OBJECTIVE: Periodontitis is a multifactorial disease that affects a wide range of populations. However, its pathogenesis remains unclear. miRNAs are now considered potential diagnostic markers for many inflammatory diseases. Thus, the aim of this study was to assess the expression of microRNA-223(miRNA-223) and microRNA-214 (miRNA-214) in gingival crevicular fluid (GCF) of smoker and nonsmoker with periodontitis.
METHODS: We conducted a prospective study among 42 participants: 14 healthy controls, 14 nonsmoker periodontitis participants, and 14 smokers with periodontitis. Eligibility criteria for inclusion were consecutive adults, aged 20-60 years, with stage III periodontitis grade B/C and no systemic diseases. All consenting participants had gingival crevicular fluid samples collected after diagnosis to assess miRNA-214 and -223 by quantitative real-time polymerase chain reaction assay.
RESULTS: ROC curve analyses for the non-smoker periodontitis group showed that miR-214 as a predictor in comparison to miR-223 had higher sensitivity [92.86%-64.29%], same specificity [100%], and a significantly higher area under the curve [0.974-0.796] respectively (p = 0.036). As for the smoker periodontitis group, a ROC curve with miR-214 as predictor in comparison to miR-223 had higher sensitivity [100%-71.43%], same specificity [100%], and a non-significantly higher area under the curve [1-0.872], respectively (p = 0.059).
CONCLUSIONS: Both miRNA-214 and 223 are reliable potential diagnostic markers for periodontitis, with miRNA-214 being more accurate for smokers with periodontitis.
CONCLUSIONS: Both miRNA-214 and 223 could be considered for potential chair-side diagnostics, by simply collecting GCF detecting the disease in its first steps and aid in preventing unrepairable damage.

BACKGROUND: Chinese immigrants experience significant disparities in tobacco use. Culturally adapted tobacco treatments targeting this population are sparse and the use is low. The low use of these treatment programs is attributed to their exclusive focus on individuals who are ready to quit and the wide range of barriers that Chinese immigrants face to access these programs. To support Chinese immigrant smokers at all levels of readiness to quit and address their access barriers, we developed the WeChat Quit Coach, a culturally and linguistically appropriate WeChat (Tencent Holdings Limited)-based peer group mobile messaging smoking cessation intervention.
OBJECTIVE: This study aims to assess the feasibility, acceptability, and preliminary effects of WeChat Quit Coach.
METHODS: We enrolled a total of 60 Chinese immigrant smokers in 2022 in New York City for a pilot randomized controlled trial (RCT) and a single-arm pilot test. The first 40 participants were randomized to either the intervention arm (WeChat Quit Coach) or the control arm (self-help print material) using 1:1 block randomization stratified by sex. WeChat Quit Coach lasted 6 weeks, featuring small peer groups moderated by a coach, daily text messages with text questions, and chat-based instant messaging support from the coach in response to peer questions. The next 20 participants were enrolled in the single-arm pilot test to further assess intervention feasibility and acceptability. All 60 participants were offered a 4-week supply of complimentary nicotine replacement therapy. Surveys were administered at baseline and 6 weeks, with participants in the pilot RCT completing an additional survey at 6 months and biochemical verification of abstinence at both follow-ups.
RESULTS: Of 74 individuals screened, 68 (92%) were eligible and 60 (88%) were enrolled. The majority of participants, with a mean age of 42.5 (SD 13.8) years, were male (49/60, 82%) and not ready to quit, with 70% (42/60) in the precontemplation or contemplation stage at the time of enrollment. The pilot RCT had follow-up rates of 98% (39/40) at 6 weeks and 93% (37/40) at 6 months, while the single-arm test achieved 100% follow-up at 6 weeks. On average, participants responded to daily text questions for 25.1 days over the 42-day intervention period and 23% (9/40) used the chat-based instant messaging support. Most participants were satisfied with WeChat Quit Coach (36/39, 92%) and would recommend it to others (32/39, 82%). At 6 months, self-reported 7-day point prevalence abstinence rates were 25% (5/20) in the intervention arm and 15% (3/20) in the control arm, with biochemically verified abstinence rates of 25% (5/20) and 5% (1/20), respectively.
CONCLUSIONS: WeChat Quit Coach was feasible and well-received by Chinese immigrants who smoke and produced promising effects on abstinence. Large trials are warranted to assess its efficacy in promoting abstinence in this underserved population.
BACKGROUND: ClinicalTrials.gov NCT05130788; https://clinicaltrials.gov/study/NCT05130788.

