Data envelopment analysis to evaluate the efficiency of tobacco treatment programs in the NCI Moonshot Cancer Center Cessation Initiative.

BACKGROUND: The Cancer Center Cessation Initiative (C3I) is a National Cancer Institute (NCI) Cancer Moonshot Program that supports NCI-designated cancer centers developing tobacco treatment programs for oncology patients who smoke. C3I-funded centers implement evidence-based programs that offer various smoking cessation treatment components (e.g., counseling, Quitline referrals, access to medications). While evaluation of implementation outcomes in C3I is guided by evaluation of reach and effectiveness (via RE-AIM), little is known about technical efficiency-i.e., how inputs (e.g., program costs, staff time) influence implementation outcomes (e.g., reach, effectiveness). This study demonstrates the application of data envelopment analysis (DEA) as an implementation science tool to evaluate technical efficiency of C3I programs and advance prioritization of implementation resources. METHODS: DEA is a linear programming technique widely used in economics and engineering for assessing relative performance of production units. Using data from 16 C3I-funded centers reported in 2020, we applied input-oriented DEA to model technical efficiency (i.e., proportion of observed outcomes to benchmarked outcomes for given input levels). The primary models used the constant returns-to-scale specification and featured cost-per-participant, total full-time equivalent (FTE) effort, and tobacco treatment specialist effort as model inputs and reach and effectiveness (quit rates) as outcomes. RESULTS: In the DEA model featuring cost-per-participant (input) and reach/effectiveness (outcomes), average constant returns-to-scale technical efficiency was 25.66 (SD = 24.56). When stratified by program characteristics, technical efficiency was higher among programs in cohort 1 (M = 29.15, SD = 28.65, n = 11) vs. cohort 2 (M = 17.99, SD = 10.16, n = 5), with point-of-care (M = 33.90, SD = 28.63, n = 9) vs. no point-of-care services (M = 15.59, SD = 14.31, n = 7), larger (M = 33.63, SD = 30.38, n = 8) vs. smaller center size (M = 17.70, SD = 15.00, n = 8), and higher (M = 29.65, SD = 30.99, n = 8) vs. lower smoking prevalence (M = 21.67, SD = 17.21, n = 8). CONCLUSION: Most C3I programs assessed were technically inefficient relative to the most efficient center benchmark and may be improved by optimizing the use of inputs (e.g., cost-per-participant) relative to program outcomes (e.g., reach, effectiveness). This study demonstrates the appropriateness and feasibility of using DEA to evaluate the relative performance of evidence-based programs.

Comparative effectiveness of mobile health smoking cessation approaches among underserved patients in primary care: Study protocol for the PROMOTE-UP trial.

INTRODUCTION: Tobacco smoking is the leading cause of preventable disease, disability, and premature death in the United States. Recent advances have led to two efficacious mobile health (mHealth) treatments for smoking cessation: iCanQuit, an Acceptance and Commitment Therapy-based behavioral treatment promoting cessation through accepting triggers and committing to values; and Motiv8, a contingency management intervention promoting smoking cessation with financial incentives via biochemically verified abstinence. This study will evaluate the comparative effectiveness of the Florida Quitline, iCanQuit alone, and iCanQuit+Motiv8 in a pragmatic trial among patients who smoke in underserved primary care settings. METHODS: The study will be an individually-randomized controlled trial with three arms (Florida Quitline, iCanQuit alone, iCanQuit+Motiv8 combined) conducted in multiple primary care practices affiliated with the OneFlorida+ Clinical Research Consortium. Adult patients who smoke will be randomized to one of the 3 study arms (n = 444/arm), stratified by healthcare setting (academic vs. community). The primary outcome will be 7-day point prevalence smoking abstinence at 6 months post-randomization. Secondary outcomes will be 12-month smoking abstinence, patient satisfaction with the interventions, and changes in patient quality of life and self-efficacy. The study will also assess how and for whom the interventions help sub-group patients in achieving smoking abstinence by measuring theory-derived factors that mediate smoking outcome-specific baseline moderators. CONCLUSIONS: Results from this study will provide evidence for the comparative effectiveness of mHealth smoking cessation interventions in healthcare settings. Use of mHealth interventions can make smoking cessation resources more equitably accessible and have far-reaching impact on community and population health. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05415761, Registered 13 June 2022.

Predicting implicit and explicit exercise identity from descriptive social norms regarding exercise.

OBJECTIVES: Exercise identity may promote exercise maintenance. However, less is known about factors that affect exercise identity. Whether descriptive social norms are potential intervention targets for identity development was evaluated. DESIGN: A cross-sectional design using data from the Attitudes, Identities, and Individual Differences (AIID) study was employed - with additional cases collected to increase sample size and power - to evaluate whether descriptive social norms regarding exercise are related to implicit and explicit exercise identities. MAIN OUTCOME MEASURES: Participants completed measures of proximal and distal descriptive social norms regarding exercise, explicit and implicit exercise identity, physical activity behavior, and demographics. Multiple regression was used to assess whether social norms regarding exercise predict exercise identities. RESULTS: Only proximal descriptive social norms were significantly associated with explicit exercise identity, whereas neither proximal nor distal descriptive social norms were associated with implicit exercise identity. The slopes for explicit and implicit identity differed when predicted by distal (but not proximal) descriptive social norms. CONCLUSIONS: Proximal descriptive social norms may be associated with explicit exercise identity and may be a worthy intervention targeting alongside identity to influence change in exercise behavior. More research is needed to further understand these relationships.