mActive-smoke

A prospective observational study using mobile health tools to assess the association of physical activity with smoking urges

Luke G. Silverman-Lloyd, Sina Kianoush, Michael Blaha, Alyse B. Sabina, Garth N. Graham, Seth Martin

Research output: Contribution to journalReview article

Abstract

Background: Evidence that physical activity can curb smoking urges is limited in scope to acute effects and largely reliant on retrospective self-reported measures. Mobile health technologies offer novel mechanisms for capturing real-time data of behaviors in the natural environment. Objective: This study aimed to explore this in a real-world longitudinal setting by leveraging mobile health tools to assess the association between objectively measured physical activity and concurrent smoking urges in a 12-week prospective observational study. Methods: We enrolled 60 active smokers (≥3 cigarettes per day) and recorded baseline demographics, physical activity, and smoking behaviors using a Web-based questionnaire. Step counts were measured continuously using the Fitbit Charge HR. Participants reported instantaneous smoking urges via text message using a Likert scale ranging from 1 to 9. On study completion, participants reported follow-up smoking behaviors in an online exit survey. Results: A total of 53 participants (aged 40 [SD 12] years, 57% [30/53] women, 49% [26/53] nonwhite) recorded at least 6 weeks of data and were thus included in the analysis. We recorded 15,365 urge messages throughout the study, with a mean of 290 (SD 62) messages per participant. Mean urge over the course of the study was positively associated with daily cigarette consumption at follow-up (Pearson r=.33; P=.02). No association existed between daily steps and mean daily urge (beta=−6.95×10−3 per 1000 steps; P=.30). Regression models of acute effects, however, did reveal modest inverse associations between steps within 30-, 60-, and 120-min time windows of a reported urge (beta=−.0191 per 100 steps, P<.001). Moreover, 6 individuals (approximately 10% of the study population) exhibited a stronger and consistent inverse association between steps and urge at both the day level (mean individualized beta=−.153 per 1000 steps) and 30-min level (mean individualized beta=−1.66 per 1000 steps). Conclusions: Although there was no association between objectively measured daily physical activity and concurrently self-reported smoking urges, there was a modest inverse relationship between recent step counts (30-120 min) and urge. Approximately 10% of the individuals appeared to have a stronger and consistent inverse association between physical activity and urge, a provocative finding warranting further study.

Original languageEnglish (US)
Article numbere121
JournalJournal of Medical Internet Research
Volume20
Issue number5
DOIs
StatePublished - May 1 2018

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Telemedicine
Smoke
Observational Studies
Smoking
Prospective Studies
Exercise
Tobacco Products
Text Messaging
Biomedical Technology
Demography
Population

Keywords

  • Activity trackers
  • Cigarette smoking
  • Exercise
  • Fitness trackers
  • MHealth
  • Mobile health
  • Physical activity
  • Smartphone
  • Smoking
  • Text messaging
  • Texting

ASJC Scopus subject areas

  • Health Informatics

Cite this

mActive-smoke : A prospective observational study using mobile health tools to assess the association of physical activity with smoking urges. / Silverman-Lloyd, Luke G.; Kianoush, Sina; Blaha, Michael; Sabina, Alyse B.; Graham, Garth N.; Martin, Seth.

In: Journal of Medical Internet Research, Vol. 20, No. 5, e121, 01.05.2018.

Research output: Contribution to journalReview article

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title = "mActive-smoke: A prospective observational study using mobile health tools to assess the association of physical activity with smoking urges",
abstract = "Background: Evidence that physical activity can curb smoking urges is limited in scope to acute effects and largely reliant on retrospective self-reported measures. Mobile health technologies offer novel mechanisms for capturing real-time data of behaviors in the natural environment. Objective: This study aimed to explore this in a real-world longitudinal setting by leveraging mobile health tools to assess the association between objectively measured physical activity and concurrent smoking urges in a 12-week prospective observational study. Methods: We enrolled 60 active smokers (≥3 cigarettes per day) and recorded baseline demographics, physical activity, and smoking behaviors using a Web-based questionnaire. Step counts were measured continuously using the Fitbit Charge HR. Participants reported instantaneous smoking urges via text message using a Likert scale ranging from 1 to 9. On study completion, participants reported follow-up smoking behaviors in an online exit survey. Results: A total of 53 participants (aged 40 [SD 12] years, 57{\%} [30/53] women, 49{\%} [26/53] nonwhite) recorded at least 6 weeks of data and were thus included in the analysis. We recorded 15,365 urge messages throughout the study, with a mean of 290 (SD 62) messages per participant. Mean urge over the course of the study was positively associated with daily cigarette consumption at follow-up (Pearson r=.33; P=.02). No association existed between daily steps and mean daily urge (beta=−6.95×10−3 per 1000 steps; P=.30). Regression models of acute effects, however, did reveal modest inverse associations between steps within 30-, 60-, and 120-min time windows of a reported urge (beta=−.0191 per 100 steps, P<.001). Moreover, 6 individuals (approximately 10{\%} of the study population) exhibited a stronger and consistent inverse association between steps and urge at both the day level (mean individualized beta=−.153 per 1000 steps) and 30-min level (mean individualized beta=−1.66 per 1000 steps). Conclusions: Although there was no association between objectively measured daily physical activity and concurrently self-reported smoking urges, there was a modest inverse relationship between recent step counts (30-120 min) and urge. Approximately 10{\%} of the individuals appeared to have a stronger and consistent inverse association between physical activity and urge, a provocative finding warranting further study.",
keywords = "Activity trackers, Cigarette smoking, Exercise, Fitness trackers, MHealth, Mobile health, Physical activity, Smartphone, Smoking, Text messaging, Texting",
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T2 - A prospective observational study using mobile health tools to assess the association of physical activity with smoking urges

AU - Silverman-Lloyd, Luke G.

