Mitigating the impact of air pollution on dementia and brain health: Setting the policy agenda.

BACKGROUND: Emerging research suggests exposure to high levels of air pollution at critical points in the life-course is detrimental to brain health, including cognitive decline and dementia. Social determinants play a significant role, including socio-economic deprivation, environmental factors and heightened health and social inequalities. Policies have been proposed more generally, but their benefits for brain health have yet to be fully explored. OBJECTIVE AND METHODS: Over the course of two years, we worked as a consortium of 20+ academics in a participatory and consensus method to develop the first policy agenda for mitigating air pollution's impact on brain health and dementia, including an umbrella review and engaging 11 stakeholder organisations. RESULTS: We identified three policy domains and 14 priority areas. Research and Funding included: (1) embracing a complexities of place approach that (2) highlights vulnerable populations; (3) details the impact of ambient PM2.5 on brain health, including current and historical high-resolution exposure models; (4) emphasises the importance of indoor air pollution; (5) catalogues the multiple pathways to disease for brain health and dementia, including those most at risk; (6) embraces a life course perspective; and (7) radically rethinks funding. Education and Awareness included: (8) making this unrecognised public health issue known; (9) developing educational products; (10) attaching air pollution and brain health to existing strategies and campaigns; and (11) providing publicly available monitoring, assessment and screening tools. Policy Evaluation included: (12) conducting complex systems evaluation; (13) engaging in co-production; and (14) evaluating air quality policies for their brain health benefits. CONCLUSION: Given the pressing issues of brain health, dementia and air pollution, setting a policy agenda is crucial. Policy needs to be matched by scientific evidence and appropriate guidelines, including bespoke strategies to optimise impact and mitigate unintended consequences. The agenda provided here is the first step toward such a plan.

The Personal Social Networks of Resettled Bhutanese Refugees During Pregnancy in the United States: A Social Network Analysis.

Women comprise 50% of the refugee population, 25% of whom are of reproductive age. Female refugees are at risk for experiencing significant hardships associated with the refugee experience, including after resettlement. For refugee women, the strength of their personal social networks can play an important role in mitigating the stress of resettlement and can be an influential source of support during specific health events, such as pregnancy. A personal social network analysis was conducted among 45 resettled Bhutanese refugee women who had given birth within the past 2 years in the Akron Metropolitan Area of Northeast Ohio. Data were collected using in-depth interviews conducted in Nepali over a 6-month period in 2016. Size, demographic characteristics of ties, frequency of communication, length of relationship, and strength of connection were the social network measures used to describe the personal networks of participants. A qualitative analysis was also conducted to assess what matters were commonly discussed within networks and how supportive participants perceived their networks to be. Overall, participants reported an average of 3 close personal connections during their pregnancy. The networks were comprised primarily of female family members whom the participant knew prior to resettlement in the U.S. Participants reported their networks as "very close" and perceived their connections to be supportive of them during their pregnancies. These results may be used to guide future research, as well as public health programming, that seeks to improve the pregnancy experiences of resettled refugee women.

A 'Cultural Models' Approach to Psychotherapy for Refugees and Asylum Seekers: A Case Study from the UK.

Despite the existence of significant research on the mental health care challenges of migrants, particularly refugees and asylum seekers, less attention has been paid to treatment approaches. We used a case study from the UK to look at the topic from a cultural models approach (which comes from cognitive anthropology) to analyse migrants' experiences with mental health care. Twenty-five refugees and asylum seekers living in North East England and Northern Ireland were interviewed who had used at least six sessions of talking therapy during the last three years. Our results suggested that adopting a 'cultural models' approach, which offers a new conceptual and methodological framework of migrants' experiences and their underlying schemas and expectations, would significantly contribute to building therapeutic alliances and provide relevant and appropriate treatments for migrant clients, particularly for unrecognised pre- and post-migration traumatic experiences.

Exploring the Networking of Academic Health Science Leaders: How and Why Do They Do It?

