Background: The persistent gap between research and practice compromises the impact of multi-level and multi-strategy community health interventions. Part of the problem is a limited understanding of how and why interventions produce change in population health outcomes. Systematic investigation of these intervention processes across studies requires sufficient reporting about interventions. Guided by a set of best processes related to the design, implementation, and evaluation of community health interventions, this article presents preliminary findings of intervention reporting in the published literature using community heart health exemplars as case examples.
The challenges posed by chronic illness have pointed out to epidemiologists the multifactorial complex nature of disease causality. This notion has been referred to as a web of causality. This web extends theoretically beyond risk markers. It includes determinants of emergence/non-emergence of disease. This web of determinants is a form of complex system. Due to its complexity, the determinants within such system are not linked to each others in a linear, predictable manner only. Predictability is possible only on a short-term basis, and unpredictability sets in over the long run. Understanding such a system of determinants calls for articulation and testing of complex models which synthesize our knowledge of multiple determinants at many scales, both biological and otherwise. Given the complexity of this web and existing knowledge about the nonlinearity of such systems, the following question is posed: Can the challenge of studying causality be adequately addressed if emphasis continues to be placed on using tools and methods that are geared towards looking at such system from a linear paradigm? Or is it time to add to the epidemiologic research agenda the notion of nonlinearity and its relevant form of analytical approaches that are being tested in other disciplines? Furthermore, the question posed here applies as well to the study of determinants of health. Addressing determinants of heath adds further complexity to our task.
To describe family context in health research, the authors tested a typology of families developed in California with a sample of families in Quebec, Canada. Family scales from the California study were submitted to focus groups, translated, and standardized on a sample of 209 parents. A panel of experts then revised the scales to make them relevant to Quebec families and to health promotion. Data from the new and revised scales were collected on 509 Quebec couples (1,018 spouses) and were clustered separately by gender, using K means. The procedure classified all respondents into family types that paralleled the original typology. Discriminant analyses indicated that family profile variables significantly distinguished family types. Comparisons with family, stress, and health variables further differentiated among the types and expanded their meaning. The study demonstrates a method for redefining and extending family data in health research with different cultural groups.
The purpose of this study was to explore attitudes, beliefs, and values related to the ecological approach among health education and health promotion workers. Data were collected using self-administered questionnaires. The sample consisted of 157 health education/promotion workers involved in Canadian regional public health organisations. The response rate was 79 per cent. Respondents tended to know the ecological approach, perceived it as effective, and acknowledged a need for interventions aimed at modifying people's environment. However, many respondents perceived that they had insufficient competencies to operationalise the ecological approach. A sizeable proportion of respondents seemed to hold values inconsistent with the ecological approach. Compared to doctors/dentists, nurses expressed a higher satisfaction with interventions targeting individuals. In general, respondents' cognitive profile was favourable to the ecological approach. It is hypothesised that the particular patterns of response obtained for some scales might be related to the respondents' previous training.
Background: There is a significant gap in the knowledge translation literature related to how research evidence actually contributes to health care decision-making. Decisions around what care to provide at the population (rather than individual) level are particularly complex, involving considerations such as feasibility, cost, and population needs in addition to scientific evidence. One example of decision-making at this "population-policy" level involves what screening questions and intervention guides to include on standardized provincial prenatal records. As mandatory medical reporting forms, prenatal records are potentially powerful vehicles for promoting population-wide evidence-based care. However, the extent to which Canadian prenatal records reflect best-practice recommendations for the assessment of well-known risk factors such as maternal smoking and alcohol consumption varies markedly across Canadian provinces and territories. The goal of this study is to better understand the interaction of contextual factors and research evidence on decision-making at the population-policy level, by examining the processes by which provincial prenatal records are reviewed and revised.
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