Vaping cessation support recommendations from adolescents who vape: a qualitative study.

BACKGROUND: Youth vaping is a serious public health concern, being more prevalent than any other tobacco use. To inform cessation interventions, we explored what adolescents perceive as their reasons for quitting and strategies to help them quit. METHOD: Semi-structured interviews were conducted with a convenience sample of 11 adolescents reporting vaping in the past 90 days and recruited from a high school in Massachusetts. Interviews were transcribed and dual-coded. Inductive thematic analysis was employed, and thematic summaries were prepared. RESULTS: Reasons adolescents reported for quitting included cost, experiencing "nic-sick" from nicotine withdrawal or excess intake, negative impacts on mood, concentration, or health, and experiencing symptoms of nicotine dependence. Nearly all tried to quit multiple times. Barriers to quitting included exposure to vaping, access to vape products, stress, and "cool" new products or flavors. Quit strategies included avoiding others vaping, seeking social support to quit, addressing peer pressure to continue vaping, learning successful quit strategies from peers, and using distraction strategies or alternatives to vaping. CONCLUSION: Many adolescents who vape want to quit, and most have tried multiple times. Interventions need to engage adolescents with varying reasons to quit, barriers, and quit strategy preferences. CLINICAL TRIAL REGISTRATION: This study is registered through ClinicalTrials.gov. The trial registration number is NCT05140915. The trial registration date is 11/18/2021.

Characterizing Pandemic-Related Changes in Smoking Over Time in a Cohort of Current and Former Smokers.

INTRODUCTION: We used a longitudinal cohort of US adults who were current or former smokers to explore how three participant-reported factors-general stress, coronavirus disease of 2019 (COVID-19) distress, and perceived risk of complications from COVID-19 related to smoking-were associated with changes in smoking status. METHODS: Smoking status was assessed at three time points. Timepoint 1 status was assessed at a prior study completion (2018-2020). Timepoint 2 (start of the pandemic), and Timepoint 3 (early phase of the pandemic) statuses were assessed using an additional survey in 2020. After classifying participants into eight groups per these time points, we compared the means of participant-reported factors and used a linear regression model to adjust for covariates. RESULTS: Participants (n = 392) were mostly female (73.9%) and non-Hispanic White (70.1%). Between Timepoints 2 and 3, abstinence rates decreased by 11%, and 40% of participants reported a smoking status change. Among those reporting a change and the highest general stress levels, newly abstinent participants had higher perceived risk of complications from COVID-19 related to smoking than those who relapsed during pandemic (mean (SD): 14.2 (3.3) vs. 12.6 (3.8)). Compared to participants who sustained smoking, those who sustained abstinence, on average, scored 1.94 less on the general stress scale (ßeta Coefficient (ß): -1.94, p-value < .01) and 1.37 more on the perceived risk of complications from COVID-19 related to smoking scale (ß: 1.37, p-value .02). CONCLUSIONS: Decreased abstinence rates are concerning. Patterns of reported factors were as expected for individuals who sustained their smoking behavior but not for those who changed. IMPLICATIONS: We observed an increase in smoking rates during the COVID-19 pandemic. In exploring how combinations of general stress levels, COVID-19 distress levels, and perceived risk of complications from COVID-19 related to smoking were associated with changes in smoking, we observed expected patterns of these factors among individuals who sustained abstinence or smoking. Among individuals who changed smoking status and reported high stress levels, those who reported a higher perceived risk of complications from COVID-19 related to smoking abstained from smoking. In contrast, those who reported a lower perceived risk of complications from COVID-19 related to smoking, started smoking. An intersectional perspective may be needed to understand smokers' pandemic-related behavior changes.

Experiences Using Family or Peer Support for Smoking Cessation and Considerations for Support Interventions: A Qualitative Study in Persons With Mental Health Conditions.

Background: The current study aimed to understand how people with mental health conditions who currently smoke or recently quit engaged with family members or peers when quitting and assessed interest in involving family or peers in cessation interventions. Methods: Adults with mental health conditions who smoke or had quit within the past 5 years were recruited from publicly funded mental health programs (N = 24). We conducted virtual qualitative interviews between November 2020 and August 2021 and analyzed the data using the rapid thematic analytic approach. Results: Most participants were men (62%), and 71% were current smokers. We found that: having family/peers who were interested in quitting presented communal quitting opportunities, communication that facilitated quitting tended to be encouraging, and strong relationships with family members increased willingness to involve them in cessation interventions. But family or peer support was less helpful for individuals who were not ready to quit. Conclusion: Training family and peers to engage in supportive behaviors may promote cessation in this population. Cessation interventions may benefit from recruiting support partners who share a strong relationship with the smoker.

