Cognitive Task Analysis Methods Research Articles

Cognitive Task Analysis: Eliciting Expert Cognition in Context

Cognitive Task Analysis (CTA) is a powerful methodological approach that can enhance the rigorous elicitation and documentation of complex cognitive processes within interview-based qualitative research. We provide insights into this set of semi-structured interviewing techniques that we contend have much to offer management researchers who wish to understand the complexities of expert cognition within specific work-related tasks. Distinct from traditional semi-structured interview methods, CTA is designed to identify the knowledge requirements underpinning expertise in complex work domains. First, we present CTA as a robust approach to eliciting complex cognition and note why, when, and where management scholars might best use its techniques. Second, we provide two examples of how CTA methods have been used to research management; specifically, using the Critical Decision Method to explore management in high-stakes environments, and Applied Cognitive Task Analysis to explore global leadership. In ending, we propose greater use of this pragmatic approach in management research and highlight potential avenues for future research that will advance understanding of complex cognition at work.

Cognitive task analysis-driven intelligent steering wheel interaction design

With the increasing levels of intelligence and automation, the relationship between humans and vehicles has evolved from a utilitarian perspective to a partnership. Among the crucial factors for enhancing user experiences are the analysis of driving tasks, the construction of user needs models, and the design of intelligent interfaces. Based on this background, this paper proposes a cognitive task analysis model using intelligent steering wheel information interaction design as the vehicle. The model aims to extract key design elements to assist designers in making design decisions, thereby improving the human-machine cooperation performance of intelligent automobiles and enhancing user perceptual experiences. Firstly, within the context of human-machine cooperation systems, a cognitive task analysis method integrating the SRK model is proposed. By analyzing the behavioral decision characteristics between the vehicle and the user, a framework for the human-machine interface (HMI) logic of the steering wheel and a dynamic layout prototype are established. Secondly, the design of the steering wheel’s HMI interaction is based on an analysis of users’ affective needs and rational physiological characteristics. This paper integrates the analysis of users’ affective needs to identify design elements that align with a high level of user satisfaction. Lastly, the design methodology model is applied to a navigation scenario, resulting in the creation of a steering wheel HMI prototype within a human-machine cooperation system. The prototype is then subjected to a combined subjective and objective experimental analysis, thereby validating the superiority of the steering wheel HMI’s detection indicators over those of the central control HMI and establishing the design pattern for the steering wheel HMI.

Development and optimisation of a mobile app (iMPAKT) for improving person-centred practice in healthcare settings: A multi-methods evaluation study.

To develop and optimise an app (iMPAKT) for improving implementation and measurement of person-centred practice in healthcare settings. Two iterative rounds of testing were carried out based on cognitive task analysis and qualitative interview methods. The System Usability Scale (SUS) was also used to evaluate the app. Quantitative data on task completion and SUS scores were evaluated descriptively, with thematic analysis performed on qualitative data. The MoSCoW prioritisation system was used to identify key modifications to improve the app. Twelve participants took part (eight health professionals and four patient and public involvement representatives). Views on design and structure of the app were positive. The majority of the 16 tasks undertaken during the cognitive task analysis were easy to complete. Mean SUS scores were 73.5/100 (SD: 7.9; range = 60-92.5), suggesting good overall usability. For one section of the app that transcribes patients speaking about their experience of care, a non-intuitive user interface and lack of transcription accuracy were identified as key issues influencing usability and acceptability. Findings from the evaluation were used to inform iterative modifications to further develop and optimise the iMPAKT App. These included improved navigational flow, and implementation of an updated artificial intelligence (AI) based Speech-To-Text software; allowing for more accurate, real-time transcription. Use of such AI-based software represents an interesting area that requires further evaluation. This is particularly apparent in relation to potential for large-scale collection of data on person-centred measures using the iMPAKT App, and for assessing initiatives designed to improve patient experience.

Estimating Cognitive Load in a Mobile Personal Health Record Application: A Cognitive Task Analysis Approach.

