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BackgroundBehavioural and cognitive interventions remain a credible approach in preventing loneliness and depression. There was a need to rapidly generate and assimilate trial-based data during COVID-19. ObjectivesWe undertook a COVID-19 parallel pilot RCT of behavioural activation for depression and loneliness [the BASIL-C19 trial ISRCTN94091479]. We also assimilate these data in a COVID-19 living systematic review [PROSPERO CRD42021298788]. MethodsPrimary care participants (>=65 years) with long-term conditions were computer randomised to Behavioural Activation (n=47) versus care-as-usual (n=49). The single blinded primary outcome was the PHQ-9. Secondary outcomes included loneliness (De Jong Gierveld Scale). Data from the BASIL-C19 trial were included in a random effects meta-analysis of depression and loneliness. FindingsThe 12 months adjusted mean difference for PHQ-9 was -0.70 (95% CI -2.61 to 1.20) and for loneliness was -0.39 (95% CI -1.43 to 0.65). Secondary 12-month trial outcomes suggested evidence of benefit for behavioural activation. The BASIL-C19 meta-analysis (13 trials) found short-term reductions in depression (standardised mean difference [SMD]=-0.31, 95%CI -0.51 to -0.11) and loneliness (SMD=-0.48, 95%CI -0.70 to -0.27). There were few long-term trials, but there was evidence of some benefit (loneliness SMD=-0.20, 95%CI -0.40 to -0.01; depression SMD=-0.20, 95%CI -0.47 to 0.07). DiscussionWe found a signal of effect in reducing loneliness and depression in the BASIL trial. Living meta-analysis provides strong evidence of short-term benefit for loneliness and depression. Clinical implicationsScalable behavioural and cognitive approaches should be considered as population-level strategies for depression and loneliness on the basis of the living systematic review. FundingThis study was funded by National Institute for Health and Care Research (NIHR) Programme Grants for Applied Research (PGfAR) RP-PG-0217-20006. Author summaryO_ST_ABSWhy was this study done?C_ST_ABS Older people with long-term conditions have been impacted by COVID-19 pandemic restrictions and have experienced social isolation. In turn, this puts them at risk for depression and loneliness, and these are bad for health and wellbeing. Psychosocial approaches, such as behavioural activation, could be helpful. Trial-based evidence is needed to demonstrate if it is possible to prevent the onset, or mitigate the impact, of loneliness and depression. There are few studies of brief psychosocial interventions to mitigate depression and loneliness, and it is important to know how emerging trial-based data adds to existing evidence. What did the researchers do and find? There was preliminary evidence that levels of loneliness were reduced at 3 months when behavioural activation was offered. At longer term (12-month) follow-up there were signals of ongoing positive impact. When BASIL-C19 data were assimilated into a living systematic review there is clear evidence of impact of brief psychological interventions on depression and loneliness in the short-term. More research into the longer-term impact is needed. What does all this mean? Behavioural activation now shows evidence of benefit which will be useful for policy makers in offering support to people who are socially isolated. This research knowledge will be useful once the COVID-19 pandemic has passed, since loneliness is common in older populations and effective scalable solutions will be needed to tackle this problem. As new trial-based data emerges, our living systematic review and meta-analysis will be updated since this is an area of active research.
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ImportancePredictive models can help identify SARS-CoV-2 patients at greatest risk of post-COVID sequelae and direct them towards appropriate care. ObjectiveTo develop and internally validate a model to predict children and young people most likely to experience at least one impairing physical symptom 3 months after a SARS-CoV-2 PCR-test and to determine whether the impact of these predictors differed by SARS-CoV-2 infection status. DesignPotential pre-specified predictors included: SARS-CoV-2 status, sex, age, ethnicity, deprivation, quality of life/functioning (5 EQ-5D-Y items), physical and mental health, and loneliness (all prior to SARS-CoV-2 testing), and number of physical symptoms at testing. Logistic regression was used to develop the model. Model performance was assessed using calibration and discrimination measures; internal validation was performed via bootstrapping; the final model was adjusted for overfitting. SettingNational cohort study of SARS-CoV-2 PCR-positive and PCR-negative participants matched according to age, sex, and geographical area. ParticipantsChildren and young people aged 11-17 years who were tested for SARS-CoV-2 infection in England, January to March 2021. Main outcome measureone or more physical symptom 3 months after initial PCR-testing which affected physical, mental or social well-being and interfered with daily living. ResultsA total of 50,836 children and young people were approached; 7,096 (3,227 test-positives, 3,869 test-negatives) who completed a questionnaire 3 months after their PCR-test were included. 39.6% (1,279/3,227) of SAR-CoV-2 PCR-positives and 30.6% (1,184/3,869) of SAR-CoV-2 PCR-negatives had at least one impairing physical symptom 3 months post-test. The final model contained predictors: SARS-COV-2 status, number of symptoms at testing, sex, age, ethnicity, self-rated physical and mental health, feelings of loneliness and four EQ-5D-Y items before testing. Internal validation showed minimal overfitting with excellent calibration and discrimination measures (optimism adjusted calibration slope:0.97527; C-statistic:0.83640). Conclusions and relevanceWe developed a risk prediction equation to identify those most at risk of experiencing at least one impairing physical symptom 3 months after a SARS-CoV-2 PCR-test which could serve as a useful triage and management tool for children and young people during the ongoing pandemic. External validation is required before large-scale implementation. Key PointsO_ST_ABSQuestionC_ST_ABSWhich children have impairing physical symptoms during the COVID-19 pandemic? FindingsUsing data from a large national matched cohort study in children and young people (CYP) aged 11-17 years (N=7,096), we developed a prediction model for experiencing at least one impairing physical symptom 3 months after testing for SARS-COV-2. Our model had excellent predictive ability, calibration and discrimination; we used it to produce a risk estimation calculator. MeaningOur developed risk calculator could serve as a useful tool in the early identification and management of CYP at risk of persisting physical symptoms in the context of the COVID-19 pandemic.
