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We examined the feasibility of using a remotely manoeuverable robot to make home hazard assessments for fall prevention. We employed use-case simulations to compare robot assessments with in-person assessments. We screened the homes of nine elderly patients (aged 65 years or more) for fall risks using the HEROS screening assessment. We also assessed the participants' perspectives of the remotely-operated robot in a survey. The nine patients had a median Short Blessed Test score of 8 (interquartile range, IQR 2-20) and a median Life-Space Assessment score of 46 (IQR 27-75). Compared to the in-person assessment (mean = 4.2 hazards identified per participant), significantly more home hazards were perceived in the robot video assessment (mean = 7.0). Only two checklist items (adequate bedroom lighting and a clear path from bed to bathroom) had more than 60% agreement between in-person and robot video assessment. Participants were enthusiastic about the robot and did not think it violated their privacy. The study found little agreement between the in-person and robot video hazard assessments. However, it identified several research questions about how to best use remotely-operated robots. [ABSTRACT FROM PUBLISHER]

Background: We are testing web-based respondent-driven sampling (RDS) chain referrals to recruit smokers to the Decide2Quit.org (D2Q) web-assisted tobacco intervention. Methods: Using an online survey of smokers, we assessed the potential of recruiting 1200 smokers in 9 months using RDS chain referrals. RDS is a complex sample design, and many factors can influence its success. We conducted simulations to determine the design of optimal RDS chains. Results: Smokers (n=48) were mostly female (72%) and between ages 30-60 (82%). Estimation of smokers in their network: 1-5 (40%), 6-10 (24%), and 10-20 (22%), with mean number of intimate family (2.2, SD=2.1) and close friend smokers (3.7, SD=3.8). Most smokers (82%) were willing to refer to D2Q and thought their friends (mean=5.0, SD=4.4, range=0-20) would be open to referral. Simulations suggested that with a quota of 3 and 10 seeds, 99.9% of the sample would be achieved in 107 days if the acceptance probability was 0.5. Acceptance probability of 25% would necessitate an increased quota. Conclusions: Our study suggests that it is possible to recruit smokers using RDS. [ABSTRACT FROM AUTHOR]

The widespread adoption of cell phones and other mobile platforms represent an opportunity to extend the benefits of personalized point-of-care healthcare applications to providers and patients in the developing world. However, the challenges facing the effective deployment of mobile health care applications are complex; thus, requiring a scalable, flexible, and configurable approach. A conceptual framework based on service-oriented-architecture is proposed to address the challenges of developing and deploying mobile health care applications. A particular emphasis of the framework is a service-agent-modeling-based personalized process support that is needed to support the diverse needs of the users. [ABSTRACT FROM AUTHOR]

BackgroundSmoking 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. ObjectiveOur aim was to examine current Twitter activity for smoking cessation. MethodsActive 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). ResultsThe 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). ConclusionsSmoking 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.

IntroductionSmoking is the most preventable cause of death. Although effective, Web-assisted tobacco interventions are underutilized and recruitment is challenging. Understanding who participates in Web-assisted tobacco interventions may help in improving recruitment. ObjectivesTo understand characteristics of smokers participating in a Web-assisted tobacco intervention (Decide2Quit.org). MethodsIn addition to the typical Google advertisements, we expanded Decide2Quit.org recruitment to include referrals from medical and dental providers. We assessed how the expanded recruitment of smokers changed the users’ characteristics, including comparison with a population-based sample of smokers from the national Behavioral Risk Factors Surveillance Survey (BRFSS). Using a negative binomial regression, we compared demographic and smoking characteristics by recruitment source, in particular readiness to quit and association with subsequent Decide2Quit.org use. ResultsThe Decide2Quit.org cohort included 605 smokers; the 2010 BRFSS dataset included 69,992. Compared to BRFSS smokers, a higher proportion of Decide2Quit.org smokers were female (65.2% vs 45.7%, P=.001), over age 35 (80.8% vs 67.0%, P=.001), and had some college or were college graduates (65.7% vs 45.9%, P=.001). Demographic and smoking characteristics varied by recruitment; for example, a lower proportion of medical- (22.1%) and dental-referred (18.9%) smokers had set a quit date or had already quit than Google smokers (40.1%, P

A conference paper on a randomized controlled trial which examined the point-of care referrals of smokers by community-based dental practices to an interactive, tailored patient education website is presented. The paper concluded that the "ReferASmoker" tool is easy to use and offers useful resources to assist with tobacco control services.