BACKGROUND: Recent studies have shown positive, though small, clinical effects of digital smoking cessation (SC) interventions for cancer survivors. However, research on associations among participant characteristics, intervention engagement, and outcomes is limited.
OBJECTIVE: This study aimed to explore the predictors and moderators of engagement and outcome of MyCourse-Quit Smoking (in Dutch: \"MijnKoers-Stoppen met Roken\"), a digital minimally guided intervention for cancer survivors.
METHODS: A secondary analysis of data from the randomized controlled trial was performed. The number of cigarettes smoked in the past 7 days at 6-month follow-up was the primary outcome measure. We analyzed interactions among participant characteristics (11 variables), intervention engagement (3 variables), and outcome using robust linear (mixed) modeling.
RESULTS: In total, 165 participants were included in this study. Female participants accessed the intervention less often than male participants (B=-11.12; P=.004). A higher Alcohol Use Disorders Identification Test score at baseline was associated with a significantly higher number of logins (B=1.10; P<.001) and diary registrations (B=1.29; P<.001). A higher Fagerström Test for Nicotine Dependence score at baseline in the intervention group was associated with a significantly larger reduction in tobacco use after 6 months (B=-9.86; P=.002). No other associations and no moderating effects were found.
CONCLUSIONS: Overall, a limited number of associations was found between participant characteristics, engagement, and outcome, except for gender, problematic alcohol use, and nicotine dependence. Future studies are needed to shed light on how this knowledge can be used to improve the effects of digital SC programs for cancer survivors.
BACKGROUND: Netherlands Trial register NTR6011/NL5434; https://onderzoekmetmensen.nl/nl/trial/22832.

BACKGROUND: Leveraging free smartphone apps can help expand the availability and use of evidence-based smoking cessation interventions. However, there is a need for additional research investigating how the use of different features within such apps impacts their effectiveness.
OBJECTIVE: We used observational data collected from an experiment of a publicly available smoking cessation app to develop supervised machine learning (SML) algorithms intended to distinguish the app features that promote successful smoking cessation. We then assessed the extent to which patterns of app feature use accounted for variance in cessation that could not be explained by other known predictors of cessation (eg, tobacco use behaviors).
METHODS: Data came from an experiment (ClinicalTrials.gov NCT04623736) testing the impacts of incentivizing ecological momentary assessments within the National Cancer Institute\'s quitSTART app. Participants\' (N=133) app activity, including every action they took within the app and its corresponding time stamp, was recorded. Demographic and baseline tobacco use characteristics were measured at the start of the experiment, and short-term smoking cessation (7-day point prevalence abstinence) was measured at 4 weeks after baseline. Logistic regression SML modeling was used to estimate participants\' probability of cessation from 28 variables reflecting participants\' use of different app features, assigned experimental conditions, and phone type (iPhone [Apple Inc] or Android [Google]). The SML model was first fit in a training set (n=100) and then its accuracy was assessed in a held-aside test set (n=33). Within the test set, a likelihood ratio test (n=30) assessed whether adding individuals\' SML-predicted probabilities of cessation to a logistic regression model that included demographic and tobacco use (eg, polyuse) variables explained additional variance in 4-week cessation.
RESULTS: The SML model\'s sensitivity (0.67) and specificity (0.67) in the held-aside test set indicated that individuals\' patterns of using different app features predicted cessation with reasonable accuracy. The likelihood ratio test showed that the logistic regression, which included the SML model-predicted probabilities, was statistically equivalent to the model that only included the demographic and tobacco use variables (P=.16).
CONCLUSIONS: Harnessing user data through SML could help determine the features of smoking cessation apps that are most useful. This methodological approach could be applied in future research focusing on smoking cessation app features to inform the development and improvement of smoking cessation apps.
BACKGROUND: ClinicalTrials.gov NCT04623736; https://clinicaltrials.gov/study/NCT04623736.

