Post-consultation acute respiratory tract infection recovery: a latent class-informed analysis of individual patient data.

BACKGROUND: There is a lack of evidence regarding post-consultation symptom trajectories for patients with respiratory tract infections (RTIs) and whether patient characteristics can be used to predict illness duration. AIM: To describe symptom trajectories in patients with RTIs, and assess baseline characteristics and adverse events associated with trajectories. DESIGN AND SETTING: The study included data about 9103 adults and children from 12 primary care studies. METHOD: A latent class-informed regression analysis of individual patient data from randomised controlled trials and observational cohort studies was undertaken. Post-consultation symptom trajectory (severity and duration), re-consultation with same or worsening illness, and admission to hospital were assessed. RESULTS: In total, 90% of participants recovered from all symptoms by 28 days, regardless of antibiotic prescribing strategy (none, immediate, and delayed antibiotics). For studies of RTI with cough as a dominant symptom (n = 5314), four trajectories were identified: 'rapid (6 days)' (90% of participants recovered within 6 days) in 52.0%; 'intermediate (10 days)' (28.9%); 'slow progressive improvement (27 days)' (12.5%); and 'slow improvement with initial high symptom burden (27 days)' (6.6%). For cough, being aged 16-64 years (odds ratio [OR] 2.57, 95% confidence interval [CI] = 1.72 to 3.85 compared with <16 years), higher presenting illness baseline severity (OR 1.51, 95% CI = 1.12 to 2.03), presence of lung disease (OR 1.78, 95% CI = 1.44 to 2.21), and median and above illness duration before consultation (≥7 days) (OR 1.99, 95% CI = 1.68 to 2.37) were associated with slower recovery (>10 days) compared with faster recovery (≤10 days). Re-consultations and admissions to hospital for cough were higher in those with slower recovery (ORs: 2.15, 95% CI = 1.78 to 2.60 and 7.42, 95% CI = 3.49 to 15.78, respectively). CONCLUSION: Older patients presenting with more severe, longer pre-consultation symptoms and chronic lung disease should be advised they are more likely to experience longer post-consultation illness durations, and that recovery rates are similar with and without antibiotics.

Supporting Weight Management during COVID-19 (SWiM-C): twelve-month follow-up of a randomised controlled trial of a web-based, ACT-based, guided self-help intervention.

OBJECTIVES: We developed a guided self-help intervention (Supporting Weight Management during COVID-19, "SWiM-C") to support adults with overweight or obesity in their weight management during the COVID-19 pandemic. This parallel, two-group trial (ISRCTN12107048) evaluated the effect of SWiM-C on weight and determinants of weight management over twelve months. METHODS: Participants (≥18 years, body-mass-index ≥25 kg/m2) were randomised to the SWiM-C intervention or to a standard advice group (unblinded). Participants completed online questionnaires at baseline, four months, and twelve months. The primary outcome was change in self-reported weight from baseline to twelve months; secondary outcomes were eating behaviour (uncontrolled eating, emotional eating, cognitive restraint of food intake), experiential avoidance, depression, anxiety, stress, wellbeing and physical activity. INTERVENTIONS: SWiM-C is based on acceptance and commitment therapy (ACT). Participants had access to an online web platform with 12 weekly modules and email and telephone contact with a trained, non-specialist coach. Standard advice was a leaflet on managing weight and mood during the COVID-19 pandemic. RESULTS: 388 participants were randomised (SWiM-C: n = 192, standard advice: n = 196). The baseline-adjusted difference in weight change between SWiM-C (n = 119) and standard advice (n = 147) was -0.81 kg (95% CI: -2.24 to 0.61 kg). SWiM-C participants reported a reduction in experiential avoidance (-2.45 [scale:10-70], 95% CI: -4.75 to -0.15), uncontrolled eating (-3.36 [scale: 0-100], 95% CI: -5.66 to -1.06), and emotional eating (-4.14 [scale:0-100], 95% CI: -7.25 to -1.02) and an increase in physical activity (8.96 [MET-min/week], 95% CI: 0.29 to 17.62) compared to standard advice participants. We found no evidence of an effect on remaining outcomes. No adverse events/side effects were reported. CONCLUSIONS: Whilst we were unable to conclude that the intervention had an effect on weight, SWiM-C improved eating behaviours, experiential avoidance and physical activity. Further refinement of the intervention is necessary to ensure meaningful effects on weight prior to implementation in practice. TRIAL REGISTRATION NUMBER: ISRCTN 12107048.

