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Background: Mental health has worsened, and substance use has increased for some people during the coronavirus (COVID-19) pandemic. Some cross-sectional studies suggest that higher COVID-19 risk perceptions are related to poorer mental health and greater risk behaviours (e.g., substance use). However, longitudinal and genetic data are needed to help to reduce the likelihood of reverse causality. Methods: We used cross-sectional, longitudinal, and polygenic risk score (PRS; for anxiety, depression, wellbeing) data from the Avon Longitudinal Study of Parents and Children (ALSPAC). We examined cross-sectional and prospective longitudinal associations between COVID-19 risk perceptions (i.e., cognitive, affective, self, other, and a combined ‘holistic’ measure) and mental health (i.e., anxiety, depression), wellbeing, and risk behaviours. Pandemic (April-July 2020) and pre-pandemic (2003-2017) data (ns = 233-5,115) were included. Results: Higher COVID-19 risk perceptions (holistic) were associated with anxiety (OR 2.78, 95% confidence interval [CI] 2.20 to 3.52), depression (OR 1.65, 95% CI 1.24 to 2.18), low wellbeing (OR 1.76, 95% CI 1.45 to 2.13), and increased alcohol use (OR 1.46, 95% CI 1.24 to 1.72). Higher COVID-19 risk perceptions were also associated with self-isolating given a suspected COVID-19 infection (OR 1.74, 95% CI 1.13 to 2.68), and less face-to-face contact (OR 0.83, 95% CI 0.70 to 0.98) and physical contact (OR 0.83, 95% CI 0.68 to 1.00). Pre-pandemic anxiety (OR 1.64, 95% CI 1.29 to 2.09) and low wellbeing (OR 1.41, 95% CI 1.15 to 1.74) were associated with higher COVID-19 risk perceptions. The depression PRS (b 0.21, 95% CI 0.02 to 0.40) and wellbeing PRS (b -0.29, 95% CI -0.48 to -0.09) were associated with higher and lower COVID-19 risk perceptions, respectively. Conclusions: Poorer mental health and wellbeing are associated with higher COVID-19 risk perceptions, and longitudinal and genetic data suggest that they may play a causal role in COVID-19 risk perceptions.

This is a snapshot of a Stage 1 registered report proposal for submission to PCI-RR.

The responsible conduct of research is foundational to the production of valid and trustworthy research. Despite this, our grasp of what dimensions responsible research (RR) might contain – and how it differs across disciplines (i.e., how it is conceptualized and operationalized) – is tenuous. Moreover, many initiatives related to developing and maintaining RR are developed within disciplinary and institutional silos which naturally limits the benefits that RR practice can have. To this end, we are working to develop a better understanding of how RR is conceived and realized, both across disciplines, and across institutions in Europe. The first step in doing this is to scope existing knowledge on the topic, of which this scoping review is a part. We searched several electronic databases for relevant published and grey literature. An initial sample of 715 articles was identified, with 75 articles included in the final sample for qualitative analysis. We find several dimensions of RR that are underemphasized or are excluded from the well-established World Conferences on Research Integrity Singapore Statement on Research Integrity (WCRI) and explore facets of these dimensions that find special relevance in a range of research disciplines.

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.

Objective: To use GWAS-by-subtraction to derive genome wide summary statistics for paternal smoking. Result: We implemented the GWAS by subtraction using a weighted linear model which defined the child-genotype paternal-phenotype association as the child-genotype child-phenotype association minus the child-genotype maternal-phenotype association. We used a Monte-Carlo simulation to validate the model and showed that it performed similarly in terms of bias to a traditional GWAS of paternal smoking. We then implemented the linear model to create GWASs of paternal smoking. Since both the input GWASs were derived from the UK Biobank, we created two GWASs, one where the input GWASs had both adjusted for genotyping chip, and one where they had not. Finally, we validated the summary statistics in a Mendelian randomisation analysis by finding an association between paternal smoking and paternal lung cancer and emphysema. We found differences between the UK Biobank genotyping chip adjusted and non- genotyping-chip adjusted GWASs. We would therefore caution naive applications of the latter GWAS, as it could be suffering from residual confounding.

BackgroundAlthough electronic cigarettes (e-cigarettes) appear to be effective in helping smokers to stop smoking, concerns about use of e-cigarettes among young people have led to restrictions on non-tobacco flavoured e-liquids in some countries. However, these restrictions could reduce the appeal of these products to non-smoking youth but could have unintended consequences for smokers and e-cigarette users (vapers). MethodsIn this qualitative study, we aimed to explore smokers’ and vapers’ opinions of unflavoured e-liquids and their beliefs about how they would be impacted by hypothetical e-liquid flavour restrictions. UK adult smokers and vapers trialled an unflavoured e-liquid instead of their usual nicotine product for four hours and completed a survey and an online interview. ResultsUsing Interpretive Phenomenological Analysis and graphically presented data, we found differences in smokers’ and vapers’ opinions of unflavoured e-liquid. If only unflavoured, tobacco flavoured, and menthol flavoured e-liquids remained on the UK market, some smokers and vapers may be unaffected, but some may be at a greater risk of relapsing to smoking or continuing smoking. Despite wanting to protect children from the harms of vaping, there was disagreement about whether flavour restrictions would be an effective method. ConclusionsThe findings indicate a potential adverse impact on smoking rates if e-liquid flavour restrictions are implemented in the UK.

