Data In Public Health Research Research Articles

Evidence for positive long- and short-term effects of vaccinations against COVID-19 in wearable sensor metrics.

Vaccines are among the most powerful tools to combat the COVID-19 pandemic. They are highly effective against infection and substantially reduce the risk of severe disease, hospitalization, ICU admission, and death. However, their potential for attenuating long-term changes in personal health and health-related wellbeing after a SARS-CoV-2 infection remains a subject of debate. Such effects can be effectively monitored at the individual level by analyzing physiological data collected by consumer-grade wearable sensors. Here, we investigate changes in resting heart rate, daily physical activity, and sleep duration around a SARS-CoV-2 infection stratified by vaccination status. Data were collected over a period of 2 years in the context of the German Corona Data Donation Project with around 190,000 monthly active participants. Compared to their unvaccinated counterparts, we find that vaccinated individuals, on average, experience smaller changes in their vital data that also return to normal levels more quickly. Likewise, extreme changes in vitals during the acute phase of the disease occur less frequently in vaccinated individuals. Our results solidify evidence that vaccines can mitigate long-term detrimental effects of SARS-CoV-2 infections both in terms of duration and magnitude. Furthermore, they demonstrate the value of large-scale, high-resolution wearable sensor data in public health research.

Carvings in stone: design research for public health investigations in the age of COVID-19

The COVID-19 pandemic presented complex challenges to public health research involving human subjects, necessitating creative thinking to maintain safe and productive qualitative data collection. In this paper, we describe how an interdisciplinary team overcame these challenges by translating in-person workshops into at-home design probes to explore connections between university students’ climate change attitudes and their health. Probes were purposively designed to facilitate and focus participation during lockdown with two key interactional components: (1) participant ⇔ probe, and (2) participant ⇔ physical environment. Thematic analysis of 18 completed probes (replete with elicitive drawing, etched stone, mapping, and writing activities) revealed a rich spectrum of climate change perceptions, eco-emotions, and key areas of impact. This case study provides insight into how pandemic-imposed restrictions presented a novel opportunity to reconceptualize how we collect qualitative data in public health research and summarizes the unique benefits of integrating such design-based approaches into the field moving forward.

The overcome of public health research data management chaos: exploratory study on research infrastructure implementation

The overcome of public health research data management chaos: exploratory study on research infrastructure implementation

An Empirical Spatial Network Model Based on Human Mobility for Epidemiological Research: A Case Study

Constructing a data-driven spatial contact network model is challenging in epidemiological research. In this study, we examine the applicability of geotagged Twitter data as an instrumental data source for tackling such a challenge. Geotagged Twitter data carrying geolocations of the account users have the strength for longitudinal data collection at a massive scale. Still, the unstructured nature of the data exerts significant methodological and computational difficulties. We focus on methodological solutions and develop a novelty approach that lets a spatial contact network emerge naturally from the massive amount of geospatial tweets. We show that such a data-driven network has reflected the assumptions made by network models regarding human behaviors and has the potential of being used for epidemiological research. To this end, we investigate the network properties and study the spread of pathogens on the proposed spatial contact network by using the homogeneous and heterogeneous susceptible–infectious–recovered (SIR) network models and the event-driven Gillespie’s algorithm. Our simulation results strongly suggest that it is feasible to explicitly construct data-driven spatial models using massive longitudinal Twitter data for public health research.

