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Use of theory in computer-based interventions to reduce alcohol use among adolescents and young adults: a systematic review

Overview of attention for article published in BMC Public Health, June 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

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Title
Use of theory in computer-based interventions to reduce alcohol use among adolescents and young adults: a systematic review
Published in
BMC Public Health, June 2016
DOI 10.1186/s12889-016-3183-x
Pubmed ID
Authors

Kathleen P. Tebb, Rebecca K. Erenrich, Carolyn Bradner Jasik, Mark S. Berna, James C. Lester, Elizabeth M. Ozer

Abstract

Alcohol use and binge drinking among adolescents and young adults remain frequent causes of preventable injuries, disease, and death, and there has been growing attention to computer-based modes of intervention delivery to prevent/reduce alcohol use. Research suggests that health interventions grounded in established theory are more effective than those with no theoretical basis. The goal of this study was to conduct a literature review of computer-based interventions (CBIs) designed to address alcohol use among adolescents and young adults (aged 12-21 years) and examine the extent to which CBIs use theories of behavior change in their development and evaluations. This study also provides an update on extant CBIs addressing alcohol use among youth and their effectiveness. Between November and December of 2014, a literature review of CBIs aimed at preventing or reducing alcohol in PsychINFO, PubMed, and Google Scholar was conducted. The use of theory in each CBI was examined using a modified version of the classification system developed by Painter et al. (Ann Behav Med 35:358-362, 2008). The search yielded 600 unique articles, 500 were excluded because they did not meet the inclusion criteria. The 100 remaining articles were retained for analyses. Many articles were written about a single intervention; thus, the search revealed a total of 42 unique CBIs. In examining the use of theory, 22 CBIs (52 %) explicitly named one or more theoretical frameworks. Primary theories mentioned were social cognitive theory, transtheoretical model, theory of planned behavior and reasoned action, and health belief model. Less than half (48 %), did not use theory, but mentioned either use of a theoretical construct (such as self-efficacy) or an intervention technique (e.g., manipulating social norms). Only a few articles provided detailed information about how the theory was applied to the CBI; the vast majority included little to no information. Given the importance of theory in guiding interventions, greater emphasis on the selection and application of theory is needed. The classification system used in this review offers a guiding framework for reporting how theory based principles can be applied to computer based interventions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 194 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 194 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 35 18%
Student > Ph. D. Student 26 13%
Researcher 19 10%
Student > Bachelor 19 10%
Student > Doctoral Student 14 7%
Other 32 16%
Unknown 49 25%
Readers by discipline Count As %
Psychology 37 19%
Medicine and Dentistry 34 18%
Nursing and Health Professions 22 11%
Social Sciences 18 9%
Computer Science 5 3%
Other 15 8%
Unknown 63 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 July 2016.
All research outputs
#3,062,131
of 23,664,476 outputs
Outputs from BMC Public Health
#3,516
of 15,349 outputs
Outputs of similar age
#55,831
of 355,133 outputs
Outputs of similar age from BMC Public Health
#77
of 250 outputs
Altmetric has tracked 23,664,476 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,349 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.2. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 355,133 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 250 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.