The etiology of running-related injury is important to consider as the effectiveness of a given running-related injury prevention intervention is dependent on whether etiologic factors are readily modifiable and consistent with a biologically plausible causal mechanism. Therefore, the purpose of the present article was to present an evidence-informed conceptual framework outlining the multifactorial nature of running-related injury etiology. In the framework, four mutually exclusive parts are presented: (a) Structure-specific capacity when entering a running session; (b) structure-specific cumulative load per running session; (c) reduction in the structure-specific capacity during a running session; and (d) exceeding the structure-specific capacity. The framework can then be used to inform the design of future running-related injury prevention studies, including the formation of research questions and hypotheses, as well as the monitoring of participation-related and non-participation-related exposures. In addition, future research applications should focus on addressing how changes in one or more exposures influence the risk of running-related injury. This necessitates the investigation of how different factors affect the structure-specific load and/or the load capacity, and the dose-response relationship between running participation and injury risk. Ultimately, this direction allows researchers to move beyond traditional risk factor identification to produce research findings that are not only reliably reported in terms of the observed cause-effect association, but also translatable in practice.

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IntroductionRunning injuries affect millions of persons every year and have become a substantial public health issue owing to the popularity of running. To ensure adherence to running, it is important to prevent injuries and to have an in-depth understanding of the aetiology of running injuries. The main purpose of the present paper was to describe the design of a future prospective cohort study exploring if a dose–response relationship exists between changes in training load and running injury occurrence, and how this association is modified by other variables.Methods and analysisIn this protocol, the design of an 18-month observational prospective cohort study is described that will include a minimum of 20 000 consenting runners who upload their running data to Garmin Connect and volunteer to be a part of the study. The primary outcome is running-related injuries categorised into the following states: (1) no injury; (2) a problem; and (3) injury. The primary exposure is change in training load (eg, running distance and the cumulative training load based on the number of strides, ground contact time, vertical oscillation and body weight). The change in training load is a time-dependent exposure in the sense that progression or regression can change many times during follow-up. Effect-measure modifiers include, but is not limited to, other types of sports activity, activity of daily living and demographics, and are assessed through questionnaires and/or by Garmin devices.Ethics and disseminationThe study design, procedures and informed consent have been evaluated by the Ethics Committee of the Central Denmark Region (Request number: 227/2016 – Record number: 1-10-72-189-16).

Background Only about half of all patients with anxiety disorders or major depression respond to cognitive behaviour therapy (CBT), even though this is an evidence-based treatment. Personalized treatment offers an approach to increase the number of patients who respond to therapy. The aim of this study was to examine predictors and moderators of (differential) treatment outcomes in transdiagnostic versus diagnosis-specific group CBT. Methods A sample of 291 patients from three different mental health clinics in Denmark was randomized to either transdiagnostic or diagnosis-specific group CBT. The study outcome was the regression slope of the individual patient's repeated scores on the WHO-5 Well-being Index. Pre-treatment variables were identified as moderators or predictors through a two-step variable selection approach. Results While the two-step approach failed to identify any moderators, four predictors were found: level of positive affect, duration of disorder, the detachment personality trait, and the coping strategy of cognitive reappraisal. A prognostic index was constructed, but did not seem to be robust across treatment sites. Conclusions Our findings give insufficient evidence to support a recommendation of either transdiagnostic or diagnosis-specific CBT for a given patient or to predict the response to the applied group therapies.

Objectives: To investigate how individuals with a history of affective disorder use and perceive their use of social media and online dating. Methods: A questionnaire focusing on affective disorders and the use of social media and online dating was handed out to outpatients from unipolar depression and bipolar disorder clinics and general practice patients with or without a history of affective disorders (latter as controls). The association between affective disorders and use of social media and online dating was analyzed using linear/logistic regression. Results: A total of 194 individuals with a history of unipolar depression, 124 individuals with a history of bipolar disorder and 196 controls were included in the analysis. Having a history of unipolar depression or bipolar disorder was not associated with the time spent on social media compared with controls. Using the controls as reference, having a history bipolar disorder was associated with use of online dating (adjusted odds ratio: 2.2 (95% CI: 1.3; 3.7)). The use of social media and online dating had a mood-congruent pattern with decreased and more passive use during depressive episodes, and increased and more active use during hypomanic/manic episodes. Among the respondents with a history of affective disorder, 51% reported that social media use had an aggravating effect on symptoms during mood episodes, while 10% reported a beneficial effect. For online dating, the equivalent proportions were 49% (aggravation) and 20% (benefit), respectively. Conclusion: The use of social media and online dating seems related to symptom deterioration among individuals with affective disorder.