Lessons Learned From Developing Dashboards to Support Decision-Making for Community Opioid Response by Community Stakeholders: Mixed Methods and Multisite Study.

BACKGROUND: Data dashboards are published tools that present visualizations; they are increasingly used to display data about behavioral health, social determinants of health, and chronic and infectious disease risks to inform or support public health endeavors. Dashboards can be an evidence-based approach used by communities to influence decision-making in health care for specific populations. Despite widespread use, evidence on how to best design and use dashboards in the public health realm is limited. There is also a notable dearth of studies that examine and document the complexity and heterogeneity of dashboards in community settings. OBJECTIVE: Community stakeholders engaged in the community response to the opioid overdose crisis could benefit from the use of data dashboards for decision-making. As part of the Communities That HEAL (CTH) intervention, community data dashboards were created for stakeholders to support decision-making. We assessed stakeholders' perceptions of the usability and use of the CTH dashboards for decision-making. METHODS: We conducted a mixed methods assessment between June and July 2021 on the use of CTH dashboards. We administered the System Usability Scale (SUS) and conducted semistructured group interviews with users in 33 communities across 4 states of the United States. The SUS comprises 10 five-point Likert-scale questions measuring usability, each scored from 0 to 4. The interview guides were informed by the technology adoption model (TAM) and focused on perceived usefulness, perceived ease of use, intention to use, and contextual factors. RESULTS: Overall, 62 users of the CTH dashboards completed the SUS and interviews. SUS scores (grand mean 73, SD 4.6) indicated that CTH dashboards were within the acceptable range for usability. From the qualitative interview data, we inductively created subthemes within the 4 dimensions of the TAM to contextualize stakeholders' perceptions of the dashboard's usefulness and ease of use, their intention to use, and contextual factors. These data also highlighted gaps in knowledge, design, and use, which could help focus efforts to improve the use and comprehension of dashboards by stakeholders. CONCLUSIONS: We present a set of prioritized gaps identified by our national group and list a set of lessons learned for improved data dashboard design and use for community stakeholders. Findings from our novel application of both the SUS and TAM provide insights and highlight important gaps and lessons learned to inform the design of data dashboards for use by decision-making community stakeholders. TRIAL REGISTRATION: ClinicalTrials.gov NCT04111939; https://clinicaltrials.gov/study/NCT04111939.

Recall and Effectiveness of Messages Promoting Smoke-Free Policies in Rural Communities.

INTRODUCTION: Low-cost media campaigns increase demand for smoke-free policies in underserved rural areas. The study examined the impact of loss- and gain-framed smoke-free print ads on recall and perceived effectiveness in rural communities, controlling for personal characteristics. METHODS: Following 6- to 9-month print media campaigns in three rural counties, recall and perceived effectiveness of loss-framed (ie, targeting dangers of secondhand smoke [SHS]) and gain-framed (ie, highlighting positive aspects of smoke-free air) ads were assessed using random-digit-dial phone surveys. Respondents were asked if they remembered each ad, whether they liked it, whether they were prompted to contact a smoke-free coalition, whether the ad made them think, and whether it prompted emotion. Mixed modeling assessed whether personal factors predicted ad recall or perceived effectiveness. RESULTS: Loss-framed ads were less likely to be recalled but more likely to prompt emotion. For ads of both frame types, females reported greater recall and perceived effectiveness than males. Those with less education reported higher perceived effectiveness of the ads but lower recall. Nonsmokers were more likely than smokers to perceive the ads as effective. Knowledge of SHS risk and support for smoke-free workplaces were positively associated with recall and effectiveness. CONCLUSIONS: Ad recall and perceived effectiveness were associated with framing and demographic and personal characteristics. Smoke-free efforts in rural areas may be bolstered by continuing to promote benefits of smoke-free workplace policies and educate on SHS risks. Rural areas may need to provide a combination of ad types and framing strategies to appeal to a wide audience. IMPLICATIONS: Rural communities are disproportionately affected by SHS and less likely to be protected by smoke-free policies. This study adds evidence-based guidance for tailoring rural smoke-free media campaigns using different framing: gain-framed messages (ie, benefits of smoke-free environments) to promote recall and loss-framed content (ie, dangers of SHS) to prompt emotion. Further, gain-framed messages that are localized to the rural community may be especially effective. Findings support designing smoke-free campaigns in rural communities with the audience in mind by tailoring messages to age, sex, and education level.

Culturally-specific smoking cessation outreach in a rural community.

