Longitudinal evidence on how Internet use affects the psychological wellbeing of older adults has been mixed. As policymakers invest in efforts to reduce the digital divide, it is important to have robust evidence on whether encouraging Internet use among older adults is beneficial, or potentially detrimental, to their wellbeing.

We observe depressive symptoms and loneliness of adults aged 50 + in the nationally representative English Longitudinal Study of Ageing, from before (2018/19) to during the coronavirus disease 2019 (COVID-19) pandemic (June/July and November/December 2020). Our quasi-experimental difference-in-differences strategy compares within-individual wellbeing changes between older adults who desired to use the Internet more but experienced barriers including lack of skills, access, and equipment, with regular Internet users who did not desire to use the Internet more. To reduce selection bias, we match both groups on demographic and socioeconomic characteristics that are predictive of Internet use. We assume that in the absence of COVID-19 – a period of increased reliance on the Internet – the wellbeing trajectories of both groups would have followed a common trend.

Compared with matched controls (N = 2983), participants reporting barriers to Internet use (N = 802) experienced a greater increase in the likelihood of depressive symptoms from before to during the pandemic, but not worse loneliness levels. This effect was stronger for women, those aged above 65 years, and those from lower-income households.

Besides enabling access to digital services, efforts to ensure older adults continue to be engaged members of an increasingly digital society could deliver returns in terms of a buffer against psychological distress.

Research suggests that there have been inequalities in the impact of the coronavirus disease 2019 (COVID-19) pandemic and related non-pharmaceutical interventions on population mental health. We explored generational, sex, and socioeconomic inequalities during the first year of the pandemic using nationally representative cohorts from the UK.

We analysed data from 26772 participants from five longitudinal cohorts representing generations born between 1946 and 2000, collected in May 2020, September–October 2020, and February–March 2021 across all five cohorts. We used a multilevel growth curve modelling approach to investigate generational, sex, and socioeconomic differences in levels of anxiety and depressive symptomatology, loneliness, and life satisfaction (LS) over time.

Younger generations had worse levels of mental and social wellbeing throughout the first year of the pandemic. Whereas these generational inequalities narrowed between the first and last observation periods for LS [−0.33 (95% CI −0.51 to −0.15)], they became larger for anxiety [0.22 (0.10, 0.33)]. Generational inequalities in depression and loneliness did not change between the first and last observation periods, but initial depression levels of the youngest cohort were worse than expected if the generational inequalities had not accelerated. Women and those experiencing financial difficulties had worse initial mental and social wellbeing levels than men and those financially living comfortably, respectively, and these gaps did not substantially differ between the first and last observation periods.

By March 2021, mental and social wellbeing inequalities persisted in the UK adult population. Pre-existing generational inequalities may have been exacerbated with the pandemic onset. Policies aimed at protecting vulnerable groups are needed.

The Research Domain Criteria (RDoC) approach proposes a novel psychiatric nosology using transdiagnostic dimensional mechanistic constructs. One candidate RDoC indicator is delay discounting (DD), a behavioral economic measure of impulsivity, based predominantly on studies examining DD and individual conditions. The current study sought to evaluate the transdiagnostic significance of DD in relation to several psychiatric conditions concurrently.

Participants were 1388 community adults (18–65) who completed an in-person assessment, including measures of DD, substance use, depression, anxiety, posttraumatic stress disorder, and attention-deficit hyperactivity disorder (ADHD). Relations between DD and psychopathology were examined with three strategies: first, examining differences by individual condition using clinical cut-offs; second, examining DD in relation to latent psychopathology variables via principal components analysis (PCA); and third, examining DD and all psychopathology simultaneously via structural equation modeling (SEM).

Individual analyses revealed elevations in DD were present in participants screening positive for multiple substance use disorders (tobacco, cannabis, and drug use disorder), ADHD, major depressive disorder (MDD), and an anxiety disorder (ps < 0.05–0.001). The PCA produced two latent components (substance involvement v. the other mental health indicators) and DD was significantly associated with both (ps < 0.001). In the SEM, unique significant positive associations were observed between the DD latent variable and tobacco, cannabis, and MDD (ps < 0.05–0.001).

These results provide some support for DD as a transdiagnostic indicator, but also suggest that studies of individual syndromes may include confounding via comorbidities. Further systematic investigation of DD as an RDoC indicator is warranted.

Treatment-resistant schizophrenia (TRS) and non-TRS may be associated with different dopaminergic and glutamatergic regulations. The concept of dysregulated glutamatergic concentrations in specific brain regions remains controversial. Herein, we aimed to assess (i) the distribution of the glutamatergic concentration in the brain, (ii) the association between working memory (WM) differences in TRS and non-TRS patients, and (iii) whether an alteration in the glutamate (Glu) level is associated with WM.

The participants included 38 TRS patients, 35 non-TRS patients, and 19 healthy controls (HCs), all of whom underwent 1.5-Tesla proton magnetic resonance spectroscopy of anterior cingulate cortex (ACC) and medial prefrontal cortex (MPFC). The ratios of glutamatergic neurometabolites to N-acetylaspartate + N-acetyl aspartylglutamate (NAAx) were calculated. Cognitive function was assessed using the Wechsler Adult Intelligence Scales, 4th Edition, which included the working memory index (WMI).

The TRS patients had a higher glutamate + glutamine (Glx)/NAAx ratio compared to the non-TRS patients and HCs in the ACC, but this was not significantly different in the MPFC. WM was negatively correlated with Glx/NAAx in the ACC among the non-TRS patients, but not in the TRS patients or HCs.

Our findings were consistent with most studies indicating that the glutamatergic concentration in the ACC plays important roles in the classification of TRS and cognition. Our results may provide potential evidence for predictors and treatment response biomarkers in TRS patients. Further research is needed to probe the value using the relationship between Glu and WM as a potential prognostic predictor of schizophrenia.