Background: Computer-tailored health communication (CTHC), a widely used strategy to increase the effectiveness of smoking cessation interventions, is focused on selecting the best messages for an individual. More recently, CTHC interventions have been tested using contextual information such as participants' current stress or location to adapt message selection. However, mood has not yet been used in CTCH interventions and may increase their effectiveness., Objective: This study aims to examine the association of mood and smoking cessation message effectiveness among adults who currently smoke cigarettes., Methods: In January 2022, we recruited a web-based convenience sample of adults who smoke cigarettes (N=615; mean age 41.13 y). Participants were randomized to 1 of 3 mood conditions (positive, negative, or neutral) and viewed pictures selected from the International Affective Picture System to induce an emotional state within the assigned condition. Participants then viewed smoking cessation messages with topics covering five themes: (1) financial costs or rewards, (2) health, (3) quality of life, (4) challenges of quitting, and (5) motivation or reasons to quit. Following each message, participants completed questions on 3 constructs: message receptivity, perceived relevance, and their motivation to quit. The process was repeated 30 times. We used 1-way ANOVA to estimate the association of the mood condition on these constructs, controlling for demographics, cigarettes per day, and motivation to quit measured during the pretest. We also estimated the association between mood and outcomes for each of the 5 smoking message theme categories., Results: There was an overall statistically significant effect of the mood condition on the motivation to quit outcome (P=.02) but not on the message receptivity (P=.16) and perceived relevance (P=.86) outcomes. Participants in the positive mood condition reported significantly greater motivation to quit compared with those in the negative mood condition (P=.005). Participants in the positive mood condition reported higher motivation to quit after viewing smoking cessation messages in the financial (P=.03), health (P=.01), quality of life (P=.04), and challenges of quitting (P=.03) theme categories. We also compared each mood condition and found that participants in the positive mood condition reported significantly greater motivation to quit after seeing messages in the financial (P=.01), health (P=.003), quality of life (P=.01), and challenges of quitting (P=.01) theme categories than those in the negative mood condition., Conclusions: Our findings suggest that considering mood may be important for future CTHC interventions. Because those in the positive mood state at the time of message exposure were more likely to have greater quitting motivations, smoking cessation CTHC interventions may consider strategies to help improve participants' mood when delivering these messages. For those in neutral and negative mood states, focusing on certain message themes (health and motivation to quit) may be more effective than other message themes., (©Donghee N Lee, Rajani S Sadasivam, Elise M Stevens. Originally published in JMIR Formative Research (https://formative.jmir.org), 22.12.2023.)

Background: A Health Equity Task Force (HETF) of members from seven Centers funded by the National Cancer Institute's (NCI) Implementation Science in Cancer Control Centers (ISC 3 ) network sought to identify case examples of how Centers were applying a focus on health equity in implementation science to inform future research and capacity-building efforts., Methods: HETF members at each ISC 3 collected information on how health equity was conceptualized, operationalized, and addressed in initial research and capacity-building efforts across the seven ISC 3 Centers funded in 2019-2020. Each Center completed a questionnaire assessing five health equity domains central to implementation science (e.g., community engagement; implementation science theories, models, and frameworks (TMFs); and engaging underrepresented scholars). Data generated illustrative examples from these five domains., Results: Centers reported a range of approaches focusing on health equity in implementation research and capacity-building efforts, including (1) engaging diverse community partners/settings in making decisions about research priorities and projects; (2) applying health equity within a single TMF applied across projects or various TMFs used in specific projects; (3) evaluating health equity in operationalizing and measuring health and implementation outcomes; (4) building capacity for health equity-focused implementation science among trainees, early career scholars, and partnering organizations; and (5) leveraging varying levels of institutional resources and efforts to engage, include, and support underrepresented scholars., Conclusions: Examples of approaches to integrating health equity across the ISC 3 network can inform other investigators and centers' efforts to build capacity and infrastructure to support growth and expansion of health equity-focused implementation science., Competing Interests: Dr. Beidas is principal at Implementation Science & Practice, LLC. She receives royalties from Oxford University Press, consulting fees from United Behavioral Health and OptumLabs, and serves on the advisory boards for Optum Behavioral Health, AIM Youth Mental Health Foundation, and the Klingenstein Third Generation Foundation outside of the submitted work. All other authors declare no relevant financial or non-financial interests., (© The Author(s) 2023.)

