Dataset Information

QuitSMART Utah: an implementation study protocol for a cluster-randomized, multi-level Sequential Multiple Assignment Randomized Trial to increase Reach and Impact of tobacco cessation treatment in Community Health Centers.

ABSTRACT: BACKGROUND:Tobacco use remains the leading cause of death and disability in the USA and is disproportionately concentrated among low socioeconomic status (SES) populations. Community Health Centers (CHCs) are a key venue for reaching low SES populations with evidence-based tobacco cessation treatment such as Quitlines. Electronic health record (EHR)-based interventions at the point-of-care, text messaging (TM), and phone counseling have the potential to increase Quitline reach and are feasible to implement within CHCs. However, there is a lack of data to inform how, when, and in what combination these strategies should be implemented. The aims of this cluster-randomized trial are to evaluate multi-level implementation strategies to increase the Reach (i.e., proportion of tobacco-using patients who enroll in the Quitline) and Impact (i.e., Reach × Efficacy [efficacy is defined as the proportion of tobacco-using patients who enroll in Quitline treatment that successfully quit]) and to evaluate characteristics of healthcare system, providers, and patients that may influence tobacco-use outcomes. METHODS:This study is a multilevel, three-phase, Sequential Multiple Assignment Randomized Trial (SMART), conducted in CHCs (N?=?33 clinics; N?=?6000 patients). In the first phase, clinics will be randomized to two different EHR conditions. The second and third phases are patient-level randomizations based on prior treatment response. Patients who enroll in the Quitline receive no further interventions. In phase two, patients who are non-responders (i.e., patients who do not enroll in Quitline) will be randomized to receive either TM or continued-EHR. In phase three, patients in the TM condition who are non-responders will be randomized to receive either continued-TM or TM?+?phone coaching. DISCUSSION:This project will evaluate scalable, multi-level interventions to directly address strategic national priorities for reducing tobacco use and related disparities by increasing the Reach and Impact of evidence-based tobacco cessation interventions in low SES populations. TRIAL REGISTRATION:This trial was registered at ClinicalTrials.gov (NCT03900767) on April 4th, 2019.

SUBMITTER: Fernandez ME

PROVIDER: S-EPMC6993416 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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QuitSMART Utah: an implementation study protocol for a cluster-randomized, multi-level Sequential Multiple Assignment Randomized Trial to increase Reach and Impact of tobacco cessation treatment in Community Health Centers.

Fernandez Maria E ME Schlechter Chelsey R CR Del Fiol Guilherme G Gibson Bryan B Kawamoto Kensaku K Siaperas Tracey T Pruhs Alan A Greene Tom T Nahum-Shani Inbal I Schulthies Sandra S Nelson Marci M Bohner Claudia C Kramer Heidi H Borbolla Damian D Austin Sharon S Weir Charlene C Walker Timothy W TW Lam Cho Y CY Wetter David W DW

Implementation science : IS 20200130 1

<h4>Background</h4>Tobacco use remains the leading cause of death and disability in the USA and is disproportionately concentrated among low socioeconomic status (SES) populations. Community Health Centers (CHCs) are a key venue for reaching low SES populations with evidence-based tobacco cessation treatment such as Quitlines. Electronic health record (EHR)-based interventions at the point-of-care, text messaging (TM), and phone counseling have the potential to increase Quitline reach and are fe ...[more]