In the shadow of privacy: Overlooked ethical concerns in COVID-19 digital epidemiology

The COVID-19 pandemic witnessed a surge in the use of health data to combat the public health threat. As a result, the use of digital technologies for epidemic surveillance showed great potential to collect vast volumes of data, and thereby respond more effectively to the healthcare challenges. However, the deployment of these technologies raised legitimate concerns over risks to individual privacy. While the ethical and governance debate focused primarily on these concerns, other relevant issues remained in the shadows. Leveraging examples from the COVID-19 pandemic, this perspective article aims to investigate these overlooked issues and their ethical implications. Accordingly, we explore the problem of the digital divide, the role played by tech companies in the public health domain and their power dynamics with the government and public research sector, and the re-use of personal data, especially in the absence of adequate public involvement. Even if individual privacy is ensured, failure to properly engage with these other issues will result in digital epidemiology tools that undermine equity, fairness, public trust, just distribution of benefits, autonomy, and minimization of group harm. On the contrary, a better understanding of these issues, a broader ethical and data governance approach, and meaningful public engagement will encourage adoption of these technologies and the use of personal data for public health research, thus increasing their power to tackle epidemics.

9.N. Workshop: It Takes Two To Improve European Child Health (Care)

Abstract Many societal developments have an impact on health care in general and on child health care, in particular. Internationally challenges include an aging population, more cultural diversity and a rising prevalence of chronic diseases among children and adolescents, revealing potential risks for child health care. A strong focus must be placed on prevention strategies that are effective, sustainable and equitable. Planning and implementing prevention strategies may require shifts in the organization of care, such as the forging and strengthening of interdisciplinary and intersectoral partnerships within a country. A promising example of such partnerships is the collaboration of public health with paediatrics. Both professional groups acknowledge the call for greater integration since prevention strategies can only be achieved and sustained by working together. The objectives of this workshop are to: • Provide a selective overview of three partnerships and plans for cooperation between public health and paediatrics. • To exchange experiences and possibilities with the audience to pave the way for further successful partnerships. In this workshop, we outline the partnership and plans for cooperation between public health and paediatrics in three European countries: Netherlands, Finland and Switzerland. In the first presentation, Danielle Jansen and Károly Illy will share the new vision towards the year 2030 of the Dutch Paediatric Society in which building blocks are presented to guarantee accessible, high-quality, timely and effective care for every child. One of the building blocks to be highlighted is the interprofessional collaboration between paediatricians and public health professionals. In the second presentation, Julia Dratva and Susanne Stronski from Switzerland will present a shared paediatric and public health vision of a digital child health booklet. The digital booklet will empower parents and adolescents, provide access to personal health irrespective of place or time, improve sharing health information among care professionals, thus ensuring continuity of care and limiting redundancy of investigations and in addition, and provide data for public health research and monitoring. Challenges and solutions will be shared with the audience. In the third presentation, Silja Kosola from Finland will present a Finnish vision for school health care where professionals trained in public health and medicine collaborate with each other as well as with teachers for the benefit of children and adolescents. This multidisciplinary collaboration across governing bodies is especially important as Finland undergoes a national reform of social and health care services. After the three presentations, we engage the audience by asking for their experiences and sharing the examples of collaborations between public health and paediatrics, as well as barriers and facilitators. At the end of the workshop, we would like to summarize the results of the workshop in an overview of preliminary best practices. Key messages • Global climatic, societal and politic developments reveal potential risks for child health cand health care, which must be countered effectively, sustainably and equitably. • Greater integration of prevention across sectors is elemental and can be achieved through interprofessional partnerships.

Toward a digital child health booklet

Abstract Public health, paediatrics as well as other health professionals share the interest in providing services and improving conditions to ensure life-long health and well-being of children and adolescents. In this interprofessional setting and aim, parents are central partners, as are adolescents when they take over the responsibility of their own health. Ensuring the availability of health data for parents and adolescents at any given time and place is a key factor to empower and improve health management and literacy, providing continuity of health information along the care chain, and analysing health data of healthy and sick children is of high importance. The digital booklet will have a positive impact on sharing of health information among care professionals, thus ensuring continuity of care and limiting redundancy of investigation, and in addition provide data for public health research and monitoring of health and determinants. The Swiss Society of Paediatrics, the ZHAW/Institute of Public Health and the Kollegium of Hausarztmedizin (general practices) founded an association to digitalize the current paper child and adolescent health booklet with the aims: 1. Empower parents as ‘owners’ of health data to take responsibility and have greater autonomy in managing their child's health and illness 2. Provide a digital infrastructure for – low-threshold and reliable source of advice – easy update of data/information, digital communication with parents – sharing of data with professionals and non-professionals involved in care of child. 3. Monitoring of children's health data (parental consent provided) The speakers with present their collaboration and project, its current status, as well challenges and solutions found.