Examining pathways between family or peer factors and smoking cessation in a nationally representative US sample of adults with mental health conditions who smoke: a structural equation analysis.

BACKGROUND: Supportive family or peer behaviors positively impact smoking cessation in people with mental health problems who smoke. However, the limited understanding of the pathways through which family or peer factors impact quitting limits the development of effective support interventions. This study examined pathways through which family or peer views on tobacco use, family or peer smoking status, and rules against smoking in the home influenced quitting in adults with mental health problems who smoke. METHODS: We used data from the Population Assessment of Tobacco and Health Study, a national longitudinal survey. Baseline data were collected in 2015, and follow-up data in 2016. We included adults' current smokers who had experienced two or more mental health symptoms in the past year (unweighted n = 4201). Structural equation modeling was used to test the relationships between family and peer factors, mediating factors, and smoking cessation. RESULTS: We found that having family or peers with negative views on tobacco use had a positive indirect effect on smoking cessation, mediated through the individual's intention to quit (regression coefficient: 0.19) and the use of evidence-based approaches during their past year quit attempt (regression coefficient: 0.32). Having rules against smoking in the home (regression coefficient: 0.33) and having non-smoking family members or peers (regression coefficient: 0.11) had a positive indirect effect on smoking cessation, mediated through smoking behaviors (regression coefficient: 0.36). All paths were statistically significant (p <  0.01). The model explained 20% of the variability in smoking outcomes. CONCLUSION: Family or peer-based cessation interventions that systematically increase intentions to quit and monitor smoking behavior may be able to assess the efficacy of family and peer support on quitting in people with mental health problems who smoke.

Video-based communication assessment for weight management counseling training in medical residents: a mixed methods study.

BACKGROUND: Physician delivered weight management counseling (WMC) occurs infrequently and physicians report lack of training and poor self-efficacy. The purpose of this study was to develop and test the Video-based Communication Assessment (VCA) for weight management counseling (WMC) training in medical residents. METHODS: This study was a mixed methods pilot conducted in 3 phases. First, we created five vignettes based on our prior data and expert feedback, then administered the vignettes via the VCA to Internal Medicine categorical residents (n = 16) from a University Medical School. Analog patients rated responses and also provided comments. We created individualized feedback reports which residents were able to view on the VCA. Lastly, we conducted debriefing interviews with the residents (n = 11) to obtain their feedback on the vignettes and personalized feedback. Interviews were transcribed, and we used thematic analysis to generate and apply codes, followed by identifying themes. RESULTS: Descriptive statistics were calculated and learning points were created for the individualized feedback reports. In VCA debriefing interviews with residents, five themes emerged: 1) Overall the VCA was easy to use, helpful and more engaging than traditional learning and assessment modes, 2) Patient scenarios were similar to those encountered in the clinic, including diversity, health literacy and different stages of change, 3) The knowledge, skills, and reminders from the VCA can be transferred to practice, 4) Feedback reports were helpful, to the point and informative, including the exemplar response of how to best respond to the scenario, and 5) The VCA provide alternatives and practice scenarios to real-life patient situations when they aren't always accessible. CONCLUSIONS: We demonstrated the feasibility and acceptability of the VCA, a technology delivered platform, for delivering WMC to residents. The VCA exposed residents to diverse patient experiences and provided potential opportunities to tailor providers responses to sociological and cultural factors in WMC scenarios. Future work will examine the effect of the VCA on WMC in actual clinical practice.

Impact of Patient Access to Online VA Notes on Healthcare Utilization and Clinician Documentation: a Retrospective Cohort Study.

