Children's daily travel to school in Johannesburg-Soweto, South Africa: geography and school choice in the Birth to Twenty cohort study

This paper has two aims: to explore approaches to the measurement of children’s daily travel to school in a context of limited geospatial data availability, and to provide data regarding school choice and distance travelled to school in Soweto-Johannesburg, South Africa. The paper makes use of data from the Birth to Twenty cohort study (n=1428) to explore three different approaches to estimating school choice and travel to school. Firstly, straight-line distance between home and school is calculated. Secondly, census geography is used to determine whether a child's home and school fall in the same area. Thirdly, distance data are used to determine whether a child attends the nearest school. Each of these approaches highlights a different aspect of mobility, and all provide valuable data. Overall, primary school aged children in Soweto-Johannesburg are shown to be travelling substantial distances to school on a daily basis. Over a third travel more than 3km, one-way, to school, 60% attend schools outside of the suburb in which they live, and only 18% attend their nearest school. These data provide evidence for high levels of school choice in Johannesburg-Soweto, and that families and children are making substantial investments in pursuit of high quality educational opportunities. Additionally, these data suggest that two patterns of school choice are evident: one pattern involving travel of substantial distances and requiring a higher level of financial investment, and a second pattern, involving choice between more local schools, requiring less travel and a more limited financial investment

Development of a digital biomarker and intervention for subclinical depression: study protocol for a longitudinal waitlist control study

Background Depression remains a global health problem, with its prevalence rising worldwide. Digital biomarkers are increasingly investigated to initiate and tailor scalable interventions targeting depression. Due to the steady influx of new cases, focusing on treatment alone will not suffice; academics and practitioners need to focus on the prevention of depression (i.e., addressing subclinical depression). Aim With our study, we aim to (i) develop digital biomarkers for subclinical symptoms of depression, (ii) develop digital biomarkers for severity of subclinical depression, and (iii) investigate the efficacy of a digital intervention in reducing symptoms and severity of subclinical depression. Method Participants will interact with the digital intervention BEDDA consisting of a scripted conversational agent, the slow-paced breathing training Breeze, and actionable advice for different symptoms. The intervention comprises 30 daily interactions to be completed in less than 45 days. We will collect self-reports regarding mood, agitation, anhedonia (proximal outcomes; first objective), self-reports regarding depression severity (primary distal outcome; second and third objective), anxiety severity (secondary distal outcome; second and third objective), stress (secondary distal outcome; second and third objective), voice, and breathing. A subsample of 25% of the participants will use smartwatches to record physiological data (e.g., heart-rate, heart-rate variability), which will be used in the analyses for all three objectives. Discussion Digital voice- and breathing-based biomarkers may improve diagnosis, prevention, and care by enabling an unobtrusive and either complementary or alternative assessment to self-reports. Furthermore, our results may advance our understanding of underlying psychophysiological changes in subclinical depression. Our study also provides further evidence regarding the efficacy of standalone digital health interventions to prevent depression. Trial registration Ethics approval was provided by the Ethics Commission of ETH Zurich (EK-2022-N-31) and the study was registered in the ISRCTN registry (Reference number: ISRCTN38841716, Submission date: 20/08/2022)

Just-in-Time Adaptive Mechanisms of Popular Mobile Apps for Individuals With Depression: Systematic App Search and Literature Review

BACKGROUND The number of smartphone apps that focus on the prevention, diagnosis, and treatment of depression is increasing. A promising approach to increase the effectiveness of the apps while reducing the individual's burden is the use of just-in-time adaptive intervention (JITAI) mechanisms. JITAIs are designed to improve the effectiveness of the intervention and reduce the burden on the person using the intervention by providing the right type of support at the right time. The right type of support and the right time are determined by measuring the state of vulnerability and the state of receptivity, respectively. OBJECTIVE The aim of this study is to systematically assess the use of JITAI mechanisms in popular apps for individuals with depression. METHODS We systematically searched for apps addressing depression in the Apple App Store and Google Play Store, as well as in curated lists from the Anxiety and Depression Association of America, the United Kingdom National Health Service, and the American Psychological Association in August 2020. The relevant apps were ranked according to the number of reviews (Apple App Store) or downloads (Google Play Store). For each app, 2 authors separately reviewed all publications concerning the app found within scientific databases (PubMed, Cochrane Register of Controlled Trials, PsycINFO, Google Scholar, IEEE Xplore, Web of Science, ACM Portal, and Science Direct), publications cited on the app's website, information on the app's website, and the app itself. All types of measurements (eg, open questions, closed questions, and device analytics) found in the apps were recorded and reviewed. RESULTS None of the 28 reviewed apps used JITAI mechanisms to tailor content to situations, states, or individuals. Of the 28 apps, 3 (11%) did not use any measurements, 20 (71%) exclusively used self-reports that were insufficient to leverage the full potential of the JITAIs, and the 5 (18%) apps using self-reports and passive measurements used them as progress or task indicators only. Although 34% (23/68) of the reviewed publications investigated the effectiveness of the apps and 21% (14/68) investigated their efficacy, no publication mentioned or evaluated JITAI mechanisms. CONCLUSIONS Promising JITAI mechanisms have not yet been translated into mainstream depression apps. Although the wide range of passive measurements available from smartphones were rarely used, self-reported outcomes were used by 71% (20/28) of the apps. However, in both cases, the measured outcomes were not used to tailor content and timing along a state of vulnerability or receptivity. Owing to this lack of tailoring to individual, state, or situation, we argue that the apps cannot be considered JITAIs. The lack of publications investigating whether JITAI mechanisms lead to an increase in the effectiveness or efficacy of the apps highlights the need for further research, especially in real-world apps

