Depression Treatment Initiation Among Patients With Versus Without Chronic Pain.

OBJECTIVE: The purpose of this study was to examine the extent to which the presence of chronic noncancer pain (CNCP) impacts the likelihood that patients with diagnoses of depression will initiate depression treatment compared with those without CNCP. METHODS: We performed a retrospective cohort study of Kaiser Permanente of Georgia members older than 18 years who received a diagnosis of depression. Demographics and medical history were extracted from the electronic health record database. Members were further classified by the presence or absence of a CNCP diagnosis. Outcomes of interest were treated as time dependent and included ( 1 ) time to fulfillment of a new antidepressant medication and ( 2 ) time to a follow-up mental health encounter. Outcomes were compared between members with and without a CNCP diagnosis using Kaplan-Meier survival curves and Cox proportional hazard regression models. RESULTS: During the study period, 22,996 members met the inclusion criteria and 27.4% had a diagnosis of CNCP. In the matched sample, there was no difference in the time to a new antidepressant fill among members with and without CNCP (hazard ratio = 0.96; 95% confidence interval = 0.90-1.02; p = .18). In contrast, members with CNCP were significantly less likely to have a new mental health encounter after diagnosis (hazard ratio = 0.87; 95% confidence interval = 0.81-0.94; p < .001). CONCLUSIONS: Patients with CNCP were significantly less likely to have a new mental health encounter after a depression diagnosis compared with patients without CNCP. Additional outreach and consideration may be needed to improve initiation of depression treatment for newly diagnosed patients with comorbid depression and CNCP.

Impact of COVID-19 on Trends in Outpatient Clinic Utilization: A Tale of 2 Departments.

BACKGROUND: The COVID-19 pandemic forced many US health care organizations to shift from mostly in-person care to a hybrid of virtual visits (VV) and in-person visits (IPV). While there was an expected and immediate shift to virtual care (VC) early in the pandemic, little is known about trends in VC use after restrictions eased. METHODS: This is a retrospective study using data from 3 health care systems. All completed visits from adult primary care (APC) and behavioral health (BH) were extracted from the electronic health record of adults aged 19 years and older from January 1, 2019 to June 30, 2021. Standardized weekly visit rates were calculated by department and site and analyzed using time series analysis. RESULTS: There was an immediate decrease in APC visits following the onset of the pandemic. IPV were quickly replaced by VV such that VV accounted for most APC visits early in the pandemic. By 2021, VV rates declined, and VC visits accounted for <50% of all APC visits. By Spring 2021, all 3 health care systems saw a resumption of APC visits as rates neared or returned to prepandemic levels. In contrast, BH visit rates remained constant or slightly increased. By April 2020, almost all BH visits were being delivered virtually at each of the 3 sites and continue to do so without changes to utilization. CONCLUSIONS: VC use peaked during the early pandemic period. While rates of VC are higher than prepandemic levels, IPV are the predominant visit type in APC. In contrast, VC use has sustained in BH, even after restrictions eased.

Development of a Common Data Model for a Multisite and Multiyear Study of Virtual Visit Implementation: A Case Study.

BACKGROUND/OBJECTIVE: In multisite studies, a common data model (CDM) standardizes dataset organization, variable definitions, and variable code structures and can support distributed data processing. We describe the development of a CDM for a study of virtual visit implementation in 3 Kaiser Permanente (KP) regions. METHODS: We conducted several scoping reviews to inform our study's CDM design: (1) virtual visit mode, implementation timing, and scope (targeted clinical conditions and departments); and (2) extant sources of electronic health record data to specify study measures. Our study covered the period from 2017 through June 2021. Integrity of the CDM was assessed by a chart review of random samples of virtual and in-person visits, overall and by specific conditions of interest (neck or back pain, urinary tract infection, major depression). RESULTS: The scoping reviews identified a need to address differences in virtual visit programs across the 3 KP regionsto harmonize measurement specifications for our research analyses. The final CDM contained patient-level, provider-level, and system-level measures on 7,476,604 person-years for KP members aged 19 years and above. Utilization included 2,966,112 virtual visits (synchronous chats, telephone visits, video visits) and 10,004,195 in-person visits. Chart review indicated the CDM correctly identified visit mode on>96% (n=444) of visits, and presenting diagnosis on >91% (n=482) of visits. CONCLUSIONS: Upfront design and implementation of CDMs may be resource intensive. Once implemented, CDMs, like the one we developed for our study, provide downstream programming and analytic efficiencies by harmonizing, in a consistent framework, otherwise idiosyncratic temporal and study site differences in source data.

