S1 Appendix -

Risk factors associated with depression in athletes include biological sex, physical pain, and history of sport-related concussion (SRC). Due to the well-documented benefits of sport and physical activity on mental health, athletes and non-athletes were recruited to assess any differences. Beyond this, athletes were also grouped by sport-type (contact/non-contact sports) due to the increased prevalence of pain and SRC in contact sports. To our knowledge, there has been no research on how these factors influence the likelihood of depression. In the current study, 144 participants completed a short survey on the above factors and the Center for Epidemiological Studies Depression Scale. Sixty-two of these reported a history of concussion. Logistic regression revealed all the above predictors to be significantly associated with the depression scale. Individuals that had previously sustained SRC, were experiencing greater physical pain and females were more likely to display poor mental health. However, we provide further evidence for the benefits of engaging in sport and physical activity as those that took part in sport were less likely to report depression. Therefore, this study provides a simple risk metric whereby sportspeople can make a better informed choice of their sporting participation, making their own cost/reward judgement.</div

Descriptive statistics depicting scores of physical pain and depression by sport-type.

Descriptive statistics depicting scores of physical pain and depression by sport-type.</p

Logistic regression predicting the likelihood of reporting meaningful depressive symptoms.

Logistic regression predicting the likelihood of reporting meaningful depressive symptoms.</p

<i>PLOS ONE</i> clinical studies checklist.

Risk factors associated with depression in athletes include biological sex, physical pain, and history of sport-related concussion (SRC). Due to the well-documented benefits of sport and physical activity on mental health, athletes and non-athletes were recruited to assess any differences. Beyond this, athletes were also grouped by sport-type (contact/non-contact sports) due to the increased prevalence of pain and SRC in contact sports. To our knowledge, there has been no research on how these factors influence the likelihood of depression. In the current study, 144 participants completed a short survey on the above factors and the Center for Epidemiological Studies Depression Scale. Sixty-two of these reported a history of concussion. Logistic regression revealed all the above predictors to be significantly associated with the depression scale. Individuals that had previously sustained SRC, were experiencing greater physical pain and females were more likely to display poor mental health. However, we provide further evidence for the benefits of engaging in sport and physical activity as those that took part in sport were less likely to report depression. Therefore, this study provides a simple risk metric whereby sportspeople can make a better informed choice of their sporting participation, making their own cost/reward judgement.</div

Correlations of independent variables.

Risk factors associated with depression in athletes include biological sex, physical pain, and history of sport-related concussion (SRC). Due to the well-documented benefits of sport and physical activity on mental health, athletes and non-athletes were recruited to assess any differences. Beyond this, athletes were also grouped by sport-type (contact/non-contact sports) due to the increased prevalence of pain and SRC in contact sports. To our knowledge, there has been no research on how these factors influence the likelihood of depression. In the current study, 144 participants completed a short survey on the above factors and the Center for Epidemiological Studies Depression Scale. Sixty-two of these reported a history of concussion. Logistic regression revealed all the above predictors to be significantly associated with the depression scale. Individuals that had previously sustained SRC, were experiencing greater physical pain and females were more likely to display poor mental health. However, we provide further evidence for the benefits of engaging in sport and physical activity as those that took part in sport were less likely to report depression. Therefore, this study provides a simple risk metric whereby sportspeople can make a better informed choice of their sporting participation, making their own cost/reward judgement.</div

Age group for each sample (N (%)).

BackgroundPrevious investigations suggest that the COVID-19 pandemic effects on alcohol consumption were heterogenous and may vary as a function of structural and psychological factors. Research examining mediating or moderating factors implicated in pandemic-occasioned changes in drinking have also tended to use single-study cross-sectional designs and convenience samples. Aims: First, to explore structural (changed employment or unemployment) and psychological (subjective mental health and drinking motives) correlates of consumption reported during the COVID-19 pandemic using a UK nationally representative (quota sampled) dataset. Second, to determine whether population-level differences in drinking during the COVID-19 pandemic (versus pre-pandemic levels) could be attributable to drinking motives. Method: Data collected from samples of UK adults before and during the pandemic were obtained and analysed: Step1 carried out structural equation modelling (SEM) to explore data gathered during a period of social restrictions after the UK’s first COVID-19-related lockdown (27 August-15 September, 2020; n = 3,798). It assessed whether drinking motives (enhancement, social, conformity, coping), employment and the perceived impact of the pandemic on subjective mental health may explain between-person differences in self-reported alcohol consumption. Step 2 multigroup SEM evaluated data gathered pre-pandemic (2018; n = 7,902) in concert with the pandemic data from step 1, to test the theory that population-level differences in alcohol consumption are attributable to variances in drinking motives. Results: Analyses of the 2020 dataset detected both direct and indirect effects of subjective mental health, drinking motives, and employment matters (e.g., having been furloughed) on alcohol use. Findings from a multigroup SEM were consistent with the theory that drinking motives explain not only individual differences in alcohol use at both time points, but also population-level increases in use during the pandemic. Conclusion: This work highlights socioeconomic and employment considerations when seeking to understand COVID-19-related drinking. It also indicates that drinking motives may be particularly important in explaining the apparent trend of heightened drinking during the pandemic. Limitations related to causal inference are discussed.</div

Final model parameters.