The boy who refused an IV: a case report of subcutaneous clodronate for bone pain in a child with Ewing Sarcoma

BACKGROUND: Bone pain in malignancy can be challenging to treat. Bisphosphonates have been found to be useful in adults with bone pain, but there are no reports of their use in children for this indication. In pediatric palliative medicine there are hurdles in translating knowledge gained primarily in adult studies into application in children. Obstacles exist in initially determining whether the evidence supports using a drug in children, and once a drug is chosen, then determining the optimal route of delivery. There is very little data to guide pediatric practitioners in this situation. CASE PRESENTATION: A 9 year old boy with disseminated Ewing Sarcoma presented with extremity pain not responsive to a combination of opiates, gabapentin and non-steroidal anti-inflammatory drugs. Clodronate, a bisphosphonate, was added to the regimen to treat bone pain. It was given subcutaneously every 4 weeks with a good response and no side effects. CONCLUSION: This case report describes the use of a bisphosphonate, clodronate, given subcutaneously to a child with Ewing sarcoma with effective relief of bone pain. It describes how the care team encountered the challenges inherent in translating adult therapy into a pediatric regimen. Furthermore the report details how a regimen was developed to address this child's concerns regarding medication administration. Further effort needs to be made at finding solutions to address the lack of good evidence for pediatric palliative therapies

Air Pollution Exposure and Abnormal Glucose Tolerance during Pregnancy: The Project Viva Cohort

Background: Exposure to fine particulate matter (PM with diameter ≤ 2.5 μm; PM2.5) has been linked to type 2 diabetes mellitus, but associations with hyperglycemia in pregnancy have not been well studied. Methods: We studied Boston, Massachusetts–area pregnant women without known diabetes. We identified impaired glucose tolerance (IGT) and gestational diabetes mellitus (GDM) during pregnancy from clinical glucose tolerance tests at median 28.1 weeks gestation. We used residential addresses to estimate second-trimester PM2.5 and black carbon exposure via a central monitoring site and spatiotemporal models. We estimated residential traffic density and roadway proximity as surrogates for exposure to traffic-related air pollution. We performed multinomial logistic regression analyses adjusted for sociodemographic covariates, and used multiple imputation to account for missing data. Results: Of 2,093 women, 65 (3%) had IGT and 118 (6%) had GDM. Second-trimester spatiotemporal exposures ranged from 8.5 to 15.9 μg/m3 for PM2.5 and from 0.1 to 1.7 μg/m3 for black carbon. Traffic density was 0–30,860 vehicles/day × length of road (kilometers) within 100 m; 281 (13%) women lived ≤ 200 m from a major road. The prevalence of IGT was elevated in the highest (vs. lowest) quartile of exposure to spatiotemporal PM2.5 [odds ratio (OR) = 2.63; 95% CI: 1.15, 6.01] and traffic density (OR = 2.66; 95% CI: 1.24, 5.71). IGT also was positively associated with other exposure measures, although associations were not statistically significant. No pollutant exposures were positively associated with GDM. Conclusions: Greater exposure to PM2.5 and other traffic-related pollutants during pregnancy was associated with IGT but not GDM. Air pollution may contribute to abnormal glycemia in pregnancy. Citation: Fleisch AF, Gold DR, Rifas-Shiman SL, Koutrakis P, Schwartz JD, Kloog I, Melly S, Coull BA, Zanobetti A, Gillman MW, Oken E. 2014. Air pollution exposure and abnormal glucose tolerance during pregnancy: the Project Viva Cohort. Environ Health Perspect 122:378–383; http://dx.doi.org/10.1289/ehp.130706