Using information from telephone panel surveys to predict reasons for refusal

One of the key problems in conducting surveys is convincing people to participate.¦However, it is often difficult or impossible to determine why people refuse. Panel surveys¦provide information from previous waves that can offer valuable clues as to why people¦refuse to participate. If we are able to anticipate the reasons for refusal, then we¦may be able to take appropriate measures to encourage potential respondents to participate¦in the survey. For example, special training could be provided for interviewers¦on how to convince potential participants to participate.¦This study examines different influences, as determined from the previous wave,¦on refusal reasons that were given by the respondents in the subsequent wave of the¦telephone Swiss Household Panel. These influences include socio-demography, social¦inclusion, answer quality, and interviewer assessment of question understanding and¦of future participation. Generally, coefficients are similar across reasons, and¦between-respondents effects rather than within-respondents effects are significant.¦While 'No interest' reasons are easier to predict, the other reasons are more situational. Survey-specific issues are able to distinguish¦different reasons to some extent.

Differing trends in the association between obesity and self-reported health in Portugal and Switzerland: data from national health surveys 1992-2007.

BACKGROUND: The escalating prevalence of obesity might prompt obese subjects to consider themselves as normal, as this condition is gradually becoming as frequent as normal weight. In this study, we aimed to assess the trends in the associations between obesity and self-rated health in two countries. METHODS: Data from the Portuguese (years 1995-6, 1998-6 and 2005-6) and Swiss (1992-3, 1997, 2002 and 2007) National Health Surveys were used, corresponding to more than 130,000 adults (64,793 for Portugal and 65,829 for Switzerland). Body mass index and self-rated health were derived from self-reported data. RESULTS: Obesity levels were higher in Portugal (17.5% in 2005-6 vs. 8.9% in 2007 in Switzerland, p < 0.001) and increased in both countries. The prevalence of participants rating their health as "bad" or "very bad" was higher in Portugal than in Switzerland (21.8% in 2005-6 vs 3.9% in 2007, p < 0.001). In both countries, obese participants rated more frequently their health as "bad" or "very bad" than participants with regular weight. In Switzerland, the prevalence of "bad" or "very bad" rates among obese participants, increased from 6.5% in 1992-3 to 9.8% in 2007, while in Portugal it decreased from 41.3% to 32.3%. After multivariate adjustment, the odds ratio (OR) of stating one self's health as "bad" or "very bad" among obese relative to normal weight participants, almost doubled in Switzerland: from 1.38 (95% confidence interval, CI: 1.01-1.87) in 1992-3 to 2.64 (95% CI: 2.14-3.26) in 2007, and similar findings were obtained after sample weighting. Conversely, no such trend was found in Portugal: 1.35 (95% CI: 1.23-1.48) in 1995-6 and 1.52 (95% CI: 1.37-1.70) in 2005-6. CONCLUSION: Obesity is increasing in Switzerland and Portugal. Obesity is increasingly associated with poorer self-health ratings in Switzerland but not in Portugal.

Characterizing the vulnerability of frequent emergency department users by applying a conceptual framework: a controlled, cross-sectional study.

BACKGROUND: Frequent emergency department (ED) users meet several of the criteria of vulnerability, but this needs to be further examined taking into consideration all vulnerability's different dimensions. This study aimed to characterize frequent ED users and to define risk factors of frequent ED use within a universal health care coverage system, applying a conceptual framework of vulnerability. METHODS: A controlled, cross-sectional study comparing frequent ED users to a control group of non-frequent users was conducted at the Lausanne University Hospital, Switzerland. Frequent users were defined as patients with five or more visits to the ED in the previous 12 months. The two groups were compared using validated scales for each one of the five dimensions of an innovative conceptual framework: socio-demographic characteristics; somatic, mental, and risk-behavior indicators; and use of health care services. Independent t-tests, Wilcoxon rank-sum tests, Pearson's Chi-squared test and Fisher's exact test were used for the comparison. To examine the -related to vulnerability- risk factors for being a frequent ED user, univariate and multivariate logistic regression models were used. RESULTS: We compared 226 frequent users and 173 controls. Frequent users had more vulnerabilities in all five dimensions of the conceptual framework. They were younger, and more often immigrants from low/middle-income countries or unemployed, had more somatic and psychiatric comorbidities, were more often tobacco users, and had more primary care physician (PCP) visits. The most significant frequent ED use risk factors were a history of more than three hospital admissions in the previous 12 months (adj OR:23.2, 95%CI = 9.1-59.2), the absence of a PCP (adj OR:8.4, 95%CI = 2.1-32.7), living less than 5 km from an ED (adj OR:4.4, 95%CI = 2.1-9.0), and household income lower than USD 2,800/month (adj OR:4.3, 95%CI = 2.0-9.2). CONCLUSIONS: Frequent ED users within a universal health coverage system form a highly vulnerable population, when taking into account all five dimensions of a conceptual framework of vulnerability. The predictive factors identified could be useful in the early detection of future frequent users, in order to address their specific needs and decrease vulnerability, a key priority for health care policy makers. Application of the conceptual framework in future research is warranted.