Mobile health applications that are designed without considering usability criteria can lead to cognitive overload, resulting in the rejection of these apps. To avoid this problem, the user interface of mobile health applications should be evaluated for cognitive load. This evaluation can contribute to the improvement of the user interface and help prevent cognitive overload for the user. In this study, we evaluated a mobile personal health records application using the cognitive task analysis method, specifically the goals, operators, methods, and selection rules (GOMS) approach, along with the related updated GOMS model and gesture-level model techniques. The GOMS method allowed us to determine the steps of the tasks and categorize them as physical or cognitive tasks. We then estimated the completion times of these tasks using the updated GOMS model and gesture-level model. All 10 identified tasks were split into 398 steps consisting of mental and physical operators. The time to complete all the tasks was 5.70 minutes and 5.45 minutes according to the updated GOMS model and gesture-level model, respectively. Mental operators covered 73% of the total fulfillment time of the tasks according to the updated GOMS model and 76% according to the gesture-level model. The inter-rater reliability analysis yielded an average of 0.80, indicating good reliability for the evaluation method. The majority of the task execution times comprised mental operators, suggesting that the cognitive load on users is high. To enhance the application's implementation, the number of mental operators should be reduced.

Adapting Cognitive Task Analysis Methods for Use in a Large Sample Simulation Study of High-Risk Healthcare Events.

Cognitive task analysis (CTA) methods are traditionally used to conduct small-sample, in-depth studies. In this case study, CTA methods were adapted for a large multi-site study in which 102 anesthesiologists worked through four different high-fidelity simulated high-consequence incidents. Cognitive interviews were used to elicit decision processes following each simulated incident. In this paper, we highlight three practical challenges that arose: (1) standardizing the interview techniques for use across a large, distributed team of diverse backgrounds; (2) developing effective training; and (3) developing a strategy to analyze the resulting large amount of qualitative data. We reflect on how we addressed these challenges by increasing standardization, developing focused training, overcoming social norms that hindered interview effectiveness, and conducting a staged analysis. We share findings from a preliminary analysis that provides early validation of the strategy employed. Analysis of a subset of 64 interview transcripts using a decompositional analysis approach suggests that interviewers successfully elicited descriptions of decision processes that varied due to the different challenges presented by the four simulated incidents. A holistic analysis of the same 64 transcripts revealed individual differences in how anesthesiologists interpreted and managed the same case.

"What brought you in today?": Modeling patient-provider clinic visits to characterize rural providers' antibiotic treatment decisions.

Designing clinical decision support (CDS) tools is challenging because clinical decision-making must account for an invisible task load: incorporating non-linear objective and subjective factors to make an assessment and treatment plan. This calls for a cognitive task analysis approach. The objectives of this study were to 1.) understand healthcare providers' decision making during a typical clinic visit, and 2.) explore how antibiotic treatment decisions are made when they arise. Two cognitive task analysis methods were applied - Hierarchical Task Analysis (HTA) and Operations Sequence Diagramming (OSD) - to 39h of observational data collected at family medicine, urgent care, and emergency medicine clinical sites. The resulting HTA models included a coding taxonomy detailing ten cognitive goals and associated sub-goals and demonstrated how the goals occur as interactions between the provider and electronic health record, the patient, and the physical clinic environment. Although the HTA detailed resources for antibiotic treatment decisions, antibiotics were a minority of drug classes ordered. The OSD shows the sequence of events and when decisions are made solely at the provider level and when shared decision making occurs with the patient. Qualitative data from the observations informed a constructed vignette case example portraying select tasks from the HTA. These findings emphasize that the scope of disease states presenting to a generalist clinical setting is broad and could include acute exacerbations of rare diseases within a time-pressured environment. CDS must be accessible, time efficient, and fit within the resource gathering task before treatment decisions are made.

Effect of a Template Case Report Based on Cognitive Task Analysis on Emergency Thinking Ability of Resident Doctors in Standardized Training.