BACKGROUND: Expiratory flow limitation (EFL) during tidal breathing and lung hyperinflation have been identified as major decisive factors for disease status, prognosis and response to therapy in obstructive lung diseases.
OBJECTIVE: To investigate the delta values between expiratory and inspiratory resistance and reactance, measured using respiratory oscillometry and its correlation with air trapping and symptoms in subjects with obstructive lung diseases.
METHODS: Four hundred and seventy-one subjects (96 with chronic obstructive pulmonary disease [COPD], 311 with asthma, 30 healthy smokers and 34 healthy subjects) were included. Spirometry, body plethysmography and respiratory oscillometry measurements were performed and the differences between the expiratory and inspiratory respiratory oscillometry values (as delta values) were calculated. Questionnaires regarding symptoms and quality of life were administered.
RESULTS: Patients with COPD and healthy smokers had an increased delta resistance at 5 Hz (R5) compared with patients with asthma (p < 0.0001 and p = 0.037, respectively) and healthy subjects (p = 0.0004 and p = 0.012, respectively). Patients with COPD also had higher values of ΔR5-R19 than healthy subjects (p = 0.0001) and patients with asthma (p < 0.0001). Delta reactance at 5 Hz (X5) was significantly more impaired in COPD patients than in asthma and healthy subjects (p < 0.0001 for all). There was a correlation between the ratio of residual volume and total lung capacity and ΔR5 (p = 0.0047; r = 0.32), ΔR5-R19 (p = 0.0002; r = 0.41) and ΔX5 (p < 0.0001; r = -0.44), for all subjects. ΔX5 correlated with symptoms in COPD, healthy smokers and patients with asthma. In addition, ΔR5 correlated with asthma symptoms.
CONCLUSIONS: EFL was most prominent in parameters measuring peripheral resistance and reactance and correlated with air trapping and airway symptoms.

BACKGROUND: Efficacy of smartphone-based interventions depends on intervention content quality and level of exposure to that content. Smartphone-based survey completion rates tend to decline over time; however, few studies have identified variables that predict this decline over longer-term interventions (eg, 26 weeks).
OBJECTIVE: This study aims to identify predictors of survey completion and message viewing over time within a 26-week smoking cessation trial.
METHODS: This study examined data from a 3-group pilot randomized controlled trial of adults who smoke (N=152) and were not ready to quit smoking within the next 30 days. For 182 days, two intervention groups received smartphone-based morning and evening messages based on current readiness to quit smoking. The control group received 2 daily messages unrelated to smoking. All participants were prompted to complete 26 weekly smartphone-based surveys that assessed smoking behavior, quit attempts, and readiness to quit. Compliance was operationalized as percentages of weekly surveys completed and daily messages viewed. Linear regression and mixed-effects models were used to identify predictors (eg, intervention group, age, and sex) of weekly survey completion and daily message viewing and decline in compliance over time.
RESULTS: The sample (mean age 50, SD 12.5, range 19-75 years; mean years of education 13.3, SD 1.6, range 10-20 years) was 67.8% (n=103) female, 74.3% (n=113) White, 77% (n=117) urban, and 52.6% (n=80) unemployed, and 61.2% (n=93) had mental health diagnoses. On average, participants completed 18.3 (71.8%) out of 25.5 prompted weekly surveys and viewed 207.3 (60.6%) out of 345.1 presented messages (31,503/52,460 total). Age was positively associated with overall weekly survey completion (P=.003) and daily message viewing (P=.02). Mixed-effects models indicated a decline in survey completion from 77% (114/148) in the first week of the intervention to 56% (84/150) in the last week of the intervention (P<.001), which was significantly moderated by age, sex, ethnicity, municipality (ie, rural/urban), and employment status. Similarly, message viewing declined from 72.3% (1533/2120) in the first week of the intervention to 44.6% (868/1946) in the last week of the intervention (P<.001). This decline in message viewing was significantly moderated by age, sex, municipality, employment status, and education.
CONCLUSIONS: This study demonstrated the feasibility of a 26-week smartphone-based smoking cessation intervention. Study results identified subgroups that displayed accelerated rates in the decline of survey completion and message viewing. Future research should identify ways to maintain high levels of interaction with mobile health interventions that span long intervention periods, especially among subgroups that have demonstrated declining rates of intervention engagement over time.
BACKGROUND: ClinicalTrials.gov NCT03405129; https://clinicaltrials.gov/ct2/show/NCT03405129.

