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INTRODUCTION: Smokeless tobacco (ST) use and cessation rates have remained unchanged while cigarette smoking has declined, and cessation rates have increased. Text message programs have proved effective for cigarette smokers but have not been evaluated for ST users. The Veterans Health Administration (VHA) created a ST-specific arm of its SmokefreeVET automated text message program to help veteran ST users quit. AIMS AND METHODS: A retrospective evaluation was conducted on a real-world sample of veteran ST users (n = 1139) who subscribed to SmokefreeVET between 2017 and 2020. Time in program, abstinence, and nicotine replacement therapy (NRT) use were evaluated and compared to 9764 cigarette smokers who subscribed to SmokefreeVET. RESULTS: Younger subscribers were more likely to opt out early; 54% of ST users and 60% of cigarette smokers completed the 6-week program. ST users were more likely to report abstinence than cigarette smokers at all time points: the primary outcome, 30-day abstinence at 6 months, was 3.9% in ST users and 2.6% in cigarette smokers (p = .05) and the secondary outcome, abstinence at 3 months, was 5.3% in ST users and 3.4% in cigarette smokers (p = .03). NRT was used by 17% of ST users and was associated with a trend toward higher abstinence compared to ST users who did not use NRT. CONCLUSION: A real-world sample of ST users were more likely to report abstinence after using the SmokefreeVET text program than cigarette smokers. Automated text message programs may be effective for increasing cessation among ST users and warrant further investigation. IMPLICATIONS: Smokeless tobacco (ST) cessation is an important public health priority and of importance for veteran and military populations that have higher rates of ST use. There have been relatively few studies conducted investigating the effectiveness of text message interventions for ST cessation, despite the proven efficacy for cigarette smokers. This study provides evidence from a large, real-world sample that text message programs may be effective for ST users and suggests that further research into this treatment modality for ST users is needed.
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Abandono do Hábito de Fumar , Envio de Mensagens de Texto , Abandono do Uso de Tabaco , Tabaco sem Fumaça , Veteranos , Humanos , Estudos Retrospectivos , Fumantes , Dispositivos para o Abandono do Uso de TabacoRESUMO
INTRODUCTION: Smoking cessation mobile health (mHealth) programs are effective and have been recommended for integration into health care services but have not been evaluated in real-world health care settings. The Veterans Health Administration, a safety net health care provider, provides health care for 9 million US military veterans. Veterans Health Administration implemented the SmokefreeVET text message program in 2013. METHODS: A retrospective evaluation of 6153 SmokefreeVET subscribers was conducted. The primary outcome was 30-day self-reported abstinence at 6 months. Secondary outcomes included percentage of opt outs, program completers, and 30-day self-reported abstinence at 3 months. RESULTS: SmokefreeVET subscribers were on average 47.5 years old and 71.4% male. Smoking cessation medication use was reported by 11.5% of subscribers at the start of their quit attempt and subscribers enrolled in the program for an average of 29 days. Subscribers who were younger, female, and heavier smokers were more likely to opt out of the six-week program early. The abstinence rate for the primary outcome, self-reported 30-day abstinence at 6 months among all subscribers was 3.7%. CONCLUSIONS: SmokefreeVET enrolled a younger and more female population of subscribers than other studies of veterans interested in tobacco treatment. The mHealth program was generally acceptable to veterans, yet strategies to increase retention may improve completion rates and outcomes. In this real-world setting, nearly half of the mHealth program subscribers combined use of the text program with smoking cessation medication. Further study of the optimal combination of mHealth with smoking cessation treatments is needed. IMPLICATIONS: mHealth smoking cessation programs can be effectively implemented within real-world health care settings, even in those serving disadvantaged populations. Further research to improve mHealth program efficacy and integration into clinical settings will increase the population-level impact of these effective smoking cessation programs.
