Technology Matters: The human touch in a digital age – a blended approach in mental healthcare delivery with children and young people

Online psychological interventions have the potential to address many current issues facing service provision in child and adolescent mental health, not least improving access to evidence‐based therapies and providing greater patient choice. Recognising this, the National Institute for Health and Care Excellence (NICE) now recommend digitally delivered therapy in the treatment of depression in children and young people (CYP). However, despite the virtual ubiquity of technology in young people’s lives, and good evidence that online treatments can be effective, there remain barriers to real‐world implementation. We argue that remote therapist support and blended approaches to therapy will be important models in harnessing the potential of digital technology in CYP mental health

The normalisation of \u27excessive\u27 workforce drug testing?

In \u27The normalization of \u27sensible\u27 recreational drug use\u27 Parker, Williams and Aldridge (2002) present data on illegal drug use by adolescents and young adults in the UK. They argue that it is both widespread and largely socially benign - ie, normal. We contrast this \u27normalisation\u27 thesis with evidence of an increase in the introduction of drug policies - and drug testing - in British organisations. Such policies construct employee drug use as excessive enough to necessitate heightened management vigilance over workers, in order to preserve corporate interests. These contrasting representations of drug use inspire our discussion. We deploy the normal/ excessive couplet to unpick drug taking, to examine organisational drug policies and to comment upon emerging and potential resistance to these policies. Our contribution is to suggest that each of these activities can be understood as simultaneously normal and excessive, in an area where orthodox and critical analyses alike tend to be far more dualistic. <br /

The COVID-19 pandemic and its impact on tic symptoms in children and young people: a prospective cohort study

To understand how children and young people with tic disorders were affected by COVID-19, we compared pre and during pandemic scores on the Yale Global Tic Severity Scale (YGTSS). Participants were young people (N = 112; male:78%; 9–17 years) randomised to the control arm of the “ORBIT-Trial” (ISRCTN70758207, ClinicalTrials.gov-NCT03483493). For this analysis, the control arm was split into two groups: one group was followed up to 12-months’ post-randomisation before the pandemic started (pre-COVID group, n = 44); the other group was impacted by the pandemic at the 12-month follow-up (during-COVID group, n = 47). Mixed effects linear regression modelling was conducted to explore differences in YGTSS at 6- and 12-months post-randomisation. There were no significant differences in tic symptom or severity between participants who were assessed before and during COVID-19. This finding was not influenced by age, gender, symptoms of anxiety or autism spectrum disorder. Thus, the COVID-19 pandemic did not significantly impact existing tic symptoms

The COVID-19 pandemic and its impact on tic symptoms in children and young people: a prospective cohort study

To understand how children and young people with tic disorders were affected by COVID-19, we compared pre and during pandemic scores on the Yale Global Tic Severity Scale (YGTSS). Participants were young people (N = 112; male:78%; 9–17 years) randomised to the control arm of the “ORBIT-Trial” (ISRCTN70758207, ClinicalTrials.gov-NCT03483493). For this analysis, the control arm was split into two groups: one group was followed up to 12-months’ post-randomisation before the pandemic started (pre-COVID group, n = 44); the other group was impacted by the pandemic at the 12-month follow-up (during-COVID group, n = 47). Mixed effects linear regression modelling was conducted to explore differences in YGTSS at 6- and 12-months post-randomisation. There were no significant differences in tic symptom or severity between participants who were assessed before and during COVID-19. This finding was not influenced by age, gender, symptoms of anxiety or autism spectrum disorder. Thus, the COVID-19 pandemic did not significantly impact existing tic symptoms

How many are at increased risk of severe COVID-19 disease? Rapid global, regional and national estimates for 2020