ObjectiveTo explore the effect of a template case report based on cognitive task analysis on the emergency thinking ability of resident doctors in standardized training.MethodsThe doctors were split into two groups, according to the date they joined the emergency department (n = 40, each group): the observation and control groups. In the observation group, the resident doctors’ teachers in standardized training adopted the cognitive task analysis method to determine the primary links of emergency thinking, made case templates, and carried out training based on the case template report. In the control group, traditional teaching methods were used by the teachers.ResultsIn the observation and control groups, the scores at departure were 88.10 ± 3.88 and 75.23 ± 7.19, respectively (P < 0.05), and the student’s ability improvement rates were 92.5% and 75.0% (P < 0.01). In addition, the awareness rate of “know how to study” and “know how to work in emergency” in the observation group was 90% and 90%, respectively. The rate of doctors that considered “missed diagnosis and misdiagnosis can be reduced” was 85%, and the rate of doctors that considered “help to learn in other departments in the future” was 80%.ConclusionTemplate case reports based on the cognitive task analysis for emergency thinking training can help resident doctors in standardized training improve their emergency thinking ability.

Cognitive Task Analysis of Unmanned Aircraft System Pilots

ABSTRACT Objective: Unmanned Aircraft System (UAS) pilots must possess a variety of cognitive skills in order to successfully perform diverse missions. They must accurately assess situations, make judgments and decisions, understand cues that may not be immediately obvious, and develop effective solutions. How may we gain perspective on how UAS pilots make decisions when higher order cognitive skills are needed to solve problems and accomplish their missions? Background: Previous UAS task analyses, both behavioral and cognitive, have seldom examined experienced, high-hour UAS operators. It is important to know how these pilots address and solve problems to improve training and design. METHOD: The Applied Cognitive Task Analysis method (ACTA) was utilized to define and examine a sampling of the cognitive task requirements of operating a civilian UAS. The task analysis included sixteen UAS journeymen and expert pilots who had between 240 and 2000 + hours of experience. Tasks such as communication, search and rescue mission planning, coping with equipment malfunction, and developing situational awareness of their environment were analyzed. Result: The analysis produced six task diagrams, which identified key cognitive considerations, captured pilot insights after flying simulated missions, and documented examples where pilots used their expertise to solve operational problems. Conclusion: This ACTA method and resulting products may contribute to the design of new training courses/programs for novice UAS pilots.

Analysis of the cognitive demands of electronic health record use

The goal of this study was to elicit the cognitive demands facing clinicians when using an electronic health record (EHR) system and learn the cues and strategies expert clinicians rely on to manage those demands. This study differs from prior research by applying a joint cognitive systems perspective to examining the cognitive aspects of clinical work. We used a cognitive task analysis (CTA) method specifically tailored to elicit the cognitive demands of an EHR system from expert clinicians from different sites in a variety of inpatient and outpatient roles. The analysis of the interviews revealed 145 unique cognitive demands of using an EHR, which were organized into 22 distinct themes across seven broad categories. In addition to confirming previously published themes of cognitive demands, the main emergent themes of this study are: 1) The EHR does not help clinicians develop and maintain awareness of the big picture; 2) The EHR does not support clinicians’ need to reason about patients’ current and future states, including effects of potential treatments; and 3) The EHR limits agency of clinicians to work individually and collaboratively. Implications for theory and EHR design and evaluation are discussed.

Combining Cognitive Task Analysis and Participatory Design Methods to Elicit and Represent Task Flows

Representations of step-by-step procedures, such as task flows, are developed and used to support technology design and evaluation as well as for training purposes in complex work domains. However, task flows may not represent how people carry out work under uncertainty, time pressure, or high-risk conditions. We combined methods of cognitive task analysis and participatory design, resulting in a new approach for developing task flows. This approach accounts for both cognitive and behavioral work and explicitly represents its dynamic nature. Additional advantages of this approach include flexibility and adaptiveness to help overcome challenges of conducting research in real-world domains, including time constraints and access to subject matter experts. We demonstrate this approach in the context of developing a task flow for a submarine watch team’s use of an updated imaging system to maintain the ship’s safety by forming and maintaining a picture of the external environment. We provide a detailed description of each phase as well as a domain-neutral ready-to-use job aid.

Integrating Cognitive Task Analysis in a PhD-Level Applied Health Sciences Qualitative Methods Course

We discuss the integration of naturalistic decision making theoretical perspective and cognitive task analysis methods (CTA) in a PhD level qualitative methods courses offered to applied health sciences students. Students planned and executed a mini CTA project that included identification of a research question, development of a proposal with an interview guide, recruitment of participants, data collection and analysis, and documentation. We share a reading list and discuss the benefits and challenges of offering this course project.