PMID: 32000812

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Project description:Tobacco cessation after cancer diagnosis leads to better patient outcomes. However, tobacco treatment services are frequently unavailable in cancer care settings, and multilevel implementation challenges can impede uptake of new programs. The National Cancer Institute (NCI) dedicated Cancer Moonshot funding through the Cancer Center Cessation Initiative (C3I) for NCI-Designated Cancer Centers to implement or enhance the implementation of tobacco treatment services. We examined a pragmatic application of the RE-AIM framework (reach, effectiveness, adoption, implementation, and maintenance) to evaluate tobacco treatment programs implemented within Cancer Centers funded through C3I. Using three C3I-funded Centers as examples, we describe how each RE-AIM construct was operationalized to evaluate the implementation of a wide range of cessation services (e.g., tobacco use screening, counseling, Quitline referral, pharmacotherapy) in this heterogeneous group of cancer care settings. We discuss the practical challenges encountered in assessing RE-AIM constructs in real world situations, including using the electronic health record (EHR) to aid in assessment. Reach and effectiveness evaluation required that Centers define the setting(s) where cessation services were implemented (to determine the "denominator"), enumerate the patient population, report current patient tobacco use, patient engagement in tobacco treatment, and 6-month cessation outcomes. To reduce site heterogeneity, increase data accuracy, and reduce burden, reach was frequently captured via standardized EHR enhancements that improved the identification of current smokers and tobacco treatment referrals. Effectiveness was determined by cessation outcomes (30-day point prevalence abstinence at 6-months post-engagement) assessed through a variety of data collection approaches. Adoption was measured by the characteristics and proportion of targeted cancer care settings and clinicians engaged in cessation service delivery. Implementation was assessed by examining the delivery of tobacco screening assessments and intervention components across sites, and provider-level implementation consistency. Maintenance assessments identified whether tobacco treatment services continued in the setting after implementation and documented the sustainability plan and organizational commitment to continued delivery. In sum, this paper demonstrates a pragmatic approach to using RE-AIM as an evaluation framework that yields relevant outcomes on common implementation metrics across widely differing tobacco treatment approaches and settings.

Project description:BACKGROUND:In the past two decades, the massive scale-up of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) has led to significant reductions in malaria mortality and morbidity. Nonetheless, the malaria burden remains high, and a dozen countries in Africa show a trend of increasing malaria incidence over the past several years. This underscores the need to improve the effectiveness of interventions by optimizing first-line intervention tools and integrating newly approved products into control programs. Because transmission settings and vector ecologies vary from place to place, malaria interventions should be adapted and readapted over time in response to evolving malaria risks. An adaptive approach based on local malaria epidemiology and vector ecology may lead to significant reductions in malaria incidence and transmission risk. METHODS/DESIGN:This study will use a longitudinal block-cluster sequential multiple assignment randomized trial (SMART) design with longitudinal outcome measures for a period of 3?years to develop an adaptive intervention for malaria control in western Kenya, the first adaptive trial for malaria control. The primary outcome is clinical malaria incidence rate. This will be a two-stage trial with 36 clusters for the initial trial. At the beginning of stage 1, all clusters will be randomized with equal probability to either LLIN, piperonyl butoxide-treated LLIN (PBO Nets), or LLIN + IRS by block randomization based on their respective malaria risks. Intervention effectiveness will be evaluated with 12?months of follow-up monitoring. At the end of the 12-month follow-up, clusters will be assessed for "response" versus "non-response" to PBO Nets or LLIN + IRS based on the change in clinical malaria incidence rate and a pre-defined threshold value of cost-effectiveness set by the Ministry of Health. At the beginning of stage 2, if an intervention was effective in stage 1, then the intervention will be continued. Non-responders to stage 1 PBO Net treatment will be randomized equally to either PBO Nets + LSM (larval source management) or an intervention determined by an enhanced reinforcement learning method. Similarly, non-responders to stage 1 LLIN + IRS treatment will be randomized equally to either LLIN + IRS + LSM or PBO Nets + IRS. There will be an 18-month evaluation follow-up period for stage 2 interventions. We will monitor indoor and outdoor vector abundance using light traps. Clinical malaria will be monitored through active case surveillance. Cost-effectiveness of the interventions will be assessed using Q-learning. DISCUSSION:This novel adaptive intervention strategy will optimize existing malaria vector control tools while allowing for the integration of new control products and approaches in the future to find the most cost-effective malaria control strategies in different settings. Given the urgent global need for optimization of malaria control tools, this study can have far-reaching implications for malaria control and elimination. TRIAL REGISTRATION:US National Institutes of Health, study ID NCT04182126 . Registered on 26 November 2019.

