Jasjit S Ahluwalia

Dr. Jasjit S Ahluwalia

orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 August 2014 in Journal of Medical Internet Research
Verified
Journal Article
Open access
HLHee Yun Lee
Hee Yun Lee
JKJoseph S Koopmeiners
Joseph S Koopmeiners
GRGreg Rhee
Greg Rhee
VRVictoria H Raveis
Victoria H Raveis
JAJasjit S Ahluwalia
Jasjit S Ahluwalia
Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

1 August 2022 in Journal of Racial and Ethnic Health Disparities
Verified
Journal Article
Closed access
PDF file
KMKayla Martha Morgan
Kayla Martha Morgan
DMDale Maglalang
Dale Maglalang
MMMollie Monnig
Mollie Monnig
JAJasjit S Ahluwalia
Jasjit S Ahluwalia
JAJaqueline Avila
Jaqueline Avila
ASAlexander Sokolovsky
Alexander Sokolovsky

15 May 2013 in The American Journal on Addictions
Verified
Journal Article
Open access
PDF file
CBCarla Berg
Carla Berg
HWHefei Wen
Hefei Wen
JCJanet R. Cummings
Janet R. Cummings
JAJasjit S Ahluwalia
Jasjit S Ahluwalia
BDBenjamin G. Druss
Benjamin G. Druss
Background and Objectives: Daily smoking rates are decreasing while intermittent or nondaily smoking rates are increasing. Little is known about the association of depression, alcohol abuse and dependence, and illicit drug abuse and dependence with different patterns of smoking, particularly nondaily smoking. Thus, we examined these relationships among current smokers versus nonsmokers and among those who smoke daily versus less frequently.Methods: We conducted a secondary analysis of 37,897 adults who participated in the 2008 National Survey on Drug Use and Health. We developed logistic regression models examining predictors of (i) current smoking and (ii) number of days smoking per month (1–10 days, 11–29 days, and ≥30 days) among current smokers, focusing on past‐year major depression, alcohol abuse and dependence, and illicit drug abuse and dependence.Results: Compared to nonsmokers, current smokers more frequently reported a major depressive episode (p < .001), alcohol dependence (p < .001) and abuse (p < .001), and illicit drug dependence (p < .001) and abuse (p < .001), controlling for sociodemographics. Among current smokers, greater smoking frequency was associated with illicit drug dependence (p = .004), but lower likelihood of alcohol dependence (p = .01), alcohol abuse (p = .01), and illicit drug abuse (p = .01).Conclusions: Although depression and substance use were associated with greater likelihood of smoking, most measures were inversely associated with frequency of smoking. Thus, it is important to examine underlying mechanisms contributing to these counterintuitive findings in order to inform intervention approaches.Scientific Significance: With increased rates of nondaily smoking, developing a greater understanding about the mental health correlates related to this pattern of smoking is critical. (Am J Addict 2013;22:581–589)

1 December 2013 in Nicotine & Tobacco Research
Verified
Journal Article
Open access
PDF file
KPKim Pulvers
Kim Pulvers
TSTaneisha S Scheuermann
Taneisha S Scheuermann
DRDevan Rae Romero
Devan Rae Romero
BBBrittany Basora
Brittany Basora
XLXianghua Luo
Xianghua Luo
JAJasjit S Ahluwalia
Jasjit S Ahluwalia
Smoker identity, or the strength of beliefs about oneself as a smoker, is a robust marker of smoking behavior. However, many nondaily smokers do not identify as smokers, underestimating their risk for tobacco-related disease and resulting in missed intervention opportunities. Assessing underlying beliefs about characteristics used to classify smokers may help explain the discrepancy between smoking behavior and smoker identity. This study examines the factor structure, reliability, and validity of the Classifying a Smoker scale among a racially diverse sample of adult smokers. A cross-sectional survey was administered through an online panel survey service to 2,376 current smokers who were at least 25 years of age. The sample was stratified to obtain equal numbers of 3 racial/ethnic groups (African American, Latino, and White) across smoking level (nondaily and daily smoking). The Classifying a Smoker scale displayed a single factor structure and excellent internal consistency (α = .91). Classifying a Smoker scores significantly increased at each level of smoking, F(3,2375) = 23.68, p < .0001. Those with higher scores had a stronger smoker identity, stronger dependence on cigarettes, greater health risk perceptions, more smoking friends, and were more likely to carry cigarettes. Classifying a Smoker scores explained unique variance in smoking variables above and beyond that explained by smoker identity. The present study supports the use of the Classifying a Smoker scale among diverse, experienced smokers. Stronger endorsement of characteristics used to classify a smoker (i.e., stricter criteria) was positively associated with heavier smoking and related characteristics. Prospective studies are needed to inform prevention and treatment efforts.

1 June 2014 in Psychology of Addictive Behaviors
Verified
Journal Article
Open access
CAClaire E. Adams
Claire E. Adams
MCMinxing Chen
Minxing Chen
LGlin guo
lin guo
CLCho Y. Lam
Cho Y. Lam
DSDiana W. Stewart
Diana W. Stewart
DWDavid W. Wetter
David W. Wetter
Recent research suggests that mindfulness benefits emotion regulation and smoking cessation. However, the mechanisms by which mindfulness affects emotional and behavioral functioning are unclear. One potential mechanism, lower affective volatility, has not been empirically tested during smoking cessation. This study examined longitudinal associations among mindfulness and emotional responding over the course of smoking cessation treatment among predominantly low-socioeconomic status (SES) African American smokers, who are at high risk for relapse to smoking and tobacco-related health disparities. Participants (N = 399, 51% female, mean age = 42, 48% with annual income <$10,000) completed a baseline measure of trait mindfulness. Negative affect, positive affect, and depressive symptoms were assessed at five time points during smoking cessation treatment (up to 31 days postquit). Volatility indices were calculated to quantify within-person instability of emotional symptoms over time. Over and above demographic characteristics, nicotine dependence, and abstinence status, greater baseline trait mindfulness predicted lower volatility of negative affect and depressive symptoms surrounding the quit attempt and up to 1 month postquit, ps < 0.05. Although volatility did not mediate the association between greater mindfulness and smoking cessation, these results are the first to show that mindfulness is linked to lower affective volatility (or greater stability) of negative emotions during the course of smoking cessation. The present study suggests that mindfulness is linked to greater emotional stability and augments the study of mindfulness in diverse populations. Future studies should examine the effects of mindfulness-based interventions on volatility and whether lower volatility explains effects of mindfulness-based treatments on smoking cessation.

29 July 2020 in Journal of the American Medical Directors Association
Verified
Journal Article
Closed access
YDYinfei Duan
Yinfei Duan
TSTetyana P Shippee
Tetyana P Shippee
WNWeiwen Ng
Weiwen Ng
OAOdichinma Akosionu
Odichinma Akosionu
MWMark Woodhouse
Mark Woodhouse
JBJohn R. Bowblis
John R. Bowblis