Substance use disorder (SUD) exacerbates the impact of Long-COVID, particularly increasing the risk of taste and olfactory disorders. Analyzing retrospective cohort data from TriNetX and over 33 million records (Jan 2020-Dec 2022), this study focused on 1,512,358 participants, revealing that SUD significantly heightens the likelihood of experiencing taste disturbances and anosmia in Long-COVID sufferers. Results indicated that individuals with SUD face a higher incidence of sensory impairments compared to controls, with older adults and women being particularly vulnerable. Smokers with SUD were found to have an increased risk of olfactory and taste dysfunctions. The findings underscore the importance of early screening, diagnosis, and interventions for Long-COVID patients with a history of SUD, suggesting a need for clinicians to monitor for depression and anxiety linked to sensory dysfunction for comprehensive care.

BACKGROUND: Open-system electronic cigarette (EC) product features, such as battery capacity, maximum output wattage, and so forth, are major components that drive product costs and may influence use patterns. Moreover, continued innovation and monitoring of product features and prices will provide critical information for designing appropriate taxation policies and product regulations.
OBJECTIVE: This study will examine how product features are associated with the prices of devices sold in web-based vape shops.
METHODS: We draw samples from 5 popular, US-based, web-based vape shops from April to August 2022 to examine starter kits, device-only products, and e-liquid container-only products. We implemented a linear regression model with a store-fixed effect to examine the association between device attributes and prices.
RESULTS: EC starter kits or devices vary significantly by type, with mod prices being much higher than pod and vape pen prices. The prices of mod starter kits were even lower than those of mod devices, suggesting that mod starter kits are discounted in web-based vape shops. The price of mod kits, mod device-only products, and pod kits increased as the battery capacity and output wattage increased. For vape pens, the price was positively associated with the volume size of the e-liquid container. On the other hand, the price of pod kits was positively associated with the number of containers.
CONCLUSIONS: A unit-based specific tax, therefore, will impose a higher tax burden on lower-priced devices such as vape pens or pod systems and a lower tax burden on mod devices. A volume- or capacity-based specific tax on devices will impose a higher tax burden on vape pens with a larger container size. Meanwhile, ad valorem taxes pegged to wholesale or retail prices would apply evenly across device types, meaning those with advanced features such as higher battery capacities and output wattage would face higher rates. Therefore, policy makers could manipulate tax rates by device type to discourage the use of certain device products.