Introduction: Understanding adolescent perceptions of vaping and roles it plays in their lives is needed to design effective interventions to help adolescents quit. We explored vaping experiences of 11 adolescents from initiation through quit attempts., Methods: A convenience sample of students who vaped in the last 90 days was recruited from one suburban high school in Massachusetts. Qualitative interviews were transcribed and coded. An inductive thematic analysis approach was employed. Areas of agreement and range of responses in code reports were summarized., Results: Eleven open-ended semi-structured interviews were conducted (mean = 32.5 minutes each). Vaping initiation often occurred when socializing with friends who also supplied vaping devices. Vaping was "something to do" and new flavors engaged adolescents further. Solitary activities coupled with vaping included video gaming, getting ready for school, talking on the phone, or studying. Peak hours for vaping included morning, before and after school, before parents returned from work, and after parents went to bed. Several vaped to address anxiety/stress. For some, anxiety control was a main reason for vaping. Participants were concerned about health effects and nicotine dependence. Cost and health effects were drivers of quitting. Quit strategies relied on willpower and distraction., Conclusions: Peers have powerful influences on the initiation and maintenance of adolescent vaping. Vaping habits can become routinized into adolescent lives. Addiction is a concern although nicotine's anxiolytic effects were valued by many. Social connection was enhanced by communal vaping, sharing, and common vernacular, secrecy and rule-breaking. We describe the context in which adolescents vape nicotine, their reasons for vaping, and reasons to quit. This information can inform the development of interventions to better address adolescents' triggers to vape, and social and psychosocial barriers to quitting. Our findings suggest a desire to quit vaping but a limited awareness of quitting strategies., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Background: After hospital discharge, patients with acute coronary syndrome (ACS) often experience symptoms that prompt them to seek acute medical attention. Early evaluation of postdischarge symptoms by health care providers may reduce unnecessary acute care utilization. However, hospital-initiated follow-up encounters are insufficient for timely detection and assessment of symptoms. While digital health tools can help address this issue, little is known about the intention to use such tools in ACS patients., Objective: This study aimed to assess ACS patients' intention to use digital health apps that support postdischarge symptom monitoring by health care providers and identify patient-perceived facilitators and barriers to app use., Methods: Using email invitations or phone calls, we recruited ACS patients discharged from a central Massachusetts health care system between December 2020 and April 2021, to participate in the study. Surveys were delivered online or via phone to individual participants. Demographics and access to technology were assessed. The intention to use a symptom monitoring app was assessed using 5-point Likert-type (from strongly agree to strongly disagree) items, such as "If this app were available to me, I would use it." Responses were compared across demographic subgroups and survey delivery methods. Two open-ended questions assessed perceived facilitators and barriers to app use, with responses analyzed using qualitative content analysis., Results: Among 100 respondents (response rate 8.1%), 45 (45%) completed the survey by phone. The respondents were on average 68 years old (SD 13 years), with 90% (90/100) White, 39% (39/100) women, and 88% (88/100) having access to the internet or a mobile phone. Most participants (65/100, 65%) agreed or strongly agreed that they would use the app, among which 53 (82%) would use the app as often as possible. The percentage of participants with the intention to use the app was 75% among those aged 65-74 years and dropped to 44% among those older than 75 years. The intention to use was higher in online survey respondents (vs phone survey respondents; odds ratio 3.07, 95% CI 1.20-7.88) after adjusting for age and access to technology. The analysis of open-ended questions identified the following 4 main facilitators (motivations): (1) easily reaching providers, (2) accessing or providing information, (3) quickly reaching providers, and (4) consulting providers for symptoms, and the following 4 main barriers: (1) privacy/security concerns, (2) uncomfortable using technology, (3) user-unfriendly app interface, and (4) preference for in-person/phone care., Conclusions: There was a strong intention to use a symptom monitoring app postdischarge among ACS patients. However, this intent decreased in patients older than 75 years. The survey identified barriers related to technology use, privacy/security, and the care delivery mode. Further research is warranted to determine if such intent translates into app use, and better symptom management and health care quality., (©Jinying Chen, Jessica G Wijesundara, Gabrielle E Enyim, Lisa M Lombardini, Ben S Gerber, Thomas K Houston, Rajani S Sadasivam. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 07.03.2022.)

