Identifying determinants of varenicline adherence using the Theoretical Domains framework: a rapid review.

BACKGROUND: Adhering to varenicline has been shown to significantly improve the chances of successfully quitting smoking, with studies indicating a twofold increase in 6-month quit rates. However, despite its potential benefits, many individuals struggle with maintaining good adherence to varenicline; thus there is a need to develop scalable strategies to help people adhere. As a first step to inform the development of an intervention to improve adherence to varenicline, we conducted a rapid literature review to identify: 1) modifiable barriers and facilitators to varenicline adherence, and 2) behaviour change techniques associated with increased adherence to varenicline. METHODS: We searched MEDLINE, Embase, APA PsycINFO, CINAHL, and the Cochrane Central Register of Controlled Trials for relevant studies published between 2006 and 2022. Search terms included "varenicline," "smoking cessation," and "adherence," and their respective subject headings and synonyms. We screened and included studies reporting modifiable determinants of adherence to varenicline and then assessed quality, extracted modifiable determinants and mapped them to the Theoretical Domains Framework version 2 and the Behaviour Change Technique Taxonomy version 1. RESULTS: A total of 1,221 titles were identified through the database searches; 61 met the eligibility criteria. Most of the studies were randomized controlled trials and predominantly focused on barriers to varenicline. Only nine studies explicitly mentioned behaviour change techniques used to help varenicline adherence. Eight domains were identified as barriers to varenicline adherence (behavioural regulation, memory, goals, intentions, beliefs about capabilities, beliefs about consequences, optimism/pessimism, and environmental context) and five as facilitators (knowledge, behavioural regulation, beliefs about capabilities, social influences, and environmental context). CONCLUSIONS: This study identifies barriers and facilitators that should be addressed when developing a complex adherence intervention tailored to patients' needs based on modifiable determinants of medication adherence, some of which are under- used by existing adherence interventions. The findings from this review will inform the design of a theory-based healthbot planned to improve varenicline adherence in people undergoing smoking cessation treatment. SYSTEMATIC REVIEW REGISTRATION: This study was registered with PROSPERO (# CRD42022321838).

Cocreation of a conversational agent to help patients adhere to their varenicline treatment: A study protocol.

Objective: Varenicline is the most efficacious approved smoking cessation medication, making it one of the most cost-effective clinical interventions for reducing tobacco-related morbidity and mortality. Adhering to varenicline is strongly associated with smoking cessation. Healthbots have the potential to help people adhere to their medications by scaling up evidence-based behavioral interventions. In this protocol, we outline how we will follow the UK's Medical Research Council's guidance to codesign a theory-informed, evidence-based, and patient-centered healthbot to help people adhere to varenicline. Methods: The study will utilize the Discover, Design and Build, and Test framework and will include three phases: (a) a rapid review and interviews with 20 patients and 20 healthcare providers to understand barriers and facilitators to varenicline adherence (Discover phase); (b) Wizard of Oz test to design the healthbot and get a sense of the questions that chatbot has to be able to answer (Design phase); and (c) building, training, and beta-testing the healthbot (Building and Testing phases) where the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability framework will be used to develop the healthbot using the simplest sensible solution, and 20 participants will beta test the healthbot. We will use the Capability, Opportunity, Motivation-Behavior (COM-B) model of behavior change and its associated framework, the Theoretical Domains Framework, to organize the findings. Conclusions: The present approach will enable us to systematically identify the most appropriate features for the healthbot based on a well-established behavioral theory, the latest scientific evidence, and end users' and healthcare providers' knowledge.

AI Conversational Agent to Improve Varenicline Adherence: Protocol for a Mixed Methods Feasibility Study.

