Aims The second Diabetes Attitudes, Wishes and Needs (DAWN2) study aimed to assess psychosocial outcomes in people with diabetes across countries for benchmarking.Methods Surveys included new and adapted questions from validated questionnaires that assess health-related quality of life, self-management, attitudes/beliefs, social support and priorities for improving diabetes care. Questionnaires were conducted online, by telephone or in person.Results Participants were 8596 adults with diabetes across 17 countries. There were significant between-country differences for all benchmarking indicators; no one country's outcomes were consistently better or worse than others. The proportion with likely depression [WHO-5 Well-Being Index (WHO-5) score ≤ 28] was 13.8% (country range 6.5-24.1%). Diabetes-related distress [Problem Areas in Diabetes Scale 5 (PAID-5) score ≥ 40] was reported by 44.6% of participants (17.2-67.6%). Overall quality of life was rated 'poor' or 'very poor' by 12.2% of participants (7.6-26.1%). Diabetes had a negative impact on all aspects investigated, ranging from 20.5% on relationship with family/friends to 62.2% on physical health. Approximately 40% of participants (18.6-64.9%) reported that their medication interfered with their ability to live a normal life. The availability of person-centred chronic illness care and support for active involvement was rated as low. Following self-care advice for medication and diet was most common, and least common for glucose monitoring and foot examination, with marked country variation. Only 48.8% of respondents had participated in diabetes educational programmes/activities to help manage their diabetes.Conclusions Cross-national benchmarking using psychometrically validated indicators can help identify areas for improvement and best practices to drive changes that improve outcomes for people with diabetes.

This review explores the relationship between engagement with the creative arts and health outcomes, specifically the health effects of music engagement, visual arts therapy, movement-based creative expression, and expressive writing. Although there is evidence that art-based interventions are effective in reducing adverse physiological and psychological outcomes, the extent to which these interventions enhance health status is largely unknown. Our hope is to establish a foundation for continued investigation into this subject and to generate further interest in researching the complexities of engagement with the arts and health.

The arts have unique qualities that can help create novel ways to engage learners. These novel ways of engagement can foster learners' ability to discover and create new meanings about a variety of topics, which in turn can lead to better medical practice. At each of these steps, specific actions by the teacher can enhance the potential for learners to move to the next step. The process can be enhanced when learners participate in the context of a group, and the group itself can undergo transformative change. Future work should focus on using this model to guide process design and outcome measurement in arts-based education.

The objective of this study was to review the evidence about what factors influence user engagement in Internet-based behavioral interventions for chronic illness. We conducted a systematic review of the recent published literature. Searches of MEDLINE (using Ovid and PubMed), The Cochrane Library, and PsycINFO, from January 2000 to December 2008, were completed. Additional articles were identified from searching the bibliographies of retrieved articles. We identified studies of interactive health communication interventions delivered via the Internet that, apart from delivering health information, had another component such as interactive tools to manage illness, decision support for treatment, or social support. We restricted the age range to adulthood. The search identified 186 abstracts; 46 articles were reviewed. We used a qualitative approach called "positive deviance" to study those interventions that have succeeded in engaging users where most have failed. Some ways to improve user engagement in Internet interventions suggested by our review include addressing health concerns that are important and relevant to an individual patient or consumer and an individualized approach, such as personally tailored advice and feedback. Interventions that are part of larger health management programs that include clinicians appear to be especially promising.

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IIn earlier issues, we discussed data collection through three types of interviews, and the first step in the analysis was transcribing and managing qualitative research data. Coding, or the process of organizing and sorting qualitative data, is the second step in data analysis. Some research methodologists believe that coding is merely technical, preparatory work for higher level thinking about the study, but coding is analysis. [1] Codes are usually used to retrieve and categorize data that are similar in meaning so the researcher can quickly find and cluster the segments that relate to one another. Depending on the size of the dataset, coding can take hours, weeks, or even months.One of the largest datasets for which I created a coding dictionary was the second Diabetes Attitudes, Wishes and Needs (DAWN2) study. In that dataset, there were over 15,000 participants who responded to an average of three open-ended questions each to a 17-country survey about psychosocial needs in diabetes. A sophisticated coding dictionary and process was needed for this project. A B S T R A C TCoding is a process used in the analysis of qualitative research, which takes time and creativity. Three steps will help facilitate this process: 1. Reading through the data and creating a storyline; 2. Categorizing the data into codes; and 3. Using memos for clarifi cation and interpretation.Remembering the research question or storyline, while coding will help keep the qualitative researcher focused on relevant codes. A data dictionary can be used to defi ne the meaning of the codes and keep the process transparent. Coding is done using either predetermined (a priori) or emergent codes, and most often, a combination of the two. By using memos to help clarify how the researcher is constructing the codes and his/her interpretations, the analysis will be easier to write in the end and have more consistency. This paper describes the process of coding and writing memos in the analysis of qualitative data related to diabetes research.

The purpose of this study was to develop a family genomic laboratory report designed to communicate genome sequencing results to parents of children who were participating in a whole genome sequencing clinical research study. Semi‐structured interviews were conducted with parents of children who participated in a whole genome sequencing clinical research study to address the elements, language and format of a sample family‐directed genome laboratory report. The qualitative interviews were followed by two focus groups aimed at evaluating example presentations of information about prognosis and next steps related to the whole genome sequencing result. Three themes emerged from the qualitative data: (i) Parents described a continual search for valid information and resources regarding their child's condition, a need that prior reports did not meet for parents; (ii) Parents believed that the Family Report would help facilitate communication with physicians and family members; and (iii) Parents identified specific items they appreciated in a genomics Family Report: simplicity of language, logical flow, visual appeal, information on what to expect in the future and recommended next steps. Parents affirmed their desire for a family genomic results report designed for their use and reference. They articulated the need for clear, easy to understand language that provided information with temporal detail and specific recommendations regarding relevant findings consistent with that available to clinicians.

Interviewing is a primary way of collecting data in qualitative research to direct the participant in responding to a specific research question. In diabetes, this may include “what are the reasons that have contributed to your success in diabetes self-management” or “how do you believe stress impacts your blood glucose?” Three types of interviews are common in social health: (1) Structured; (2) semi-structured; and (3) narrative interview. These range in a format including specified sets of questions to the telling of patient stories in an organic way. This paper describes the differences between these types of interviews and examples of each related to diabetes research.