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Abandono do Hábito de Fumar , Telemedicina , Envio de Mensagens de Texto , Saúde dos Veteranos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Estados Unidos , United States Department of Veterans AffairsRESUMO
BACKGROUND: Research using the Veterans Health Administration (VA) electronic medical records (EMR) has been limited by a lack of reliable smoking data. OBJECTIVE: To evaluate the validity of using VA EMR "Health Factors" data to determine smoking status among veterans with recent military service. DESIGN: Sensitivity, specificity, area under the receiver-operating curve (AUC), and kappa statistics were used to evaluate concordance between VA EMR smoking status and criterion smoking status. PARTICIPANTS: Veterans (N = 2025) with service during the wars in Iraq/Afghanistan who participated in the VA Mid-Atlantic Post-Deployment Mental Health (PDMH) Study. MAIN MEASURES: Criterion smoking status was based on self-report during a confidential study visit. VA EMR smoking status was measured by coding health factors data entries (populated during automated clinical reminders) in three ways: based on the most common health factor, the most recent health factor, and the health factor within 12 months of the criterion smoking status data collection date. KEY RESULTS: Concordance with PDMH smoking status (current, former, never) was highest when determined by the most commonly observed VA EMR health factor (κ = 0.69) and was not significantly impacted by psychiatric status. Agreement was higher when smoking status was dichotomized: current vs. not current (κ = 0.73; sensitivity = 0.84; specificity = 0.91; AUC = 0.87); ever vs. never (κ = 0.75; sensitivity = 0.85; specificity = 0.90; AUC = 0.87). There were substantial missing Health Factors data when restricting analyses to a 12-month period from the criterion smoking status date. Current smokers had significantly more Health Factors entries compared to never or former smokers. CONCLUSIONS: The use of computerized tobacco screening data to determine smoking status is valid and feasible. Results indicating that smokers have significantly more health factors entries than non-smokers suggest that caution is warranted when using the EMR to select cases for cohort studies as the risk for selection bias appears high.
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Campanha Afegã de 2001- , Registros Eletrônicos de Saúde/normas , Guerra do Iraque 2003-2011 , Fumar/epidemiologia , United States Department of Veterans Affairs/normas , Saúde dos Veteranos/normas , Adulto , Estudos de Coortes , Registros Eletrônicos de Saúde/estatística & dados numéricos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Fumar/psicologia , Estados Unidos/epidemiologia , United States Department of Veterans Affairs/estatística & dados numéricos , Veteranos/psicologia , Veteranos/estatística & dados numéricos , Saúde dos Veteranos/estatística & dados numéricosRESUMO
OBJECTIVE: To develop a machine learning-based predictive algorithm to identify patients with type 2 diabetes mellitus (T2DM) who are candidates for initiation of U-500R insulin (U-500R). METHODS: A retrospective cohort of patients with T2DM was used from a large US administrative claims and electronic health records (EHR) database affiliated with Optum. Predictor variables derived from the data were used to identify appropriate supervised machine learning models including least absolute shrinkage and selection operator (LASSO) and extreme gradient boosted (XGBoost) methods. Predictive performance was assessed using precision-recall (PR) and receiver operating characteristic (ROC) area under the curve (AUC). The clinical interpretation of the final model was supported by fitting the final set of variables from the LASSO and XGBoost models to a traditional logistic regression model. Model choice was determined by comparing Akaike Information Criterion (AIC), residual deviances, and scaled Brier scores. RESULTS: Among 81,242 patients who met the study eligibility criteria, 577 initiated U-500R and were assigned to the positive class. Predictors of U-500R initiation included overweight/obesity, neuropathy, HbA1c ≥9% and 8%-9%, BUN 23.8 to <112 mg/dl, ALT 35.9-2056.2 U/L, no radiological chest exams, no GFR labs, and gait/mobility abnormalities. The best performing model was the LASSO model with an ROC AUC of 0.776 on the hold-out test set. CONCLUSION: This study successfully developed and validated a machine learning-based algorithm to identify U-500R candidates among patients with T2DM. This may help health care providers and decision-makers to understand important characteristics of patients who could use U-500R therapies which in turn could support policies and guidelines for optimal patient management.