Theoretical arguments and empirical investigations indicate that a high proportion of published findings are false or do not replicate. The current position paper provides a broad perspective on this scientific error, focusing both on reform history and on opportunities for future reform. Talking points are organised along four main themes: methodological reform, statistical reform, publishing reform, and institutional reform. For each of these four themes, we discuss the current state of affairs, existing knowledge gaps, and opportunities for future reform. The resulting agenda should provide a useful resource for ushering in an era that is marked by a lower prevalence of scientific error.

Two-sample MR is an increasingly popular method for strengthening causal inference in epidemiological studies. For the effect estimates to be meaningful, the studies used to estimate the variant-exposure and variant-outcome associations must come from comparable populations. A recent systematic review of two-sample MR studies found that, if assessed at all, MR studies assessed this assumption by checking that the genetic association studies had similar demographics. However, it is unclear if this is sufficient because less easily accessible factors, such as the prevalence of smoking for a lung cancer MR study, may also be important. Our letter therefore proposes an easy to implement falsification test which to the best of our knowledge is the first quantitative method for assessing this assumption. Since recent theoretical developments in causal inference suggest that a casual effect estimate can generalise from one study to another if there is exchangeability of effect modifiers, we suggest testing the homogeneity of variant-phenotype associations for a phenotype which has been measured in both genetic association studies as a method of exploring the ‘same-population’ test. We additionally developed a simple R package to facilitate the implementation of this test.

Background: The Research Excellence Framework (REF) in the United Kingdom is a system to assess the quality of research, requiring higher education institutions to select a sample of research outputs to submit for assessment. We tested whether prediction markets, in a novel application, could help institutions decide which research outputs to submit to the REF. Methods: Prediction markets are tools used to aggregate knowledge from a group who trade on the outcomes of future events. We ran six different prediction markets across three institutions in four different academic fields, asking participants to predict which papers in their department would score above a certain threshold in the REF.Results: Despite low participation in some markets, overall the prediction markets predicted mock REF outcomes with greater than 70% accuracy. We also compared the results of one market to random forests and logistic regression models trained to predict REF scores using bibliometrics, and found they had similar accuracy with prediction markets and high correlation with final market price, suggesting trades were partly informed by publication metrics. Conclusions: Our study provides a proof of concept that prediction markets can be used to forecast REF ratings, and that they capture similar information to other methods. Due to their pragmatic limitations, prediction markets are unlikely to entirely replace other methods of REF selection or research assessment, but they may offer a useful addition to REF selection and may be valuable in training contexts.

Background: It has been proposed that antidepressants operate by increasing sensitivity to positive versus negative information. Increasing positive affective learning within social contexts may play a key role in remediating negative self-schema. We investigated the association between change in biased learning of social evaluations about the self and others, and mood during early antidepressant treatment. Method: Prospective cohort assessing patients recruited from primary care sites in South West England at four timepoints over the first 8 weeks of antidepressant treatment. At each timepoint participants completed self-report measures of depression (BDI-II, PHQ-9), anxiety (GAD-7), and a computerised task measuring learning of social evaluations about the self, a friend, and a stranger. Results: We did not find evidence that learning about the self was associated with a reduction in PHQ-9 (b=0.08, 95%CI:-0.05,0.20, p=0.239) or BDI-II scores (b=0.10, 95%CI:-0.18,0.38, p=0.469). We found some weak evidence that increased positive learning about the friend was associated with a reduction in BDI-II scores (b=0.30, 95%CI:-0.02, 0.62, p=0.069). However, exploratory analyses indicated stronger evidence that increased positive learning about the self (b=0.18, 95% CI:0.07,0.28, p=0.002) and a friend (b=0.22, 95%CI:0.10,0.35, p=0.001) was associated with a reduction in anxiety.Conclusions: Change in social evaluation learning was more reliably associated with a reduction in anxiety rather than depression. Antidepressants may treat anxiety symptoms by remediating negative affective biases towards socially threatening information directed towards the self and close others. However, our findings are based on exploratory analyses within a small sample and require further replication.

Background: Major Depressive Disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls.Methods: Participants from Generation Scotland (N=1,109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n=43), MDD-remitted (n=282), or controls (n=784). Analysis included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). Results: For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition (e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)). Results for remitted-MDD were less consistent.Conclusions: This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by g, with no evidence for affective biases in remitted individuals.

We present consensus-based guidance for conducting and documenting multi-analyst studies. We discuss why broader adoption of the multi-analyst approach will strengthen the robustness of results and conclusions in empirical sciences.