Investigating relationships among cancer survivors' engagement in an online support community, social support perceptions, well-being, and moderating effects of existing (offline) social support.

PURPOSE: Socially supportive relationships help cancer survivors cope with their diagnosis and may improve quality of life; however, many survivors report unmet support and information needs. Online communities of survivors may address these needs, but research on their benefits have been equivocal. This cross-sectional, self-report study investigated relationships among cancer survivors' level of engagement in an online survivor community (The American Cancer Society Cancer Survivors Network®; CSN), perceptions of emotional/informational support available from online communities ("online social support"), well-being, and moderating effects of "offline social support." METHODS: Participants were 1255 registered users of the CSN who completed surveys between 2013 and 2014. Three types of engagement with the CSN-social/communal, interpersonal communication, and informational/search engagement-were identified through principal components analysis. Regression analyses examined hypotheses. RESULTS: More frequent social/communal and interpersonal communication engagement were associated with increased online social support (p < .0001), and the relationship between interpersonal communication engagement and online social support was strongest for survivors reporting lower offline social support (interaction ß = - .35, p < .001). Greater online social support was associated with increased well-being, but only among survivors reporting low offline social support (interaction ß = - .35, p < .0001). CONCLUSIONS: Engagement in online survivor communities may increase support perceptions that promote well-being, but benefits may accrue more to survivors reporting low offline social support. IMPLICATIONS FOR CANCER SURVIVORS: Newly diagnosed cancer survivors, particularly those with unmet emotional/informational support needs, should be given the opportunity to communicate with other survivors through online survivor support networks.

Disentangling Efficacy and Expectations: A Prospective, Cross-lagged Panel Study of Cancer Survivors' Physical Activity.

Background: Despite demonstrated utility of Bandura's social cognitive theory for increasing physical activity among cancer survivors, the validity of the originally hypothesized relationships among self-efficacy, outcome expectations, and physical activity behavior continues to be debated. Purpose: To explore the temporal ordering of outcome expectations and self-efficacy as they relate to moderate-to-vigorous physical activity behavior. Methods: Longitudinal data from cancer survivors (N = 1,009) recently completing treatment were used to fit six cross-lagged panel models, including one parent model, one model representing originally hypothesized variable relationships, and four alternative models. All models contained covariates and used full information maximum likelihood and weighted least squares mean and variance adjusted estimation. Tests of equal fit between the parent model and alternative models were conducted. Results: The model depicting Bandura's originally hypothesized relationships showed no statistically significant relationship between outcome expectations and physical activity (p = .18), and was a worse fit to the data, compared with the parent model [Χ2 (1) = 5.92, p = .01]. An alternative model showed evidence of a reciprocal relationship between self-efficacy and outcome expectations, and was statistically equivalent to the parent model [Χ2(1) = 2.01, p = .16]. Conclusions: This study provides evidence against Bandura's theoretical assertions that (a) self-efficacy causes outcome expectations and not vice versa, and (b) outcome expectation has a direct effect on physical activity. Replication within population subgroups and for other health behaviors will determine whether the social cognitive theory needs modification. Future trials should test whether differential construct ordering results in clinically meaningful differences in physical activity behavior change.

Topic Modeling of Smoking- and Cessation-Related Posts to the American Cancer Society's Cancer Survivor Network (CSN): Implications for Cessation Treatment for Cancer Survivors Who Smoke.