BackgroundPrevious investigations suggest that the COVID-19 pandemic effects on alcohol consumption were heterogenous and may vary as a function of structural and psychological factors. Research examining mediating or moderating factors implicated in pandemic-occasioned changes in drinking have also tended to use single-study cross-sectional designs and convenience samples. Aims: First, to explore structural (changed employment or unemployment) and psychological (subjective mental health and drinking motives) correlates of consumption reported during the COVID-19 pandemic using a UK nationally representative (quota sampled) dataset. Second, to determine whether population-level differences in drinking during the COVID-19 pandemic (versus pre-pandemic levels) could be attributable to drinking motives. Method: Data collected from samples of UK adults before and during the pandemic were obtained and analysed: Step1 carried out structural equation modelling (SEM) to explore data gathered during a period of social restrictions after the UK’s first COVID-19-related lockdown (27 August-15 September, 2020; n = 3,798). It assessed whether drinking motives (enhancement, social, conformity, coping), employment and the perceived impact of the pandemic on subjective mental health may explain between-person differences in self-reported alcohol consumption. Step 2 multigroup SEM evaluated data gathered pre-pandemic (2018; n = 7,902) in concert with the pandemic data from step 1, to test the theory that population-level differences in alcohol consumption are attributable to variances in drinking motives. Results: Analyses of the 2020 dataset detected both direct and indirect effects of subjective mental health, drinking motives, and employment matters (e.g., having been furloughed) on alcohol use. Findings from a multigroup SEM were consistent with the theory that drinking motives explain not only individual differences in alcohol use at both time points, but also population-level increases in use during the pandemic. Conclusion: This work highlights socioeconomic and employment considerations when seeking to understand COVID-19-related drinking. It also indicates that drinking motives may be particularly important in explaining the apparent trend of heightened drinking during the pandemic. Limitations related to causal inference are discussed.</div

Final model diagram (values are standardised estimates).

Final model diagram (values are standardised estimates).</p

Pattern matrix showing loadings of variables on the extracted principal components.

Pattern matrix showing loadings of variables on the extracted principal components.</p

S2 File -

BackgroundPrevious investigations suggest that the COVID-19 pandemic effects on alcohol consumption were heterogenous and may vary as a function of structural and psychological factors. Research examining mediating or moderating factors implicated in pandemic-occasioned changes in drinking have also tended to use single-study cross-sectional designs and convenience samples. Aims: First, to explore structural (changed employment or unemployment) and psychological (subjective mental health and drinking motives) correlates of consumption reported during the COVID-19 pandemic using a UK nationally representative (quota sampled) dataset. Second, to determine whether population-level differences in drinking during the COVID-19 pandemic (versus pre-pandemic levels) could be attributable to drinking motives. Method: Data collected from samples of UK adults before and during the pandemic were obtained and analysed: Step1 carried out structural equation modelling (SEM) to explore data gathered during a period of social restrictions after the UK’s first COVID-19-related lockdown (27 August-15 September, 2020; n = 3,798). It assessed whether drinking motives (enhancement, social, conformity, coping), employment and the perceived impact of the pandemic on subjective mental health may explain between-person differences in self-reported alcohol consumption. Step 2 multigroup SEM evaluated data gathered pre-pandemic (2018; n = 7,902) in concert with the pandemic data from step 1, to test the theory that population-level differences in alcohol consumption are attributable to variances in drinking motives. Results: Analyses of the 2020 dataset detected both direct and indirect effects of subjective mental health, drinking motives, and employment matters (e.g., having been furloughed) on alcohol use. Findings from a multigroup SEM were consistent with the theory that drinking motives explain not only individual differences in alcohol use at both time points, but also population-level increases in use during the pandemic. Conclusion: This work highlights socioeconomic and employment considerations when seeking to understand COVID-19-related drinking. It also indicates that drinking motives may be particularly important in explaining the apparent trend of heightened drinking during the pandemic. Limitations related to causal inference are discussed.</div