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Background Area-based initiatives that include a focus on community empowerment are increasingly being seen as potentially an important way of improving health and reducing inequalities. However, there is little empirical evidence on the pathways between communities having more control and health outcomes. Purpose To identify pathways to health improvement in a community-led area-based community empowerment initiative. Methods Longitudinal data on mental health, community control, area belonging, satisfaction, social cohesion and safety were collected over two time points, 6 months apart from 48 participants engaged in the Big Local programme, England. Qualitative comparative analysis (QCA) was used to explore pathways to health improvement. Results There was no clear single pathway that led to mental health improvement but positive changes in ‘neighbourhood belonging’ featured in 4/5 health improvement configurations. Further, where respondents experienced no improvement in key social participation/control factors, they experienced no health improvement. Conclusion This study demonstrates a potential pathway between an improvement in ‘neighbourhood belonging’ and improved mental health outcomes in a community empowerment initiative. Increasing neighbourhood belonging could be a key target for mental health improvement interventions.

This paper critically discusses the utility of using qualitative comparative analysis (QCA) in geographical research following the ‘complexity turn’. Although QCA methodology has increasingly been applied in other social science disciplines, it is not widely used by geographers. The major benefit of QCA is that it can handle complexity by exploring different pathways that generate the same outcome, which applies to much spatial research. Significantly, QCA is case – rather than variable – oriented, which is hugely important when considering the significance of context. In this paper we illustrate how QCA can be applied in the discipline of geography through a case study of area-level health resilience. We argue that QCA can be usefully applied to such geographical questions as it aids our understanding of the complex processes that lead to spatial variations in health. Moreover, QCA enables geographical research to bridge the quantitative–qualitative divide. We conclude that QCA has great potential for exploring the complex, spatial factors that influence area-level health resilience by being context-sensitive and case-oriented. We make the case for applying this methodology in future geographical research.

Background This paper explores the value of qualitative comparative analysis (QCA) in public health research using the example of a pilot case management intervention for long-term incapacity benefit recipients. It uses QCA to examine how the ‘health improvement’ effects of the intervention varied by individual and service characteristics. Methods Data for 131 participants receiving the intervention were collected over 9 months. Health improvement was measured using the EuroQual Visual Analogue Scale. Socio-demographic, health behaviour data were also collected. Data on service use was obtained from the provider's client records. Crisp set QCA was conducted to identify which individual and service characteristics were most likely to produce a health benefit after participation in the intervention. Results Health improvement was most likely amongst younger participants, men aged over 50 and those with an occupational history of skilled manual work or higher and less likely amongst older women, those with a musculoskeletal condition and those with semi- or un-skilled backgrounds. Service characteristics had no impact. Conclusions The QCA identified potential causal pathways for health improvement from the intervention with important potential implications for health inequalities. QCA should be considered as a viable and practical method in the public health evaluation tool box.

This paper presents a Qualitative Comparative Analysis (QCA) analysis of data produced as part of the evaluation a Nation Health Service commissioned intervention in the North East of England. QCA is a case-oriented method that allows systematic comparison of cases as configurations of set memberships based on their attributes and the relationship of these to particular outcomes. QCA provides an alternative to conventional quantitative approaches which are generally concerned with isolating the independent effect of one variable whilst controlling the influence of others. Instead, QCA allows for interactions between multiple attributes and recognises that the same outcomes may be generated by different configurations of attributes. The intervention evaluated provided case management for individuals who were out of work due to ill health, and had been for three years or more. It aimed to improve the health of individuals and move them closer to the labour market. The intervention and a comparison group were assessed at base line (T1), after 3 months — (T2) after 6 months (end of the intervention — T3) and after 9 months (three months post intervention — T4). The size of the respective populations at each time point were, Intervention group at T1, N = 131, T2, N = 44, T3, N = 79, T4, N = 95. Comparison group at T1, N = 229, T2, N = 188, T3, N = 166, T4, N = 154. General health was measured using EQ5-D (a standardised instrument for use as a measure of general health outcome) and SF-8. Two condition specific measures were included: the Hospital Anxiety and Depression Scale (HADS) and the Nordic Musculoskeletal questionnaire. Data was also collected on socio demographics (gender, age, housing tenure), social capital (contact with family and friends and participation with the wider community), and work history (previous jobs, time spent in the job, time spent on sickness absence). The aim of the QCA analysis was to identify whether individuals with certain characteristics or combinations of characteristics benefited from the intervention. In order to do this the cases were sorted according to whether their EQ-5D VAS (Visual Analogue Scale) scores (a self rated measure of general health) narrowed or did not narrow towards the population norm for the measure between baseline (T1) and (T4) 9 months (three months post intervention — T4). Cases which narrowed towards the UK population norm of 82.48 were judged to be experiencing a health improvement whilst those whose scores did not narrow towards the norm were judged to not have experienced a health improvement. A crisp set (cs) QCA analysis was then performed. The paper assesses the benefits of using QCA, and asks whether it can provide a viable and practical tool for social policy evaluations.

This article shows how Qualitative Comparative Analysis (QCA) can be used to understand what works to address complex policy problems at a local level, using the example of tackling high rates of teenage conceptions in England’s most deprived local authority areas. QCA is a promising method for providing evidence in situations where interventions interact with contexts, enabling causal pathways to be discerned from how sets of conditions combine with particular outcomes: in this instance, whether inequalities in conception rates do or do not narrow, compared with the England average. A wide range of survey and secondary data, sourced in collaboration with practitioners, was explored to identify conditions that might show a relationship with the outcome. Applying QCA’s process of logical reduction enabled identification of sets of cases. Two narrowing sets and three not-narrowing sets are presented, showing how there are different pathways to narrowing and not-narrowing outcomes, and how conditions often combine to have causal effect. Although based on systematic cross-case comparison, the article also demonstrates the importance of judgement and interpretation in QCA.

This study explores why progress with tackling health inequalities has varied among a group of local authority areas in England that were set targets to narrow important health outcomes compared to national averages. It focuses on premature deaths from cancers and cardiovascular disease (CVD) and whether the local authority gap for these outcomes narrowed. Survey and secondary data were used to create dichotomised conditions describing each area. For cancers, ten conditions were found to be associated with whether or not narrowing occurred: presence/absence of a working culture of individual commitment and champions; spending on cancer programmes; aspirational or comfortable/complacent organisational cultures; deprivation; crime; assessments of strategic partnership working, commissioning and the public health workforce; frequency of progress reviews; and performance rating of the local Primary Care Trust (PCT). For CVD, six conditions were associated with whether or not narrowing occurred: a PCT budget closer or further away from target; assessments of primary care services, smoking cessation services and local leadership; presence/absence of a few major programmes; and population turnover. The method of Qualitative Comparative Analysis was used to find configurations of these conditions with either the narrowing or not narrowing outcomes. Narrowing cancer gaps were associated with three configurations in which individual commitment and champions was a necessary condition, and not narrowing was associated with a group of conditions that had in common a high level of bureaucratic-type work. Narrowing CVD gaps were associated with three configurations in which a high assessment of either primary care or smoking cessation services was a necessary condition, and not narrowing was associated with two configurations that both included an absence of major programmes. The article considers substantive and theoretical arguments for these configurations being causal and as pointing to ways of improving progress with tackling health inequalities.