INTRODUCTION: Smoking is a risk factor in at least 18 cancers, and approximately two-thirds of cancer survivors continue smoking following diagnosis. Text mining of survivors' online posts related to smoking and quitting could inform strategies to reduce smoking in this vulnerable population. METHODS: We identified posts containing smoking/cessation-related keywords from the Cancer Survivors Network (CSN), an online cancer survivor community of 166 000 members and over 468 000 posts since inception. Unsupervised topic model analysis of posts since 2000 using Latent Dirichlet Allocation extracted 70 latent topics which two subject experts inspected for themes based on representative terms. Posterior analysis assessed the distribution of topics within posts, and the range of themes discussed across posts. RESULTS: Less than 1% of posts (n = 3998) contained smoking/cessation-related terms, and covered topics related to cancer diagnoses, treatments, and coping. The most frequent smoking-related topics were quit smoking methods (5.4% of posts), and the environment for quitters (2.9% of posts), such as the stigma associated with being a smoker diagnosed with cancer and lack of empathy experienced compared to nonsmokers. Smoking as a risk factor for one's diagnosis was a primary topic in only 1.7% of smoking/cessation-related posts. CONCLUSIONS: The low frequency of smoking/cessation-related posts may be due to expected criticism/stigma for smoking but may also suggests a need for health care providers to address smoking and assist with quitting in the diagnostic and treatment process. Topic model analysis revealed potential barriers that should be addressed in devising clinical or population-level interventions for cancer survivors who smoke. IMPLICATIONS: Although smoking is a major risk factor for cancer, little is known about cancer patients' or survivors' views or concerns about smoking and quitting. This study used text mining of posts to an online community of cancer patients and survivors to investigate contexts in which smoking or quitting is discussed. Results indicated that smoking and quitting discussions were relatively rare, but nevertheless provide insight into barriers that may need to be addressed in cessation interventions for survivors.

Access to telehealth and changes in diabetes care patterns during the pandemic: evidence from a large integrated health system in the Southeast USA.

INTRODUCTION: To examine the role of telehealth in diabetes care and management during versus pre-COVID-19 pandemic. RESEARCH DESIGN AND METHODS: We included adults (≥18 years) with prevalent diabetes as of January 1, 2018, and continuously enrolled at Kaiser Permanente Georgia through December 31, 2021 (n=22,854). We defined pre (2018-2019) and during COVID-19 (2020-2021) periods. Logistic generalized estimating equations (GEEs) assessed the within-subject change in adherence to seven annual routine care processes (blood pressure (BP), hemoglobin A1C (HbA1c), cholesterol, creatinine, urine-albumin-creatinine ratio (UACR), eye and foot examinations) pre versus during COVID-19 among telehealth users (ie, more than one telehealth visit per year per period) and non-telehealth users. Linear GEE compared mean laboratory measurements pre versus during COVID-19 by telehealth use. RESULTS: The proportion of telehealth users increased from 38.7% (2018-2019) to 91.5% (2020-2021). During (vs pre) the pandemic, adherence to all care processes declined in telehealth (range: 1.6% for foot examinations to 12.4% for BP) and non-telehealth users (range: 1.9% for foot examinations to 40.7% for BP). In telehealth users, average HbA1c (mean difference: 0.4% (95% CI 0.2% to 0.6%), systolic BP (1.62 mm Hg (1.44 to 1.81)), and creatinine (0.03 mg/dL (0.02 to 0.04)), worsened during (vs pre) COVID-19, while low density lipoprotein (LDL) cholesterol improved (-9.08 mg/dL (-9.77 to -8.39)). For UACR, odds of elevated risk of kidney disease increased by 48% (OR 1.48 (1.36-1.62)). Patterns were similar in non-telehealth users. CONCLUSIONS: Telehealth use increased during the pandemic and alleviated some of the observed declines in routine diabetes care and management.

Engaging staff to improve COVID-19 vaccination response at long-term care facilities (ENSPIRE): A cluster randomized trial of co-designed, tailored vaccine promotion materials.