Expert knowledge elicitation in the firefighting domain and the implications for training novices

Background/PurposeExperienced firefighters often make important decisions in fast-paced fire ground environments characterised by uncertainty and evolving conditions, mostly under considerable time-pressure. The nature of these environments inadvertently presents firefighters with novel situations that occasionally challenge their expertise, subsequently necessitating a reliance on intuitive as opposed to rational decisions. The purpose of this study is to elicit the tacitly held knowledge and intuitive thought processes that were used by 31 experts while managing a range of complex, non-routine fire incidents.Design/Methodology/ApproachThe study used a formal knowledge elicitation technique known as the critical decision method (CDM). CDM is a qualitative strategy that applies a set of cognitive probes to explore the cognitive processes that aid the performance of a complex task. This method was preferred to other cognitive task analysis methods as it specifically favours the use of retrospective incident accounts and incidents that were both challenging and memorable. Using the full CDM protocol, 31 experienced firefighters were interviewed across various fire stations in the UK and Nigeria (UK = 15, Nigeria = 16). The interview transcripts were coded, categorised and analysed using the emergent themes analysis approach.FindingsThe results from the study identified 134 decision points across the 31 incident accounts. A total of 42 salient cues sought by experts at each decision point were revealed and organised into a critical cue inventory. The identified cues were subsequently categorised into five distinct types based on the type of information each cue relayed to an incident commander. The study further developed a decision-making model – information filtering and intuitive decision-making model – that describes how experienced firefighters made difficult fire ground decisions amidst multiple informational sources. The model ultimately showed experts’ preferences for intuitive decisions as the default-thinking mode, with deliberation only required on few instances as conditions warranted. The study also compiled and indexed the cognitive strategies elicited from the expert firefighters into a competence assessment framework.Practical ImplicationsIn light of existing debate about the accessibility of expert knowledge, the current study not only provides empirical evidence detailing the practical application of the CDM as a formal knowledge elicitation method but also delineates a range of cognitive outputs from the elicitation process that ultimately holds relevance for knowledge transfer from expert to novices. The study identified a range of training needs and discussed the practical implications of transferring expert knowledge into learning tasks that could subsequently aid the cognitive development of novices. In particular, the study proposed adopting the four-component instructional design model in organising the CDM outputs for training purposes.Originality/ValueWhile it is generally taken that experts, because of their extensive domain knowledge and well-developed schema, often perform considerably (and sometimes exceptionally) well when solving complex problems, finding a credible and objective method to model what experts know and do continues to pose a challenge, particularly when such revelation is crucially required for training purposes. This study is therefore timely since its tacit and intuitive knowledge outputs can now be applied to enhance the development of training curricula for novices. The learning tasks developed from the CDM outputs are hoped to facilitate organisational learning not only within the firefighting domain but also across other high reliability organisations. It is extremely important that expert knowledge is preserved in these domains especially in countries such as the UK, where the rate of real fires has been on decline, which in turn suggests that the quality of experiential knowledge required to manage complex non-routine fire cases may also be on decline. The current study also presents and discusses insights based on the cultural differences observed between the UK and the Nigerian fire services.

UAS integration in congested terminal airspace: challenges posed to pilots

There is increasing demand to operate unmanned aircraft systems (UAS) in congested terminal environments, such as busy commercial airports. With this demand comes challenges to pilots. To identify these challenges, we conducted critical decision method (CDM) interviews with pilots. CDM is a cognitive task analysis method aimed at uncovering tacit cognitive challenges. Eight pilots from the U.S. were interviewed including four UAS pilots and four commercial pilots. Interviews were analyzed using thematic analysis, resulting in the identification of four categories of cognitive challenges: (i) noticing anomalies, (ii) diagnosing automation behavior, (iii) understanding when and how to intervene, and (iv) coordinating with air traffic control. In this paper, we describe each challenge, highlight real-world examples from our interviews, and provide some recommendations for addressing the implications of integrating UAS in congested terminal airspace.

