Deconstructing interventions: approaches to studying behavior change techniques across obesity interventions

Deconstructing interventions into the specific techniques that are used to change behavior represents a new frontier in behavioral intervention research. This paper considers opportunities and challenges in employing the Behavior Change Techniques Taxonomy (BCTTv1) developed by Michie and colleagues, to code the behavior change techniques (BCTs) across multiple interventions addressing obesity and capture dose received at the technique level. Numerous advantages were recognized for using a shared framework for intervention description. Coding interventions at levels of the social ecological framework beyond the individual level, separate coding for behavior change initiation vs. maintenance, fidelity of BCT delivery, accounting for BCTs mode of delivery, and tailoring BCTs, present both challenges and opportunities. Deconstructing interventions and identifying the dose required to positively impact health-related outcomes could enable important gains in intervention science

Health and social care staff responses to working with people with a learning disability who display sexual offending type behaviours

This study found that 59% of social care staff were currently supporting a client with a learning disability who had offended or displayed an offending type behaviour. The range of behaviours was similar to that displayed by clients in a secure health facility and included rape, sexual assault and exposure. Only 22.9% of social care staff had received training in this area, while none of the health stuff had. Both groups expressed low levels of confidence in supporting this client group. The areas of difficulty were common to both groups and included personal attitudes and attitudes of others to the behaviour, and concern over risk, responsibility and safety. In respect of attitudes, social care staff were found to be significantly more likely to hold negative attitudes towards the person's behaviour, while health staff were significantly more likely to feel negatively towards the person. Health staff were significantly more likely to identify training as a means of further support, while social care staff identified professional input. Both groups identified the need for theoretical training about working with this client group. Despite this no significant differences were found between those who had and had not received training and confidence, attitudes and the need for further support

Statistical Learning Methods to Identify Nonwear Periods From Accelerometer Data

Background: Accelerometers are used to objectively measure movement in free-living individuals. Distinguishing nonwear from sleep and sedentary behavior is important to derive accurate measures of physical activity, sedentary behavior, and sleep. We applied statistical learning approaches to examine their promise in detecting nonwear time and compared the results with commonly used wear time (WT) algorithms. Methods: Fifteen children, aged 4–17, wore an ActiGraph wGT3X- BT monitor on their hip during overnight polysomnography. We applied Hidden Markov Models (HMM) and Gaussian Mixture Models (GMM) to classify states of nonwear and wear in triaxial acceleration data. Performance of methods was compared with WT algorithms across two conditions with differing amounts of consecutive nonwear. Clinical scoring of polysomnography served as the gold standard. Results: When the length of nonwear was less than or equal to WT algorithms’ predefined thresholds for consecutive nonwear time, GMM methods yielded improved classification error, specificity, positive predictive value, and negative predictive value over commonly used algorithms. HMM was superior to one algorithm for sensitivity and negative predictive value. When the length of nonwear was longer, results were mixed, with the commonly used algorithms performing better on some parameters but GMM with the greatest specificity. However, all approached the upper limits of performance for almost all metrics. Conclusions: GMM and HMM demonstrated robust, consistently strong performance across multiple conditions, surpassing or remaining competitive with commonly used WT algorithms which had marked inaccuracy when nonwear time periods were shorter. Of the two statistical learning algorithms, GMM was superior to HMM

Dietary patterns and associations with body mass index in low-income, ethnic minority youth in the United States according to baseline data from four randomized controlled trials

Few studies have derived data-driven dietary patterns in youth in the United States (US). This study examined data-driven dietary patterns and their associations with BMI measures in predominantly low-income, racial/ethnic minority US youth. Data were from baseline assessments of the four Childhood Obesity Prevention and Treatment Research (COPTR) Consortium trials: NET-Works (N=534; 2–4-year-olds), GROW (N=610; 3–5-year-olds), GOALS (N=241; 7–11-year-olds), and IMPACT (N=360; 10–13-year-olds). Weight and height were measured. Children/adult proxies completed 3 24-hour dietary recalls. Dietary patterns were derived for each site from 24 food/beverage groups using k-means cluster analysis. Multivariable linear regression models examined associations of dietary patterns with BMI and percentage of the 95th BMI percentile. Healthy (produce and whole grains) and Unhealthy (fried food, savory snacks, and desserts) patterns were found in NET-Works and GROW. GROW additionally had a dairy and sugar-sweetened beverage based pattern. GOALS had a similar Healthy pattern and a pattern resembling a traditional Mexican diet. Associations between dietary patterns and BMI were only observed in IMPACT. In IMPACT, youth in the Sandwich (cold cuts, refined grains, cheese, and miscellaneous [e.g., condiments]) compared to Mixed (whole grains and desserts) cluster had significantly higher BMI [β=0.99 (95% CI: 0.01, 1.97)] and percentage of the 95th BMI percentile [β=4.17 (95% CI: 0.11, 8.24)]. Healthy and Unhealthy patterns were the most common dietary patterns in COPTR youth, but diets may differ according to age, race/ethnicity, or geographic location. Public health messages focused on healthy dietary substitutions may help youth mimic a dietary pattern associated with lower BMI

Adjunctive rifampicin for Staphylococcus aureus bacteraemia (ARREST): a multicentre, randomised, double-blind, placebo-controlled trial.

