Dimensions of quality of life and psychosocial variables most salient to colorectal cancer patients

Colorectal cancer is one of the most common invasive cancers, and is responsible for considerable physical and psychosocial morbidity. Understanding the quality of life experienced by colorectal cancer patients is essential for evaluating the full impact of the disease on individuals, their families and their communities. Patient perspective is essential in establishing a proper understanding of the quality of life of colorectal cancer patients. Despite this, few studies have employed a qualitative methodology to explore quality of life issues for colorectal cancer patients. A review of the literature identified only seven qualitative studies pertaining to quality of life issues for colorectal cancer patients, a surprising finding given the prevalence of this cancer. Accordingly, this study sought to build on the findings of previous qualitative research by providing descriptive data on the quality of life and psychosocial variables most salient to colorectal cancer patients. Six core themes emerged from interview and focus group data: Satisfaction with diagnosis and treatment; support (including information provision); quality of life; benefits of diagnosis; making sense of the cancer experience; and coping strategies. The information derived from this study will help inform the development of supportive care services to address the needs of the increasing number of people diagnosed with colorectal cancer. Copyright (c) 2005 John Wiley & Sons, Ltd.

Assessing the quality of risk factor survey data: lessons from the WHO MONICA Project

Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.

Quality of service in flexible workflows through process constraints

Workflow technology has delivered effectively for a large class of business processes, providing the requisite control and monitoring functions. At the same time, this technology has been the target of much criticism due to its limited ability to cope with dynamically changing business conditions which require business processes to be adapted frequently, and/or its limited ability to model business processes which cannot be entirely predefined. Requirements indicate the need for generic solutions where a balance between process control and flexibility may be achieved. In this paper we present a framework that allows the workflow to execute on the basis of a partially specified model where the full specification of the model is made at runtime, and may be unique to each instance. This framework is based on the notion of process constraints. Where as process constraints may be specified for any aspect of the workflow, such as structural, temporal, etc. our focus in this paper is on a constraint which allows dynamic selection of activities for inclusion in a given instance. We call these cardinality constraints, and this paper will discuss their specification and validation requirements.