BACKGROUND: In an effort to foster patient engagement, some healthcare systems provide their patients with open notes, enabling them to access their clinical notes online. In January 2013, the Veterans Health Administration (VA) implemented online access to clinical notes ("VA Notes") through the Blue Button feature of its patient portal. OBJECTIVE: To measure the association of online patient access to clinical notes with changes in healthcare utilization and clinician documentation behaviors. DESIGN: A retrospective cohort study. PATIENTS: Patients accessing My HealtheVet (MHV), the VA's online patient portal, between July 2011 and January 2015. MAIN MEASURES: Use of healthcare services (primary care clinic visits and online electronic secure messaging), and characteristics of physician clinical documentation (readability of notes). KEY RESULTS: Among 882,575 unique portal users, those who accessed clinical notes (16.2%; N = 122,972) were younger, more racially homogenous (white), and less likely to be financially vulnerable. Compared with non-users, Notes users more frequently used the secure messaging feature on the portal (mean of 2.6 messages (SD 7.0) v. 0.87 messages (SD 3.3) in January-July 2013), but their higher use of secure messaging began prior to VA Notes implementation, and thus was not temporally related to the implementation. When comparing clinic visit rates pre- and post-implementation, Notes users had a small but significant increase in rate of 0.36 primary care clinic visits (2012 v. 2013) compared to portal users who did not view their Notes (p = 0.01). At baseline, the mean reading ease of primary care clinical notes was 53.8 (SD 10.1) and did not improve after implementation of VA Notes. CONCLUSIONS: VA Notes users were different than patients with portal access who did not view their notes online, and they had higher rates of healthcare service use prior to and after VA Notes implementation. Opportunities exist to improve clinical note access and readability.

Teaching Medical Students to Help Patients Manage Their Weight: Outcomes of an Eight-School Randomized Controlled Trial.

BACKGROUND: Given the rising rates of obesity there is a pressing need for medical schools to better prepare students for intervening with patients who have overweight or obesity and for prevention efforts. OBJECTIVE: To assess the effect of a multi-modal weight management curriculum on counseling skills for health behavior change. DESIGN: A pair-matched, group-randomized controlled trial (2015-2020) included students enrolled in eight U.S. medical schools randomized to receive either multi-modal weight management education (MME) or traditional weight management education (TE). SETTING/PARTICIPANTS: Students from the class of 2020 (N=1305) were asked to participate in an objective structured clinical examination (OSCE) focused on weight management counseling and complete pre and post surveys. A total of 70.1% of eligible students (N=915) completed the OSCE and 69.3% (N=904) completed both surveys. INTERVENTIONS: The MME implemented over three years included a web-based course, a role-play classroom exercise, a web-patient encounter with feedback, and an enhanced clerkship experience with preceptors trained in weight management counseling (WMC). Counseling focused on the 5As (Ask, Advise, Assess, Assist, Arrange) and patient-centeredness. MEASUREMENTS: The outcome was student 5As WMC skills assessed using an objective measure, an OSCE, scored using a behavior checklist, and a subjective measure, student self-reported skills for performing the 5As. RESULTS: Among MME students who completed two of three WMC components compared to those who completed none, exposure was significantly associated with higher OSCE scores and self-reported 5A skills. LIMITATIONS: Variability in medical schools requiring participation in the WMC curriculum. CONCLUSIONS: This trial revealed that medical students struggle with delivering weight management counseling to their patients who have overweight or obesity. Medical schools, though restrained in adding curricula, should incorporate should incorporate multiple WMC curricula components early in medical student education to provide knowledge and build confidence for supporting patients in developing individualized plans for weight management. NIH TRIAL REGISTRY NUMBER: R01-194787.

Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement.

BACKGROUND: Motivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Typically, motivational messaging systems have not actively sought feedback on each message, preventing a closer examination of the user-system engagement. This study assessed the granular user-system engagement around a recommender system (a new system that actively sought user feedback on each message to improve message selection) for promoting smoking cessation and the impact of engagement on cessation outcome. METHODS: We prospectively followed a cohort of current smokers enrolled to use the recommender system for 6 months. The system sent participants motivational messages to support smoking cessation every 3 days and used machine learning to incorporate user feedback (i.e., user's rating on the perceived influence of each message, collected on a 5-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement on perceiving the influence on quitting smoking) to improve the selection of the following message. We assessed user-system engagement by various metrics, including user response rate (i.e., the percent of times a user rated the messages) and the perceived influence of messages. We compared retention rates across different levels of user-system engagement and assessed the association between engagement and the 7-day point prevalence abstinence (missing outcome = smoking) by using multiple logistic regression. RESULTS: We analyzed data from 731 participants (13% Black; 73% women). The user response rate was 0.24 (SD = 0.34) and user-perceived influence was 3.76 (SD = 0.84). The retention rate positively increased with the user response rate (trend test P < 0.001). Compared with non-response, six-month cessation increased with the levels of response rates: low response rate (odds ratio [OR] = 1.86, 95% confidence interval [CI]: 1.07-3.23), moderate response rate (OR = 2.30, 95% CI: 1.36-3.88), high response rate (OR = 2.69, 95% CI: 1.58-4.58). The association between perceived message influence and the outcome showed a similar pattern. CONCLUSIONS: High user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation. TRIAL REGISTRATION: Registration Identifier: NCT03224520 . Registration date: July 21, 2017.

