oru.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Analyzing repeated data collected by mobile phones and frequent text messages: An example of Low back pain measured weekly for 18 weeks
Institute of Environmental Medicine, Unit of Intervention and Implementation Research, Karolinska Institutet, Stockholm, Sweden.
Institute of Environmental Medicine, Unit of Intervention and Implementation Research, Karolinska Institutet, Stockholm, Sweden.
Clinical Locomotion Network, Nordic Institute of Chiropractic and Clinical Biomechanics, Odense, Denmark.
Institute of Regional Health Services Research, University of Southern Denmark, Odense, Denmark.
Show others and affiliations
2012 (English)In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 12, article id 105Article in journal (Refereed) Published
Abstract [en]

Background: Repeated data collection is desirable when monitoring fluctuating conditions. Mobile phones can be used to gather such data from large groups of respondents by sending and receiving frequently repeated short questions and answers as text messages.

The analysis of repeated data involves some challenges. Vital issues to consider are the within-subject correlation, the between measurement occasion correlation and the presence of missing values.

The overall aim of this commentary is to describe different methods of analyzing repeated data. It is meant to give an overview for the clinical researcher in order for complex outcome measures to be interpreted in a clinically meaningful way.

Methods: A model data set was formed using data from two clinical studies, where patients with low back pain were followed with weekly text messages for 18 weeks. Different research questions and analytic approaches were illustrated and discussed, as well as the handling of missing data. In the applications the weekly outcome “number of days with pain” was analyzed in relation to the patients’ “previous duration of pain” (categorized as more or less than 30 days in the previous year).

Research questions with appropriate analytical methods

1: How many days with pain do patients experience? This question was answered with data summaries.

2: What is the proportion of participants “recovered” at a specific time point? This question was answered using logistic regression analysis.

3: What is the time to recovery? This question was answered using survival analysis, illustrated in Kaplan-Meier curves, Proportional Hazard regression analyses and spline regression analyses.

4: How is the repeatedly measured data associated with baseline (predictor) variables? This question was answered using generalized Estimating Equations, Poisson regression and Mixed linear models analyses.

5: Are there subgroups of patients with similar courses of pain within the studied population?A visual approach and hierarchical cluster analyses revealed different subgroups using subsets of the model data.

Conclusions: We have illustrated several ways of analysing repeated measures with both traditional analytic approaches using standard statistical packages, as well as recently developed statistical methods that will utilize all the vital features inherent in the data.

Place, publisher, year, edition, pages
BioMed Central, 2012. Vol. 12, article id 105
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
URN: urn:nbn:se:oru:diva-66140DOI: 10.1186/1471-2288-12-105ISI: 000308375400001PubMedID: 22824413Scopus ID: 2-s2.0-84865754036OAI: oai:DiVA.org:oru-66140DiVA, id: diva2:1193332
Note

Funding Agencies:

Swedish Chiropractors' Association  

European Chiropractors' Union 

Available from: 2018-03-26 Created: 2018-03-26 Last updated: 2018-05-15Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records BETA

Bodin, Lennart

Search in DiVA

By author/editor
Bodin, Lennart
In the same journal
BMC Medical Research Methodology
Health Care Service and Management, Health Policy and Services and Health Economy

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 2 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf