The COVID-19 pandemic posed an unprecedented global challenge, with past evidence suggesting negative psychological effects with the additional concern that social and physical restrictions might disproportionately affect adolescents.

To explore mental health and its wider determinants in young people in the UK during 1 year of the COVID-19 pandemic (August 2020–August 2021).

A representative sample of 11 898 participants (48.7% female) aged between 13 and 19 years (mean = 16.1) participated in five waves of data collection. Using validated self-reported questionnaires for loneliness, anxiety and depression, this survey measured the extent and nature of the mental health impacts of the coronavirus pandemic and help-seeking behaviours, and changes over time.

Young people experienced higher levels of anxiety during the summer and fall 2020, followed by higher levels of depression during the winter 2020–2021, with loneliness gradually increasing then peaking during the spring and summer of 2021. Young people who were older, female, with pre-existing mental-health issues and experiencing financial difficulties were at higher risk of anxiety, depression and loneliness. Help-seeking behaviours reduced the risk of depression and loneliness.

The COVID-19 pandemic had substantial impact on young people, whether on their mental health, their social contacts and interactions or their perspective on what the future holds for them. Young people strongly advocated for better teacher training, and a better integration of mental health services, particularly within their schools.

Autistic women are at high risk of developing restrictive eating disorders (REDs), such as anorexia nervosa.

This study provides an overview of the clinical characteristics of autistic women with REDs to (i) enhance understanding of increased risk, and (ii) support the identification of autistic women in eating disorder services.

We compared self-reported autistic and disordered eating characteristics of: autistic participants with REDs (Autism + REDs; n = 57); autistic participants without REDs (Autism; n = 69); and women with REDs who are not autistic (REDs; n = 80). We also included a group of women with high autistic traits (HATs) and REDs, but no formal autism diagnosis (HATs + REDs; n = 38).

Autism + REDs participants scored similarly to Autism participants in terms of autistic characteristics and to REDs participants in terms of experiencing traditional disordered eating symptoms. Autism + REDs participants were distinguished from both groups by having more restricted and repetitive behaviours and autism-specific eating behaviours related to sensory processing, flexibility and social differences. HATs + REDs participants showed a similar pattern of scores to Autism + REDs participants, and both also presented with high levels of co-occurring mental health difficulties, particularly social anxiety.

The presentation of autistic women with REDs is complex, including both traditional disordered eating symptoms and autism-related needs, as well as high levels of co-occurring mental health difficulties. In eating disorder services, the REDs presentation of autistic women and those with HATs should be formulated with reference to autism-specific eating behaviours and co-occurring difficulties. Treatment adaptations should be offered to accommodate autistic characteristics and related needs.

Approximately 6.5 million Americans ages 65 and older have Alzheimer’s disease and related dementias, a prevalence projected to triple by 2060. While subtle impairment in cognition and instrumental activities of daily living (IADLs) arises in the mild cognitive impairment (MCI) phase, early detection of these insidious changes is difficult to capture given limitations. Traditional IADL assessments administered infrequently are less sensitive to early MCI and not conducive to tracking subtle changes that precede significant declines. Continuous passive monitoring of IADLs using sensors and software in home environments is a promising alternative. The purpose of this study was to determine which remotely monitored IADLs best distinguish between MCI and normal cognition.

Participants were 65 years or older, independently community-dwelling, and had at least one daily medication and home internet access. Clinical assessments were performed at baseline. Electronic pillboxes (MedTracker) and computer software (Worktime) measured daily medication and computer habits using the Oregon Center for Aging and Technology (ORCATECH) platform. The Survey for Memory, Attention, and Reaction Time (SMART; Trail A, Trail B, and Stroop Tests) is a self-administered digital cognitive assessment that was deployed monthly. IADL data was aggregated for each participant at baseline (first 90 days) in each domain and various features developed for each. The receiver operating characteristic area under the curve (ROC-AUC) was calculated for each feature.

Traditional IADL Questionnaires.

At baseline, 103 participants (normal n = 59, Mage = 73.6±5.5; MCI n = 44, Mage = 76.0±6.1) completed three functional questionnaires (Functional Activities Questionnaire; Measurement of Everyday Cognition (ECog), both self-report and informant). The Informant ECog demonstrated the highest AUC (72% AUC, p = <.001).

Remotely monitored in-home IADLs and self-administered brief online cognitive test performance.

Eighty-four had medication data (normal n = 48, Mage = 73.2±5.4; MCI n = 36, Mage = 75.6±6.9). Four features related to pillbox-use frequency (73% AUC) and four features related to pillbox-use time (62% AUC) were developed. The discrepancy between self-reported frequency of use versus actual use was the most discriminating (67% AUC, p = .03).

Sixty-six had computer data (normal n = 38, Mage = 73.6±6.1; MCI n = 28, Mage = 76.6±6.8). Average usage time showed 64% AUC (p = .048) and usage variability showed 60% AUC (p = .18).