Experiences and perceptions of referrals to a community-based physical activity program for cancer survivors: a qualitative exploration.

BACKGROUND: Physical activity rates in cancer survivors continue to be low despite the known benefits and availability of evidence-based programs. LIVESTRONG at the Y is a national community-based physical activity program offered cost-free to cancer survivors, though is underutilized. We explored perceptions and experiences of staff and participating survivors to better understand program awareness, referrals and participation. METHODS: LIVESTRONG at the Y program staff [directors (n = 16), instructors (n = 4)] and survivors (n = 8) from 8 United States YMCAs took part in 30-min semi-structured phone interviews between March-May 2019. Interviews were digitally recorded, transcribed, and evaluated using a thematic analysis approach. RESULTS: Program staff themes included: 1) Program awareness should be further developed for both the general public and medical providers; 2) Strong relationships with medical providers increased program referrals; 3) Electronic referral systems between providers and LIVESTRONG would help to streamline the referral process; and 4) Bi-directional communication between program staff and medical providers is key to providing patient progress updates. Survivor themes included: 1) Survivors trust their medical team and the information they provide about physical activity; 2) Providers need to incorporate an action plan and referrals for survivors to be active once treatments are completed; and 3) Personal experiences of those who participated in LIVESTRONG resonate with survivors and increase participation. CONCLUSIONS: LIVESTRONG staff reported the need for an integrated electronic referral system and bi-directional communication with providers about participant progress. Survivors want physical activity education, electronic referrals and follow-up from their healthcare team, coupled with peer support from other survivors. Cancer care provider knowledge and electronic referrals during and after treatment may expedite and increase participation in this community-based program.

The Association Between Patient-reported Clinical Factors and 30-day Acute Care Utilization in Chronic Heart Failure.

BACKGROUND: Heart failure patients have high rates of repeat acute care use. Current efforts for risk prediction often ignore postdischarge data. OBJECTIVE: To identify postdischarge patient-reported clinical factors associated with repeat acute care use. RESEARCH DESIGN: In a prospective cohort study that followed patients with chronic heart failure for 30 days postdischarge, for 7 days after discharge (or fewer days if patients used acute care within 7 days postdischarge), patients reported health status, heart failure symptoms, medication management, knowledge of follow-up plans, and other issues using a daily interactive automatic phone call. SUBJECTS: A total of 156 patients who had responded to phone surveys. MEASURES: The outcome variable was dichotomous 30-day acute care use (rehospitalization or emergency department visit). We examined the association between each patient-reported issue and the outcome, using multivariable logistic regression to adjust for confounders. RESULTS: Patients were 63 years old (SD=12.4), with 51% African-American and 53% women. Within 30 days postdischarge, 30 (19%) patients used acute care. After adjustment, poor health status [odds ratio (OR)=3.53; 95% confidence interval (CI), 1.06-11.76], pain (OR=2.44; 95% CI, 1.02-5.84), and poor appetite (OR=3.05; 95% CI, 1.13-8.23) were positively associated with 30-day acute care utilization. Among 58 reports of pain in follow-up nursing notes, 39 (67%) were noncardiac, 2 (3%) were cardiac, and 17 (29%) were indeterminate. CONCLUSIONS: Patient-reported poor health status, pain, and poor appetite were positively associated with 30-day acute care utilization. These novel postdischarge markers require further study before incorporation into risk prediction to drive quality improvement efforts.

Secure Asynchronous Communication Between Smokers and Tobacco Treatment Specialists: Secondary Analysis of a Web-Assisted Tobacco Intervention in the QUIT-PRIMO and National Dental PBRN Networks.