Supporting Weight Management During COVID (SWiM-C): A Randomized Trial of an ACT-Based Intervention

Background: We developed a web-based, acceptance-based, guided self-help intervention (Supporting Weight Management during COVID-19, "SWiM-C") which aimed to support adults with over-weight or obesity in their weight management and emotional well-being during the COVID-19 pandemic. This study evaluates the effect of SWiM-C on weight and determinants of weight over twelve months. Methods: We randomized 388 participants (>18 years, BMI >25kg/m2) to the SWiM-C intervention (n=192) or a control group (n=196). SWiM-C is based on acceptance and commitment therapy (ACT) and is delivered remotely via an online web platform (12 weekly modules) and contact via telephone and email with a trained, non-specialist coach. The control group received a leaflet on weight management and wellbeing during the pandemic. Participants completed online questionnaires at baseline, 4 months, and 12 months. The primary outcome was change in self-reported weight from baseline to 12 months;secondary outcomes were eating behavior, experiential avoidance, mental health, wellbeing and physical activity. Results: At 12 months, the adjusted difference in weight between SWiM-C and control group participants was -0.81kg (95% CI: -2.24 to 0.61kg). SWiM-C participants reported a greater reduction in experiential avoidance (-2.45, 95% CI: -4.75 to -0.15), uncontrolled eating (-3.36, 95% CI: -5.66 to -1.06), and emotional eating (-4.14, 95% CI: -7.25 to -1.02), and an increase in physical activity (8.96, 95% CI: 0.29 to 17.62) compared to the control group. No differences in mental health or wellbeing were observed at 12 months. Conclusions: Whilst the effect of the SWiM-C intervention on weight was inconclusive, SWiM-C improved eating behaviors, physical activity and psychological flexibility. These variables have been previously identified as determinants of successful weight management. Further refinement of the intervention is necessary to ensure meaningful effects on weight prior to implementation in practice. By being remotely delivered using non-specialists, SWiM-C enhances scalability and population reach while minimizing cost.

Self-sampling to identify pathogens and inflammatory markers in patients with acute sore throat: Feasibility study.

Introduction: Sore throat is a common reason for overuse of antibiotics. The value of inflammatory or biomarkers in throat swab or saliva samples in predicting benefit from antibiotics is unknown. Methods: We used the 'person-based approach' to develop an online tool to support self-swabbing and recruited adults and children with sore throats through participating general practices and social media. Participants took bacterial and viral swabs and a saliva sponge swab and passive drool sample. Bacterial swabs were cultured for streptococcus (Group A, B, C, F and G). The viral swab and saliva samples were tested using a routine respiratory panel PCR and Covid-19 PCR testing. We used remaining viral swab and saliva sample volume for biomarker analysis using a panel of 13 biomarkers. Results: We recruited 11 asymptomatic participants and 45 symptomatic participants. From 45 symptomatic participants, bacterial throat swab, viral throat swab, saliva sponge and saliva drool samples were returned by 41/45 (91.1%), 43/45 (95.6%), 43/45 (95.6%) and 43/45 (95.6%) participants respectively. Three saliva sponge and 6 saliva drool samples were of insufficient quantity. Two adult participants had positive bacterial swabs. Six participants had a virus detected from at least one sample (swab or saliva). All of the biomarkers assessed were detectable from all samples where there was sufficient volume for testing. For most biomarkers we found higher concentrations in the saliva samples. Due to low numbers, we were not able to compare biomarker concentrations in those who did and did not have a bacterial pathogen detected. We found no evidence of a difference between biomarker concentrations between the symptomatic and asymptomatic participants but the distributions were wide. Conclusions: We have demonstrated that it is feasible for patients with sore throat to self-swab and provide saliva samples for pathogen and biomarker analysis. Typical bacterial and viral pathogens were detected but at low prevalence rates. Further work is needed to determine if measuring biomarkers using oropharyngeal samples can help to differentiate between viral and bacterial pathogens in patients classified as medium or high risk using clinical scores, in order to better guide antibiotic prescribing and reduce inappropriate prescriptions.

