ArticleBMC medical research methodology2011
Predicting complete loss to follow-up after a health-education program: number of absences and face-to-face contact with a researcher.
Article in BMC medical research methodology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Factors associated with loss to follow-up of outpatients with depression in general hospitals.The Journal of international medical research · 2020Observational
- Factors associated with missed assessments in a 2-year longitudinal study of acute respiratory distress syndrome survivors.BMC medical research methodology · 2018Article
- Understanding and Preventing Loss to Follow-up: Experiences From the Spinal Cord Injury Model Systems.Topics in spinal cord injury rehabilitation · 2018Article
- Attrition in a 30-year follow-up of a perinatal birth risk cohort: factors change with age.PeerJ · 2014Article
- Decay of impact after self-management education for people with chronic illnesses: changes in anxiety and depression over one year.PloS one · 2013Article
- Factors associated with study attrition among HIV-infected risky drinkers in St. Petersburg, Russia.HIV clinical trialsArticle
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundResearch on health-education programs requires longitudinal data. Loss to follow-up can lead to imprecision and bias, and complete loss to follow-up is particularly damaging. If that loss is predictable, then efforts to prevent it can be focused on those program participants who are at the highest risk. We identified predictors of complete loss to follow-up in a longitudinal cohort study.
methodsData were collected over 1 year in a study of adults with chronic illnesses who were in a program to learn self-management skills. Following baseline measurements, the program had one group-discussion session each week for six weeks. Follow-up questionnaires were sent 3, 6, and 12 months after the baseline measurement. A person was classified as completely lost to follow-up if none of those three follow-up questionnaires had been returned by two months after the last one was sent.We tested two hypotheses: that complete loss to follow-up was directly associated with the number of absences from the program sessions, and that it was less common among people who had had face-to-face contact with one of the researchers. We also tested predictors of data loss identified previously and examined associations with specific diagnoses.Using the unpaired t-test, the U test, Fisher's exact test, and logistic regression, we identified good predictors of complete loss to follow-up.
resultsThe prevalence of complete loss to follow-up was 12.2% (50/409). Complete loss to follow-up was directly related to the number of absences (odds ratio; 95% confidence interval: 1.78; 1.49-2.12), and it was inversely related to age (0.97; 0.95-0.99). Complete loss to follow-up was less common among people who had met one of the researchers (0.51; 0.28-0.95) and among those with connective tissue disease (0.29; 0.09-0.98). For the multivariate logistic model the area under the ROC curve was 0.77.
conclusionsComplete loss to follow-up after this health-education program can be predicted to some extent from data that are easy to collect (age, number of absences, and diagnosis). Also, face-to-face contact with a researcher deserves further study as a way of increasing participation in follow-up, and health-education programs should include it.
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