BACKGROUND: Varenicline is a pharmacological intervention for tobacco dependence that is safe and effective in facilitating smoking cessation. Enhanced adherence to varenicline augments the probability of prolonged smoking abstinence. However, research has shown that one-third of people who use varenicline are nonadherent by the second week. There is evidence showing that behavioral support helps with medication adherence. We have designed an artificial intelligence (AI) conversational agent or health bot, called "ChatV," based on evidence of what works as well as what varenicline is, that can provide these supports. ChatV is an evidence-based, patient- and health care provider-informed health bot to improve adherence to varenicline. ChatV has been programmed to provide medication reminders, answer questions about varenicline and smoking cessation, and track medication intake and the number of cigarettes. OBJECTIVE: This study aims to explore the feasibility of the ChatV health bot, to examine if it is used as intended, and to determine the appropriateness of proceeding with a randomized controlled trial. METHODS: We will conduct a mixed methods feasibility study where we will pilot-test ChatV with 40 participants. Participants will be provided with a standard 12-week varenicline regimen and access to ChatV. Passive data collection will include adoption measures (how often participants use the chatbot, what features they used, when did they use it, etc). In addition, participants will complete questionnaires (at 1, 4, 8, and 12 weeks) assessing self-reported smoking status and varenicline adherence, as well as questions regarding the acceptability, appropriateness, and usability of the chatbot, and participate in an interview assessing acceptability, appropriateness, fidelity, and adoption. We will use "stop, amend, and go" progression criteria for pilot studies to decide if a randomized controlled trial is a reasonable next step and what modifications are required. A health equity lens will be adopted during participant recruitment and data analysis to understand and address the differences in uptake and use of this digital health solution among diverse sociodemographic groups. The taxonomy of implementation outcomes will be used to assess feasibility, that is, acceptability, appropriateness, fidelity, adoption, and usability. In addition, medication adherence and smoking cessation will be measured to assess the preliminary treatment effect. Interview data will be analyzed using the framework analysis method. RESULTS: Participant enrollment for the study will begin in January 2024. CONCLUSIONS: By using predetermined progression criteria, the results of this preliminary study will inform the determination of whether to advance toward a larger randomized controlled trial to test the effectiveness of the health bot. Additionally, this study will explore the acceptability, appropriateness, fidelity, adoption, and usability of the health bot. These insights will be instrumental in refining the intervention and the health bot. TRIAL REGISTRATION: ClinicalTrials.gov NCT05997901; https://classic.clinicaltrials.gov/ct2/show/NCT05997901. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/53556.

A Motivational Interviewing Chatbot With Generative Reflections for Increasing Readiness to Quit Smoking: Iterative Development Study.

BACKGROUND: The motivational interviewing (MI) approach has been shown to help move ambivalent smokers toward the decision to quit smoking. There have been several attempts to broaden access to MI through text-based chatbots. These typically use scripted responses to client statements, but such nonspecific responses have been shown to reduce effectiveness. Recent advances in natural language processing provide a new way to create responses that are specific to a client's statements, using a generative language model. OBJECTIVE: This study aimed to design, evolve, and measure the effectiveness of a chatbot system that can guide ambivalent people who smoke toward the decision to quit smoking with MI-style generative reflections. METHODS: Over time, 4 different MI chatbot versions were evolved, and each version was tested with a separate group of ambivalent smokers. A total of 349 smokers were recruited through a web-based recruitment platform. The first chatbot version only asked questions without reflections on the answers. The second version asked the questions and provided reflections with an initial version of the reflection generator. The third version used an improved reflection generator, and the fourth version added extended interaction on some of the questions. Participants' readiness to quit was measured before the conversation and 1 week later using an 11-point scale that measured 3 attributes related to smoking cessation: readiness, confidence, and importance. The number of quit attempts made in the week before the conversation and the week after was surveyed; in addition, participants rated the perceived empathy of the chatbot. The main body of the conversation consists of 5 scripted questions, responses from participants, and (for 3 of the 4 versions) generated reflections. A pretrained transformer-based neural network was fine-tuned on examples of high-quality reflections to generate MI reflections. RESULTS: The increase in average confidence using the nongenerative version was 1.0 (SD 2.0; P=.001), whereas for the 3 generative versions, the increases ranged from 1.2 to 1.3 (SD 2.0-2.3; P<.001). The extended conversation with improved generative reflections was the only version associated with a significant increase in average importance (0.7, SD 2.0; P<.001) and readiness (0.4, SD 1.7; P=.01). The enhanced reflection and extended conversations exhibited significantly better perceived empathy than the nongenerative conversation (P=.02 and P=.004, respectively). The number of quit attempts did not significantly change between the week before the conversation and the week after across all 4 conversations. CONCLUSIONS: The results suggest that generative reflections increase the impact of a conversation on readiness to quit smoking 1 week later, although a significant portion of the impact seen so far can be achieved by only asking questions without the reflections. These results support further evolution of the chatbot conversation and can serve as a basis for comparison against more advanced versions.