BACKGROUND: Within a web-assisted tobacco intervention, we provided a function for smokers to asynchronously communicate with a trained tobacco treatment specialist (TTS). Previous studies have not attempted to isolate the effect of asynchronous counseling on smoking cessation. OBJECTIVE: This study aimed to conduct a semiquantitative analysis of TTS-smoker communication and evaluate its association with smoking cessation. METHODS: We conducted a secondary analysis of data on secure asynchronous communication between trained TTSs and a cohort of smokers during a 6-month period. Smokers were able to select their preferred TTS and message them using a secure web-based form. To evaluate whether the TTS used evidence-based practices, we coded messages using the Motivational Interviewing Self-Evaluation Checklist and Smoking Cessation Counseling (SCC) Scale. We assessed the content of messages initiated by the smokers by creating topical content codes. At 6 months, we assessed the association between smoking cessation and the amount of TTS use and created a multivariable model adjusting for demographic characteristics and smoking characteristics at baseline. RESULTS: Of the 725 smokers offered asynchronous counseling support, 33.8% (245/725) messaged the TTS at least once. A total of 1082 messages (TTSs: 565; smokers 517) were exchanged between the smokers and TTSs. The majority of motivational interviewing codes were those that supported client strengths (280/517, 54.1%) and promoted engagement (280/517, 54.1%). SCC code analysis showed that the TTS provided assistance to smokers if they were willing to quit (247/517, 47.8%) and helped smokers prepare to quit (206/517, 39.8%) and anticipate barriers (197/517, 38.1%). The majority of smokers' messages discussed motivations to quit (234/565, 41.4%) and current and past treatments (talking about their previous use of nicotine replacement therapy and medications; 201/565, 35.6%). The majority of TTS messages used behavioral strategies (233/517, 45.1%), offered advice on treatments (189/517, 36.5%), and highlighted motivations to quit (171/517, 33.1%). There was no association between the amount of TTS use and cessation. In the multivariable model, after adjusting for gender, age, race, education, readiness at baseline, number of cigarettes smoked per day at baseline, and the selected TTS, smokers messaging the TTS one or two times had a smoking cessation odds ratio (OR) of 0.8 (95% CI 0.4-1.4), and those that messaged the TTS more than two times had a smoking cessation OR of 1.0 (95% CI 0.4-2.3). CONCLUSIONS: Our study demonstrated the feasibility of using asynchronous counseling to deliver evidence-based counseling. Low participant engagement or a lack of power could be potential explanations for the nonassociation with smoking cessation. Future trials should explore approaches to increase participant engagement and test asynchronous counseling in combination with other approaches for improving the rates of smoking cessation.

Primary Care Providers' Opening of Time-Sensitive Alerts Sent to Commercial Electronic Health Record InBaskets.

BACKGROUND: Time-sensitive alerts are among the many types of clinical notifications delivered to physicians' secure InBaskets within commercial electronic health records (EHRs). A delayed alert review can impact patient safety and compromise care. OBJECTIVE: To characterize factors associated with opening of non-interruptive time-sensitive alerts delivered into primary care provider (PCP) InBaskets. DESIGN AND PARTICIPANTS: We analyzed data for 799 automated alerts. Alerts highlighted actionable medication concerns for older patients post-hospital discharge (2010-2011). These were study-generated alerts sent 3 days post-discharge to InBaskets for 75 PCPs across a multisite healthcare system, and represent a subset of all urgent InBasket notifications. MAIN MEASURES: Using EHR access and audit logs to track alert opening, we performed bivariate and multivariate analyses calculating associations between patient characteristics, provider characteristics, contextual factors at the time of alert delivery (number of InBasket notifications, weekday), and alert opening within 24 h. KEY RESULTS: At the time of alert delivery, the PCPs had a median of 69 InBasket notifications and had received a median of 379.8 notifications (IQR 295.0, 492.0) over the prior 7 days. Of the 799 alerts, 47.1% were opened within 24 h. Patients with longer hospital stays (>4 days) were marginally more likely to have alerts opened (OR 1.48 [95% CI 1.00-2.19]). Alerts delivered to PCPs whose InBaskets had a higher number of notifications at the time of alert delivery were significantly less likely to be opened within 24 h (top quartile >157 notifications: OR 0.34 [95% CI 0.18-0.61]; reference bottom quartile ≤42). Alerts delivered on Saturdays were also less likely to be opened within 24 h (OR 0.18 [CI 0.08-0.39]). CONCLUSIONS: The number of total InBasket notifications and weekend delivery may impact the opening of time-sensitive EHR alerts. Further study is needed to support safe and effective approaches to care team management of InBasket notifications.

Share2Quit: Online Social Network Peer Marketing of Tobacco Cessation Systems.

