Reconciling specific and unspecific risk factors: the interplay between theory and data

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Protecting against researcher bias in secondary data analysis: challenges and potential solutions

Analysis of secondary data sources (such as cohort studies, survey data, and administrative records) has the potential to provide answers to science and society’s most pressing questions. However, researcher biases can lead to questionable research practices in secondary data analysis, which can distort the evidence base. While pre-registration can help to protect against researcher biases, it presents challenges for secondary data analysis. In this article, we describe these challenges and propose novel solutions and alternative approaches. Proposed solutions include approaches to (1) address bias linked to prior knowledge of the data, (2) enable pre-registration of non-hypothesis-driven research, (3) help ensure that pre-registered analyses will be appropriate for the data, and (4) address difficulties arising from reduced analytic flexibility in pre-registration. For each solution, we provide guidance on implementation for researchers and data guardians. The adoption of these practices can help to protect against researcher bias in secondary data analysis, to improve the robustness of research based on existing data

Are IQ and educational outcomes in teenagers related to their cannabis use? A prospective cohort study

The UK Medical Research Council (MRC), Wellcome Trust and University of Bristol provide core support for ALSPAC. This research was specifically funded by an MRC Studentship awarded to the first autho

Electronic cigarette and smoking paraphernalia point of sale displays: an observational study in England

BACKGROUND: Tobacco point of sale (POS) retail displays are banned in many countries, including in England, due in part to evidence linking them to greater susceptibility to smoking in children. There is no equivalent ban on displays of electronic cigarettes (e-cigarettes) or smoking paraphernalia (eg, cigarette lighters) in England, which are often positioned alongside covered tobacco storage units. This observational study describes the visibility and placement of e-cigarette and smoking paraphernalia POS displays in major tobacco retailers in two cities in England to inform future research examining their possible links to susceptibility to tobacco smoking, particularly in children. METHODS: Researchers visited all small- and large-format stores of four supermarket chains and a randomly selected sample of convenience stores, in Bristol and Cambridge. A standardised checklist was used to create a total visibility score for POS displays of (a) e-cigarettes and (b) smoking paraphernalia, plus other measures of visibility and placement. These were described for the total sample and compared between areas of low, medium, and high deprivation using general linear models adjusting for store location and store type. RESULTS: The visibility checklist was completed in 133 of 166 stores (80% completion rate). Both e-cigarette and smoking paraphernalia POS displays were present in 96% of stores. POS displays were highly visible across all stores: mean (SD) total visibility scores, out of 17, were 14.7 (1.8) for e-cigarettes and 12.7 (1.8) for smoking paraphernalia. There was no clear evidence of differences in visibility by area of deprivation. CONCLUSION: E-cigarette and smoking paraphernalia POS displays are near ubiquitous and highly visible in major tobacco retailers in two cities in England. The impact of these displays on tobacco smoking in children and adults is unknown, meriting urgent research to assess their effect on susceptibility to tobacco smoking in children

Gamification for health promotion: systematic review of behaviour change techniques in smartphone apps

Funding from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical, Research Council and the National Institute for Health Research, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged

