-related).

In a subsample of 4441 participants assessed twice, anxiety in the population (measured by the Generalised Anxiety Disorder-7 screener) was higher in the first weeks of war than during the strongest COVID-19 restrictions. Anxiety was elevated across the whole age spectrum, and the mean was above the cut-off for mild anxiety. Over 95% of participants expressed various degrees of fear of the impact of war, whereas the percentage for other investigated fears was 0.47–0.82. A one-point difference in the fear of the impact of war was associated with a 2.5 point (95% CI 2.42–2.58) increase in anxiety (11.9% of the maximum anxiety score). For emotional distress, the increase was 0.67 points (0.66–0.68) (16.75% of the maximum score).

The population in Germany reacted to the Russo-Ukrainian war with substantial distress, exceeding reactions during the strongest restrictions in the COVID-19 pandemic. Fear of the impact of war was associated with worse mental health.

There is cumulative evidence of the importance of exploring the change of dynamics between symptoms over time as reflective of consolidation of psychopathology.

To explore the interactions between symptoms of ICD-11 adjustment disorder before and after the second lockdown of the COVID-19 pandemic in Israel and identify the most central symptoms and their concurrent and prospective associations with probable adjustment disorder.

This is a population-based study drawn from a probability-based internet panel. A representative sample of the adult Israeli population was assessed at two time points (T1, pre-second lockdown, n = 1029, response rate 76.17%; T2, post-second lockdown, n = 764, response rate 74.24%). Symptoms of adjustment disorder were assessed by the International Adjustment Disorder Questionnaire (IADQ).

Although the overall strength of associations at the two measurement points was similar and two same communities were found, there was a significant change in their structure, with a more consolidated network at T2. The most central item was ‘difficult to relax’ in both networks. Cross-sectionally, all symptoms of failure to adapt significantly predicted adjustment disorder. ‘Worry a lot more’ (preoccupation) and ‘difficult to adapt to life’ (failure to adapt) at T1 significantly predicted this diagnosis at T2.

Adjustment disorder symptoms consolidated during the second lockdown of the pandemic. In line with the ICD-11 conceptualisation of adjustment disorder, both preoccupation and failure-to-adapt symptoms have prognostic validity. This highlights the importance of identifying and targeting adjustment disorder symptoms during a period of stress such as the COVID-19 pandemic.