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Diabetes Mellitus Tipo 2 , Adulto , Humanos , Diabetes Mellitus Tipo 2/tratamento farmacológico , Insulina/uso terapêutico , Estudos Retrospectivos , Aprendizado de Máquina , AlgoritmosRESUMO
Accurate identification of patient populations is an essential component of clinical research, especially for medical conditions such as chronic cough that are inconsistently defined and diagnosed. We aimed to develop and compare machine learning models to identify chronic cough from medical and pharmacy claims data. In this retrospective observational study, we compared 3 machine learning algorithms based on XG Boost, logistic regression, and neural network approaches using a large claims and electronic health record database. Of the 327,423 patients who met the study criteria, 4,818 had chronic cough based on linked claims-electronic health record data. The XG Boost model showed the best performance, achieving a Receiver-Operator Characteristic Area Under the Curve (ROC-AUC) of 0.916. We selected a cutoff that favors a high positive predictive value (PPV) to minimize false positives, resulting in a sensitivity, specificity, PPV, and negative predictive value of 18.0%, 99.6%, 38.7%, and 98.8%, respectively on the held-out testing set (n = 82,262). Logistic regression and neural network models achieved slightly lower ROC-AUCs of 0.907 and 0.838, respectively. The XG Boost and logistic regression models maintained their robust performance in subgroups of individuals with higher rates of chronic cough. Machine learning algorithms are one way of identifying conditions that are not coded in medical records, and can help identify individuals with chronic cough from claims data with a high degree of classification value.
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Tosse Crônica , Registros Eletrônicos de Saúde , Humanos , Estudos Retrospectivos , Algoritmos , Aprendizado de MáquinaRESUMO
Many interventions for cannabis use disorder (CUD) are associated with decreases in frequency and quantity of use but fail to increase overall rates of sustained abstinence. It is currently unknown whether reductions in use (in the absence of sustained abstinence) result in clinically significant improvements in functioning. The objective of this study was to refine a mobile contingency management approach to reduce cannabis use to ultimately evaluate whether reductions in frequency and quantity of cannabis are related to improvements in functional and mental health status. Three cohorts of participants (nâ¯=â¯18 total, nâ¯=â¯10 women) were enrolled and completed 2 weeks of ecological momentary assessment (EMA) during a baseline ad lib cannabis use period, followed by a 6-week reduction period. Participants completed EMA assessments multiple times per day and were prompted to provide videotaped saliva cannabis testing 2-3 times daily. Data from participants who were at least 80% adherent to all EMA prompts were analyzed (13 out of 18). During the ad lib phase, participants were using cannabis on 94% of the days and reported using a mean of 1.42 grams daily. The intervention was a mobile application that participants used to record cannabis use by saliva tests to bioverify abstinence and participants completed electronic diaries to report their grams used. During the 6-week intervention phase, participants reported reducing their use days to 47% of the days with a reported mean of .61 grams daily. In the last cohort, at least 50% of the heavy users were able to reduce their cannabis use by at least 50%. The effect of cannabis reduction (versus abstinence) is largely unknown. Observations suggest that it is possible to develop a mobile intervention to reduce cannabis use among heavy users, and this paradigm can be utilized in future work to evaluate whether reductions in cannabis use among heavy users will result in improvements in functional and mental health status.
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Cannabis , Abuso de Maconha , Transtornos Relacionados ao Uso de Substâncias , Humanos , Feminino , Abuso de Maconha/terapia , Abuso de Maconha/psicologia , Resultado do Tratamento , Terapia ComportamentalRESUMO
Background: Recent findings indicate that firefighters may be at increased risk for death by suicide; however, there has been only limited suicide prevention work in fire service to date. Aim: The objective of this program evaluation project was to develop and evaluate a web-based Safety Planning Intervention (SPI) training course for firefighter peer support specialists. Method: Peer support specialists who completed the web-based SPI training were administered evaluation questionnaires before the training and then again at a 3-month follow-up assessment. Results: A total of 213 peer support specialists completed the SPI training. Most participants took 2-3 h to complete the training. Participants generally reported high levels of satisfaction with the course, with the vast majority (94.4%) indicating they would recommend it to their peers. Course completers also demonstrated significant gains in SPI knowledge and self-efficacy from baseline to 3-month follow-up (all p's < .001). Moreover, the percentage of participants who reported completing a safety plan with someone they suspected at being of risk for suicide increased approximately 7-fold from baseline (3.5%) to 3-month follow-up (25.2%; p < .001). Participants further reported that 97.6% of the safety plans that they completed resulted in a positive outcome. Limitations: This was a program evaluation project that did not include a control group. Thus, causality cannot be inferred. Conclusions: The present findings suggest that web-based SPI training is a feasible and scalable approach for training peer support specialists to deliver the SPI to at-risk individuals.