Supporting Weight Management during COVID-19: A Randomized Controlled Trial of a Web-Based, ACT-Based, Guided Self-Help Intervention.

INTRODUCTION: Adults with overweight and obesity are vulnerable to weight gain and mental health deterioration during the COVID-19 pandemic. We developed a web-based, guided self-help intervention based on Acceptance and Commitment Therapy (ACT) that aims to support adults with overweight and obesity to prevent weight gain by helping them to manage their eating behaviours, be more physically active, and protect their emotional wellbeing ("SWiM-C"). SWiM-C is a guided self-help programme using non-specialist guides to enhance scalability and population reach while minimizing cost. This study evaluated the effect of SWiM-C on bodyweight, eating behaviour, physical activity, and mental wellbeing in adults with overweight and obesity over 4 months during the COVID-19 pandemic in the UK. METHODS: We randomized adults (BMI ≥25 kg/m2) to SWiM-C or to a wait-list standard advice group. Participants completed outcome assessments online at baseline and 4 months. The primary outcome was self-measured weight; secondary outcomes were eating behaviour, physical activity, experiential avoidance/psychological flexibility, depression, anxiety, stress, and wellbeing. We estimated differences between study groups in change in outcomes from baseline to 4 months using linear regression, adjusted for outcome at baseline and the randomization stratifiers (BMI, sex). The trial was pre-registered (ISRCTN12107048). RESULTS: 486 participants were assessed for eligibility; 388 participants were randomized (196 standard advice, 192 SWiM-C), and 324 were analysed. The adjusted difference in weight between SWiM-C and standard advice was -0.60 kg (-1.67 to 0.47, p = 0.27). SWiM-C led to improvements in uncontrolled eating (-3.61 [-5.94 to -1.28]), cognitive restraint (5.28 [2.81-7.75]), experiential avoidance (-3.39 [-5.55 to -1.23]), and wellbeing (0.13 [0.07-0.18]). CONCLUSIONS: SWiM-C improved several psychological determinants of successful weight management and had a protective effect on wellbeing during the pandemic. However, differences in weight and some other outcomes were compatible with no effect of the intervention, suggesting further refinement of the intervention is needed.

Infection Control Behavior at Home During the COVID-19 Pandemic: Observational Study of a Web-Based Behavioral Intervention (Germ Defence).

BACKGROUND: To control the COVID-19 pandemic, people should adopt protective behaviors at home (self-isolation, social distancing, putting shopping and packages aside, wearing face coverings, cleaning and disinfecting, and handwashing). There is currently limited support to help individuals conduct these behaviors. OBJECTIVE: This study aims to report current household infection control behaviors in the United Kingdom and examine how they might be improved. METHODS: This was a pragmatic cross-sectional observational study of anonymous participant data from Germ Defence between May 6-24, 2020. Germ Defence is an open-access fully automated website providing behavioral advice for infection control within households. A total of 28,285 users sought advice from four website pathways based on household status (advice to protect themselves generally, to protect others if the user was showing symptoms, to protect themselves if household members were showing symptoms, and to protect a household member who is at high risk). Users reported current infection control behaviors within the home and intentions to change these behaviors. RESULTS: Current behaviors varied across all infection control measures but were between sometimes (face covering: mean 1.61, SD 1.19; social distancing: mean 2.40, SD 1.22; isolating: mean 2.78, SD 1.29; putting packages and shopping aside: mean 2.75, SD 1.55) and quite often (cleaning and disinfecting: mean 3.17, SD 1.18), except for handwashing (very often: mean 4.00, SD 1.03). Behaviors were similar regardless of the website pathway used. After using Germ Defence, users recorded intentions to improve infection control behavior across all website pathways and for all behaviors (overall average infection control score mean difference 0.30, 95% CI 0.29-0.31). CONCLUSIONS: Self-reported infection control behaviors other than handwashing are lower than is optimal for infection prevention, although handwashing is much higher. Advice using behavior change techniques in Germ Defence led to intentions to improve these behaviors. Promoting Germ Defence within national and local public health and primary care guidance could reduce COVID-19 transmission.