BACKGROUND: COVID-19 vaccination rates among long-term care center (LTCC) workers are among the lowest of all frontline health care workers. Current efforts to increase COVID-19 vaccine uptake generally focus on strategies that have proven effective for increasing influenza vaccine uptake among health care workers including educational and communication strategies. Experimental evidence is lacking on the comparative advantage of educational strategies to improve vaccine acceptance and uptake, especially in the context of COVID-19. Despite the lack of evidence, education and communication strategies are recommended to improve COVID-19 vaccination rates and decrease vaccine hesitancy (VH), especially strategies using tailored messaging for disproportionately affected populations. METHODS: We describe a cluster-randomized comparative effectiveness trial with 40 LTCCs and approximately 4000 LTCC workers in 2 geographically, culturally, and ethnically distinct states. We compare the effectiveness of two strategies for increasing COVID-19 booster vaccination rates and willingness to promote COVID-19 booster vaccination: co-design processes for tailoring educational messages vs. an enhanced usual care comparator. Our study focuses on the language and/or cultural groups that are most disproportionately affected by VH and low COVID-19 vaccine uptake in these LTCCs. CONCLUSION: Finding effective methods to increase COVID-19 vaccine uptake and decrease VH among LTCC staff is critical. Beyond COVID-19, better approaches are needed to improve vaccine uptake and decrease VH for a variety of existing vaccines as well as vaccines created to address novel viruses as they emerge.

Racial Disparities in COVID-19 Severity Are Partially Mediated by Chronic Stress-Evidence from a Large Integrated Healthcare System.

BACKGROUND: Racial and ethnic minorities have experienced a disproportionate burden of severe COVID-19. Whether chronic stress, also disproportionately experienced by racial and ethnic minorities, explains this excess risk is unknown. METHODS: We identified 9577 adults (≥ 18 years) diagnosed with COVID-19 from January 1, 2020, through September 30, 2021, enrolled in Kaiser Permanente Georgia (KPGA) with complete biomarker data. Self-reported race (Black or White) was defined from electronic medical records. Chronic stress, defined as allostatic load (AL), a composite score (scale 0-7) based on seven cardio-metabolic biomarkers, was categorized as below (low AL) or above (high AL) the median. Severe COVID-19 was defined as hospitalization or mortality within 30 days of COVID-19 diagnosis. The association between race, AL, and severe COVID-19 was assessed using multivariable Poisson regression. The mediating effect of AL was assessed using the Valeri and VanderWeele method. All results were expressed as risk ratios (RRs) with 95% confidence intervals. RESULTS: Overall, Black (vs. White) KPGA members had an 18% excess risk of AL (RR: 1.18, 95%CI: 1.14-1.23) and a 24% excess risk of severe COVID-19 (RR: 1.24, 95%CI: 1.12, 1.37). AL explained 23% of the Black-White disparities in severe COVID-19. CONCLUSIONS: In our study, chronic stress, characterized by AL, partially mediated Black-White disparities in severe COVID-19 outcomes.

Disruption to routine diabetes care processes during the pandemic: evidence from a large integrated health system in the Southeast United States.

INTRODUCTION: We investigated the impact of the COVID-19 pandemic on annual adherence to seven diabetes care guidelines and risk factor management among people with diabetes. RESEARCH DESIGN AND METHODS: We included all adults (aged ≥18 years) with prevalent diabetes as of 1 January 2018, who were continuously enrolled at Kaiser Permanente Georgia (KPGA) through 31 December 2021 (n=22 854). Prevalent diabetes was defined as a history of at least one of a diagnosis code for diabetes, use of antihyperglycemic medication, or at least one laboratory value of HbA1c, fasting plasma glucose or random glucose in the diabetic range. We defined pre-COVID (2018-2019) and during COVID (2020-2021) cohorts. Cohort-specific laboratory measurements (ie, blood pressure (BP), HbA1c, cholesterol, creatinine, urine-albumin-creatinine ratio (UACR)) and procedures (ie, eye and foot examinations) were determined from KPGA's electronic medical record data. We used logistic generalized estimating equations (GEE), adjusted for baseline age, to assess the within-subject change in guideline adherence (ie, at least one measurement per year per period) from pre-COVID to during COVID era overall, and by age, sex, and race. Linear GEE compared mean laboratory measurements pre and during COVID. RESULTS: The proportion of adults meeting each of the seven diabetes care guidelines decreased significantly during (vs pre) COVID (range in absolute reductions: -0.8% to -11.2%) with greatest reductions seen for BP (-11.2%) and cholesterol (-8.8%). Declines were similar across age, sex, and race subgroups. Average HbA1c and systolic BP increased 0.11% and 1.6 mmHg, respectively, while low-density lipoprotein cholesterol declined 8.9 mg/dL. The proportion of adults at high risk of kidney disease (ie, UACR ≥300 mg/g) increased from 6.5% to 9.4%. CONCLUSIONS: In an integrated healthcare system, the proportion of people with diabetes meeting guideline-recommended screenings decreased during the pandemic, coinciding with worsening glucose, kidney, and (some) cardiovascular risk profiles. Follow-up is needed to assess the long-term implications of these care gaps.