Background: Although African Americans have the lowest rates of smoking onset and progression to daily smoking, they are less likely to achieve long-term cessation. Interventions tailored to promote use of cessation resources in African American individuals who smoke are needed. In our past work, we demonstrated the effectiveness of a technology-assisted peer-written message intervention for increasing smoking cessation in non-Hispanic White smokers. In this formative study, we have adapted this intervention to be specific for African American smokers., Objective: We aimed to report on the qualitative analysis of messages written by African American current and former smokers for their peers in response to hypothetical scenarios of smokers facing cessation challenges., Methods: We recruited African American adult current and former smokers (n=41) via ResearchMatch between April 2017 and November 2017. We asked participants to write motivational messages for their peers in response to smoking-related hypothetical scenarios. We also collected data on sociodemographic factors and smoking characteristics. Thematic analysis was conducted to identify cessation strategies suggested by the study participants., Results: Among the study participants, 60% (25/41) were female. Additionally, more than half (23/41, 56%) were thinking about quitting, 29% (12/41) had set a quit date, and 27% (11/41) had used electronic cigarettes in the past 30 days. Themes derived from the qualitative analysis of peer-written messages were (1) behavioral strategies, (2) seeking help, (3) improvements in quality of life, (4) attitudes and expectations, and (5) mindfulness/religious or spiritual practices. Under the behavioral strategies theme, distraction strategies were the most frequently suggested strategies (referenced 84 times in the 318 messages), followed by use of evidence-based treatments/cessation strategies. Within the seeking help theme, subthemes included seeking help or support from family/friends or close social networks (referenced 56 times) and health care professionals (referenced 22 times). The most frequent subthemes that emerged from improvements in the quality of life theme included improving one's health (referenced 22 times) and quality of life (referenced 21 times). Subthemes that emerged from the attitude and expectations theme included practicing positive self-talk (referenced 27 times), autonomy/independence from the smoking habit (referenced six times), and financial cost of smoking (referenced five times). The two subthemes that emerged from the mindfulness/religious or spiritual practices theme were use of self-awareness techniques (referenced 36 times) and religious or spiritual practices to cope (referenced 13 times)., Conclusions: Our approach to adapt a prior peer-message intervention to African American smokers yielded a set of evidence-based messages that may be suitable for smokers at all phases of motivation to quit (ready to quit or not ready to quit). In future research, we plan to assess the impact of texting these messages to African American smokers in a smoking cessation trial., (©Catherine S Nagawa, Jamie M Faro, Anitha J Menon, Mayuko Ito Fukunaga, Jessica H Williams, Dalton Mourao, Oluwabunmi M Emidio, Maryann Davis, Lori Pbert, Sarah L Cutrona, Thomas K Houston, Rajani S Sadasivam. Originally published in JMIR Formative Research (https://formative.jmir.org), 30.04.2021.)

Background: COVID-19 has had significant health-related and behavioral impacts worldwide. Cancer survivors (hereafter referred to as "survivors") are particularly prone to behavioral changes and are encouraged to be more vigilant and observe stricter social distancing measures., Objective: We explored (1) changes in physical activity and sedentary behaviors since the onset of COVID-19, along with changes in mental health status, and (2) alternative strategies to support survivors' physical activity and social health during and after COVID-19, along with the role of digital health in such strategies., Methods: A questionnaire was distributed among survivors participating (currently or previously) in the community-based physical activity program LIVESTRONG at the Young Men's Christian Association (YMCA), from 3 sites outside an urban area in Massachusetts. Questions addressed pre-COVID-19 vs current changes in physical activity and sedentary behavior. Anxiety and depression were assessed using the 2-item Generalized Anxiety Disorder scale (GAD-2) and 2-item Patient Health Questionnaire (PHQ-2), and scores ≥3 indicated a clinical diagnosis of anxiety or depression, respectively. Digital health preferences were assessed through closed-ended questions. Open-ended responses addressing other preferences for physical activity programs and social support were analyzed, coded, and categorized into themes., Results: Among 61 participants (mean age 62 [SD 10.4] years; females: 51/61 [83.6%]), 67.2% (n=41) reported decreased physical activity and 67.2% (n=41) reported prolonged sitting times since the onset of COVID-19. Further, 24.6% (n=15) and 26.2% (n=16) met the GAD-2 and PHQ-2 criteria for clinical anxiety and depression, respectively. All participants owned a cellphone; 90% (n=54) owned a smartphone. Preferences for physical activity programs (n=28) included three themes: (1) use of digital or remote platforms (Zoom, other online platforms, and video platforms), (2) specific activities and locations (eg, outdoor activities, walking, gardening, biking, and physical activities at the YMCA and at senior centers), and (3) importance of social support regardless of activity type (eg, time spent with family, friends, peers, or coaches). The survey revealed a mean score of 71.8 (SD 21.4; scale 0-100) for the importance of social support during physical activity programs. Social support preferences (n=15) revealed three themes: (1) support through remote platforms (eg, texting, Zoom, phone calls, emails, and Facebook), (2) tangible in-person support (YMCA and senior centers), and (3) social support with no specific platform (eg, small gatherings and family or friend visits)., Conclusions: Physical activity and mental health are critical factors for the quality of life of survivors, and interventions tailored to their activity preferences are necessary. Digital or remote physical activity programs with added social support may help address the ongoing needs of survivors during and after the pandemic., (©Jamie M Faro, Kristin M Mattocks, Catherine S Nagawa, Stephenie C Lemon, Bo Wang, Sarah L Cutrona, Rajani S Sadasivam. Originally published in JMIR Cancer (http://cancer.jmir.org), 03.02.2021.)

Background: The Patient Experience Recommender System for Persuasive Communication Tailoring (PERSPeCT) is a machine learning recommender system with a database of messages to motivate smoking cessation. PERSPeCT uses the collective intelligence of users (ie, preferences and feedback) and demographic and smoking profiles to select motivating messages. PERSPeCT may be more beneficial for tailoring content to minority groups influenced by complex, personally relevant factors., Objective: The objective of this study was to describe and evaluate the use of PERSPeCT in African American people who smoke compared with white people who smoke., Methods: Using a quasi-experimental design, we compared African American people who smoke with a historical cohort of white people who smoke, who both received up to 30 emailed tailored messages over 65 days. People who smoke rated the daily message in terms of perceived influence on quitting smoking for 30 days. Our primary analysis compared daily message ratings between the two groups using a t test. We used a logistic model to compare 30-day cessation between the two groups and adjusted for covariates., Results: The study included 119 people who smoke (African Americans, 55/119; whites, 64/119). At baseline, African American people who smoke were significantly more likely to report allowing smoking in the home (P=.002); all other characteristics were not significantly different between groups. Daily mean ratings were higher for African American than white people who smoke on 26 of the 30 days (P<.001). Odds of quitting as measured by 30-day cessation were significantly higher for African Americans (odds ratio 2.3, 95% CI 1.04-5.53; P=.03) and did not change after adjusting for allowing smoking at home., Conclusions: Our study highlighted the potential of using a recommender system to personalize for African American people who smoke., Trial Registration: ClinicalTrials.gov NCT02200432; https://clinicaltrials.gov/ct2/show/NCT02200432., International Registered Report Identifier (irrid): RR2-10.2196/jmir.6465., (©Jamie M Faro, Catherine S Nagawa, Jeroan A Allison, Stephenie C Lemon, Kathleen M Mazor, Thomas K Houston, Rajani S Sadasivam. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 27.04.2020.)