BACKGROUND: Staphylococcus aureus bacteraemia is a common cause of severe community-acquired and hospital-acquired infection worldwide. We tested the hypothesis that adjunctive rifampicin would reduce bacteriologically confirmed treatment failure or disease recurrence, or death, by enhancing early S aureus killing, sterilising infected foci and blood faster, and reducing risks of dissemination and metastatic infection. METHODS: In this multicentre, randomised, double-blind, placebo-controlled trial, adults (≥18 years) with S aureus bacteraemia who had received ≤96 h of active antibiotic therapy were recruited from 29 UK hospitals. Patients were randomly assigned (1:1) via a computer-generated sequential randomisation list to receive 2 weeks of adjunctive rifampicin (600 mg or 900 mg per day according to weight, oral or intravenous) versus identical placebo, together with standard antibiotic therapy. Randomisation was stratified by centre. Patients, investigators, and those caring for the patients were masked to group allocation. The primary outcome was time to bacteriologically confirmed treatment failure or disease recurrence, or death (all-cause), from randomisation to 12 weeks, adjudicated by an independent review committee masked to the treatment. Analysis was intention to treat. This trial was registered, number ISRCTN37666216, and is closed to new participants. FINDINGS: Between Dec 10, 2012, and Oct 25, 2016, 758 eligible participants were randomly assigned: 370 to rifampicin and 388 to placebo. 485 (64%) participants had community-acquired S aureus infections, and 132 (17%) had nosocomial S aureus infections. 47 (6%) had meticillin-resistant infections. 301 (40%) participants had an initial deep infection focus. Standard antibiotics were given for 29 (IQR 18-45) days; 619 (82%) participants received flucloxacillin. By week 12, 62 (17%) of participants who received rifampicin versus 71 (18%) who received placebo experienced treatment failure or disease recurrence, or died (absolute risk difference -1·4%, 95% CI -7·0 to 4·3; hazard ratio 0·96, 0·68-1·35, p=0·81). From randomisation to 12 weeks, no evidence of differences in serious (p=0·17) or grade 3-4 (p=0·36) adverse events were observed; however, 63 (17%) participants in the rifampicin group versus 39 (10%) in the placebo group had antibiotic or trial drug-modifying adverse events (p=0·004), and 24 (6%) versus six (2%) had drug interactions (p=0·0005). INTERPRETATION: Adjunctive rifampicin provided no overall benefit over standard antibiotic therapy in adults with S aureus bacteraemia. FUNDING: UK National Institute for Health Research Health Technology Assessment

Health and social care workers' knowledge and application of the concept of duty of care

This study used vignettes to examine the understanding and application of the concept of duty of care by health and social care staff working in learning disability services, and the relationship of this to promoting client choice. The study found that health care staff had a significantly broader understanding of the concept of duty of care than social care staff, and were significantly more likely to emphasise client safety. Implications of the findings are discussed

An Evaluation of the Impact of a One-Day Challenging Behaviour Course on the Knowledge of Health and Social Care Staff Working in Learning Disability Services

The present study evaluates the impact of a one-day challenging behaviour course on the knowledge of 59 staff (20 health, 20 social care, 19 day care) as compared with a control group (n = 73). The study found that training led to a significant increase in knowledge in the trained group on all factors but one. This was the identification of the main factors important in responding to challenging behaviour. In relation to this, staff appeared to identify only those factors either which would clearly be within their remit or which they would be more likely to use in their daily work, e.g. health staff identifying psychological approaches, day care and residential staff identifying reactive strategies. Gains in knowledge were found to be similar in those groups followed up immediately, 3–6 months and 6–12 months after training. No significant differences in scores between baseline and follow-up were found for the group who had not received training

Effects of Varying Epoch Lengths, Wear Time Algorithms, and Activity Cut-Points on Estimates of Child Sedentary Behavior and Physical Activity from Accelerometer Data

<div><p>Objective</p><p>To examine the effects of accelerometer epoch lengths, wear time (WT) algorithms, and activity cut-points on estimates of WT, sedentary behavior (SB), and physical activity (PA).</p><p>Methods</p><p>268 7–11 year-olds with BMI ≥ 85^th percentile for age and sex wore accelerometers on their right hips for 4–7 days. Data were processed and analyzed at epoch lengths of 1-, 5-, 10-, 15-, 30-, and 60-seconds. For each epoch length, WT minutes/day was determined using three common WT algorithms, and minutes/day and percent time spent in SB, light (LPA), moderate (MPA), and vigorous (VPA) PA were determined using five common activity cut-points. ANOVA tested differences in WT, SB, LPA, MPA, VPA, and MVPA when using the different epoch lengths, WT algorithms, and activity cut-points.</p><p>Results</p><p>WT minutes/day varied significantly by epoch length when using the NHANES WT algorithm (p < .0001), but did not vary significantly by epoch length when using the ≥ 20 minute consecutive zero or Choi WT algorithms. Minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA varied significantly by epoch length for all sets of activity cut-points tested with all three WT algorithms (all p < .0001). Across all epoch lengths, minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA also varied significantly across all sets of activity cut-points with all three WT algorithms (all p < .0001).</p><p>Conclusions</p><p>The common practice of converting WT algorithms and activity cut-point definitions to match different epoch lengths may introduce significant errors. Estimates of SB and PA from studies that process and analyze data using different epoch lengths, WT algorithms, and/or activity cut-points are not comparable, potentially leading to very different results, interpretations, and conclusions, misleading research and public policy.</p></div