ArticleBMC medical research methodology2016
Searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (SMS) to collect repeated measures among patients with low back pain.
Article in BMC medical research methodology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Development and initial testing of a brief, generic self-reported disability questionnaire: The Universal Disability Index.PloS one · 2024Article
- AAAPT: Assessment of the Acute Pain Trajectory.Pain medicine (Malden, Mass.) · 2021Article
- Feasibility study: one year fortnightly follow-up of the evolution of supra-spinatus degeneration via text-messages.Chiropractic & manual therapies · 2020Observational
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile technology has opened opportunities within health care and research to allow for frequent monitoring of patients. This has given rise to detailed longitudinal information and new insights concerning behaviour and development of conditions over time. Responding to frequent questionnaires delivered through mobile technology has also shown good compliance, far exceeding that of traditional paper questionnaires. However, to optimize compliance, the burden on the subjects should be kept at a minimum. In this study, the effect of using fewer data points compared to the full data set was examined, assuming that fewer measurements would lead to better compliance.
methodWeekly text-message responses for 6 months from subjects recovering from an episode of low back pain (LBP) were available for this secondary analysis. Most subjects showed a trajectory with an initial improvement and a steady state thereafter. The data were originally used to subgroup (cluster) patients according to their pain trajectory. The resulting 4-cluster solution was compared with clusters obtained from five datasets with fewer data-points using Kappa agreement as well as inspection of estimated pain trajectories. Further, the relative risk of experiencing a day with bothersome pain was compared week by week to show the effects of discarding some weekly data.
resultsOne hundred twenty-nine subjects were included in this analysis. Using data from every other weekly measure had the highest agreement with the clusters from the full dataset, weighted Kappa = 0.823. However, the visual description of pain trajectories favoured using the first 18 weekly measurements to fully capture the phases of improvement and steady-state. The weekly relative risks were influenced by the pain trajectories and 18 weeks or every other weekly measure were the optimal designs, next to the full data set.
conclusionsA population recovering from an episode of LBP could be described using every other weekly measurement, an option which requires fewer weekly measures than measuring weekly for 18 weeks. However a higher measuring frequency might be needed in the beginning of a clinical course to fully map the pain trajectories.
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