Background: Smoking is the leading cause of preventable death and disease, yet implementation of smoking cessation in inpatient settings is inconsistent. The Technology Inpatient Program for Smokers (TIPS) is an implementation program designed to reach smokers with a mobile health (mHealth) intervention using stakeholder-supported strategies., Objective: The purpose of this study was to determine the impact of the TIPS implementation strategies on smoker-level engagement of the mHealth intervention during care transition., Methods: We examined varying intensities (passive motivational posters only and posters + active nurse-led facilitation) of TIPS strategies on four hospital units located in two sites. Unit-level and smoker-level adoption was monitored during active implementation (30 weeks) and sustainability follow-up (30 weeks). Process measures reflecting the reach, effectiveness, adoption, implementation, maintenance (RE-AIM) framework, stakeholder reported adaptations of strategies, and formative evaluation data were collected and analyzed., Results: For our smoker-level reach, 103 smokers signed up for the mHealth intervention in-hospital, with minimal decline during sustainability follow-up. While posters + nurse facilitation did not lead to higher reach than posters alone during active implementation (27 vs 30 signed up), it did lead to higher engagement of smokers (85.2% vs 73.3% completion of the full 2-week intervention). TIPS strategy adoption and fidelity varied by unit, including adoption of motivational posters (range: weeks 1 and 5), fidelity of posters (0.4% to 16.2% of posters missing per unit weekly) and internal facilitation of nurse training sessions (average of 2 vs 7.5 by site). Variable maintenance costs of the program totaled US $6.63 (US $683.28/103) per smoker reached. Reported family-member facilitation of mHealth sign-up was an observation of unintended behavior., Conclusions: TIPS is a feasible and low-cost implementation program that successfully engages smokers in an mHealth intervention and sustains engagement after discharge. Further testing of nurse facilitation and expanding reach to patient family and friends as an implementation strategy is needed., (©Amanda C Constance Blok, Rajani S Sadasivam, Timothy P Hogan, Angela Patterson, Nicole Day, Thomas K Houston. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 04.10.2019.)

Commercial mobile apps for health behavior change are flourishing in the marketplace, but little evidence exists to support their use. This paper summarizes methods for evaluating the content, usability, and efficacy of commercially available health apps. Content analyses can be used to compare app features with clinical guidelines, evidence-based protocols, and behavior change techniques. Usability testing can establish how well an app functions and serves its intended purpose for a target population. Observational studies can explore the association between use and clinical and behavioral outcomes. Finally, efficacy testing can establish whether a commercial app impacts an outcome of interest via a variety of study designs, including randomized trials, multiphase optimization studies, and N-of-1 studies. Evidence in all these forms would increase adoption of commercial apps in clinical practice, inform the development of the next generation of apps, and ultimately increase the impact of commercial apps., (©Danielle E Jake-Schoffman, Valerie J Silfee, Molly E Waring, Edwin D Boudreaux, Rajani S Sadasivam, Sean P Mullen, Jennifer L Carey, Rashelle B Hayes, Eric Y Ding, Gary G Bennett, Sherry L Pagoto. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 18.12.2017.)