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Bombeiros , Suicídio , Humanos , Prevenção do Suicídio , Inquéritos e Questionários , InternetRESUMO
INTRODUCTION: Smokers with posttraumatic stress disorder (PTSD) smoke at higher prevalence rates and are more likely to relapse early in a quit attempt. Innovative methods are needed to enhance quit rates, particularly in the early quit period. Web-based contingency-management (CM) approaches have been found helpful in reducing smoking among other difficult-to-treat smoker populations but are limited by the need for computers. This pilot study builds on the web-based CM approach by evaluating a smartphone-based application for CM named mobile CM (mCM). METHODS: Following a 2-week training period, 22 smokers with PTSD were randomized to a 4-week mCM condition or a yoked (i.e., noncontingent 4-week mCM condition). All smokers received 2 smoking cessation counseling sessions, nicotine replacement, and bupropion. Participants could earn up to $690 ($530 for mCM, $25.00 for assessments and office visits [up to 5], and $35.00 for equipment return). The average earned was $314.00. RESULTS: Compliance was high during the 2-week training period (i.e., transmission of videos) (93%) and the 4-week treatment period (92%). Compliance rates did not differ by group assignment. Four-week quit rates (verified with CO) were 82% for the mCM and 45% for the yoked controls. Three-month self-report quit rates were 50% in the mCM and 18% in the yoked controls. CONCLUSIONS: mCM may be a useful adjunctive smoking cessation treatment component for reducing smoking among smokers with PTSD, particularly early in a smoking quit attempt.
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Terapia Comportamental/métodos , Abandono do Hábito de Fumar/métodos , Prevenção do Hábito de Fumar , Transtornos de Estresse Pós-Traumáticos/complicações , Tabagismo/terapia , Adulto , Antidepressivos de Segunda Geração/uso terapêutico , Bupropiona/uso terapêutico , Terapia Combinada , Estudos de Viabilidade , Feminino , Humanos , Internet , Masculino , Pessoa de Meia-Idade , Cooperação do Paciente , Projetos Piloto , Recidiva , Fumar/psicologia , Abandono do Hábito de Fumar/economia , Abandono do Hábito de Fumar/psicologia , Transtornos de Estresse Pós-Traumáticos/psicologia , Dispositivos para o Abandono do Uso de Tabaco/estatística & dados numéricos , Tabagismo/psicologia , Resultado do TratamentoRESUMO
Tobacco cessation is reduced in U.S. military veterans experiencing homelessness. Mobile contingency management (mCM) is a promising treatment for tobacco use among populations experiencing homelessness, but past CM studies have largely been small, have relied on in-person follow-up, and/or lacked long-term biochemically verified abstinence measures. Veterans who smoked and were experiencing homelessness (N = 127) were randomly assigned to mCM treatment (4 weeks of mCM, 5 weeks of telehealth counseling, and the option of 12 weeks of pharmacotherapy) or VA standard care (3 biweekly group sessions and clinically appropriate pharmacotherapy), and all participants were randomly assigned to a $100 longer-term financial incentive for abstinence at 3-month follow-up. Participants were followed at 3-, 6-, and 12-months post-randomization, with the a priori main outcome designated as biochemically verified prolonged abstinence (with lapses) at 6-month follow-up. At 6-months, participants in the mCM group were significantly more likely to meet criteria for prolonged abstinence (OR = 3.1). Across time points, veterans in the mCM group had twice the odds of prolonged abstinence as those in the standard care group. However, by the 12-month follow-up, there was no statistically significant group difference in abstinence. Cost-effectiveness analysis indicated a modest increase in cost ($1,133) associated with an increase of one quality-adjusted life year saved for the intervention compared to standard care. mCM is a cost-effective approach to smoking cessation among veterans experiencing homelessness. Considering waning potency of this and other tobacco cessation interventions at 12-month follow-up, it is crucial to implement strategies to sustain abstinence for individuals experiencing homelessness.