Linking fathers and children in administrative data for public health research: A systematic scoping review.

ObjectivesThe evidence-base for inter-related paternal and child health trajectories is not supported by linked, routinely collected administrative data in England. We conducted a scoping review to identify methods used globally for linking fathers and children in administrative data for public health research and map these methods onto dimensions of fatherhood.
 ApproachWe searched PubMed, Scopus and Google/Google Scholar for articles published 2000-2020 from OECD countries that link fathers’ and children’s records in administrative data. Search terms included for example: “father” and “administrative data” or “record linkage”. The exposures of interest were any demographic, health, or other characteristics of fathers during their offspring's childhood or prior to birth captured within administrative data. We included studies where paternal information came from fathers' linked records and if outcomes were related to child health and development (e.g. educational attainment, behavioural outcomes, hospital admissions) measured before 18 years of age.
 ResultsWe identified 77 studies that quantified the association between paternal exposures and child health and development outcomes, using linked administrative data on fathers and their children. Four methods have been used globally to link fathers and children across vital statistics, health, social care, education, and criminal justice records. These methods are based on personal identity numbers (PINs), address or household identifiers, information from birth registrations, or health claims. We mapped what we can learn from these different linkages to dimensions of fatherhood identified through a conceptual framework. For example, for the linkage method based on address/household identifiers, co-residency may be used as a proxy for all dimensions of paternal involvement. However, substantial assumptions are needed when using linkage methods as proxies for paternal involvement.
 ConclusionIn many settings, changes in practice (such as recording fathers’ National Health Service numbers on hospital birth notifications in England) are required to facilitate linkage of father-child health data at the population level. This would help advance fatherhood research and enable targeted service offers to new fathers.

Barriers and facilitators of cross-sectoral data linkage to inform healthy public policy and practice: lessons from three case study projects in Scotland.

ObjectivesWe sought to describe barriers and facilitators faced by three research projects aiming to link routinely-collected data across various sectors, to produce evidence to inform healthy public policy. We conducted these case studies as a part of a wider research project on cross-sectoral sharing and linkage of secondary data. ApproachWe selected the case studies to cover a range of target populations and datasets. The chosen projects investigated (1) the health of care-experienced children; (2) the intersection of homelessness, justice involvement, drug use, and severe mental illness; (3) multi-morbidity among adults receiving social care. Information about timelines and governance processes was collected from lead investigators, including specific barriers and facilitators encountered, using a standardised pro forma and follow-up interviews. Thematic analysis was carried out by the research team, informed by themes identified in a parallel scoping review of existing literature on evidence use for healthy public policy and practice. ResultsEach project involved between 6 and 11 agencies, with co-ordination across multiple institutions and geographies proving challenging. Due to challenges encountered, all projects had to amend their original geographical or demographic scope. Forty-four barriers and facilitators to sharing and linkage of cross-sectoral routinely-collected data for public health research were identified. These included but were not limited to: integration of current data in an ever-changing linkage landscape; the need for timely feedback in undertaking the study; standardisation of information governance processes; highlighting the resourcing and funding issues for data linkage projects; the need for data controllers to recognise the value of such projects; and issues relating to staff turnover and workload pressures. ConclusionThe interconnected nature of barriers and facilitators identified by the case studies suggests the importance of a whole-systems approach to cross-sectoral linkage. While literature offers relatively few case studies of cross-sectoral linkage for health research, the value of their insight into the linkage landscape derived from real-life experience is substantial.

Ethical, Legal, and Sociocultural Issues in the Use of Mobile Technologies and Call Detail Records Data for Public Health in the East African Region: Scoping Review.

