title: Adolescent time use clusters: a systematic review.
abstract: OBJECTIVE
  Recent research suggests that patterns or clusters of time use may affect health in ways that cannot be explained by the effect of individual behaviors alone. The aim of this research was to systematically review the literature examining adolescent time use clusters and associated correlates.
  
  
  METHODS
  Systematic searches of six online databases for relevant observational studies were conducted. At least two authors reviewed abstract and full text selection meeting eligibility criteria. Included studies were quality scored, had data extracted, and cluster types and cluster associations interpreted.
  
  
  RESULTS
  Nineteen studies were identified for inclusion, and 18 of them investigated cluster-correlate associations. Twenty-nine cluster types were identified, characterized by both individual (e.g., church) and co-occurring behaviors (e.g., physical activity and screen [technoactive]). Nineteen correlate categories were identified (e.g., socioeconomic and weight status). Consistent patterns of cluster-correlate association were found. For example, the technoactive cluster type is more likely to be male and to have low school orientation.
  
  
  CONCLUSIONS
  Despite the between-study differences, consistent cluster and cluster-correlate patterns were still evident. Cluster analysis of adolescent time use behaviors appears to be an emerging and useful classification technique, one which may have implications for targeted health-related interventions.
authors.affiliation: Health and Use of Time Group, School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia. Katia.Ferrar@mymail.unisa.edu.au
authors.forename: Katia
authors.initials: K
authors.lastname: Ferrar
authors.forename: Cindy
authors.initials: C
authors.lastname: Chang
authors.forename: Ming
authors.initials: M
authors.lastname: Li
authors.forename: Tim S
authors.initials: TS
authors.lastname: Olds
mesh_terms: D000293:Adolescent; D000294:Adolescent Behavior; D002648:Child; D016000:Cluster Analysis; D005260:Female; D015438:Health Behavior; D006801:Humans; D008297:Male; D013995:Time