INTRODUCTION: Although technology-assisted tobacco interventions (TATIs) are effective, they are underused due to recruitment challenges. We tested whether we could successfully recruit smokers to a TATI using peer marketing through a social network (Facebook). METHODS: We recruited smokers on Facebook using online advertisements. These recruited smokers (seeds) and subsequent waves of smokers (peer recruits) were provided the Share2Quit peer recruitment Facebook app and other tools. Smokers were incentivized for up to seven successful peer recruitments and had 30 days to recruit from date of registration. Successful peer recruitment was defined as a peer recruited smoker completing the registration on the TATI following a referral. Our primary questions were (1) whether smokers would recruit other smokers and (2) whether peer recruitment would extend the reach of the intervention to harder-to-reach groups, including those not ready to quit and minority smokers. RESULTS: Overall, 759 smokers were recruited (seeds: 190; peer recruits: 569). Fifteen percent (n = 117) of smokers successfully recruited their peers (seeds: 24.7%; peer recruits: 7.7%) leading to four recruitment waves. Compared to seeds, peer recruits were less likely to be ready to quit (peer recruits 74.2% vs. seeds 95.1%), more likely to be male (67.1% vs. 32.9%), and more likely to be African American (23.8% vs. 10.8%) (p < .01 for all comparisons). CONCLUSIONS: Peer marketing quadrupled our engaged smokers and enriched the sample with not-ready-to-quit and African American smokers. Peer recruitment is promising, and our study uncovered several important challenges for future research. IMPLICATIONS: This study demonstrates the successful recruitment of smokers to a TATI using a Facebook-based peer marketing strategy. Smokers on Facebook were willing and able to recruit other smokers to a TATI, yielding a large and diverse population of smokers.

Computer Administered Safety Planning for Individuals at Risk for Suicide: Development and Usability Testing.

BACKGROUND: Safety planning is a brief intervention that has become an accepted practice in many clinical settings to help prevent suicide. Even though it is quick compared to other approaches, it frequently requires 20 min or more to complete, which can impede adoption. A self-administered, Web-based safety planning application could potentially reduce clinician time, help promote standardization and quality, and provide enhanced ability to share the created plan. OBJECTIVE: The aim of this study was to design, build, and test the usability of a Web-based, self-administered safety planning application. METHODS: We employed a user-centered software design strategy led by a multidisciplinary team. The application was tested for usability with a target sample of suicidal patients. Detailed observations, structured usability ratings, and Think Aloud procedures were used. Suicidal ideation intensity and perceived ability to cope were assessed pre-post engagement with the Web application. RESULTS: A total of 30 participants were enrolled. Usability ratings were generally strong, and all patients successfully built a safety plan. However, the completeness of the safety plan varied. The mean number of steps completed was 5.5 (SD 0.9) out of 6, with 90% (27/30) of participants completing at least 5 steps and 67% (20/30) completing all 6 steps. Some safety planning steps were viewed as inapplicable to some individuals. Some confusion in instructions led to modifications to improve understandability of each step. Ratings of suicide intensity after completion of the application were significantly lower than preratings, pre: mean 5.11 (SD 2.9) versus post: mean 4.46 (SD 3.0), t27=2.49, P=.02. Ratings of ability to cope with suicidal thoughts after completion of the application were higher than preratings, with the difference approaching statistical significance, pre: mean 5.93 (SD 2.9), post: mean 6.64 (SD 2.4), t27=-2.03, P=.05. CONCLUSIONS: We have taken the first step toward identifying the components needed to maximize usability of a self-administered, Web-based safety planning application. Results support initial consideration of the application as an adjunct to clinical contact. This allows for the clinician or other personnel to provide clarification, when needed, to help the patient build the plan, and to help review and revise the draft.

Impact of a Collective Intelligence Tailored Messaging System on Smoking Cessation: The Perspect Randomized Experiment.

