Systems thinking in COVID-19 recovery is urgently needed to deliver sustainable development for women and girls.

In low-income and middle-income countries, such as those in sub-Saharan Africa and Latin America, the COVID-19 pandemic has had substantial implications for women's wellbeing. Policy responses to the COVID-19 pandemic have highlighted the gendered aspect of pandemics; however, addressing the gendered implications of the COVID-19 pandemic comprehensively and effectively requires a planetary health perspective that embraces systems thinking to inequalities. This Viewpoint is based on collective reflections from research done by the authors on COVID-19 responses by international and regional organisations, and national governments, in Latin America and sub-Saharan Africa between June, 2020, and June, 2021. A range of international and regional actors have made important policy recommendations to address the gendered implications of the COVID-19 pandemic on women's health and wellbeing since the start of the pandemic. However, national-level policy responses to the COVID-19 pandemic have been partial and inconsistent with regards to gender in both sub-Saharan Africa and Latin America, largely failing to recognise the multiple drivers of gendered health inequalities. This Viewpoint proposes that addressing the effects of the COVID-19 pandemic on women in low-income and middle-income countries should adopt a systems thinking approach and be informed by the question of who is affected as opposed to who is infected. In adopting the systems thinking approach, responses will be more able to recognise and address the direct gendered effects of the pandemic and those that emerge indirectly through a combination of long-standing structural inequalities and gendered responses to the pandemic.

Repurposing NGO data for better research outcomes: a scoping review of the use and secondary analysis of NGO data in health policy and systems research.

BACKGROUND: Non-governmental organisations (NGOs) collect and generate vast amounts of potentially rich data, most of which are not used for research purposes. Secondary analysis of NGO data (their use and analysis in a study for which they were not originally collected) presents an important but largely unrealised opportunity to provide new research insights in critical areas, including the evaluation of health policy and programmes. METHODS: A scoping review of the published literature was performed to identify the extent to which secondary analysis of NGO data has been used in health policy and systems research (HPSR). A tiered analytical approach provided a comprehensive overview and descriptive analyses of the studies that (1) used data produced or collected by or about NGOs; (2) performed secondary analysis of the NGO data (beyond the use of an NGO report as a supporting reference); and (3) analysed NGO-collected clinical data. RESULTS: Of the 156 studies that performed secondary analysis of NGO-produced or collected data, 64% (n = 100) used NGO-produced reports (mostly to a limited extent, as a contextual reference or to critique NGO activities) and 8% (n = 13) analysed NGO-collected clinical data. Of these studies, 55% (n = 86) investigated service delivery research topics and 48% (n = 51) were undertaken in developing countries and 17% (n = 27) in both developing and developed countries. NGOs were authors or co-authors of 26% of the studies. NGO-collected clinical data enabled HPSR within marginalised groups (e.g. migrants, people in conflict-affected areas), albeit with some limitations such as inconsistent and missing data. CONCLUSION: We found evidence that NGO-collected and produced data are most commonly perceived as a source of supporting evidence for HPSR and not as primary source data. However, these data can facilitate research in under-researched marginalised groups and in contexts that are hard to reach by academics such as conflict-affected areas. NGO-academic collaboration could help address issues of NGO data quality to facilitate their more widespread use in research. The use of NGO data use could enable relevant and timely research in the areas of programme evaluation and health policy and advocacy to improve health and reduce health inequalities, especially in marginalised groups and developing countries.

The relationship between anxiety and acute mountain sickness.

INTRODUCTION: Whilst the link between physical factors and risk of high altitude (HA)-related illness and acute mountain sickness (AMS) have been extensively explored, the influence of psychological factors has been less well examined. In this study we aimed to investigate the relationship between 'anxiety and AMS risk during a progressive ascent to very HA. METHODS: Eighty health adults were assessed at baseline (848m) and over 9 consecutive altitudes during a progressive trek to 5140m. HA-related symptoms (Lake Louise [LLS] and AMS-C Scores) and state anxiety (State-Trait-Anxiety-Score [STAI Y-1]) were examined at each altitude with trait anxiety (STAI Y-2) at baseline. RESULTS: The average age was 32.1 ± 8.3 years (67.5% men). STAI Y-1 scores fell from 848m to 3619m, before increasing to above baseline scores (848m) at ≥4072m (p = 0.01). STAI Y-1 scores correlated with LLS (r = 0.31; 0.24-0.3; P<0.0001) and AMS-C Scores (r = 0.29; 0.22-0.35; P<0.0001). There was significant main effect for sex (higher STAI Y-1 scores in women) and altitude with no sex-x-altitude interaction on STAI Y-1 Scores. Independent predictors of significant state anxiety included female sex, lower age, higher heart rate and increasing LLS and AMS-C scores (p<0.0001). A total of 38/80 subjects (47.5%) developed AMS which was mild in 20 (25%) and severe in 18 (22.5%). Baseline STAI Y-2 scores were an independent predictor of future severe AMS (B = 1.13; 1.009-1.28; p = 0.04; r2 = 0.23) and STAI Y-1 scores at HA independently predicted AMS and its severity. CONCLUSION: Trait anxiety at low altitude was an independent predictor of future severe AMS development at HA. State anxiety at HA was independently associated with AMS and its severity.

Not all risks are equal: the risk taking inventory for high-risk sports.

Although high-risk sport participants are typically considered a homogenous risk-taking population, attitudes to risk within the high-risk domain can vary considerably. As no validated measure allows researchers to assess risk taking within this domain, we validated the Risk Taking Inventory (RTI) for high-risk sport across four studies. The RTI comprises seven items across two factors: deliberate risk taking and precautionary behaviors. In Study 1 (n = 341), the inventory was refined and tested via a confirmatory factor analysis used in an exploratory fashion. The subsequent three studies confirmed the RTI's good model-data fit via three further separate confirmatory factor analyses. In Study 2 (n = 518) and in Study 3 (n = 290), concurrent validity was also confirmed via associations with other related traits (sensation seeking, behavioral activation, behavioral inhibition, impulsivity, self-esteem, extraversion, and conscientiousness). In Study 4 (n = 365), predictive validity was confirmed via associations with mean accidents and mean close calls in the high-risk domain. Finally, in Study 4, the self-report version of the inventory was significantly associated with an informant version of the inventory. The measure will allow researchers and practitioners to investigate risk taking as a variable that is conceptually distinct from participation in a high-risk sport.