Infection control in the home: a qualitative study exploring perceptions and experiences of adhering to protective behaviours in the home during the COVID-19 pandemic.

OBJECTIVES: We sought to explore people's experiences and perceptions of implementing infection control behaviours in the home during the COVID-19 pandemic, guided by an online behavioural intervention. DESIGN: Inductive qualitative study. SETTING: UK public during the COVID-19 pandemic. PARTICIPANTS: Thirteen people took part in telephone interviews, and 124 completed a qualitative open-text survey. All were recruited from the public. Most survey participants were aged over 60 years, while interview participants were more distributed in age. Most reported being at increased risk from COVID-19, and were white British. INTERVENTION: Online behavioural intervention to support infection control behaviours in the home during the COVID-19 pandemic. DATA COLLECTION: Telephone think-aloud interviews and qualitative survey data. DATA ANALYSIS: The think-aloud interview data and qualitative survey data were analysed independently using inductive thematic analysis. The findings were subsequently triangulated. RESULTS: Thematic analysis of the telephone interviews generated seven themes: perceived risk; belief in the effectiveness of protective behaviours; acceptability of distancing and isolation; having capacity to perform the behaviours; habit forming reduces effort; having the confidence to perform the behaviours; and social norms affect motivation to engage in the behaviours. The themes identified from the survey data mapped well onto the interview analysis. Isolating and social distancing at home were less acceptable than cleaning and handwashing, influenced by the need for intimacy with household members. This was especially true in the absence of symptoms and when perceived risk was low. People felt more empowered when they understood that even small changes, such as spending some time apart, were worthwhile to reduce exposure and lessen viral load. CONCLUSIONS: The current study provided valuable insight into the acceptability and feasibility of protective behaviours, and how public health guidance could be incorporated into a behaviour change intervention for the public during a pandemic.

Adapting Behavioral Interventions for a Changing Public Health Context: A Worked Example of Implementing a Digital Intervention During a Global Pandemic Using Rapid Optimisation Methods.

Background: A rigorous approach is needed to inform rapid adaptation and optimisation of behavioral interventions in evolving public health contexts, such as the Covid-19 pandemic. This helps ensure that interventions are relevant, persuasive, and feasible while remaining evidence-based. This paper provides a set of iterative methods to rapidly adapt and optimize an intervention during implementation. These methods are demonstrated through the example of optimizing an effective online handwashing intervention called Germ Defense. Methods: Three revised versions of the intervention were rapidly optimized and launched within short timeframes of 1-2 months. Optimisations were informed by: regular stakeholder engagement; emerging scientific evidence, and changing government guidance; rapid qualitative research (telephone think-aloud interviews and open-text surveys), and analyses of usage data. All feedback was rapidly collated, using the Table of Changes method from the Person-Based Approach to prioritize potential optimisations in terms of their likely impact on behavior change. Written feedback from stakeholders on each new iteration of the intervention also informed specific optimisations of the content. Results: Working closely with clinical stakeholders ensured that the intervention was clinically accurate, for example, confirming that information about transmission and exposure was consistent with evidence. Patient and Public Involvement (PPI) contributors identified important clarifications to intervention content, such as whether Covid-19 can be transmitted via air as well as surfaces, and ensured that information about difficult behaviors (such as self-isolation) was supportive and feasible. Iterative updates were made in line with emerging evidence, including changes to the information about face-coverings and opening windows. Qualitative research provided insights into barriers to engaging with the intervention and target behaviors, with open-text surveys providing a useful supplement to detailed think-aloud interviews. Usage data helped identify common points of disengagement, which guided decisions about optimisations. The Table of Changes was modified to facilitate rapid collation and prioritization of multiple sources of feedback to inform optimisations. Engagement with PPI informed the optimisation process. Conclusions: Rapid optimisation methods of this kind may in future be used to help improve the speed and efficiency of adaptation, optimization, and implementation of interventions, in line with calls for more rapid, pragmatic health research methods.