PURPOSE: Networking is essential to leadership effectiveness in the business context. Yet little is known about leadership networking within the academic health science context. If we are going to train academic leaders, we must first understand the relational, network-based activities of their work. The purpose of this study was to explore how academic health science leaders engage in networking activities in the academic health science context. METHOD: A constructivist grounded theory approach guided our study. The authors interviewed 24 academic health science leaders who were enrolled in the New and Evolving Academic Leadership program at the University of Toronto and used social network mapping as an elicitation method. Interviews, which were conducted between September 2014 and June 2015, explored participants' networks and networking activities. Constant comparative analysis was used to analyze the interviews, with attention paid to identifying key networking activities. RESULTS: Academic health science leaders were found to engage in 4 types of networking activities: role bound, project based, goal/vision informed, and opportunity driven. These 4 types were influenced by participants' conception of their role and their perceived leadership work context, which in turn influenced their sense of agency. CONCLUSIONS: The networking activities identified in this study of academic health science leaders resonate with effective networking activities found in other fields. The findings highlight that these activities can be facilitated by focusing on leaders' perceptions about role and work context. Leadership development should thus attend to these perceptions to encourage effective networking skills.

Factors Associated with the Presence of Strong Social Supports in Bhutanese Refugee Women During Pregnancy.

Social support may mitigate stress related to the refugee experience, including during resettlement. For refugee women, social support can play an important role during pregnancy. In-depth interviews were conducted within a sample of 45 Bhutanese refugee women. Perceived social support was measured using the Norbeck Social Support Questionnaire. Averaged social support scores are reported to account for personal network size. Participants were identified as "low support" and "high support" based on their reported score. The mean social support score reported was 18.9. Participants experiencing a secondary resettlement within the U.S. were 4.52 (95% CI 1.19-17.15) times as likely to report a "high support" network compared to participants who resettled directly from Nepal. Personal social networks are an important source of support for resettled refugee women during pregnancy in the U.S.. Refugee women who experience secondary resettlement may perceive stronger support from their personal connections.

Exploring comorbid depression and physical health trajectories: A case-based computational modelling approach.

While comorbid depression/physical health is a major clinical concern, the conventional methods of medicine make it difficult to model the complexities of this relationship. Such challenges include cataloguing multiple trends, developing multiple complex aetiological explanations, and modelling the collective large-scale dynamics of these trends. Using a case-based complexity approach, this study engaged in a richly described case study to demonstrate the utility of computational modelling for primary care research. N = 259 people were subsampled from the Diamond database, one of the largest primary care depression cohort studies worldwide. A global measure of depressive symptoms (PHQ-9) and physical health (PCS-12) were assessed at 3, 6, 9, and 12 months and then annually for a total of 7 years. Eleven trajectories and 2 large-scale collective dynamics were identified, revealing that while depression is comorbid with poor physical health, chronic illness is often low dynamic and not always linked to depression. Also, some of the cases in the unhealthy and oscillator trends remain ill without much chance of improvement. Finally, childhood abuse, partner violence, and negative life events are greater amongst unhealthy trends. Computational modelling offers a major advance for health researchers to account for the diversity of primary care patients and for developing better prognostic models for team-based interdisciplinary care.

Allostatic Load as a Complex Clinical Construct: A Case-Based Computational Modeling Approach.

