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Characteristics and motives of non-responders in a stepwise cardiometabolic disease prevention program in primary care.
European Journal of Public Health 2021 May 11
BACKGROUND: A high response rate is an important condition for effective prevention programs. We aimed at gaining insight into the characteristics and motives of non-responders in different stages of a stepwise prevention program for cardiometabolic diseases (CMD) in primary care.
METHODS: We performed a non-response analysis within a randomized controlled trial assessing the effectiveness of a stepwise CMD prevention program in the Netherlands. Patients between 45 and 70 years without known CMD were invited for stage 1 of the program, completing a CMD risk score. Patients with an increased risk were advised to visit their general practice for additional measurements, stage 2 of the program. We analyzed determinants of non-response using data from the risk score, electronic medical records, questionnaires and Statistics Netherlands.
RESULTS: Non-response in stage 1 was associated with a younger age, male sex, a migration background, a low prosperity score, self-employment, being single and having lower consultations rates in general practice. Non-response in stage 2 was associated with a low prosperity score, being employed, having no chronic illness, smoking, a normal waist circumference, a negative family history for cardiovascular disease or diabetes and having a lower consultation rate. More than half of the non-responders in stage 2 reported not visiting the GP because they did not expect to have any CMD, despite their increased risk.
CONCLUSIONS: To achieve a larger and more equal uptake of prevention programs for CMD, we should use methods adapted to characteristics of non-responders, such as targeted invitation methods and improved risk communication.
METHODS: We performed a non-response analysis within a randomized controlled trial assessing the effectiveness of a stepwise CMD prevention program in the Netherlands. Patients between 45 and 70 years without known CMD were invited for stage 1 of the program, completing a CMD risk score. Patients with an increased risk were advised to visit their general practice for additional measurements, stage 2 of the program. We analyzed determinants of non-response using data from the risk score, electronic medical records, questionnaires and Statistics Netherlands.
RESULTS: Non-response in stage 1 was associated with a younger age, male sex, a migration background, a low prosperity score, self-employment, being single and having lower consultations rates in general practice. Non-response in stage 2 was associated with a low prosperity score, being employed, having no chronic illness, smoking, a normal waist circumference, a negative family history for cardiovascular disease or diabetes and having a lower consultation rate. More than half of the non-responders in stage 2 reported not visiting the GP because they did not expect to have any CMD, despite their increased risk.
CONCLUSIONS: To achieve a larger and more equal uptake of prevention programs for CMD, we should use methods adapted to characteristics of non-responders, such as targeted invitation methods and improved risk communication.
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