BACKGROUND: Outside health care, content tailoring is driven algorithmically using machine learning compared to the rule-based approach used in current implementations of computer-tailored health communication (CTHC) systems. A special class of machine learning systems ("recommender systems") are used to select messages by combining the collective intelligence of their users (ie, the observed and inferred preferences of users as they interact with the system) and their user profiles. However, this approach has not been adequately tested for CTHC. OBJECTIVE: Our aim was to compare, in a randomized experiment, a standard, evidence-based, rule-based CTHC (standard CTHC) to a novel machine learning CTHC: Patient Experience Recommender System for Persuasive Communication Tailoring (PERSPeCT). We hypothesized that PERSPeCT will select messages of higher influence than our standard CTHC system. This standard CTHC was proven effective in motivating smoking cessation in a prior randomized trial of 900 smokers (OR 1.70, 95% CI 1.03-2.81). METHODS: PERSPeCT is an innovative hybrid machine learning recommender system that selects and sends motivational messages using algorithms that learn from message ratings from 846 previous participants (explicit feedback), and the prior explicit ratings of each individual participant. Current smokers (N=120) aged 18 years or older, English speaking, with Internet access were eligible to participate. These smokers were randomized to receive either PERSPeCT (intervention, n=74) or standard CTHC tailored messages (n=46). The study was conducted between October 2014 and January 2015. By randomization, we compared daily message ratings (mean of smoker ratings each day). At 30 days, we assessed the intervention's perceived influence, 30-day cessation, and changes in readiness to quit from baseline. RESULTS: The proportion of days when smokers agreed/strongly agreed (daily rating ≥4) that the messages influenced them to quit was significantly higher for PERSPeCT (73%, 23/30) than standard CTHC (44%, 14/30, P=.02). Among less educated smokers (n=49), this difference was even more pronounced for days strongly agree (intervention: 77%, 23/30; comparison: 23%, 7/30, P<.001). There was no significant difference in the frequency which PERSPeCT randomized smokers agreed or strongly agreed that the intervention influenced them to quit smoking (P=.07) and use nicotine replacement therapy (P=.09). Among those who completed follow-up, 36% (20/55) of PERSPeCT smokers and 32% (11/34) of the standard CTHC group stopped smoking for one day or longer (P=.70). CONCLUSIONS: Compared to standard CTHC with proven effectiveness, PERSPeCT outperformed in terms of influence ratings and resulted in similar cessation rates. CLINICALTRIAL: Clinicaltrials.gov NCT02200432; https://clinicaltrials.gov/ct2/show/NCT02200432 (Archived by WebCite at http://www.webcitation.org/6lEJY1KEd).

Health Information Brokers in the General Population: An Analysis of the Health Information National Trends Survey 2013-2014.

BACKGROUND: Health information exchanged between friends or family members can influence decision making, both for routine health questions and for serious health issues. A health information broker is a person to whom friends and family turn for advice or information on health-related topics. Characteristics and online behaviors of health information brokers have not previously been studied in a national population. OBJECTIVE: The objective of this study was to examine sociodemographic characteristics, health information seeking behaviors, and other online behaviors among health information brokers. METHODS: Data from the Health Information National Trends Survey (2013-2014; n=3142) were used to compare brokers with nonbrokers. Modified Poisson regression was used to examine the relationship between broker status and sociodemographics and online information seeking. RESULTS: Over half (54.8%) of the respondents were consulted by family or friends for advice or information on health topics (ie, they acted as health information brokers). Brokers represented 54.1% of respondents earning <$20,000 yearly and 56.5% of respondents born outside the United States. Women were more likely to be brokers (PR 1.34, 95% CI 1.23-1.47) as were those with education past high school (PR 1.42, CI 1.22-1.65). People aged ≥75 were less likely to be brokers as compared to respondents aged 35-49 (PR 0.81, CI 0.67-0.99). Brokers used the Internet more frequently for a variety of online behaviors such as seeking health information, creating and sharing online content, and downloading health information onto a mobile device; and also reported greater confidence in obtaining health information online. CONCLUSIONS: More than 50% of adults who responded to this national survey, including those with low income and those born abroad, were providing health information or advice to friends and family. These individuals may prove to be effective targets for initiatives supporting patient engagement and disease management, and may also be well-positioned within their respective social networks to propagate health messages.

Collective-Intelligence Recommender Systems: Advancing Computer Tailoring for Health Behavior Change Into the 21st Century.

BACKGROUND: What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior theories. In collective-intelligence recommender systems (hereafter recommender systems) used by Web 2.0 companies (eg, Netflix and Amazon), machine learning algorithms combine user profiles and continuous feedback ratings of content (from themselves and other users) to empirically tailor content. Augmenting current theory-based CTHC with empirical recommender systems could be evaluated as the next frontier for CTHC. OBJECTIVE: The objective of our study was to uncover barriers and challenges to using recommender systems in health promotion. METHODS: We conducted a focused literature review, interviewed subject experts (n=8), and synthesized the results. RESULTS: We describe (1) limitations of current CTHC systems, (2) advantages of incorporating recommender systems to move CTHC forward, and (3) challenges to incorporating recommender systems into CTHC. Based on the evidence presented, we propose a future research agenda for CTHC systems. CONCLUSIONS: We promote discussion of ways to move CTHC into the 21st century by incorporation of recommender systems.

An observational study of social and emotional support in smoking cessation Twitter accounts: content analysis of tweets.

