Evidence map›Paper›PMID 29398067›Full record

ReviewAddictive behaviors2018

The use of ambulatory assessment in smoking cessation.

Christine Vinci, Aaron Haslam, Cho Y Lam, Santosh Kumar, David W Wetter

Abstract readReview
In one paragraph

Review in Addictive behaviors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Associations between morning affect and later-day smoking urges and behavior.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2024
    Trial
  2. Trial
  3. Bidirectional Relationships Between Sleep Quality and Nicotine Vaping: Studying Young Adult e-cigarette Users in Real Time and Real Life.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Observational
  12. Trajectories of motivation and self-efficacy during a smoking quit attempt: An ecological momentary assessment study.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2022
    Article
  13. Daily associations among craving, affect, and social interactions in the lives of patients during residential opioid use disorder treatment.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2021
    Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Christine VinciMoffitt Cancer Center, USA. Electronic address: christine.vinci@moffitt.org.
Aaron HaslamTexas Tech, USA.
Cho Y LamUniversity of Utah, USA.
Santosh KumarUniversity of Memphis, USA.
David W WetterUniversity of Utah, USA.

Funding

Training ProgramU54CA153505 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BASEN-ENGQUIST, KAREN M, FERNANDEZ, MARIA EULALIA · 2010 to 2015
$4.7M
Eliminating Tobacco-Related Disparities amount African American SmokersR01MD010362 · NIMHD · UNIVERSITY OF UTAH · PI LAM, CHO YAN · 2016 to 2020
$4.0M
Socioeconomic status, stress, and smoking cessationR01CA190329 · NCI · UNIVERSITY OF UTAH · PI LAM, CHO YAN · 2015 to 2020
$3.4M
Novel use of mHealth data to identify states of vulnerability and receptivity to JITAIs SupplementU01CA229437 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NAHUM-SHANI, INBAL BILLIE, WETTER, DAVID W · 2018 to 2022
$2.8M
Taxi STEP (Social networks, Technology, and Exercise through Pedometers)U01MD010648 · NIMHD · SLOAN-KETTERING INST CAN RESEARCH · PI GANY, FRANCESCA M · 2016 to 2020
$2.8M
Race/Ethnicity and the Process of Smoking CessationR01DA014818 · NIDA · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI WETTER, DAVID W · 2001 to 2006
$2.0M
Applying mHealth to Tobacco-related Health Disparities: Enhancing aspects of Resiliency to aid Cessation EffortsR00MD010468 · NIMHD · H. LEE MOFFITT CANCER CTR & RES INST · PI VINCI, CHRISTINE · 2017 to 2019
$741k
NCI NIH HHS R01 CA190329NCI NIH HHS U01 CA229437NCI NIH HHS U54 CA153505NIDA NIH HHS R01 DA014818NIMHD NIH HHS R00 MD010468NIMHD NIH HHS U01 MD010648
6 · The paper itself

Abstract

Ambulatory assessment of smoking behavior has greatly advanced our knowledge of the smoking cessation process. The current article first provides a brief overview of ecological momentary assessment for smoking cessation and highlights some of the primary advantages and scientific advancements made from this data collection method. Next, a discussion of how certain data collection tools (i.e., smoking topography and carbon monoxide detection) that have been traditionally used in lab-based settings are now being used to collect data in the real world. The second half of the paper focuses on the use of wearable wireless sensors to collect data during the smoking cessation process. Details regarding how these sensor-based technologies work, their application to newer tobacco products, and their potential to be used as intervention tools are discussed. Specific focus is placed on the opportunity to utilize novel intervention approaches, such as Just-In-Time Adaptive Interventions, to intervene upon smoking behavior. Finally, a discussion of some of the current challenges and limitations related to using sensor-based tools for smoking cessation are presented, along with suggestions for future research in this area.

Indexed as

Ecological Momentary AssessmentHumansMonitoring, AmbulatorySmokingSmoking CessationAmbulatory assessmentSmoking cessationWearable technology

Identifiers

PMID29398067
PMCPMC5964000

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.