Background: Over the last several years there has been widespread development of medical data warehouses. Current data warehouses focus on individual cases, but lack the ability to identify family members that could be used for dyadic or familial research. Currently, the patient's family history in the medical record is the only documentation we have to understand the health status and social habits of their family members. Identifying familial linkages in a phenotypic data warehouse can be valuable in cohort identification and in beginning to understand the interactions of diseases among families., Objective: The goal of the Familial, Associational, & Incidental Relationships (FAIR) initiative is to identify an index set of patients' relationships through elements in a data warehouse., Methods: Using a test set of 500 children, we measured the sensitivity and specificity of available linkage algorithm identifiers (eg, insurance identification numbers and phone numbers) and validated this tool/algorithm through a manual chart audit., Results: Of all the children, 52.4% (262/500) were male, and the mean age of the cohort was 8 years old (SD 5). Of the children, 51.6% (258/500) were identified as white in race. The identifiers used for FAIR were available for the majority of patients: insurance number (483/500, 96.6%), phone number (500/500, 100%), and address (497/500, 99.4%). When utilizing the FAIR tool and various combinations of identifiers, sensitivity ranged from 15.5% (62/401) to 83.8% (336/401), and specificity from 72% (71/99) to 100% (99/99). The preferred method was matching patients using insurance or phone number, which had a sensitivity of 72.1% (289/401) and a specificity of 94% (93/99). Using the Informatics for Integrating Biology and the Bedside (i2b2) warehouse infrastructure, we have now developed a Web app that facilitates FAIR for any index population., Conclusions: FAIR is a valuable research and clinical resource that extends the capabilities of existing data warehouses and lays the groundwork for family-based research. FAIR will expedite studies that would otherwise require registry or manual chart abstraction data sources.

Background: Smoking is the number one preventable cause of death in the United States. Effective Web-assisted tobacco interventions are often underutilized and require new and innovative engagement approaches. Web-based peer-driven chain referrals successfully used outside health care have the potential for increasing the reach of Internet interventions., Objective: The objective of our study was to describe the protocol for the development and testing of proactive Web-based chain-referral tools for increasing the access to Decide2Quit.org, a Web-assisted tobacco intervention system., Methods: We will build and refine proactive chain-referral tools, including email and Facebook referrals. In addition, we will implement respondent-driven sampling (RDS), a controlled chain-referral sampling technique designed to remove inherent biases in chain referrals and obtain a representative sample. We will begin our chain referrals with an initial recruitment of former and current smokers as seeds (initial participants) who will be trained to refer current smokers from their social network using the developed tools. In turn, these newly referred smokers will also be provided the tools to refer other smokers from their social networks. We will model predictors of referral success using sample weights from the RDS to estimate the success of the system in the targeted population., Results: This protocol describes the evaluation of proactive Web-based chain-referral tools, which can be used in tobacco interventions to increase the access to hard-to-reach populations, for promoting smoking cessation., Conclusions: Share2Quit represents an innovative advancement by capitalizing on naturally occurring technology trends to recruit smokers to Web-assisted tobacco interventions.

Resource effect studies can be useful in highlighting areas of improvement in informatics tools. Before a large randomized trial, we tested the functions of the Decide2Quit.org Web-assisted tobacco intervention using smokers (N=204) recruited via Google advertisements. These smokers were given access to Decide2Quit.org for six months and we tracked their usage and assessed their six months cessation using a rigorous follow-up. Multiple, interesting findings were identified: we found the use of tailored emails to dramatically increase participation for a short period. We also found varied effects of the different functions. Functions supporting "seeking social support" (Your Online Community and Family Tools), Healthcare Provider Tools, and the Library had positive effects on quit outcomes. One surprising finding, which needs further investigation, was that writing to our Tobacco Treatment Specialists was negatively associated with quit outcomes.

Engaging busy healthcare providers in online continuing education interventions is challenging. In an Internet-delivered intervention for dental providers, we tested a series of email-delivered reminders - cues to action. The intervention included case-based education and downloadable practice tools designed to encourage providers to increase delivery of smoking cessation advice to patients. We compared the impact of email reminders focused on 1) general project announcements, 2) intervention related content (smoking cessation), and 3) unrelated content (oral cancer prevention focused content). We found that email reminders dramatically increased participation. The content of the message had little impact on the participation, but day of the week was important - messages sent at the end of the week had less impact, likely due to absence from clinic on the weekend. Email contact, such as day of week an email is sent and notice of new content post-ing, is critical to longitudinal engagement. Further research is needed to understand which messages and how frequently, will maximize participation.

Links between clinical and public health interventions are limited. Using the Internet as a delivery method provides the potential to link multiple intervention components, but this potential has not yet been realized. In this poster, we present results of a formative assessment to identify approaches to improving clinical-public health linkages.