Heterogeneity in Meta-Analyses of Genome-Wide Association Investigations

BACKGROUND: Meta-analysis is the systematic and quantitative synthesis of effect sizes and the exploration of their diversity across different studies. Meta-analyses are increasingly applied to synthesize data from genome-wide association (GWA) studies and from other teams that try to replicate the genetic variants that emerge from such investigations. Between-study heterogeneity is important to document and may point to interesting leads. METHODOLOGY/PRINCIPAL FINDINGS: To exemplify these issues, we used data from three GWA studies on type 2 diabetes and their replication efforts where meta-analyses of all data using fixed effects methods (not incorporating between-study heterogeneity) have already been published. We considered 11 polymorphisms that at least one of the three teams has suggested as susceptibility loci for type 2 diabetes. The I2 inconsistency metric (measuring the amount of heterogeneity not due to chance) was different from 0 (no detectable heterogeneity) for 6 of the 11 genetic variants; inconsistency was moderate to very large (I2 = 32-77%) for 5 of them. For these 5 polymorphisms, random effects calculations incorporating between-study heterogeneity revealed more conservative p-values for the summary effects compared with the fixed effects calculations. These 5 associations were perused in detail to highlight potential explanations for between-study heterogeneity. These include identification of a marker for a correlated phenotype (e.g. FTO rs8050136 being associated with type 2 diabetes through its effect on obesity); differential linkage disequilibrium across studies of the identified genetic markers with the respective culprit polymorphisms (e.g., possibly the case for CDKAL1 polymorphisms or for rs9300039 and markers in linkage disequilibrium, as shown by additional studies); and potential bias. Results were largely similar, when we treated the discovery and replication data from each GWA investigation as separate studies. SIGNIFICANCE: Between-study heterogeneity is useful to document in the synthesis of data from GWA investigations and can offer valuable insights for further clarification of gene-disease associations

Illness Schema Activation and the Effects of Illness Seasonality on Accessibility of Implicit Illness-Related Information

The Common-Sense Model (CSM) of illness self-regulation is a leading theoretical framework describing the process by which an individual recognizes that he or she is physically ill and subsequently attempts to manage that illness state. The CSM proposes that people possess schematically organized implicit cognitive representations of health threats comprising information about illness such as symptoms, causes, label, duration, consequences, and procedures for managing threat [1, 2, 3, 4]. The proposed function of these stored knowledge structures is to activate a self-regulation process that might protect or restore a state of well-being [5]. The CSM proposes that the schematic representation is centrally activated by detection of deviations from the normal functioning self (i.e., experienced symptoms). The identification of illness and the initiation of self-management attempts follow from the search for illness-relevant cognitive structures and the matching of the content of illness schema to the symptomatic experience. For example, a headache (a symptomatic deviation from normal somatic experience) might activate illness schemata containing the cognitive representation of “headache” such as “hangover,” “dehydration,” or “flu.” The matching of the symptom to a particular illness schema will follow from the search and match to other aspects of plausible illness representations, such as its probable cause or duration (timeline).Full Tex

Effect on Adherence to Nicotine Replacement Therapy of Informing Smokers Their Dose Is Determined by Their Genotype: A Randomised Controlled Trial

BACKGROUND: The behavioural impact of pharmacogenomics is untested. We tested two hypotheses concerning the behavioural impact of informing smokers their oral dose of NRT is tailored to analysis of DNA. METHODS AND FINDINGS: We conducted an RCT with smokers in smoking cessation clinics (N = 633). In combination with NRT patch, participants were informed that their doses of oral NRT were based either on their mu-opioid receptor (OPRM1) genotype, or their nicotine dependence questionnaire score (phenotype). The proportion of prescribed NRT consumed in the first 28 days following quitting was not significantly different between groups: (68.5% of prescribed NRT consumed in genotype vs 63.6%, phenotype group, difference = 5.0%, 95% CI -0.9,10.8, p = 0.098). Motivation to make another quit attempt among those (n = 331) not abstinent at six months was not significantly different between groups (p = 0.23). Abstinence at 28 days was not different between groups (p = 0.67); at six months was greater in genotype than phenotype group (13.7% vs 7.9%, difference = 5.8%, 95% CI 1.0,10.7, p = 0.018). CONCLUSIONS: Informing smokers their oral dose of NRT was tailored to genotype not phenotype had a small, statistically non-significant effect on 28-day adherence to NRT. Among those still smoking at six months, there was no evidence that saying NRT was tailored to genotype adversely affected motivation to make another quit attempt. Higher abstinence rate at six months in the genotype arm requires investigation. TRIAL REGISTRATION: Controlled-Trials.com ISRCTN14352545.</p