Examining the creation of synergy in community coalitions for smoke-free environments in Armenia and Georgia.

Community coalitions depend on their members to synergistically pool diverse resources, including knowledge and expertise, community connections and varied perspectives, to identify and implement strategies and make progress toward community health improvement. Several coalition theories suggest synergy is the key mechanism driving coalition effectiveness. The Community Coalition Action Theory (CCAT) asserts that synergy depends on how well coalitions engage their members and leverage their resources, which is influenced by coalition processes, member participation and satisfaction and benefits outweighing costs. The current study used mixed methods, including coalition member surveys (n = 83) and semi-structured interviews with leaders and members (n = 42), to examine the process of creating collaborative synergy in 14 community coalitions for smoke-free environments in Armenia and Georgia. Members, typically seven per coalition representing education, public health, health care and municipal administration sectors, spent an average of 16 hr/month on coalition-related work. Common benefits included making the community a better place to live and learning more about tobacco control. The greatest cost was attending meetings or events at inconvenient times. Members contributed various resources, including their connections and influence, skills and expertise and access to population groups and settings. Strong coalition processes, greater benefits and fewer costs of participation and satisfaction were correlated with leveraging of member resources, which in turn, was highly correlated with collaborative synergy. Consistent with CCAT, effective coalition processes created a positive climate where membership benefits outweighed costs, and members contributed their resources in a way that created collaborative synergy.

Examining local smoke-free coalitions in Armenia and Georgia: context and outcomes of a matched-pairs community-randomised controlled trial.

INTRODUCTION: Local coalitions can advance public health initiatives such as smoke-free air but have not been widely used or well-studied in low-income and middle-income countries. METHODS: We conducted a matched-pairs community-randomised controlled trial in 28 communities in Armenia and Georgia (N=14/country) in which we helped establish local coalitions in 2019 and provided training and technical assistance for coalition activity promoting smoke-free policy development and enforcement (2019-2021). Surveys of ~1450 households (Fall 2018, May-June 2022) were conducted to evaluate coalition impact on smoke-free policy support, smoke-free home adoption, secondhand smoke exposure (SHSe), and coalition awareness and activity exposure, using multivariable mixed modelling. RESULTS: Bivariate analyses indicated that, at follow-up versus baseline, both conditions reported greater smoke-free home rates (53.6% vs 38.5%) and fewer days of SHSe on average (~11 vs ~12 days), and that intervention versus control condition communities reported greater coalition awareness (24.3% vs 12.2%) and activity exposure (71.2% vs 64.5%). Multivariable modelling indicated that intervention (vs control) communities reported greater rates of complete smoke-free homes (adjusted Odds Ratio [aOR] 1.55, 95% confiedence interval [CI] 1.11 to 2.18, p=0.011) and coalition awareness (aOR 2.89, 95% CI 1.44 to 8.05, p=0.043) at follow-up. However, there were no intervention effects on policy support, SHSe or community-based activity exposure. CONCLUSIONS: Findings must be considered alongside several sociopolitical factors during the study, including national smoke-free policies implementation (Georgia, 2018; Armenia, 2022), these countries' participation in an international tobacco legislation initiative, the COVID-19 pandemic and regional/local war). The intervention effect on smoke-free homes is critical, as smoke-free policy implementation provides opportunities to accelerate smoke-free home adoption via local coalitions. TRIAL REGISTRATION NUMBER: NCT03447912.

The inclusion of e-cigarettes and heated tobacco products in smoke-free home and car rules: A cross-sectional survey of adults in Armenia and Georgia.

INTRODUCTION: Understanding who includes e-cigarettes and heated tobacco products (HTPs) in smoke-free home or car rules could inform public health interventions, particularly in countries with high smoking prevalence and recently implemented national smoke-free laws, like Armenia and Georgia. METHODS: In 2022, we conducted a cross-sectional survey among 1468 adults in 28 Armenian and Georgian communities (mean age=42.92 years; 51.4% female, 31.6% past-month smoking). Multilevel regression (accounting for clustering within communities; adjusted for sociodemographics and cigarette use) examined e-cigarette/HTP perceptions (risk, social acceptability) and use intentions in relation to: 1) including e-cigarettes/HTPs in home and car rules among participants with home and car rules, respectively (logistic regressions); and 2) intention to include e-cigarettes/HTPs in home rules (linear regression, 1 = 'not at all' to 7 = 'extremely') among those without home rules. RESULTS: Overall, 72.9% (n=1070) had home rules, 86.5% of whom included e-cigarettes/HTPs; 33.9% (n=498) had car rules, 81.3% of whom included e-cigarettes/HTPs. Greater perceived e-cigarette/HTP risk was associated with including e-cigarettes/HTPs in home rules (AOR=1.28; 95% CI: 1.08-1.50) and car rules (AOR=1.46; 95% CI: 1.14-1.87) and next-year intentions to include e-cigarettes/HTPs in home rules (ß=0.38; 95% CI: 0.25-0.50). Lower e-cigarette/HTP use intentions were associated with including e-cigarettes/HTPs in home rules (AOR=0.75; 95% CI: 0.63-0.88). While perceived social acceptability was unassociated with the outcomes, other social influences were: having children and no other household smokers was associated with including e-cigarettes/HTPs in car rules, and having children was associated with intent to include e-cigarettes/HTPs in home rules. CONCLUSIONS: Interventions to address gaps in home and car rules might target e-cigarette/HTP risk perceptions.

Scaling the EQUIPPED medication safety program: Traditional and hub-and-spoke implementation models.

BACKGROUND: The EQUIPPED (Enhancing Quality of Prescribing Practices for Older Adults Discharged from the Emergency Department) medication safety program is an evidence-informed quality improvement initiative to reduce potentially inappropriate medications (PIMs) prescribed by Emergency Department (ED) providers to adults aged 65 and older at discharge. We aimed to scale-up this successful program using (1) a traditional implementation model at an ED with a novel electronic medical record and (2) a new hub-and-spoke implementation model at three new EDs within a health system that had previously implemented EQUIPPED (hub). We hypothesized that implementation speed would increase under the hub-and-spoke model without cost to PIM reduction or site engagement. METHODS: We evaluated the effect of the EQUIPPED program on PIMs for each ED, comparing their 12-month baseline to 12-month post-implementation period prescribing data, number of months to implement EQUIPPED, and facilitators and barriers to implementation. RESULTS: The proportion of PIMs at all four sites declined significantly from pre- to post-EQUIPPED: at traditional site 1 from 8.9% (8.1-9.6) to 3.6% (3.6-9.6) (p < 0.001); at spread site 1 from 12.2% (11.2-13.2) to 7.1% (6.1-8.1) (p < 0.001); at spread site 2 from 11.3% (10.1-12.6) to 7.9% (6.4-8.8) (p = 0.045); and at spread site 3 from 16.2% (14.9-17.4) to 11.7% (10.3-13.0) (p < 0.001). Time to implement was equivalent at all sites across both models. Interview data, reflecting a wide scope of responsibilities for the champion at the traditional site and a narrow scope at the spoke sites, indicated disproportionate barriers to engagement at the spoke sites. CONCLUSIONS: EQUIPPED was successfully implemented under both implementation models at four new sites during the COVID-19 pandemic, indicating the feasibility of adapting EQUIPPED to complex, real-world conditions. The hub-and-spoke model offers an effective way to scale-up EQUIPPED though a speed or quality advantage could not be shown.