BackgroundThe exponential scale and pace of real-time data generated from mobile phones present opportunities for new insights and challenges across multiple sectors, including health care delivery and public health research. However, little attention has been given to the new ethical, social, and legal concerns related to using these mobile technologies and the data they generate in Africa.ObjectiveThe objective of this scoping review was to explore the ethical and related concerns that arise from the use of data from call detail records and mobile technology interventions for public health in the context of East Africa.MethodsWe searched the PubMed database for published studies describing ethical challenges while using mobile technologies and related data in public health research between 2000 and 2020. A predefined search strategy was used as inclusion criteria with search terms such as “East Africa,” “mHealth,” “mobile phone data,” “public health,” “ethics,” or “privacy.” We screened studies using prespecified eligibility criteria through a two-stage process by two independent reviewers. Studies were included if they were (1) related to mobile technology use and health, (2) published in English from 2000 to 2020, (3) available in full text, and (4) conducted in the East African region. We excluded articles that (1) were conference proceedings, (2) studies presenting an abstract only, (3) systematic and literature reviews, (4) research protocols, and (5) reports of mobile technology in animal subjects. We followed the five stages of a published framework for scoping reviews recommended by Arksey and O’Malley. Data extracted included title, publication year, target population, geographic region, setting, and relevance to mobile health (mHealth) and ethics. Additionally, we used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Extension for Scoping Reviews checklist to guide the presentation of this scoping review. The rationale for focusing on the five countries in East Africa was their geographic proximity, which lends itself to similarities in technology infrastructure development.ResultsOf the 94 studies identified from PubMed, 33 met the review inclusion criteria for the final scoping review. The 33 articles retained in the final scoping review represent studies conducted in three out of five East African countries: 14 (42%) from Uganda, 13 (39%) from Kenya, and 5 (16%) from Tanzania. Three main categories of concerns related to the use of mHealth technologies and mobile phone data can be conceptualized as (1) ethical issues (adequate informed consent, privacy and confidentiality, data security and protection), (2) sociocultural issues, and (3) regulatory/legal issues.ConclusionsThis scoping review identified major cross-cutting ethical, regulatory, and sociocultural concerns related to using data from mobile technologies in the East African region. A comprehensive framework that accounts for the critical concerns raised would be valuable for guiding the safe use of mobile technology data for public health research purposes.

Linking fathers and children in administrative data for public health research: a systematic scoping review

BackgroundGrowing evidence on the inter-related health trajectories of mothers and their children is supported by linked, routinely collected, administrative data held by the UK National Health Service and government departments. A similar evidence base for fathers is hindered by the scarcity of necessary information held in maternity or birth records in England. We conducted a scoping review to develop a conceptual model of dimensions of fatherhood, identify and categorise the methods used for linking fathers with their children in administrative data for public health research, and map these methods onto the dimensions of fatherhood. MethodsWe developed a framework of social fathering by integrating the key components from relevant theoretical models and empirical studies. We searched PubMed, Scopus, and Google Scholar for articles published between Jan 1, 2000, and Dec 31, 2020, from countries belonging to the Organisation for Economic Co-operation and Development that link fathers' and children's records in administrative data. Search terms included: “father” and “administrative data” or “record linkage”. Studies were excluded if child outcomes were measured after the age of 18 years. FindingsWe identified 77 studies that quantified the association between paternal exposures and child health and development outcomes, using linked administrative data on fathers and their children. Four methods have been used globally to link fathers and children across vital statistics, health, social care, education, and justice records. These methods are based on personal identity numbers (PINs) for national identification, address or household identifiers, information found on birth registrations, or health claims. InterpretationTo our knowledge, this review is the first to identify linkage methods used for father-child pairs using routinely collected records and to present the range of paternal exposures and child outcomes studied using administrative data. We mapped what we can learn from these linkages to the dimensions of fatherhood. However, significant assumptions are made when using linkage methods as proxies for paternal involvement. Currently, there is no way to link fathers and children's health data at the population level in England and, therefore, changes in practice are required to facilitate father-child linkage. To advance fatherhood research for child and family public health, we recommend routinely recording paternal National Health Service numbers as part of hospital birth notifications. FundingUCL Grand Challenges and the Medical Research Council.