The Association Between Black vs. White Race and 30-Day Hospitalization Among People Diagnosed with COVID-19 Within an Integrated Care Setting: a Cohort Study.

BACKGROUND: Black Americans are more likely to experience hospitalization from COVID-19 compared with White Americans. Whether this excess risk differs by age, sex, obesity, or diabetes, key risk factors for COVID hospitalization, among an integrated population with uniform healthcare access, are less clear. METHODS: We identified all adult members (≥ 18 years) of Kaiser Permanente Georgia (KPGA) diagnosed with COVID-19 between January 1, 2020, and September 30, 2021 (N = 24,564). We restricted the analysis to members of Black or White race identified from electronic medical records. Our primary outcome was first hospitalization within 30 days of COVID-19 diagnosis. To assess the association between race and 30-day hospitalization, we performed multivariable logistic regression adjusting for several member and neighborhood-level characteristics, and tested for interactions of race with age, sex, diabetes, and obesity. A regression-based decomposition method was then used to estimate how much of the observed race disparity in 30-day hospitalization could be explained by member and neighborhood-level factors. RESULTS: Overall, 11.27% of Black KPGA members were hospitalized within 30 days of a COVID diagnosis, as compared with 9.44% of White KPGA members. Black (vs. White) KPGA members had a 34% (aOR: 1.32 [95% CI: 1.19-1.47]) higher odds of 30-day hospitalization following COVID-19 after accounting for clinical differences. The odds of 30-day hospitalization in Black vs. White KPGA members did not differ significantly by sex (men: 1.46 [1.25-1.70]; women: 1.24 [1.07-1.43]), by age (18-29 years: 1.33 [0. 841-2.10]; 30-49 years: 1.26 [1.02-1.56]; ≥ 50 years: 1.24 [1.10-1.41]); by diabetes status (with diabetes: 1.38 [1.16-1.66]; without diabetes: 1.26 [1.11-1.44]), or by obesity (with obesity: 1.31 [1.15-1.50]; without obesity: 1.28 [1.06-1.53]). Factors that, if Black and White KPGA members had the same level of exposure, would be most likely to reduce the Black-White disparity in 30-day hospitalization from COVID-19 were obesity, history of flu vaccine, and neighborhood-level income and social vulnerability. CONCLUSIONS: Early in the pandemic, Black (vs. White) members of an integrated health system had higher odds of being hospitalized within 30 days of COVID-19 diagnosis and this excess risk was similar by sex, age, and comorbidities. Factors that explained the largest proportions of race-based disparities were obesity, receipt of flu vaccine, and neighborhood-level social determinants of health. These findings suggest that social determinants of health, or other unmeasured factors, may be drivers of racial disparities in COVID-19 outcomes.

Dexamethasone Suppression Testing in a Contemporary Cohort with Adrenal Incidentalomas in Two U.S. Integrated Healthcare Systems.

Autonomous cortisol secretion (ACS) from an adrenal adenoma can increase the risk for comorbidities and mortality. The dexamethasone suppression test (DST) is the standard method to diagnose ACS. A multi-site, retrospective cohort of adults with diagnosed adrenal tumors was used to understand patient characteristics associated with DST completion and ACS. Time to DST completion was defined using the lab value and result date; follow-up time was from the adrenal adenoma diagnosis to the time of completion or censoring. ACS was defined by a DST > 1.8 µg/dL (50 nmol/L). The Cox proportional hazards regression model assessed associations between DST completion and patient characteristics. In patients completing a DST, a logistic regression model evaluated relationships between elevated ACS and covariates. We included 24,259 adults, with a mean age of 63.1 years, 48.1% obese, and 28.7% with a Charlson comorbidity index ≥ 4. Approximately 7% (n = 1768) completed a DST with a completion rate of 2.36 (95% CI 2.35, 2.37) per 100 person-years. Fully adjusted models reported that male sex and an increased Charlson comorbidity index were associated with a lower likelihood of DST completion. Current or former smoking status and an increased Charlson comorbidity index had higher odds of a DST > 1.8 µg/dL. In conclusion, clinical policies are needed to improve DST completion and the management of adrenal adenomas.