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OBJECTIVE: Problematic anger is commonly reported among veterans with posttraumatic stress disorder (PTSD) and is associated with numerous psychosocial impairments. There is a clear need to develop innovative and effective anger interventions. One of the cognitive mechanisms associated with anger is the hostile interpretation bias, which is the tendency to interpret ambiguous interpersonal situations as hostile. The current study presents a successive cohort design methodology to develop and refine a mobile treatment application, entitled Mobile Anger Reduction Intervention (MARI), which uses interpretation bias modification techniques to modify hostile interpretation bias. METHOD: Two cohorts (total N = 13) of veterans with PTSD and problematic anger used the MARI application for 4 weeks. After each cohort, qualitative and quantitative data were used to modify the MARI application. The intervention is described, as well as the qualitative and quantitative findings and subsequent changes made to the mobile application based on participant feedback. RESULTS: Treatment adherence was high (90% of participants completed all sessions). Participants reported that they found the treatment helpful and easy to use and experienced improvements in hostile interpretation bias and problematic anger. CONCLUSIONS: This study demonstrates the utility of a successive cohort treatment design for the development of mobile interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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BACKGROUND: The aim of this study was to develop a predictive model to classify people with type 2 diabetes (T2D) into expected levels of success upon bolus insulin initiation. METHODS: Machine learning methods were applied to a large nationally representative insurance claims database from the United States (dNHI database; data from 2007 to 2017). We trained boosted decision tree ensembles (XGBoost) to assign people into Class 0 (never meeting HbA1c goal), Class 1 (meeting but not maintaining HbA1c goal), or Class 2 (meeting and maintaining HbA1c goal) based on the demographic and clinical data available prior to initiating bolus insulin. The primary objective of the study was to develop a model capable of determining at an individual level, whether people with T2D are likely to achieve and maintain HbA1c goals. HbA1c goal was defined at <8.0% or reduction of baseline HbA1c by >1.0%. RESULTS: Of 15 331 people with T2D (mean age, 53.0 years; SD, 8.7), 7800 (50.9%) people met HbA1c goal but failed to maintain that goal (Class 1), 4510 (29.4%) never attained this goal (Class 0), and 3021 (19.7%) people met and maintained this goal (Class 2). Overall, the model's receiver operating characteristic (ROC) was 0.79 with greater performance on predicting those in Class 2 (ROC = 0.92) than those in Classes 0 and 1 (ROC = 0.71 and 0.62, respectively). The model achieved high area under the precision-recall curves for the individual classes (Class 0, 0.46; Class 1, 0.58; Class 2, 0.71). CONCLUSIONS: Predictive modeling using routine health care data reasonably accurately classified patients initiating bolus insulin who would achieve and maintain HbA1c goals, but less so for differentiation between patients who never met and who did not maintain goals. Prior HbA1c was a major contributing parameter for the predictions.
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Diabetes Mellitus Tipo 2 , Insulina , Humanos , Pessoa de Meia-Idade , Insulina/uso terapêutico , Diabetes Mellitus Tipo 2/tratamento farmacológico , Hipoglicemiantes/uso terapêutico , Hemoglobinas Glicadas , Glicemia , Insulina Regular Humana/uso terapêuticoRESUMO
BACKGROUND: This study was designed to examine the concordance of proposed DSM-V posttraumatic stress disorder (PTSD) criteria with DSM-IV classification rules and examine the impact of the proposed DSM-V PTSD criteria on prevalence. METHOD: The sample (N = 185) included participants who were recruited for studies focused on trauma and health conducted at an academic medical center and VA medical center in the southeastern United States. The prevalence and concordance between DSM-IV and the proposed DSM-V classifications were calculated based on results from structured clinical interviews. Prevalence rates and diagnostic efficiency indices including sensitivity, specificity, area under the curve (AUC), and Kappa were calculated for each of the possible ways to define DSM-V PTSD. RESULTS: Ninety-five percent of the sample reported an event that met both DSM-IV PTSD Criterion A1 and A2, but only 89% reported a trauma that met Criterion A on DSM-V. Results examining concordance between DSM-IV and DSM-V algorithms indicated that several of the algorithms had AUCs above 0.90. The requirement of two symptoms from both Clusters D and E provided strong concordance to DSM-IV (AUC = 0.93; Kappa = 0.86) and a greater balance between sensitivity and specificity than requiring three symptoms in both Clusters D and E. CONCLUSIONS: Despite several significant changes to the diagnostic criteria for PTSD for DSM-V, several possible classification rules provided good concordance with DSM-IV. The magnitude of the impact of DSM-V decision rules on prevalence will be largely affected by the DSM-IV PTSD base rate in the population of interest.