Evaluation of Multiple Imputation with Large Proportions of Missing Data: How Much Is Too Much?

Background:Multiple Imputation (MI) is known as an effective method for handling missing data in public health research. However, it is not clear that the method will be effective when the data contain a high percentage of missing observations on a variable.Methods:Using data from “Predictive Study of Coronary Heart Disease” study, this study examined the effectiveness of multiple imputation in data with 20% missing to 80% missing observations using absolute bias (|bias|) and Root Mean Square Error (RMSE) of MI measured under Missing Completely at Random (MCAR), Missing at Random (MAR), and Not Missing at Random (NMAR) assumptions.Results:The |bias| and RMSE of MI was much smaller than of the results of CCA under all missing mechanisms, especially with a high percentage of missing. In addition, the |bias| and RMSE of MI were consistent regardless of increasing imputation numbers from M=10 to M=50. Moreover, when comparing imputation mechanisms, MCMC method had universally smaller |bias| and RMSE than those of Regression method and Predictive Mean Matching method under all missing mechanisms.Conclusion:As missing percentages become higher, using MI is recommended, because MI produced less biased estimates under all missing mechanisms. However, when large proportions of data are missing, other things need to be considered such as the number of imputations, imputation mechanisms, and missing data mechanisms for proper imputation.

13.C. Workshop: Epistemic and ethical innovations in public health research

Abstract About 90% of the biomedical data accessible to researchers was created in the last two years. These data have a very meaningful impact both in creating public policies on health, as well as public health research. This certainly implies complex technical problems on how to store, analyse and distribute data, but it also brings relevant epistemological issues. In this workshop we will present some of such problems and discuss how epistemic innovation is key in order to tackle ethical issues related to the use of big data in public health research. Databases implied in public health research are so huge that they rise relevant questions about how scientific method is applied, such as what counts as evidence of a hypothesis when data can not be directly apprehended by humans, how to distinguish correlation from causation, or in which cases the provider of a database can be considered co-author of a research paper. To consider such issues nowadays, current protocols do not hold, and we need innovation in methodological and epistemic procedures. At the same time, due to the fact that a relevant deal of such biomedical data is linked to individual people, and how medical data can be used to predict and transform human behavior, there are ethical questions difficult to solve as they imply new challenges. Some of them are related to communication issues, so patients and citizens understand these new ethical problems that didn't arise before the development of big data; others relate to the way in which public health researchers can and can't store, analyse and distribute information, and some others relate to the limits on which technologies are ethically, safe and which ones bring erosion of basic human rights. The four contributions in the workshop analyse these questions in some detail. During the workshop we will present a coherent understanding on what is epistemic innovation, some logical tools necessary for its development, and then we will discuss several cases on how epistemic innovation applies to different aspects of public health research, also commenting its relevance when tackling ethical problems that may arise. Key messages The workshop deepens the ethical and epistemological innovations involved in public health policies and research, specially related to big data. The workshop analyses novel aspects of public health ethics

Role of the Built and Online Social Environments on Expression of Dining on Instagram.