Understanding Racial Disparities in COVID-19-Related Complications: Protocol for a Mixed Methods Study.

BACKGROUND: In the United States, the COVID-19 pandemic has magnified the disproportionate and long-standing health disparities experienced by Black communities. Although it is acknowledged that social determinants of health (SDOH) rather than biological factors likely contribute to this disparity, few studies using rigorous analytic approaches in large, information-rich community-based data sets are dedicated to understanding the underlying drivers of these racial disparities. OBJECTIVE: The overall aim of our study is to elucidate the mechanisms by which racial disparities in severe COVID-19 outcomes arise, using both quantitative and qualitative methods. METHODS: In this protocol, we outline a convergent parallel mixed methods approach to identifying, quantifying, and contextualizing factors that contribute to the dramatic disparity in COVID-19 severity (ie, hospitalization, mortality) in Black versus white COVID-19 patients within the integrated health care system of Kaiser Permanente Georgia (KPGA). Toward this end, we will generate two quantitative cohorts of KPGA members with a confirmed COVID-19 diagnosis between January 1, 2020, and September 30, 2021: (1) an electronic medical record (EMR) cohort including routinely captured data on diagnoses, medications, and laboratory values, and a subset of patients hospitalized at Emory Healthcare to capture additional in-hospital data; and (2) a survey cohort, where participants will answer a range of questions related to demographics (eg, race, education), usual health behaviors (eg, physical activity, smoking), impact of COVID-19 (eg, job loss, caregiving responsibilities), and medical mistrust. Key outcomes of interest for these two cohorts include hospitalization, mortality, intensive care unit admission, hospital readmission, and long COVID-19. Finally, we will conduct qualitative semistructured interviews to capture perceptions of and experiences of being hospitalized with COVID-19 as well as related interactions with KPGA health care providers. We will analyze and interpret the quantitative and qualitative data separately, and then integrate the qualitative and quantitative findings using a triangulation design approach. RESULTS: This study has been funded by a Woodruff Health Sciences grant from December 2020 to December 2022. As of August 31, 2022, 31,500 KPGA members diagnosed with COVID-19 have been included in the EMR cohort, including 3028 who were hospitalized at Emory Healthcare, and 482 KPGA members completed the survey. In addition, 20 KPGA members (10 Black and 10 white) have been interviewed about their experiences navigating care with COVID-19. Quantitative and qualitative data cleaning and coding have been completed. Data analysis is underway with results anticipated to be published in December 2022. CONCLUSIONS: Results from this mixed methods pilot study in a diverse integrated care setting in the southeastern United States will provide insights into the mechanisms underpinning racial disparities in COVID-19 complications. The quantitative and qualitative data will provide important context to generate hypotheses around the mechanisms for racial disparities in COVID-19, and may help to inform the development of multilevel strategies to reduce the burden of racial disparities in COVID-19 and its ongoing sequelae. Incorporating contextual information, elucidated from qualitative interviews, will increase the efficacy, adoption, and sustainability of such strategies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/38914.

Implications of Attrition in a Longitudinal Web-Based Survey: An Examination of College Students Participating in a Tobacco Use Study.