A qualitative study on stakeholder perceptions of digital prosthetic socket fabrication for transtibial amputations.

BACKGROUND: Digital residual limb shape capture (three-dimensional [3D] scanning), computer-assisted design (CAD), and computer-assisted manufacturing with 3D printing technology show promise for a completely digital process of fabricating prosthetic sockets for patients with limb loss. The effectiveness and quality of digitally designed 3D-printed lower extremity prosthetic sockets is understudied, and there is lack of data on the patient and prosthetist experiences with this digital workflow. OBJECTIVE: To obtain stakeholder feedback on the feasibility and acceptability of using a completely digital prosthetic fabrication process consisting of 3D scanning, CAD, and 3D printing in a rehabilitation setting for adults with transtibial limb amputations. STUDY DESIGN: Qualitative design. METHODS: Study participants with a transtibial-level amputation were fit with a prosthetic socket fabricated using digital shape capture with a 3D scanner, CAD, and 3D printing in addition to a traditionally handcasted manually fabricated socket. Participants tried on and evaluated both sockets. Semistructured interviews took place after the fitting appointments. A focus group was conducted with prosthetists to obtain their feedback. Audio data were transcribed verbatim, and an inductive content analysis was undertaken. RESULTS: Eleven patient participants and 3 prosthetists identified 4 main themes: 1) openness and enthusiasm for digital prosthetic fabrication; 2) relative advantages of digital fabrication vs. traditional socket fabrication; 3) readiness of the technology used for adoption in practice; and 4) digital prosthetic workflow and 3D printing implementation considerations. CONCLUSIONS: Patients and prosthetists were enthusiastic about digital prosthetic socket fabrication and saw potential advantages over traditional methods. Both patients and prosthetists had concerns about the durability, safety, and aesthetics of the 3D printed sockets in this study. Further studies are needed to optimize digital prosthetic fabrication with 3D printing in prosthetic practice.

3D printing and amputation: a scoping review.

PURPOSE: Three-dimensional (3D) printing is an innovative technology being utilized to create prostheses for individuals with limb loss. However, there is a paucity of research on the feasibility of using this technology to fabricate prostheses. A scoping review was conducted to map the literature on 3D printing and its applications in the field of amputation. MATERIALS AND METHODS: Using a scoping review framework, a systematic literature search was conducted in three electronic databases (MEDLINE, EMBASE and CINAHL) for all indexed literature up to 29 June 2018. RESULTS: Twenty-eight articles met the inclusion criteria. The majority of studies had small sample sizes (five participants or less; n = 20) and used a case study design (n = 17). The benefits of 3D printing technology include higher levels of customization and lower production costs. However, the functionality of 3D printed prostheses is lacking. There is also a need for more robust research designs to obtain a better understanding of the advantages and disadvantages of 3D printed prostheses and its impact on end-user outcomes. CONCLUSIONS: The use of 3D printing technology has a number of benefits for improving the manufacturing process of devices for people with lower and upper limb loss. However, more research and technological advancements are required to fully understand the impact of this technology on patients and how it will affect their daily life. The long-term effects of this technology will also need to be investigated in order to produce a more sustainable alternative to traditional prostheses.IMPLICATIONS FOR REHABILITATIONThe use of 3D printing technology for the fabrication of prosthetics for persons with limb-loss has a number of promising features to improve the fitting and customization of these devices for this patient population.Although the costs of producing 3D printed devices is less expensive and burdensome than traditional approaches to manufacturing techniques, there is a need for additional technological advancements to improve the functionality of these devices.Future research needs to adopt more robust research designs with larger sample sizes to provide a better understanding of the viability of using 3D printing technology to improve patient outcomes.