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Manual Diagnóstico e Estatístico de Transtornos Mentais , Transtornos de Estresse Pós-Traumáticos/diagnóstico , Adulto , Área Sob a Curva , Feminino , Humanos , Masculino , Prevalência , Sensibilidade e Especificidade , Sudeste dos Estados Unidos/epidemiologia , Transtornos de Estresse Pós-Traumáticos/classificação , Transtornos de Estresse Pós-Traumáticos/epidemiologiaRESUMO
BACKGROUND: The affective states most strongly associated with nonsuicidal self-injury (NSSI) remain poorly understood, particularly among veterans. This study used ecological momentary assessment (EMA) to examine relationships between affect ratings and NSSI urges and behaviors among veterans with NSSI disorder. METHODS: Participants (N = 40) completed EMA entries via mobile phone for 28 days (3722 total entries). Entries included intensity ratings for five basic affective states, as well as NSSI urges and behaviors, during the past 4 hours. RESULTS: Bivariate analyses indicated that each affect variable was significantly associated with both NSSI urges and behaviors. Angry/hostile and sad were most strongly associated with both NSSI urges and behaviors. A multivariate regression revealed that angry/hostile, disgusted with self, and happy (inversely related) were contemporaneously (within the same period) associated with NSSI behaviors, whereas all five basic affective states were contemporaneously associated with NSSI urges. In a lagged model, angry/hostile and sad were associated with subsequent NSSI urges but not behaviors. CONCLUSIONS: Findings highlight the relevance of particular affective states to NSSI and the potential utility of targeting anger in treatments for NSSI among veterans. There is a need for future EMA research study to further investigate temporal relationships between these variables.
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Comportamento Autodestrutivo , Veteranos , Ira , Avaliação Momentânea Ecológica , Emoções , Humanos , Comportamento Autodestrutivo/diagnóstico , Comportamento Autodestrutivo/psicologiaRESUMO
INTRODUCTION: Cannabis is the most widely used illicit drug in the U.S. with 19.8 million current users. Population-based data indicate that almost all cannabis users (90%) have a lifetime history of tobacco smoking and the majority (74%) currently smoke tobacco. Among cannabis users, smoking tobacco is associated with increased frequency of cannabis use, increased morbidity, and poorer cannabis cessation outcomes. There is a lack of research, however, focused on addressing cessation of both substances simultaneously. The purpose of the current pilot study was to evaluate the feasibility and acceptability of a multi-component tobacco/cannabis abstinence treatment. METHODS: Five participants completed Abstinence Reinforcement Therapy, an intervention that included five sessions of cognitive-behavioral telephone counseling for tobacco/cannabis, pharmacotherapy for smoking cessation, and five weeks of mobile contingency management to remain abstinent from tobacco and cannabis. RESULTS: Feasibility of recruitment, retention and treatment completion was high. Satisfaction with the treatment was also high. CONCLUSION: Results support the feasibility and acceptability of this approach with dual cannabis and tobacco users and suggest that further research examining the efficacy of this approach is warranted.