Background: Body dissatisfaction is a key part of the psychopathology of eating disorders, but there is a lack of consensus as to whether the dissatisfaction arises from misperception of body size, and if such misperception applies to others’ as well as own size. Methods: We conducted a case control study of women with and without an eating disorder, confirmed using the Eating Disorders Examination. We used a range of measures to investigate differences between groups in their perception of others’ and own body size, and satisfaction with own size, including rating photographs of other women, manipulating an avatar to “own” and “ideal” size, and novel implicit measures (Lexical Decision and Implicit Association Tasks). Results: We recruited 30 cases and 30 controls. Cases rated 12% more photographs of other women as overweight and 7% fewer as underweight, even after adjusting for participant BMI. We found no evidence for a difference between groups in the accuracy of their avatar representation of own size, but cases rated themselves as larger using a VAS scale and had a smaller avatar-demonstrated “ideal BMI” (case ideal BMI: 15.5 (95% CI 14.1, 16.9); control ideal BMI: 21.6 (95% CI 21.6 (20.4, 22.8)). We found no strong evidence for between-group differences on implicit measures. Discussion: Our results suggest that people with eating disorders are equally accurate at judging size, but have lower set points for their view of “normal weight” than controls. This lower threshold for what constitutes “normal” weight may contribute to patients with eating disorders’ dissatisfaction with their own size.

Background: Body dissatisfaction is a key feature of eating disorders. It is measured using questionnaires asking about satisfaction with body parts, or how feelings about weight and shape influence behaviour. Qualitative research finds that women most frequently use clothing to manage their appearance. Methods: We designed an Outfit Choice Task to assess clothing choice. We compared it with existing measures of body dissatisfaction in: Study 1, (online study of 244 women); Study 2 (face-to-face study of 93 women); and Study 3 (case-control study of 30 women with, and 30 without, a diagnosed eating disorder). Results: The Outfit Choice Task factor analysed into five factors comprising different types of outfit. Scores were strongly associated with existing measures of body dissatisfaction, after adjusting for Body Mass Index and age. Mean scores were lower (greater dissatisfaction) in those with an eating disorder (4.22 (95% 3.91, 4.52)) than controls (5.35 (95% CI 5.05, 5.64)). Discussion: The Outfit Choice Task provides a novel way of measuring body dissatisfaction. Since women are most likely to use clothing to manage concerns with their appearance, this scale is likely to be very relevant to women, and has potential use for measuring change in body dissatisfaction.

Aims: Across three eye-tracking studies, we examined how the location, framing, immediacy, and severity of health warnings on branded cigarette packs affected visual attention and self-reported avoidance of and reactance to warnings. Design: Study 1: smoking status × warning immediacy (short-term vs. long-term) × warning location (top of back vs. bottom of pack). Study 2: smoking status × warning framing (gain-framed vs. loss-framed) × warning format (text-only vs. pictorial). Study 3: smoking status × warning severity (highly-severe vs. moderately-severe). Setting: University of Bristol, UK, eye-tracking laboratory. Participants Study 1: non-smokers (n=25), weekly smokers (n=25), and daily smokers (n=25). Study 2: non-smokers (n=37), smokers contemplating quitting (n=37) and smokers not contemplating quitting (n=43). Study 3: non-smokers (n=27), weekly smokers (n=26) and daily smokers (n=26). Measurements: For all studies: relative number of fixations to the warning vs. the brand, self-reported avoidance of and reactance to warnings and for Study 3: effect of warning on quitting motivation. Findings: Study 1: Greater self-reported avoidance (p0.001). Study 3: Greater self-reported avoidance of (p

Background. The aim of these studies was to investigate the effect of nucleated glasses on the likeability and drinking rate of lager in social alcohol drinkers. Methods. In Study 1, participants (n = 116) were asked to taste two glasses of lager (280 ml each) in separate 5-minute taste tests and fill out a likeability questionnaire (items on a 100 mm visual analogue scale (VAS)) after each glass in a within-subjects design with one factor of glass (nucleated, non-nucleated). In Study 2, participants (n = 160) were asked to consume a pint of lager (568 ml) and fill out a likeability questionnaire in a between-subjects design with one factor of glass (nucleated, non-nucleated). Results. There was no clear evidence that likeability of lager differed between nucleated and non-nucleated glasses in either study. In Study 1, there was strong evidence (nucleated: 74.2, non-nucleated: 64.0, MD = 10.2, 95% CI: 6.1, 14.2, p < 0.001) that lager in nucleated glasses was more visually appealing (single item from likeability measure) than lager in non-nucleated glasses. In Study 2, there was no clear evidence (nucleated: 16.9 mins, non-nucleated: 16.3 mins, MD: 0.6 mins, p = 0.57) that lager was consumed at different rates from nucleated and non-nucleated glasses.Conclusions. Nucleated lager glasses do not appear to alter the likeability or consumption (volume consumed or drinking rate) of lager, although they do seem to increase the visual appeal of lager.