BACKGROUND: Smoking continues to be the number one preventable cause of premature death in the United States. While evidence for the effectiveness of smoking cessation interventions has increased rapidly, questions remain on how to effectively disseminate these findings. Twitter, the second largest online social network, provides a natural way of disseminating information. Health communicators can use Twitter to inform smokers, provide social support, and attract them to other interventions. A key challenge for health researchers is how to frame their communications to maximize the engagement of smokers. OBJECTIVE: Our aim was to examine current Twitter activity for smoking cessation. METHODS: Active smoking cessation related Twitter accounts (N=18) were identified. Their 50 most recent tweets were content coded using a schema adapted from the Roter Interaction Analysis System (RIAS), a theory-based, validated coding method. Using negative binomial regression, the association of number of followers and frequency of individual tweet content at baseline was assessed. The difference in followership at 6 months (compared to baseline) to the frequency of tweet content was compared using linear regression. Both analyses were adjusted by account type (organizational or not organizational). RESULTS: The 18 accounts had 60,609 followers at baseline and 68,167 at 6 months. A total of 24% of tweets were socioemotional support (mean 11.8, SD 9.8), 14% (mean 7, SD 8.4) were encouraging/engagement, and 62% (mean 31.2, SD 15.2) were informational. At baseline, higher frequency of socioemotional support and encouraging/engaging tweets was significantly associated with higher number of followers (socioemotional: incident rate ratio [IRR] 1.09, 95% CI 1.02-1.20; encouraging/engaging: IRR 1.06, 95% CI 1.00-1.12). Conversely, higher frequency of informational tweets was significantly associated with lower number of followers (IRR 0.95, 95% CI 0.92-0.98). At 6 months, for every increase by 1 in socioemotional tweets, the change in followership significantly increased by 43.94 (P=.027); the association was slightly attenuated after adjusting by account type and was not significant (P=.064). CONCLUSIONS: Smoking cessation activity does exist on Twitter. Preliminary findings suggest that certain content strategies can be used to encourage followership, and this needs to be further investigated.

Vaping Cessation Support Recommendations from Adolescents Who Vape: A Qualitative Study.

Background: Youth vaping is an epidemic, being more prevalent than any other tobacco use. To inform cessation interventions, we explored what adolescents perceive to be their reasons for quitting and strategies to help in their quit efforts. Method: Semi-structured interviews were conducted with a convenience sample of 11 adolescents reporting vaping in the past 90 days and recruited from a high school in Massachusetts. Interviews were transcribed, and dual coded. Inductive thematic analysis was employed and thematic summaries were prepared. Results: Reasons adolescents reported for quitting included: cost; experiencing "nic-sick" from nicotine withdrawal or excess intake; negative impacts on mood, concentration, or health; and experiencing symptoms of nicotine dependence. Nearly all tried to quit multiple times. Barriers to quitting included: exposure to vaping; access to vape products; stress; and "cool" new products or flavors. Quit strategies included: avoiding others vaping; seeking social support to quit; addressing peer pressure to continue vaping; learning successful quit strategies from peers; and using distraction strategies or alternatives to vaping. Conclusion: Many adolescents who vape want to quit and most have tried multiple times. Interventions need to engage adolescents with varying reasons to quit, barriers, and quit strategy preferences. Clinical Trial Registration: This study is registered through ClinicalTrials.gov. The trial registration number is NCT05140915. The trial registration date is 11/18/2021.

Stopping use of E-cigarettes and smoking combustible cigarettes: findings from a large longitudinal digital smoking cessation intervention study in the United States.

OBJECTIVE: Digital interventions have been widely implemented to promote tobacco cessation. However, implementations of these interventions have not yet considered how participants' e-cigarette use may influence their quitting outcomes. We explored the association of e-cigarette use and quitting smoking within the context of a study testing a digital tobacco cessation intervention among individuals in the United States who were 18 years and older, smoked combustible cigarettes, and enrolled in the intervention between August 2017 and March 2019. RESULTS: We identified four e-cigarette user groups (n = 990) based on the participants' baseline and six-month e-cigarette use (non-users, n = 621; recently started users, n = 60; sustained users, n = 187; recently stopped users, n = 122). A multiple logistic regression was used to estimate the adjusted odds ratios (AOR) of six-month quit outcome and the e-cigarette user groups. Compared to e-cigarette non-users, the odds of quitting smoking were significantly higher among recently stopped users (AOR = 1.68, 95% CI [1.06, 2.67], p = 0.03). Participants who were most successful at quitting combustible cigarettes also stopped using e-cigarettes at follow-up, although many sustained using both products. Findings suggest that digital tobacco cessation interventions may carefully consider how to promote e-cigarette use cessation among participants who successfully quit smoking. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT03224520 (July 21, 2017).