Online social communities are becoming windows for learning more about the health of populations, through information about our health-related behaviors and outcomes from daily life. At the same time, just as public health data and theory has shown that aspects of the built environment can affect our health-related behaviors and outcomes, it is also possible that online social environments (e.g., posts and other attributes of our online social networks) can also shape facets of our life. Given the important role of the online environment in public health research and implications, factors which contribute to the generation of such data must be well understood. Here we study the role of the built and online social environments in the expression of dining on Instagram in Abu Dhabi; a ubiquitous social media platform, city with a vibrant dining culture, and a topic (food posts) which has been studied in relation to public health outcomes. Our study uses available data on user Instagram profiles and their Instagram networks, as well as the local food environment measured through the dining types (e.g., casual dining restaurants, food court restaurants, lounges etc.) by neighborhood. We find evidence that factors of the online social environment (profiles that post about dining versus profiles that do not post about dining) have different influences on the relationship between a user’s built environment and the social dining expression, with effects also varying by dining types in the environment and time of day. We examine the mechanism of the relationships via moderation and mediation analyses. Overall, this study provides evidence that the interplay of online and built environments depend on attributes of said environments and can also vary by time of day. We discuss implications of this synergy for precisely-targeting public health interventions, as well as on using online data for public health research.

A short history of time use research; implications for public health

BackgroundThis section defined time use (TU) research, illustrating its relevance for public health. TUR in the health context is the study of health-enhancing and health-compromising behaviours that are assessed across a 24 h day. The central measurement is the use of Time Use Diaries, which capture 24–48 h, typically asking about behaviour in each 15-min period. TUR is used for understanding correlates of health behaviours, and as a form of population surveillance, assessing behavioural trends over time.Main bodyThis paper is a narrative review examining the history of time use research, and the potential uses of TU data for public health research. The history of TUR started in studies of the labour force and patterns of work in the late 19th and early twentieth century, but has more recently been applied to examining health issues. Initial studies had a more economic purpose but over recent decades, TU data have been used to describe the distribution and correlates of health-enhancing patterns of human time use. These studies require large multi-country population data sets, such as the harmonised Multinational Time Use Study hosted at the University of Oxford. TU data are used in physical activity research, as they provide information across the 24-h day, that can be examined as time spent sleeping, sitting/standing/light activity, and time spent in moderate-vigorous activities. TU data are also used for sleep research, examining eating and dietary patterns, exploring geographic distributions in time use behaviours, examining mental health and subjective wellbeing, and examining these data over time. The key methodological challenge has been the development of harmonised methods, so population TU data sets can be compared within and between-countries and over time.ConclusionsTUR provides new methods for examining public health research questions where a temporal dimension is important. These time use surveys have provided unique data over decades and in many countries that can be compared. They can be used for examining the effects of some large public health interventions or policies within and between countries.

A Pilot Randomized Controlled Trial of a Digital Intervention Aimed at Improving Food Purchasing Behavior: The Front-of-Pack Food Labels Impact on Consumer Choice Study.

BackgroundMost food in the United Kingdom is purchased in supermarkets, and many of these purchases are routinely tracked through supermarket loyalty card data. Using such data may be an effective way to develop remote public health interventions and to measure objectively their effectiveness at changing food purchasing behavior.ObjectiveThe Front-of-pack food Labels: Impact on Consumer Choice (FLICC) study is a pilot randomized controlled trial of a digital behavior change intervention. This pilot trial aimed to collect data on recruitment and retention rates and to provide estimates of effect sizes for the primary outcome (healthiness of ready meals and pizzas purchased) to inform a larger trial.MethodsThe intervention consisted of a website where participants could access tailored feedback on previous purchases of ready meals and pizzas, set goals for behavior change, and model and practice the recommended healthy shopping behavior using traffic light labels. The control consisted of Web-based information on traffic light labeling. Participants were recruited via email from a list of loyalty card holders held by the participating supermarket. All food and drink purchases for the participants for the 6 months before recruitment, during the 6-week intervention period, and during a 12-week washout period were transferred to the research team by the participating supermarket. Healthiness of ready meals and pizzas was measured using a predeveloped scale based solely on the traffic light colors on the foods. Questionnaires were completed at recruitment, end of the intervention, and end of washout to estimate the effect of the intervention on variables that mediate behavior change (eg, belief and intention formation).ResultsWe recruited 496 participants from an initial email to 50,000 people. Only 3 people withdrew from the study, and purchase data were received for all other participants. A total of 208 participants completed all 3 questionnaires. There was no difference in the healthiness of purchased ready meals and pizzas between the intervention and control arms either during the intervention period (P=.32) or at washout (P=.59).ConclusionsAlthough the FLICC study did not find evidence of an impact of the intervention on food purchasing behavior, the unique methods used in this pilot trial are informative for future studies that plan to use supermarket loyalty card data in collaboration with supermarket partners. The experience of the trial showcases the possibilities and challenges associated with the use of loyalty card data in public health research.Trial RegistrationISRCTN Registry ISRCTN19316955; http://www.isrctn.com/ISRCTN19316955 (Archived by WebCite at http://www.webcitation.org/76IVZ9WjK)International Registered Report Identifier (IRRID)RR2-10.1186/s40814-015-0015-1