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Fumar Cigarros/terapia , Abuso de Maconha/terapia , Motivação , Reforço Psicológico , Abandono do Hábito de Fumar/métodos , Adulto , Monóxido de Carbono/análise , Fumar Cigarros/epidemiologia , Terapia Cognitivo-Comportamental/métodos , Comorbidade , Dronabinol/análise , Estudos de Viabilidade , Feminino , Humanos , Masculino , Abuso de Maconha/epidemiologia , Pessoa de Meia-Idade , Satisfação do Paciente , Projetos Piloto , Saliva/química , Telemedicina , Telefone , Dispositivos para o Abandono do Uso de TabacoRESUMO
BACKGROUND: SmokefreeVET is a text messaging smoking cessation program available to veterans enrolled in the Veterans Health Administration. SmokefreeVET was developed in collaboration with the National Cancer Institute as part of the SmokefreeTXT initiative. PURPOSE: To evaluate the real world use of and effectiveness of the SmokefreeVET program for SmokefreeVET users who enrolled between 2013 and 2014. METHODS: Demographics and smoking behavior of 1470 SmokefreeVET users who enrolled between 2013 and 2014 were analyzed. Latent growth mixture modeling was used to identify discrete classes of SmokefreeVET users based on engagement patterns. Multi-level modeling determined class differences in abstinence. RESULTS: The average age of the SmokefreeVET user was 48, 75% of users were male, and 84% were daily smokers. After five weeks, 13% of all users reported abstinence from smoking. Five statistically distinct engagement classes of SmokefreeVET users were identified. Highly engaged classes were significantly less likely to opt-out and more likely to report abstinence. Over 60% of users who were classified as high engagers throughout the program reported abstinence 5weeks after their quit date. Users were more likely to report abstinence after two weeks if they used smoking cessation medication than those that did not use medication (OR=9.01, p<0.001). CONCLUSIONS: SmokefreeVET may be effective at supporting abstinence among a real world group of highly engaged users. Smoking cessation medication use was also associated with abstinence in SmokefreeVET users. Engagement appears to be a critical component when assessing the efficacy of a text messaging smoking cessation intervention.
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Abandono do Hábito de Fumar/métodos , Envio de Mensagens de Texto , Adulto , Idoso , Idoso de 80 Anos ou mais , Análise de Variância , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Aceitação pelo Paciente de Cuidados de Saúde/estatística & dados numéricos , Política Antifumo , Estados Unidos , Veteranos , Adulto JovemRESUMO
INTRODUCTION: Smoking is the most preventable cause of morbidity and mortality in U.S. veterans. Rural veterans in particular have elevated risk for smoking and smoking-related illness. However, these veterans underutilize smoking cessation treatment, which suggests that interventions for rural veterans should optimize efficacy and reach. OBJECTIVE: The primary goal of the current study is to evaluate the effectiveness of an intervention that combines evidenced based treatment for smoking cessation with smart-phone based, portable contingency management on smoking rates compared to a contact control intervention in a randomized controlled trial among rural Veteran smokers. Specifically, Veterans will be randomized to receive Abstinence Reinforcement Therapy (ART) which combines evidenced based cognitive-behavioral telephone counseling (TC), a tele-medicine clinic for access to nicotine replacement (NRT), and mobile contingency management (mCM) or a control condition (i.e., TC and NRT alone) that will provide controls for therapist, medication, time and attention effects. METHODS: Smokers were identified using VHA electronic medical records and recruited proactively via telephone. Participants (N=310) are randomized to either ART or a best practice control consisting of telephone counseling and telemedicine. Participating patients will be surveyed at 3-months, 6-months and 12-months post-randomization. The primary outcome measure is self-reported and biochemically validated prolonged abstinence at 6-month follow-up. DISCUSSION: This trial is designed to test the relative effectiveness of ART compared to a telehealth-only comparison group. Dissemination of this mHealth intervention for veterans in a variety of settings would be warranted if ART improves smoking outcomes for rural veterans and is cost-effective.
