A Q methodology study of stakeholders' views about accountability for promoting healthy food environments in England through the responsibility deal food network

In March 2011, the United Kingdom's (UK's) Government launched five Public Health Responsibility Deal Networks to address public health priorities. The Networks used voluntary partnerships to influence peoples' choice architecture to move them toward healthier behaviors. The purpose of this research was to conduct an exploratory study of diverse stakeholders' perspectives about perceived responsibility and accountability expectations to improve food environments in England through the Food Network partnerships. A purposive sample of policy elites (n=31) from government, academia, food industry and non-government organizations sorted 48 statements related to improving food environments in England. Statements were grounded in three theoretical perspectives (i.e., legitimacy, nudge and public health law). PQMethod 2.33 statistical software program used factor analysis to identify viewpoints based on intra-individual differences for how participants sorted statements. The results revealed three distinct viewpoints, which explained 64% of the variance for 31 participants, and emphasized different expectations about responsibility. The food environment protectors (n=17) underscored government responsibility to address unhealthy food environments if voluntary partnerships are ineffective; the partnership pioneers (n=12) recognized government-industry partnerships as legitimate and necessary to address unhealthy food environments; and the commercial market defenders (n=1) emphasized individual responsibility for food choices and rejected government intervention to improve food environments. Consensus issues included: protecting children's right to health; food industry practices that can and should be changed; government working with industry on product reformulation; and building consumer support for economically viable healthy products. Contentious issues were: inadequacy of accountability structures and government inaction to regulate food marketing practices targeting children. We conclude that understanding different viewpoints is a step toward building mutual trust to strengthen accountability structures that may help stakeholders navigate ideologically contentious issues to promote healthy food environments in England.

`Don`t call me sweetie!` patients differ from nurses in their perceptions of caring

Effective nursing care relies on congruent nurse-patient perception of needs. This study used Q methodology to compare nurses' and patients' perceptions of important nursing care behaviour. Q methodology applies statistical analysis to qualitative data through a technique of comparative rating using a forced choice format. The Care Q Sort, comprising fifty statements of nursing behaviour, was administered to nurses and patients from medical wards. Participants ranked the nursing behaviours from most to least important. Analysis was completed on 74 rankings. There was agreement for many behaviours but bimodal distributions for nurses' scores for some statements which may be attributable to different professional levels. An additional open comments section provided an experiential dimension to the research results. The findings will inform nursing practice and patient care planning.

An empirical study on accountability for promoting healthy food environments in England through the public health responsibility deal food network

Objective: In 2011, the United Kingdom launched five Public Health Responsibility Deal Networks inspired by ‘nudge theory’ to facilitate healthy-lifestyle behaviors. This study used Q methodology to examine stakeholders’ views about responsibility and accountability for healthy food environments to reduce obesity and diet-related chronic diseases. Design: A purposive sample of policy elites (n=31) from government, academia, food industry and civil society sorted 48 statements grounded in three theoretical perspectives (i.e., legitimacy, nudge and public health law). Factor analysis identified intra-individual statement sorting differences. Results: A three-factor solution explained 64 percent of the variance across three distinct viewpoints: food environment protectors (n=17) underscored government responsibility to address unhealthy food environments; partnership pioneers (n=12) recognized government-industry partnerships as legitimate; and the commercial market defenders (n=1) emphasized individual responsibility for food choices and rejected any government intervention. Conclusions: Building trust and strengthening accountability structures may help stakeholders navigate differences to engage in constructive actions. This research may inform efforts in other countries where voluntary industry partnerships are pursued to address unhealthy food environments.

Stakeholder analysis in urban development : the application of stakeholder circle methodology and social network analysis

The increasing research interest on stakeholder analysis in urban planning reflects a growing recognition that stakeholders can and should influence the decision-making. This paper concentrates on exploring the techniques for analysing stakeholders, especially the application of the Stakeholder Circle tool and Social Network Analysis. An urban renewal project and an infrastructure project in Australia are presented as case studies to verify the use of these two techniques. The stakeholders are identified and prioritized from two different points of view, namely, the attribute evaluations in the Stakeholder Circle tool, and the relationship network analysis. The paper ends with a discussion on the strengths and limitations of the techniques for stakeholder analysis. No method for stakeholder identification and prioritization is perfect. The selection of the approaches is an art with extensive considerations of ‘when, what, and how’ to choose methods to achieve the project objectives. Each method has its own strengths and limitations. Combining several methods when necessary is the best way to analyse stakeholders.