BACKGROUND: Web-based survey research has several benefits, including low cost and burden, as well as high use of the Internet, particularly among young adults. In the context of longitudinal studies, attrition raises concerns regarding the validity of data, given the potential associations with individual and institutional characteristics, or the focal area of study (eg, cigarette use). OBJECTIVES: The objective of this study was to compare baseline characteristics of nonresponders versus responders in a sample of young adult college students in a Web-based longitudinal study regarding tobacco use. METHODS: We conducted a secondary data analysis of 3189 college students from seven Georgia colleges and universities in a 2-year longitudinal study. We examined baseline tobacco use, as well as individual- and institutional-level factors, as predictors of attrition between wave 1 (October and November 2014) and wave 2 (February and March 2015) using multilevel modeling. Results: A total 13.14% (419/3189) participants were lost to follow-up at wave 2. Predictors of nonresponse were similar in the models examining individual-level factors and institutional-level factors only and included being black versus white (odds ratio [OR] 1.74, CI 1.23-2.46); being male versus female (OR 1.41, CI 1.10-1.79); seeking a bachelor's degree versus advanced degree (OR 1.41, CI 1.09-1.83); not residing on campus (OR 0.62, CI 0.46-0.84); past 30-day tobacco use (OR 1.41, CI 1.10-1.78); attending a nonprivate college (OR 0.48, CI 0.33-0.71); and attending a college with ≤10,000 students (OR 0.56, CI 0.43-0.73). CONCLUSIONS: Future longitudinal studies should assess predictors of attrition to examine how survey topic and other individual and institutional factors might influence the response to allow for correction of selection bias.

Polytobacco, marijuana, and alcohol use patterns in college students: A latent class analysis.

Limited research has examined polysubstance use profiles among young adults focusing on the various tobacco products currently available. We examined use patterns of various tobacco products, marijuana, and alcohol using data from the baseline survey of a multiwave longitudinal study of 3418 students aged 18-25 recruited from seven U.S. college campuses. We assessed sociodemographics, individual-level factors (depression; perceptions of harm and addictiveness,), and sociocontextual factors (parental/friend use). We conducted a latent class analysis and multivariable logistic regression to examine correlates of class membership (Abstainers were referent group). Results indicated five classes: Abstainers (26.1% per past 4-month use), Alcohol only users (38.9%), Heavy polytobacco users (7.3%), Light polytobacco users (17.3%), and little cigar and cigarillo (LCC)/hookah/marijuana co-users (10.4%). The most stable was LCC/hookah/marijuana co-users (77.3% classified as such in past 30-day and 4-month timeframes), followed by Heavy polytobacco users (53.2% classified consistently). Relative to Abstainers, Heavy polytobacco users were less likely to be Black and have no friends using alcohol and perceived harm of tobacco and marijuana use lower. Light polytobacco users were older, more likely to have parents using tobacco, and less likely to have friends using tobacco. LCC/hookah/marijuana co-users were older and more likely to have parents using tobacco. Alcohol only users perceived tobacco and marijuana use to be less socially acceptable, were more likely to have parents using alcohol and friends using marijuana, but less likely to have friends using tobacco. These findings may inform substance use prevention and recovery programs by better characterizing polysubstance use patterns.

Reasons for Polytobacco Use among Young Adults: Scale Development and Validation.

INTRODUCTION: Limited research has examined reasons for polytobacco use, an increasing public health problem, particularly among young adults. We examined reasons for polytobacco use among users of more than one tobacco product in the past 4 months enrolled in an ongoing six-wave longitudinal study of 3,418 students aged 18-25 from seven US colleges and universities. METHODS: An expert panel generated items related to reasons for polytobacco use, included in Wave 3 (administered in Summer 2015). Participants reporting use of more than one tobacco product in the past four months (n=540) were asked to complete the Reasons for Polytobacco Use scale and measures related to tobacco/nicotine use/dependence, use motives, perceptions of tobacco, parental/friend use, other substance use, and mental health. We conducted a factor analysis and then examined convergent and discriminant validity for the derived factors. RESULTS: Our sample was an average age of 20.40 (SD=1.84), 48.0% male, and 21.9% Black. Four factors were identified: Instrumentality, Social Context, Displacement, and Experimentation. Instrumentality was the only factor associated with little cigar/cigarillo and marijuana use. Displacement and Social Context showed similar associations; however, Social Context was associated with having friends who used tobacco while Displacement was not. Experimentation was associated with greater perceived addictiveness and harm of using tobacco products as well as greater perceived social acceptability of tobacco use. CONCLUSIONS: Each of the four factors identified demonstrated unique convergent and discriminant validity. The use of this scale to characterize polytobacco using young adults may help inform and target cessation or prevention interventions.