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A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study

Overview of attention for article published in JMIR mHealth and uHealth, September 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

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21 tweeters
facebook
2 Facebook pages

Citations

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33 Dimensions

Readers on

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88 Mendeley
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Title
A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study
Published in
JMIR mHealth and uHealth, September 2016
DOI 10.2196/mhealth.5787
Pubmed ID
Authors

Felix Naughton, Naughton, Felix, Hopewell, Sarah, Lathia, Neal, Schalbroeck, Rik, Brown, Chloë, Mascolo, Cecilia, McEwen, Andy, Sutton, Stephen, Naughton, F, Hopewell, S, Lathia, N, Schalbroeck, R, Brown, C, Mascolo, C, McEwen, A, Sutton, S

Abstract

A major cause of lapse and relapse to smoking during a quit attempt is craving triggered by cues from a smoker's immediate environment. To help smokers address these cue-induced cravings when attempting to quit, we have developed a context-aware smoking cessation app, Q Sense, which uses a smoking episode-reporting system combined with location sensing and geofencing to tailor support content and trigger support delivery in real time. We sought to (1) assess smokers' compliance with reporting their smoking in real time and identify reasons for noncompliance, (2) assess the app's accuracy in identifying user-specific high-risk locations for smoking, (3) explore the feasibility and user perspective of geofence-triggered support, and (4) identify any technological issues or privacy concerns. An explanatory sequential mixed-methods design was used, where data collected by the app informed semistructured interviews. Participants were smokers who owned an Android mobile phone and were willing to set a quit date within one month (N=15). App data included smoking reports with context information and geolocation, end-of-day (EoD) surveys of smoking beliefs and behavior, support message ratings, and app interaction data. Interviews were undertaken and analyzed thematically (N=13). Quantitative and qualitative data were analyzed separately and findings presented sequentially. Out of 15 participants, 3 (20%) discontinued use of the app prematurely. Pre-quit date, the mean number of smoking reports received was 37.8 (SD 21.2) per participant, or 2.0 (SD 2.2) per day per participant. EoD surveys indicated that participants underreported smoking on at least 56.2% of days. Geolocation was collected in 97.0% of smoking reports with a mean accuracy of 31.6 (SD 16.8) meters. A total of 5 out of 9 (56%) eligible participants received geofence-triggered support. Interaction data indicated that 50.0% (137/274) of geofence-triggered message notifications were tapped within 30 minutes of being generated, resulting in delivery of a support message, and 78.2% (158/202) of delivered messages were rated by participants. Qualitative findings identified multiple reasons for noncompliance in reporting smoking, most notably due to environmental constraints and forgetting. Participants verified the app's identification of their smoking locations, were largely positive about the value of geofence-triggered support, and had no privacy concerns about the data collected by the app. User-initiated self-report is feasible for training a cessation app about an individual's smoking behavior, although underreporting is likely. Geofencing was a reliable and accurate method of identifying smoking locations, and geofence-triggered support was regarded positively by participants.

Twitter Demographics

The data shown below were collected from the profiles of 21 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 87 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 28%
Student > Master 12 14%
Unspecified 11 13%
Researcher 11 13%
Student > Doctoral Student 7 8%
Other 22 25%
Readers by discipline Count As %
Psychology 23 26%
Unspecified 19 22%
Computer Science 18 20%
Medicine and Dentistry 9 10%
Social Sciences 7 8%
Other 12 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 16 February 2017.
All research outputs
#830,086
of 11,498,490 outputs
Outputs from JMIR mHealth and uHealth
#178
of 635 outputs
Outputs of similar age
#29,746
of 238,229 outputs
Outputs of similar age from JMIR mHealth and uHealth
#10
of 28 outputs
Altmetric has tracked 11,498,490 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 635 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.7. This one has gotten more attention than average, scoring higher than 71% 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 238,229 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 87% of its contemporaries.
We're also able to compare this research output to 28 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 64% of its contemporaries.