Project description:BackgroundThe sequential multiple assignment randomized trial (SMART) design allows for changes in the intervention during the trial period. Despite its potential and feasibility for defining the best sequence of interventions, so far, it has not been utilized in a smartphone/gamified intervention for physical activity.ObjectiveWe aimed to investigate the feasibility of the SMART design for assessing the effects of a smartphone app intervention to improve physical activity in adults. We also aimed to describe the participants' perception regarding the protocol and the use of the app for physical activity qualitatively.MethodsWe conducted a feasibility 24-week/two-stage SMART in which 18 insufficiently active participants (<10,000 steps/day) were first randomized to group 1 (smartphone app only), group 2 (smartphone app + tailored messages), and a control group (usual routine during the protocol). Participants were motivated to increase their step count by at least 2000 steps/day each week. Based on the 12-week intermediate outcome, responders continued the intervention and nonresponders were rerandomized to subsequent treatment, including a new group 3 (smartphone app + tailored messages + gamification) in which they were instructed to form groups to use several game elements available in the chosen app (Pacer). We considered responders as those with any positive slope in the linear relationship between weeks and steps per day at the end of the first stage of the intervention. We compared the accelerometer-based steps per day before and after the intervention, as well as the slopes of the app-based steps per day between the first and second stages of the intervention.ResultsTwelve participants, including five controls, finished the intervention. We identified two responders in group 1. We did not observe relevant changes in the steps per day either throughout the intervention or compared with the control group. However, the rerandomization of five nonresponders led to a change in the slope of the steps per day (median -198 steps/day [IQR -279 to -103] to 20 steps/day [IQR -204 to 145]; P=.08). Finally, in three participants from group 2, we observed an increase in the number of steps per day up to the sixth week, followed by an inflection to baseline values or even lower (ie, a quadratic relationship). The qualitative analysis showed that participants' reports could be classified into the following: (1) difficulty in managing the app and technology or problems with the device, (2) suitable response to the app, and (3) difficulties to achieve the goals.ConclusionsThe SMART design was feasible and changed the behavior of steps per day after rerandomization. Rerandomization should be implemented earlier to take advantage of tailored messages. Additionally, difficulties with technology and realistic and individualized goals should be considered in interventions for physical activity using smartphones.Trial registrationBrazilian Registry of Clinical Trials RBR-8xtc9c; http://www.ensaiosclinicos.gov.br/rg/RBR-8xtc9c/.

Project description:BackgroundTobacco use adversely affects oral health. Clinical guidelines recommend that dental providers promote tobacco abstinence and provide patients who use tobacco with brief tobacco use cessation counselling. Research shows that these guidelines are seldom implemented, however. To improve guideline adherence and to develop effective interventions, it is essential to understand provider behaviour and challenges to implementation. This study aimed to develop a theoretically informed measure for assessing among dental providers implementation difficulties related to tobacco use prevention and cessation (TUPAC) counselling guidelines, to evaluate those difficulties among a sample of dental providers, and to investigate a possible underlying structure of applied theoretical domains.MethodsA 35-item questionnaire was developed based on key theoretical domains relevant to the implementation behaviours of healthcare providers. Specific items were drawn mostly from the literature on TUPAC counselling studies of healthcare providers. The data were collected from dentists (n = 73) and dental hygienists (n = 22) in 36 dental clinics in Finland using a web-based survey. Of 95 providers, 73 participated (76.8%). We used Cronbach's alpha to ascertain the internal consistency of the questionnaire. Mean domain scores were calculated to assess different aspects of implementation difficulties and exploratory factor analysis to assess the theoretical domain structure. The authors agreed on the labels assigned to the factors on the basis of their component domains and the broader behavioural and theoretical literature.ResultsInternal consistency values for theoretical domains varied from 0.50 ('emotion') to 0.71 ('environmental context and resources'). The domain environmental context and resources had the lowest mean score (21.3%; 95% confidence interval [CI], 17.2 to 25.4) and was identified as a potential implementation difficulty. The domain emotion provided the highest mean score (60%; 95% CI, 55.0 to 65.0). Three factors were extracted that explain 70.8% of the variance: motivation (47.6% of variance, ? = 0.86), capability (13.3% of variance, ? = 0.83), and opportunity (10.0% of variance, ? = 0.71).ConclusionsThis study demonstrated a theoretically informed approach to identifying possible implementation difficulties in TUPAC counselling among dental providers. This approach provides a method for moving from diagnosing implementation difficulties to designing and evaluating interventions.

Dataset Information

QuitSMART Utah: an implementation study protocol for a cluster-randomized, multi-level Sequential Multiple Assignment Randomized Trial to increase Reach and Impact of tobacco cessation treatment in Community Health Centers.

Publications

QuitSMART Utah: an implementation study protocol for a cluster-randomized, multi-level Sequential Multiple Assignment Randomized Trial to increase Reach and Impact of tobacco cessation treatment in Community Health Centers.

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