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Terapia Cognitivo-Comportamental/métodos , População Rural , Abandono do Hábito de Fumar/métodos , Telemedicina/métodos , Dispositivos para o Abandono do Uso de Tabaco , Veteranos , Humanos , Projetos de Pesquisa , Abandono do Hábito de Fumar/economia , Estados Unidos , United States Department of Veterans AffairsRESUMO
INTRODUCTION: Smoking rates are 80% among persons who are homeless, and these smokers have decreased odds of quitting smoking. Little is known about relapse rates among homeless smokers. More information is needed regarding both quit rates and innovative methods to treat smoking cessation among homeless smokers. Web-based contingency management (CM) approaches have been found helpful in reducing smoking among other difficult-to-treat smoker populations but have been generally limited by the need for computers or frequent clinic-based carbon monoxide (CO) monitoring. This open pilot study builds on a web-based CM approach by evaluating a smartphone-based application for CM named mobile CM (mCM). The study was conducted from January 1, 2013-April 15, 2014. METHOD: Following a 1-week training period, 20 homeless veteran smokers (≥ 10 cigarettes daily for 1 year or more and a CO baseline level ≥ 10 ppm) participated in a multicomponent smoking cessation intervention including 4 weeks of mCM. All smokers received 4 smoking cessation counseling sessions, nicotine replacement, and bupropion (if medically eligible). Participants could earn up to $815 ($480 for mCM, $100 for CO readings showing abstinence [ie, 6 ppm or less] at posttreatment and follow-up, and $35 for equipment return). RESULTS: Mean compensation for the mCM component was $286 of a possible $480. Video transmission compliance was high during the 1-week training (97%) and the 4-week treatment period (87%). Bioverified 7-day point prevalence abstinence was 50% at 4 weeks. Follow-up bioverified single assessment point prevalence abstinence was 55% at 3 months and 45% at 6 months. CONCLUSIONS: Results of this open pilot study suggest that mCM may be a useful adjunctive smoking cessation treatment component for reducing smoking among homeless veterans. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01789710.
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Pessoas Mal Alojadas , Aplicativos Móveis , Abandono do Hábito de Fumar/métodos , Tabagismo/terapia , Veteranos , Idoso , Bupropiona/uso terapêutico , Aconselhamento , Inibidores da Captação de Dopamina/uso terapêutico , Feminino , Seguimentos , Humanos , Masculino , Pessoa de Meia-Idade , Dispositivos para o Abandono do Uso de Tabaco , Tabagismo/tratamento farmacológico , Resultado do TratamentoRESUMO
The risk of smoking increases with specific psychiatric diagnoses (e.g., posttraumatic stress disorder); but the risk has also been shown to increase as a function of the number of psychiatric illnesses with which a person is diagnosed. The current study examined this association and other correlates of smoking-psychiatric comorbidity in a sample of U.S. Iraq- and Afghanistan-era veterans who have served since September 11, 2001. The sample consisted of 1,691 veterans (Mage = 37.5 years, 20.2% women, 53.2% minority). Veterans completed measures of smoking history, nicotine dependence, and smoking expectancies; they also underwent a structured diagnostic interview to establish any current and/or lifetime psychiatric diagnoses. Consistent with previous studies, the number of comorbid diagnoses was significantly associated with both heavy (>20 cigarettes/day) and light-to-moderate (≤20 cigarette/day) smoking. Moreover, among current smokers, significant correlations between self-reported dependence and number of diagnoses were observed. Examination of self-reported smoking expectancies revealed that a greater number of diagnoses were associated with greater expectancies of negative affect reduction, stimulation and state enhancement, taste and sensorimotor manipulation, social facilitation, craving and addiction, and boredom reduction. The present findings confirm the association between the number of comorbid diagnoses reported in previous studies, and extends those findings by identifying smoking expectancies differences among smokers with comorbid diagnoses.
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Transtornos Mentais/epidemiologia , Fumar/epidemiologia , Veteranos/estatística & dados numéricos , Adulto , Campanha Afegã de 2001- , Comorbidade , Feminino , Humanos , Guerra do Iraque 2003-2011 , Masculino , Estados Unidos/epidemiologiaRESUMO
This study evaluated the effect of childhood trauma exposure and the role of resilience on both depressive symptoms and suicidal ideation. The study evaluated 1,488 military personnel and veterans, who served after September 2001, for depressive, suicidal, and PTSD symptoms, combat exposure, childhood trauma exposure, and resiliency. Participants were enrolled as part of an ongoing multicenter study. Outcome measures were depressive symptoms and suicidal ideation. After controlling for the effects of combat exposure and PTSD, results revealed that childhood trauma exposures were significantly associated with depressive symptoms and suicidal ideation. In addition, resilience was negatively associated with depressive symptoms and suicidal ideation, suggesting a potential protective effect. These findings suggest that evaluation of childhood trauma is important in the clinical assessment and treatment of depressive symptoms and suicidal ideation among military personnel and veterans.