OBJECTIVE: Tobacco use is the leading preventable cause of death, resulting in 443,000 US deaths per year. Rural adults have higher smoking prevalence and less access to tobacco dependence treatment than their urban counterparts. This study examined exposure to a culturally specific smoking cessation outreach intervention, assessing whether exposure was associated with cessation behaviors. DESIGN AND SAMPLE: Post-test only quasi-experimental study. Targeted adult smokers (N = 251) living in a rural, economically distressed southeastern US county for at least 6 months. MEASUREMENTS: Five outreach elements (brochures/pushcards, posters, print and radio advertisements, quilt made by local artisans) based on themes from focus groups with current and former smokers and paired with brief tobacco cessation counseling, and were delivered over 6 months in 2009-2010. Exposure and cessation behavior indicators were collected via cross-sectional random-digit dial survey. The total intervention exposure score was 4.8 (SD = 4.3, range 0-19). RESULTS: Intervention exposure was associated with having talked to a health care provider about quitting smoking in the past 6 months and planning to quit smoking in the next 6 months. CONCLUSIONS: Culturally specific outreach materials based on personal narratives are a promising population-based intervention to motivate rural smokers to consider cessation.

Do smoke-free laws in rural, distressed counties encourage cessation?

The authors examined the association between smoke-free laws and smoking/cessation behaviors and secondhand smoke exposure among current and former smokers in rural, distressed counties. A quasi-experimental, two-group design compared outcomes between participants from a county with a longstanding smoke-free law (n = 252) and those living in four demographically similar counties without smoke-free laws ( n = 250). Participants were recruited using random digit dialing. Controlling for demographic factors, those in the treatment group reported greater nicotine dependence, were more likely to have smoke-free workplaces, and less likely to have smoke-free homes. There were no differences in smoking status, past-year quit attempts, intent to quit in 5 years, cigarettes per day, or time since last cigarette. Smokers in the treatment group were just as likely to attempt to quit, despite greater nicotine dependence. Findings showed that making nonsmoking the social norm through policy change may be more difficult in rural, distressed areas.

Time since smoke-free law and smoking cessation behaviors.

INTRODUCTION: We examined the association between time since implementation of a smoke-free law and cessation behaviors among current and former smokers. METHODS: A quasiexperimental, three-group design assessed smoking and cessation behaviors via brief telephone interviews with 295 randomly selected current and former smokers who had quit since a smoke-free law took effect in their community. Participants lived in one of four communities that had implemented a smoke-free law in the preceding 6-8 months (n = 106), 18 months (n = 87), or 36 months (n = 102). RESULTS: Compared with those living in communities with relatively new smoke-free laws (6-8 months), those in communities with more established laws (18 and 36 months) were more likely to (a) be former smokers and (b) report a longer time since smoking their last cigarette. Compared with the 6- to 8-month group, those in the 36-month group were more likely to have tried to quit since the law was implemented. DISCUSSION: Smoke-free laws may have a delayed effect on cessation among adults. The longer a smoke-free law is in effect, the more likely adults will attempt to quit smoking and become former smokers. Maintaining the integrity of smoke-free laws over time is an important population-based quit strategy.

Public support for smoke-free laws in rural communities.

BACKGROUND: There has been an upward trend in smoke-free laws in countries, states, and municipalities in recent years. However, these laws are more likely to be enacted in urban areas. The purpose of this study was to examine public opinion of smoke-free laws and to determine if there was a difference in support for these laws between urban and rural dwellers. METHODS: A series of random-digit-dialed phone surveys was conducted in 2005-2006 with 3672 adult Kentucky residents living in rural and urban communities without smoke-free laws. In addition to demographics, respondents were asked whether they would support a local law prohibiting smoking in public places. Responses were weighted to adjust for an over-representation of women in the sample relative to the population. Logistic regression was used to test for a rural/urban difference in support; data analysis was conducted in 2007. RESULTS: Respondents were primarily women, Caucasian, with at most a high school education, and nonsmokers; the average age was 49.3 years. About half lived in rural communities. More than half (59.6%) supported a local smoke-free law. Controlling for age, gender, ethnicity, education, and smoking status, there was a significant difference in the level of support for a smoke-free law between rural and urban respondents. Compared to urban dwellers, rural residents were more likely to support these laws (OR=1.21; 95% CI=1.03, 1.42). CONCLUSIONS: When controlling for demographic differences between groups, rural residents were more likely than those in urban settings to support a law for local smoke-free public places.

Public opinion and smoke-free laws.

Public support for Lexington-Fayette County, Kentucky's smoke-free law, perception of health risks from exposure to secondhand smoke (SHS), smoking behaviors, and frequency of visiting restaurants, bars, and entertainment venues were assessed pre- and post-law. Two cohorts of noninstitutionalized adults (N = 2,146) were randomly selected and invited to participate in a 10- to 15-min telephone survey. Public support for the smoke-free law increased from 56% to 63%, and respondents were 1.3 times more likely to perceive SHS exposure as a health risk after the law took effect. Although adult smoking and home smoking policy did not change post-law, adults frequented public venues at least as much as before the law. Lexington adults favored the smoke-free legislation despite living in a traditionally protobacco climate. The smoke-free law acted as a public health intervention as it increased perception of risk of heart disease and cancer from SHS exposure.