Investigating site-level longitudinal effects of population health interventions: Gay-Straight Alliances and school safety.

There is limited research on evaluating nonrandomized population health interventions. We aimed to introduce a new approach for assessing site-level longitudinal effects of population health interventions (SLEPHI) by innovatively applying multiple group multilevel (MG-ML) modeling to repeated cycles of cross-sectional data collected from different individuals of the same sites at different times, a design commonly employed in public health research. For illustration, we used this SLEPHI method to examine the influence of Gay-Straight Alliances (GSAs) on school-level perceived safety among lesbian, gay, and bisexual (LGB) and heterosexual (HET) adolescents. Individual-level data of perceived school safety came from 1625 LGB students (67.4% female; mean age, 15.7 years) and 37,597 HET students (50.2% female; mean age, 15.4 years) attending Grades 7–12 in 135 schools, which participated in 3 British Columbia Adolescent Health Surveys (BCAHS: 2003, 2008, 2013) in Canada. School-level data of GSA length since established were collected by telephone in 2008 and 2014. Nested MG-ML models suggested that after accounting for secular trend, cohort effects, measurement error, measurement equivalence, and student age, GSA length linearly related to increased school-level perceived safety among LGB students (b = 1.57, SE = 0.21, p < .001, β = 0.32) and also among HET students (β = 0.34 in 2003 & 2013, β = 0.32 in 2008) although statistical differences between years for HET youth were likely due to the large sample size. By conducting MG-ML analysis on repeated cross-sectional surveys, this SLEPHI method accounted for many confounding factors and followed schools for a longer period than most longitudinal designs can follow individuals. Therefore, we drew a stronger conclusion than previous observational research about GSAs and LGB students’ well-being. The SLEPHI method can be widely applied to other repeated cycles of cross-sectional data in public health research.

Using CPRD data for public health research.

When you join a practice as a partner, you generally buy a share of the practice’s ‘fixtures and fittings’. Things like the autoclave (which gurgled alarmingly until, in one glorious explosion, was no more), and the chipped coffee mugs, plus the expensive computer. Thus, in 1990, when I joined my first practice, I was relieved that the computer came for free. ‘Some company gave it to us, so they can use our prescribing data.’ The rules of this freebie — ensuring all consultations were logged, and all prescriptions had a documented indication — seemed good notekeeping practice, a rare merger of the needs of my morals and those of my wallet. A few rules were less helpful. We kept getting shirty reminders to record the Apgar score of all our births. This was a chore (and almost certainly worthless). Welcome to the world of Value Added Medical …

Metadata Correction: Mobile Phone Ownership Is Not a Serious Barrier to Participation in Studies: Descriptive Study

[This corrects the article DOI: 10.2196/mhealth.8123.].

Using real‐world patient data to improve healthcare outcomes

Dr Janet Valentine is a champion of collaboration – a quality much needed for her role as the director of Clinical Practice Research Datalink (CPRD) at the MHRA. She talks to Kate Stewart about how CPRD is contributing to improvements in drug safety and clinical practice through the use of real‐world patient data in public health research.