One hundred and two completed the SMART (normal n = 59, Mage = 73.6±5.5; MCI n = 43, Mage = 75.9±6.2). Eleven features related to survey completion time demonstrated 80% AUC in discriminating cognition. Eleven features related to the number of clicks during the survey demonstrated 70% AUC. Lastly, seven mouse movement features demonstrated 71% AUC.

Pillbox use frequency combined features and self-administered brief online cognitive test combined features (e.g., completion times, mouse cursor movements) have acceptable to excellent ability to discriminate between normal cognition and MCI and are relatively comparable to informant rated IADL questionnaires. General computer usage habits demonstrated lower discriminatory ability. Our approach has applied implications for detecting and tracking older adults’ declining cognition and function in real world contexts.

Subjective cognitive decline (SCD, i.e., perceived cognitive decline without neuropsychological deficits) is associated with Alzheimer’s disease pathology and increased risk for cognitive impairment but is heterogenous in etiology and has been linked to other factors including personality and depression. Mental wellbeing (i.e., the perception and functioning of social, emotional, and health-related aspects of one’s life) has been associated with subjective memory complaints, but its relationship with other subjective cognitive domains is poorly understood. Further characterizing the relationship between mental wellbeing and SCD could refine understanding of SCD and inform development of interventions that prevent progression to objective cognitive decline. This study aimed to describe the relationship between mental wellbeing and subjective decline in multiple cognitive domains and examine whether this relationship differs between older adults with normal cognition and those with mild cognitive impairment (MCI).

Community-dwelling older adults (normal: n = 58, Mage = 73.7±5.6; MCI: n = 43, Mage = 75.9±6.1) completed the Everyday Cognition scale, a validated self-report measure of SCD, and the RAND-36 Health Survey, a validated self-report measure of health-related quality of life which includes a mental wellbeing subscale. Spearman’s rank correlations were conducted between self-reported mental wellbeing and each self-reported cognitive domain (i.e., memory, language, visuospatial, and executive function) for the Normal Cognition and MCI groups.

Worse mental wellbeing was associated with worse subjective language and executive function in the normal group, rs(56) = -.42, p =.001; rs(56) = -.37, p =.005, but not for the MCI group, rs(41) = -.23, p =.15; rs(41) = -.12, p =.46. Worse mental wellbeing was associated with worse subjective visuospatial function in the MCI group, rs(41) = -.39, p =.009, but not in the normal group, rs(56) = -.11, p =.39. For both groups, worse mental wellbeing was associated with worse subjective memory, rs(56) = -.45, p < .001; rs(41) = -.37, p =.02. While this correlation was greater in the normal group, the difference was not significant (z = 0.38, p =.71).

These results suggest that perceptions of mental wellbeing are related to perceptions of cognitive decline in multiple domains, and that the specific domains involved differ between normal and MCI groups. The differential associations may mean perception of specific cognitive domains more strongly affect mental wellbeing, or mental wellbeing more acutely influences perception of those domains. The overall observed relationship between SCD and mental wellbeing may have several explanations: the impact of broader health perceptions may extend to cognitive perception, behavioral changes associated with poor wellbeing may reduce subjective cognitive function, or worse subjective cognitive function may lead to negative experiences of wellbeing. Future longitudinal investigation could inform causal inferences. The more limited associations between mental wellbeing and SCD among MCI individuals may point to the role of decreased self-awareness (due to cognitive impairment) precluding detection of subtle changes in cognition or wellbeing. This study highlights the importance of better understanding mental wellbeing in experiences of SCD in both normal and MCI older adults to improve cognitive and mental health outcomes.

An alternative surgical approach for hypoplastic left heart syndrome is the Hybrid pathway, which delays the risk of acute kidney injury outside of the newborn period. We sought to determine the incidence, and associated morbidity, of acute kidney injury after the comprehensive stage 2 and the cumulative incidence after the first two operations in the Hybrid pathway.

A single centre, retrospective study was conducted of hypoplastic left heart patients completing the second-stage palliation in the Hybrid pathway from 2009 to 2018. Acute kidney injury was defined utilising Kidney Diseases Improving Global Outcomes criteria. Perioperative and post-operative characteristics were analysed.

Sixty-one patients were included in the study cohort. The incidence of acute kidney injury was 63.9%, with 36.1% developing severe injury. Cumulatively after the Hybrid Stage 1 and comprehensive stage 2 procedures, 69% developed acute kidney injury with 36% developing severe injury. The presence of post-operative acute kidney injury was not associated with an increase in 30-day mortality (acute kidney injury 7.7% versus none 9.1%; p = > 0.9). There was a significantly longer median duration of intubation among those with acute kidney injury (acute kidney injury 32 (8, 155) hours vs. no injury 9 (0, 94) hours; p = 0.018).

Acute kidney injury after the comprehensive stage two procedure is common and accounts for most of the kidney injury in the first two operations of the Hybrid pathway. No difference in mortality was detected between those with acute kidney injury and those without, although there may be an increase in morbidity.