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      Motives for (not) participating in a lifestyle intervention trial

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          Abstract

          Background

          Non-participants can have a considerable influence on the external validity of a study. Therefore, we assessed the socio-demographic, health-related, and lifestyle behavioral differences between participants and non-participants in a comprehensive CVD lifestyle intervention trial, and explored the motives and barriers underlying the decision to participate or not.

          Methods

          We collected data on participants (n = 50) and non-participants (n = 50) who were eligible for inclusion in a comprehensive CVD lifestyle interventional trial. Questionnaires and a hospital patient records database were used to assess socio-demographic, health-related and lifestyle behavioral variables. Univariate and multivariate logistic regression was used to describe the relationship between explanatory variables and study participation. Furthermore, motives and barriers that underlie study participation were investigated by means of questionnaires.

          Results

          Participants were younger, single, had a higher level of education and were employed. No statistically significant differences were found in health measures and behavioral variables. The motives for participation that were most frequently reported were: the perception of being unhealthy and willingness to change their lifestyle. The main barriers reported by non-participants were financial arguments and time investment.

          Conclusion

          The differences between participants and non-participants in a lifestyle intervention trial are in mainly demographic factors. The participants consent in order to alter their lifestyle, and/or because they want to improve their health. To minimize non-participation, it is recommended that access to a lifestyle intervention program should be easy and cause no financial restraints.

          Trial registration

          ISRCTN69776211.

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          Most cited references17

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          [Measuring the quality of life in economic evaluations: the Dutch EQ-5D tariff].

          To value EQ-5D health states by a general Dutch public. EQ-5D is a standardised questionnaire that is used to calculate quality-adjusted life-years for cost-utility analysis. Descriptive. A sample of 309 Dutch adults from Rotterdam and surroundings was asked to value 17 EQ-5D health states using the time trade-off method. Regression analysis was applied to the valuations of these 17 health states. By means of the estimated regression coefficients, which together constitute the so-called Dutch tariff, valuations can be determined for all possible EQ-5D health states. These values reflect the relative desirability of health states on a scale where 1 refers to full health and 0 refers to death. Societal valuations are necessary in order to correct life-years for the quality of life. Complete data were obtained from 298 persons. Theywere representative for the Dutch population as far as age, gender and subjective health were concerned, but had a somewhat higher educational level. The estimated Dutch EQ-5D tariff revealed that the respondents assigned the most weight to (preventing) pain and anxiety or depression, followed by mobility, self-care and the activities of daily living. The Dutch tariff differed from the UK ('Measurement and Valuation of Health') tariff, which is currently used in Dutch cost-utility analyses. Compared to UK respondents, Dutch respondents assigned more weight to anxiety and depression and less weight to the other dimensions. Conclusion. The valuation of health states by this representative Dutch study group differed from the valuation that is currently used in Dutch cost-utility analyses.
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            Barriers to participation in randomised controlled trials: a systematic review.

            A systematic review of three bibliographic databases from 1986 to 1996 identified 78 papers reporting barriers to recruitment of clinicians and patients to randomised controlled trials. Clinician barriers included: time constraints, lack of staff and training, worry about the impact on the doctor-patient relationship, concern for patients, loss of professional autonomy, difficulty with the consent procedure, lack of rewards and recognition, and an insufficiently interesting question. Patient barriers included: additional demands of the trial, patient preferences, worry caused by uncertainty, and concerns about information and consent. To overcome barriers to clinician recruitment, the trial should address an important research question and the protocol and data collection should be as straightforward as possible. The demands on clinicians and patients should be kept to a minimum. Dedicated research staff may be required to support clinical staff and patients. The recruitment aspects of a randomised controlled trial should be carefully planned and piloted. Further work is needed to quantify the extent of problems associated with clinician and patient participation, and proper evaluation is required of strategies to overcome barriers.
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              Survey non-response in the Netherlands: effects on prevalence estimates and associations.

              Differences in respondent characteristics may lead to bias in prevalence estimates and bias in associations. Both forms of non-response bias are investigated in a study on psychosocial factors and cancer risk, which is a sub-study of a large-scale monitoring survey in the Netherlands. Respondents of a cross-sectional monitoring project (MORGEN; N = 22,769) were also asked to participate in a prospective study on psychosocial factors and cancer risk (HLEQ; N = 12,097). To investigate diverse aspects of non-response in the HLEQ on prevalence estimates and associations are studied, based on information gathered in the MORGEN-project. A response percentage of 45% was obtained in the MORGEN-project. Response rates were found to be lower among men and younger people. The HLEQ showed a response percentage of 56%, and respondents reported higher socioeconomic status, better subjective health and healthier lifestyle behaviors than non-respondents. However, associations between smoking status and either socioeconomic status or subjective health based on respondents only were not statistically different from those based on the entire MORGEN-population. Non-response leads to bias in prevalence estimates of current smoking, current alcohol intake, and low physical activity or poor subjective health. However, non-response did not cause bias in the examined associations.
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                Author and article information

                Journal
                BMC Med Res Methodol
                BMC Medical Research Methodology
                BioMed Central
                1471-2288
                2008
                10 April 2008
                : 8
                : 17
                Affiliations
                [1 ]Department of General Practice, EMGO Institute, VU University Medical Center, v.d. Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
                [2 ]Institute of Health Sciences, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands
                [3 ]Department of Vascular Surgery, VU University Medical Center, Amsterdam, The Netherlands
                [4 ]Department of Cardiology, VU University Medical Center, Amsterdam, The Netherlands
                Article
                1471-2288-8-17
                10.1186/1471-2288-8-17
                2365955
                18402683
                ecffd11b-2607-4482-8b5d-71b13ee1c131
                Copyright © 2008 Lakerveld et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 December 2007
                : 10 April 2008
                Categories
                Research Article

                Medicine
                Medicine

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