BackgroundThe risk of severe COVID-19 disease is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 illness, and how this varies between countries may inform the design of possible strategies to shield those at highest risk.MethodsWe estimated the number of individuals at increased risk of severe COVID-19 disease by age (5-year age groups), sex and country (n=188) based on prevalence data from the Global Burden of Disease (GBD) study for 2017 and United Nations population estimates for 2020. We also calculated the number of individuals without an underlying condition that could be considered at-risk because of their age, using thresholds from 50-70 years. The list of underlying conditions relevant to COVID-19 disease was determined by mapping conditions listed in GBD to the guidelines published by WHO and public health agencies in the UK and US. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity.ResultsWe estimate that 1.7 (1.0 - 2.4) billion individuals (22% [15-28%] of the global population) are at increased risk of severe COVID-19 disease. The share of the population at increased risk ranges from 16% in Africa to 31% in Europe. Chronic kidney disease (CKD), cardiovascular disease (CVD), diabetes and chronic respiratory disease (CRD) were the most prevalent conditions in males and females aged 50+ years. African countries with a high prevalence of HIV/AIDS and Island countries with a high prevalence of diabetes, also had a high share of the population at increased risk. The prevalence of multimorbidity (&gt;1 underlying conditions) was three times higher in Europe than in Africa (10% vs 3%).ConclusionBased on current guidelines and prevalence data from GBD, we estimate that one in five individuals worldwide has a condition that is on the list of those at increased risk of severe COVID-19 disease. However, for many of these individuals the underlying condition will be undiagnosed or not severe enough to be captured in health systems, and in some cases the increase in risk may be quite modest. There is an urgent need for robust analyses of the risks associated with different underlying conditions so that countries can identify the highest risk groups and develop targeted shielding policies to mitigate the effects of the COVID-19 pandemic.Research in contextEvidence before this studyAs the COVID-19 pandemic evolves, countries are considering policies of ‘shielding’ the most vulnerable, but there is currently very limited evidence on the number of individuals that might need to be shielded. Guidelines on who is currently believed to be at increased risk of severe COVID-19 illness have been published online by the WHO and public health agencies in the UK and US. We searched PubMed (“Risk factors” AND “COVID-19”) without language restrictions, from database inception until April 5, 2020, and identified 62 studies published between Feb 15, 2020 and March 20, 2020. Evidence from China, Italy and the USA indicates that older individuals, males and those with underlying conditions, such as CVD, diabetes and CRD, are at greater risk of severe COVID-19 illness and death.Added value of this studyThis study combines evidence from large international databases and new analysis of large multimorbidity studies to inform policymakers about the number of individuals that may be at increased risk of severe COVID-19 illness in different countries. We developed a tool for rapid assessments of the number and percentage of country populations that would need to be targeted under different shielding policies.Implications of all the available evidenceQuantifying how many and who is at increased risk of severe COVID-19 illness is critical to help countries design more effective interventions to protect vulnerable individuals and reduce pressure on health systems. This information can also inform a broader assessment of the health, social and economic implications of shielding various groups.</jats:sec

Relative recency influences object-in-context memory

In two experiments rats received training on an object-in-context (OIC) task, in which they received preexposure to object A in context x, followed by exposure to object B in context y. In a subsequent test both A and B are presented in either context x or context y. Usually more exploration is seen of the object that has not previously been paired with the test context, an effect attributed to the ability to remember where an object was encountered. However, in the typical version of this task, object A has also been encountered less recently than object B at test. This is precisely the arrangement in tests of ‘relatively recency’ (RR), in which more remotely presented objects are explored more than objects experienced more recently. RR could contaminate performance on the OIC task, by enhancing the OIC effect when animals are tested in context y, and masking it when the test is in context x. This possibility was examined in two experiments, and evidence for superior performance in context y was obtained. The implications of this for theoretical interpretations of recognition memory and the procedures used to explore it are discussed

Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study.

BACKGROUND: The risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk. METHODS: We estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as "at increased risk of severe COVID-19" in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection-hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection-hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies. FINDINGS: We estimated that 1·7 billion (UI 1·0-2·4) people, comprising 22% (UI 15-28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from 66% of those aged 70 years or older). We estimated that 349 million (186-787) people (4% [3-9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from <1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3-12) of males to be at high risk compared with 3% (2-7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease. INTERPRETATION: About one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds. FUNDING: UK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research

Opportunities and challenges of delivering digital clinical trials: lessons learned from a randomised controlled trial of an online behavioural intervention for children and young people

Background: Despite being the gold standard of research to determine effectiveness, randomised controlled trials (RCTs) often struggle with participant recruitment, engagement and retention. These issues may be exacerbated when recruiting vulnerable populations, such as participants with mental health issues. We aimed to update understanding of the scope of these problems in trials of health technology, and identify possible solutions through reflecting on experiences from an exemplar trial (Online Remote Behavioural Intervention for Tics; ORBIT).Method: We extracted anonymised data on recruitment, retention and requests for more funding and time from trials funded by the largest funder of health technology trials in the UK (the National Institute of Health Research Health Technology Assessment) between 2010-2020, and compared these with data from a recent, successful trial (ORBIT). ORBIT aimed to assess the clinical- and cost-effectiveness of blended online and human behavioural therapy for tics in young people. Many of the trial procedures, including recruitment, the intervention and data collection, were undertaken online. Results: Data were extracted on 51 trials conducted between 2010 and 2020. 60% of trials failed to reach their original recruitment target and only 44% achieved their follow-up in the specified time frame. In contrast, ORBIT recruited to target and achieved 90% follow up. We posit that these achievements are related to a) judicious use of digital technology for trial procedures and b) adequate numbers of highly trained and motivated trial staff. We provide details of both these to help other research teams plan and cost for successful trials. Conclusion: An approach combining human and online methods may be advantageous in facilitating trial delivery, particularly in paediatric mental health services. Given the importance of successful clinical trials in advancing healthcare delivery and the waste of human and economic resources associated with unsuccessfully delivered trials, it is imperative that trials are appropriately costed and future research focusses on improving trial design and delivery. Trial registration: The ORBIT Trial is registered with ISRTCN (ISRCTN70758207) and clinicaltrials.gov (NCT03483493)