AU - Kianoush, Sina

AU - Blaha, Michael

AU - Sabina, Alyse B.

AU - Graham, Garth N.

AU - Martin, Seth

PY - 2018/5/1

Y1 - 2018/5/1

N2 - Background: Evidence that physical activity can curb smoking urges is limited in scope to acute effects and largely reliant on retrospective self-reported measures. Mobile health technologies offer novel mechanisms for capturing real-time data of behaviors in the natural environment. Objective: This study aimed to explore this in a real-world longitudinal setting by leveraging mobile health tools to assess the association between objectively measured physical activity and concurrent smoking urges in a 12-week prospective observational study. Methods: We enrolled 60 active smokers (≥3 cigarettes per day) and recorded baseline demographics, physical activity, and smoking behaviors using a Web-based questionnaire. Step counts were measured continuously using the Fitbit Charge HR. Participants reported instantaneous smoking urges via text message using a Likert scale ranging from 1 to 9. On study completion, participants reported follow-up smoking behaviors in an online exit survey. Results: A total of 53 participants (aged 40 [SD 12] years, 57% [30/53] women, 49% [26/53] nonwhite) recorded at least 6 weeks of data and were thus included in the analysis. We recorded 15,365 urge messages throughout the study, with a mean of 290 (SD 62) messages per participant. Mean urge over the course of the study was positively associated with daily cigarette consumption at follow-up (Pearson r=.33; P=.02). No association existed between daily steps and mean daily urge (beta=−6.95×10−3 per 1000 steps; P=.30). Regression models of acute effects, however, did reveal modest inverse associations between steps within 30-, 60-, and 120-min time windows of a reported urge (beta=−.0191 per 100 steps, P<.001). Moreover, 6 individuals (approximately 10% of the study population) exhibited a stronger and consistent inverse association between steps and urge at both the day level (mean individualized beta=−.153 per 1000 steps) and 30-min level (mean individualized beta=−1.66 per 1000 steps). Conclusions: Although there was no association between objectively measured daily physical activity and concurrently self-reported smoking urges, there was a modest inverse relationship between recent step counts (30-120 min) and urge. Approximately 10% of the individuals appeared to have a stronger and consistent inverse association between physical activity and urge, a provocative finding warranting further study.

AB - Background: Evidence that physical activity can curb smoking urges is limited in scope to acute effects and largely reliant on retrospective self-reported measures. Mobile health technologies offer novel mechanisms for capturing real-time data of behaviors in the natural environment. Objective: This study aimed to explore this in a real-world longitudinal setting by leveraging mobile health tools to assess the association between objectively measured physical activity and concurrent smoking urges in a 12-week prospective observational study. Methods: We enrolled 60 active smokers (≥3 cigarettes per day) and recorded baseline demographics, physical activity, and smoking behaviors using a Web-based questionnaire. Step counts were measured continuously using the Fitbit Charge HR. Participants reported instantaneous smoking urges via text message using a Likert scale ranging from 1 to 9. On study completion, participants reported follow-up smoking behaviors in an online exit survey. Results: A total of 53 participants (aged 40 [SD 12] years, 57% [30/53] women, 49% [26/53] nonwhite) recorded at least 6 weeks of data and were thus included in the analysis. We recorded 15,365 urge messages throughout the study, with a mean of 290 (SD 62) messages per participant. Mean urge over the course of the study was positively associated with daily cigarette consumption at follow-up (Pearson r=.33; P=.02). No association existed between daily steps and mean daily urge (beta=−6.95×10−3 per 1000 steps; P=.30). Regression models of acute effects, however, did reveal modest inverse associations between steps within 30-, 60-, and 120-min time windows of a reported urge (beta=−.0191 per 100 steps, P<.001). Moreover, 6 individuals (approximately 10% of the study population) exhibited a stronger and consistent inverse association between steps and urge at both the day level (mean individualized beta=−.153 per 1000 steps) and 30-min level (mean individualized beta=−1.66 per 1000 steps). Conclusions: Although there was no association between objectively measured daily physical activity and concurrently self-reported smoking urges, there was a modest inverse relationship between recent step counts (30-120 min) and urge. Approximately 10% of the individuals appeared to have a stronger and consistent inverse association between physical activity and urge, a provocative finding warranting further study.

KW - Activity trackers

KW - Cigarette smoking

KW - Exercise

KW - Fitness trackers

KW - MHealth

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KW - Physical activity

KW - Smartphone

KW - Smoking

KW - Text messaging

KW - Texting

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