Allostatic load (AL) is a complex clinical construct, providing a unique window into the cumulative impact of stress. However, due to its inherent complexity, AL presents two major measurement challenges to conventional statistical modeling (the field's dominant methodology): it is comprised of a complex causal network of bioallostatic systems, represented by an even larger set of dynamic biomarkers; and, it is situated within a web of antecedent socioecological systems, linking AL to differences in health outcomes and disparities. To address these challenges, we employed case-based computational modeling (CBM), which allowed us to make four advances: (1) we developed a multisystem, 7-factor (20 biomarker) model of AL's network of allostatic systems; (2) used it to create a catalog of nine different clinical AL profiles (causal pathways); (3) linked each clinical profile to a typology of 23 health outcomes; and (4) explored our results (post hoc) as a function of gender, a key socioecological factor. In terms of highlights, (a) the Healthy clinical profile had few health risks; (b) the pro-inflammatory profile linked to high blood pressure and diabetes; (c) Low Stress Hormones linked to heart disease, TIA/Stroke, diabetes, and circulation problems; and (d) high stress hormones linked to heart disease and high blood pressure. Post hoc analyses also found that males were overrepresented on the High Blood Pressure (61.2%), Metabolic Syndrome (63.2%), High Stress Hormones (66.4%), and High Blood Sugar (57.1%); while females were overrepresented on the Healthy (81.9%), Low Stress Hormones (66.3%), and Low Stress Antagonists (stress buffers) (95.4%) profiles.

Data mining: qualitative analysis with health informatics data.

The new computational algorithms emerging in the data mining literature--in particular, the self-organizing map (SOM) and decision tree analysis (DTA)--offer qualitative researchers a unique set of tools for analyzing health informatics data. The uniqueness of these tools is that although they can be used to find meaningful patterns in large, complex quantitative databases, they are qualitative in orientation. To illustrate the utility of these tools, the authors review the two most popular: the SOM and DTA. They provide a basic definition of health informatics, focusing on how data mining assists this field, and apply the SOM and DTA to a hypothetical example to demonstrate what these tools are and how qualitative researchers can use them.

Anatomy and histology as socially networked learning environments: some preliminary findings.

PURPOSE: An exploratory study to better understand the "networked" life of the medical school as a learning environment. METHOD: In a recent academic year, the authors gathered data during two six-week blocks of a sequential histology and anatomy course at a U.S. medical college. An eight-item questionnaire captured different dimensions of student interactions. The student cohort/network was 48 first-year medical students. Using social network analysis (SNA), the authors focused on (1) the initial structure and the evolution of informal class networks over time, (2) how informal class networks compare to formal in-class small-group assignments in influencing student information gathering, and (3) how peer assignment of professionalism role model status is shaped more by informal than formal ties. In examining these latter two issues, the authors explored not only how formal group assignment persisted over time but also how it functioned to prevent the tendency for groupings based on gender or ethnicity. RESULTS: The study revealed an evolving dynamic between the formal small-group learning structure of the course blocks and the emergence of informal student networks. For example, whereas formal group membership did influence in-class questions and did prevent formation of groups of like gender and ethnicity, outside-class questions and professionalism were influenced more by informal group ties where gender and, to a much lesser extent, ethnicity influence student information gathering. CONCLUSIONS: The richness of these preliminary findings suggests that SNA may be a useful tool in examining an array of medical student learning encounters.

The increasing complexities of professionalism.

Organized medicine's modern-day professionalism movement has reached the quarter-century mark. In this article, the authors travel to an earlier time to examine the concept of profession within the work of Abraham Flexner. Although Flexner used the concept sparingly, it is clear that much of his writing on reforming medical education is grounded in his views on physicians as professionals and medicine as a profession. In the first half, the authors explore Flexner's views of profession, which were (1) empirically (as opposed to philosophically) grounded, (2) case based and comparatively framed, (3) sociological in orientation, and (4) systems based, with professionalism conceptualized as dynamic, evolving, and multidimensional. In the second half, the authors build on Flexner's systems perspective to introduce a complexity science understanding of professionalism. They define professionalism as a complex system, introduce a seven-part typology of professionalism, and explore how the organization of physician work and various flash points within medicine today reveal not one but several competing forms of professionalism at work. The authors then develop a tripartite model of professionalism with analysis at the micro, meso, and macro levels. They conclude with observations on how best to frame professionalism as a force for change in 21st-century medical education. Flexner's reforms were grounded in his vision of two particular types of professional-the physician clinician and the full-time academic physician-scientist. The authors propose reform grounded in professionalism as a complex system composed of competing types.