A scoping review of the relationship between running and mental health

Poor mental health contributes significantly to global morbidity. The evidence regarding physical benefits of running are well-established. However, the mental health impacts of running remain unclear. An overview of the relationship between running and mental health has not been published in the last 30 years. The purpose of this study was to review the literature on the relationship between running and mental health. Our scoping review used combinations of running terms (e.g., Run* and Jog*) and mental health terms (general and condition specific). Databases used were Ovid(Medline), Ovid(Embase), ProQuest and SportDiscus. Quantitative study types reporting on the relationships between running and mental health were included. Database searches identified 16,401 studies; 273 full-texts were analysed with 116 studies included. Overall, studies suggest that running bouts of variable lengths and intensities, and running interventions can improve mood and mental health and that the type of running can lead to differential effects. However, lack of controls and diversity in participant demographics are limitations that need to be addressed. Cross-sectional evidence shows not only a range of associations with mental health but also some associations with adverse mental health (such as exercise addiction). This review identified extensive literature on the relationship between running and mental health

Do framed mental health messages on social media influence university students’ motivation for physical activity?

Message framing has been used as a strategy for promoting physical activity (PA) in university students, but the effectiveness of gain-framed (GF), or loss-framed (LF) messages is variable. This study aims to investigate the effects on motivation and PA behaviour of framed messaging on social media in university students. Gain- and loss-framed messages communicated the mental health outcomes of PA. A three-arm feasibility study (n = 148) collected pre-post intervention online questionnaire responses to assess motivation for PA, exercise, active travel, and PA levels, in response to the messaging intervention on Facebook. Both GF and LF messages effectively increased average motivation for PA in comparison to controls (GF by 0.3 (on a 7-point Likert scale), 9% [95% CI: 3–17%], p = 0.007, LF by 0.3, 10% [CI: 3–18%], p = 0.005). Average motivation for exercise increased in comparison to controls (GF by 0.6, 16% [95% CI: 6–26%], p = 0.001, LF by 0.5, 14.6% [95% CI: 5–26%], p p p < 0.001). No meaningful differences between GF or LF messages were observed. Framed messages regarding mental health outcomes of PA delivered via social media could be effective for increasing PA motivation in university students. However, based on our results there is no gain- or loss-framed advantage

A modified Delphi study to enhance and gain international consensus on the Physical Activity Messaging Framework (PAMF) and Checklist (PAMC)

Abstract Introduction Physical activity messaging is an important step in the pathway towards improving population physical activity levels, but best practice is not yet understood. A gap in the literature exists for a physical activity messaging framework to help guide creation and evaluation of messages. This study aimed to further develop and improve, and gain international expert consensus on, a standardised Physical Activity Messaging Framework and Checklist. Methods A modified Delphi study consisting of three online survey rounds was conducted. Each survey gathered feedback from an international expert panel using quantitative and qualitative methods. The framework and checklist were amended between each round based on survey results until consensus (defined a priori as 80% agreement) was reached. Results The final expert panel (n = 40, 55% female) came from nine countries and comprised academics (55%), healthcare and other professionals (22.5%) and government officials or policymakers (22.5%). Consensus was reached in survey 3 with 85 and 87.5% agreement on the framework and checklist, respectively. Conclusion This study presents an expert- and evidence-informed framework and checklist for physical activity messaging. If used consistently, the Physical Activity Messaging Framework and Checklist may improve practice by encouraging evidence-based and target audience-focused messages, as well as enhance the research base on physical activity messaging by harmonising key terminologies and improving quality of reporting. Key next steps include further refining the Physical Activity Messaging Framework and Checklist based on their use in real-world settings

Different analysis methods of Scottish and English child physical activity data explain the majority of the difference between the national prevalence estimates

Abstract Background The percentages of children in Scotland and England meeting the aerobic physical activity (PA) recommendation differ greatly according to estimates derived from the respective national health surveys. The Scottish Health Survey (SHeS) usually estimates over 70% meeting the recommendation; Health Survey for England (HSE) estimates are usually below 25%. It is plausible that these differences originate from different analysis methods. The HSE monitors the percentage of children in England that undertake 60 min of moderate-to-vigorous PA on each day of the week (‘Daily Minimum Method’ (DMM)). The SHeS monitors the proportion that undertakes at least seven sessions of moderate-to-vigorous PA, with an average daily duration ≥60 min in Scotland (‘Weekly Average Method’ (WAM)). We aimed to establish how much this difference in analysis methods influences prevalence estimates. Methods PA data from 5 to 15 year olds in the 2015 HSE and SHeS were reanalysed (weighted n = 3840 and 965, respectively). Two comparable pairs of estimates were derived: a DMM and WAM estimate from the HSE not including travel to/from school, and WAM estimates from the HSE and the SHeS including travel to/from school. It is not possible to calculate a DMM estimate from the SHeS due to questionnaire design. Results were presented for the total samples, and by sex and age sub-groups. Results The HSE WAM estimate was 31.7 (95% CI: 30.2–33.3) percentage points higher than the DMM estimate (54.3% (95% CI: 52.6–56.0) and 22.6% (95% CI: 21.2–24.1) respectively). The magnitude of this difference differed by age group but not sex. When comparable WAM estimates were derived from the SHeS and the HSE, the SHeS was 11.8 percentage points higher (73.6% (95% CI: 69.8–77.1) and 61.8% (95% CI: 60.2–63.5) respectively). The magnitude of this difference differed by age group and sex. Conclusions The results indicate that the difference in the analysis method explains the majority (approximately 30 percentage points) of the difference in the child PA prevalence estimates between Scotland and England (leaving approximately 12 percentage points representing true differences or related to questionnaire differences). These results will help national surveillance determine how to increase comparability between the U.K. home nations

The Physical Activity Messaging Framework (PAMF) and Checklist (PAMC): International consensus statement and user guide

Effective physical activity messaging plays an important role in the pathway towards changing physical activity behaviour at a population level. The Physical Activity Messaging Framework (PAMF) and Checklist (PAMC) are outputs from a recent modified Delphi study. This sought consensus from an international expert panel on how to aid the creation and evaluation of physical activity messages. In this paper, we (1) present an overview of the various concepts within the PAMF and PAMC, (2) discuss in detail how the PAMF and PAMC can be used to create physical activity messages, plan evaluation of messages, and aid understanding and categorisation of existing messages, and (3) highlight areas for future development and research. If adopted, we propose that the PAMF and PAMC could improve physical activity messaging practice by encouraging evidence-based and target population-focused messages with clearly stated aims and consideration of potential working pathways. They could also enhance the physical activity messaging research base by harmonising key messaging terminologies, improving quality of reporting, and aiding collation and synthesis of the evidence