Characterization of a high-resolution breath acetone meter for ketosis monitoring.

BACKGROUND: The ketone bodies beta-hydroxybutyrate (BHB) and acetone are endogenous products of fatty acid metabolism. Although ketone levels can be monitored by measuring either blood BHB or breath acetone, determining the precise correlation between these two measurement methods has been challenging. The purpose of this study is to characterize the performance of a novel portable breath acetone meter (PBAM) developed by Readout, Inc., to compare single versus multiple daily ketone measurements, and to compare breath acetone (BrAce) and blood BHB measurements. METHODS: We conducted a 14-day prospective observational cohort study of 21 subjects attempting to follow either a low-carbohydrate/ketogenic or a standard diet. Subjects were asked to concurrently measure both blood BHB and BrAce five times per day and report the results using an online data entry system. We evaluated the utility of multiple daily measurements by calculating the coefficient of variation (CV) for each daily group of measurements. We calculated the correlation between coincident BrAce and blood BHB measurements using linear ordinary least squares regression analysis. We assessed the ability of the BrAce measurement to accurately predict blood BHB states using receiver operating characteristic (ROC) analysis. Finally, we calculated a daily ketone exposure (DKE) using the area under the curve (AUC) of a ketone concentration versus time graph and compared the DKE of BrAce and blood BHB using linear ordinary least squares regression. RESULTS: BrAce and blood BHB varied throughout the day by an average of 44% and 46%, respectively. The BrAce measurement accurately predicted whether blood BHB was greater than or less than the following thresholds: 0.3 mM (AUC = 0.898), 0.5 mM (AUC = 0.854), 1.0 mM (AUC = 0.887), and 1.5 mM (AUC = 0.935). Coincident BrAce and blood BHB measurements were moderately correlated with R 2 = 0.57 (P < 0.0001), similar to literature reported values. However, daily ketone exposures, or areas under the curve, for BrAce and blood BHB were highly correlated with R 2 = 0.80 (P < 0.0001). CONCLUSIONS: The results validated the performance of the PBAM. The BrAce/BHB correlation was similar to literature values where BrAce was measured using highly accurate lab instruments. Additionally, BrAce measurements using the PBAM can be used to predict blood BHB states. The relatively high daily variability of ketone levels indicate that single blood or breath ketone measurements are often not sufficient to assess daily ketone exposure for most users. Finally, although single coincident blood and breath ketone measurements show only a moderate correlation, possibly due to the temporal lag between BrAce and blood BHB, daily ketone exposures for blood and breath are highly correlated.

Use of activity theory-based need finding for biomedical device development.

Identifying the appropriate needs for biomedical device design is challenging, especially for less structured environments. The paper proposes an alternate need-finding method based on Cultural Historical Activity Theory and expanded to explicitly examine the role of devices within a socioeconomic system. This is compared to a conventional need-finding technique in a preliminary study with engineering student teams. The initial results show that the Activity Theory-based technique allows teams to gain deeper insights into their needs space.

Design-to-fabricate: maker hardware requires maker software.

As a result of consumer-level 3D printers' increasing availability and affordability, the audience for 3D-design tools has grown considerably. However, current tools are ill-suited for these users. They have steep learning curves and don't take into account that the end goal is a physical object, not a digital model. A new class of "maker"-level design tools is needed to accompany this new commodity hardware. However, recent examples of such tools achieve accessibility primarily by constraining functionality. In contrast, the meshmixer project is building tools that provide accessibility and expressive power by leveraging recent computer graphics research in geometry processing. The project members have had positive experiences with several 3D-design-to-print workshops and are exploring several design-to-fabricate problems. This article is part of a special issue on 3D printing.