BACKGROUND: Cigarette smoking remains one of the leading causes of preventable death worldwide. A worldwide study by the World Health Organization concluded that more than 8 million people die every year from smoking, tobacco consumption, and secondhand smoke. The most effective tobacco cessation programs require personalized human intervention combined with costly pharmaceutical supplementation, making them unaffordable or inaccessible to most tobacco users. Thus, digital interventions offer a promising alternative to these traditional methods. However, the leading smartphone apps available in the market today have either not been studied in a clinical setting or are unable to match the smoking cessation success rates of their expensive offline counterparts. We would like to understand whether QuitSure, a novel smoking cessation app built by Rapidkart Online Private Limited, is able to bridge this efficacy gap and deliver affordable and effective smoking cessation at scale.
OBJECTIVE: Our objective was to do an initial exploration into the engagement, efficacy, and safety of QuitSure based on the self-reported experiences of its users. Outcomes measured were program completion, the effect of program completion on smoking behavior, including self-reported cessation outcomes, and negative health events from using the app.
METHODS: All QuitSure registered users who created their accounts on the QuitSure app between April 1, 2021, and February 28, 2022, were sent an anonymized web-based survey. The survey results were added to their engagement data on the app to evaluate the feasibility and efficacy of the app as a smoking cessation intervention. The data were analyzed using descriptive statistics (frequencies and percentages) and the χ2 test of independence.
RESULTS: In total, 1299 users who had completed the QuitSure program submitted the survey and satisfied the inclusion criteria of the study. Of these, 1286 participants had completed the program more than 30 days before filling out the survey, and 1040 (80.1%, 95% CI 79.1%-82.6%) of them had maintained prolonged abstinence for at least 30 days after program completion. A majority of participants (770/891, 86.4%) who were still maintaining abstinence at the time of submitting the survey did not experience any severe nicotine withdrawal symptoms, while 41.9% (373/891) experienced no mild withdrawal symptoms either. Smoking quantity prior to completing the program significantly affected quit rates (P<.001), with heavy smokers (>20 cigarettes per day) having a lower 30-day prolonged abstinence rate (relative risk=0.91; 95% CI 90.0%-96.2%) compared to lighter smokers. No additional adverse events outside of known nicotine withdrawal symptoms were reported.
CONCLUSIONS: The nature of web-based surveys and cohort selection allows for extensive unknown biases. However, the efficacy rates of survey respondents who completed the program were high and provide a case for further investigation in the form of randomized controlled trials on the QuitSure tobacco cessation program.

BACKGROUND: Smoking is an independent and modifiable risk factor for the onset and development of psoriasis; however, evidence on the association between tobacco smoking and psoriasis treatment efficacy is limited. This study aimed to explore the influence of smoking on treatment efficacy in a cohort of patients with psoriasis in Shanghai, China.
METHODS: Patients with psoriasis were recruited from the Shanghai Skin Disease Hospital between 2021 and 2022. The treatment for patients with psoriasis includes acitretin, methotrexate, narrow-band ultraviolet/benvitimod, and biologics. Data were collected using a structured questionnaire, physical examination, and disease severity estimation at baseline, week four, and week eight. The achievement of a ≥75% reduction in psoriasis area and severity index (PASI75) score from baseline to week 8 was set as the primary outcome for treatment efficacy estimation. Data were analyzed using SAS 9.4.
RESULTS: A total of 560 patients with psoriasis were enrolled in this study, who were predominantly males (72.9%). The average age of patients was 48.4 years, and 38.8% of them were current smokers, 5.0% of them were former smokers. The median score of PASI among patients changed from 11.1 (interquartile range, IQR: 7.9-16.6) at baseline to 6.2 at week 4 and 3.1 at week 8, and 13.8% and 47.3% of patients with psoriasis achieved PASI75 at weeks 4 and 8, respectively. Logistic regression indicated that patients without tobacco smoking had a higher proportion of PASI75 achievement at week 8. The adjusted odds ratio (AOR) was 11.43 (95% CI: 6.91-18.89), 14.14 (95% CI: 8.27-24.20), and 3.05 (95% CI: 1.20-7.76) for non-smokers compared with smokers, current smokers, and former smokers, respectively. Moreover, former smokers had higher PASI75 achievement than current smokers (AOR=3.37), and patients with younger smoking initiation age, longer smoking duration, and higher smoking intensity had lower PASI75 achievement.
CONCLUSIONS: Tobacco smoking was negatively associated with PASI75 achievement both in current and former smokers, and former smokers had higher PASI75 achievement than current smokers. The implementation of tobacco control measures is beneficial for improving treatment responses.