Cognitive Task Analysis Methods in Envisioned Tactical Command Decision Making

The battlespace is a volatile and complex environment in which tactical commanders face cognitively challenging responsibilities, compounded with the increased complexity of emerging cyber warfare. It is critical that tactical commanders gain adequate situation awareness for effective decision making to achieve mission success. While current tools enable distribution of large quantities and types of information, they do not adequately support the underlying cognitive work and information needs of tactical commanders. We performed a domain analysis using Cognitive Task Analysis methods, developing a prototypical operational scenario representative of current and envisioned environments, centered on a cyber-attack. Using this analysis, we identified cognitive and information requirements for information displays that support effective tactical decision making. Tactical commanders need to understand dynamic situations in the field, understand the viable courses of actions, know how their mission fits into the larger mission, and communicate with their company subordinates and higher echelons of command.

The Cognitive Process of Wildland Fire Chainsaw Troubleshooting: Structure, Content, and Training

Wildland firefighting often involves the creation of a fireline (a break in vegetative fuels), an operation commonly hindered by the break-down of gas-powered chainsaws. Some firefighters may not possess the knowledge and skills needed to address break-downs quickly, which threatens productivity and safety. The Applied Cognitive Task Analysis method was used to examine the troubleshooting process of an expert wildland fire sawyer. This included elicitations of key steps in this process, specific pieces of valuable knowledge, and sources of expertise. These results show that much of the expert understanding of complex faults was developed on-the-job rather than during a formal training program. This study highlights areas where training and job aids may be improved to support wildland firefighters in chainsaw troubleshooting and provides preliminary support of ACTA as a tool for training specialists in this domain.

An Opportunity for Cognitive Task Analysis in Neonatal Resuscitation.

Approximately 10% of newborn infants require resuscitative intervention at birth. Ideally, this care is provided by a team of expert healthcare professionals who possess exceptional cognitive, psychomotor, and communication skills. Human errors and deviations from resuscitation protocol are common and may be attributable to excessive cognitive demand experienced by the resuscitation team. Cognitive Task Analysis (CTA) is a group of methods used to assess knowledge, judgments, goals, and decision-making of expert healthcare professionals. These methods may be used during neonatal resuscitation to gain an improved understanding of the approaches used by healthcare professionals. CTA methods have been applied in many medical disciplines including neonatology. CTA has been used to identify information previously confined to the intuition of experts. This information has been used to assess, develop, and improve medical technology, clinical decision support tools (DSTs), communication structure, and training methods. Knowledge attained through CTA might be applied similarly to neonatal resuscitation, which may in turn decrease human errors, and improve patient safety.

How well do software assistants for minimally invasive partial nephrectomy meet surgeon information needs? A cognitive task analysis and literature review study.

IntroductionIntraoperative software assistance is gaining increasing importance in laparoscopic and robot-assisted surgery. Within the user-centred development process of such systems, the first question to be asked is: What information does the surgeon need and when does he or she need it? In this article, we present an approach to investigate these surgeon information needs for minimally invasive partial nephrectomy and compare these needs to the relevant surgical computer assistance literature.Materials and methodsFirst, we conducted a literature-based hierarchical task analysis of the surgical procedure. This task analysis was taken as a basis for a qualitative in-depth interview study with nine experienced surgical urologists. The study employed a cognitive task analysis method to elicit surgeons' information needs during minimally invasive partial nephrectomy. Finally, a systematic literature search was conducted to review proposed software assistance solutions for minimally invasive partial nephrectomy. The review focused on what information the solutions present to the surgeon and what phase of the surgery they aim to support.ResultsThe task analysis yielded a workflow description for minimally invasive partial nephrectomy. During the subsequent interview study, we identified three challenging phases of the procedure, which may particularly benefit from software assistance. These phases are I. Hilar and vascular management, II. Tumour excision, and III. Repair of the renal defects. Between these phases, 25 individual challenges were found which define the surgeon information needs. The literature review identified 34 relevant publications, all of which aim to support the surgeon in hilar and vascular management (phase I) or tumour excision (phase II).ConclusionThe work presented in this article identified unmet surgeon information needs in minimally invasive partial nephrectomy. Namely, our results suggest that future solutions should address the repair of renal defects (phase III) or put more focus on the renal collecting system as a critical anatomical structure.

Development of a Clinical Interface for a Novel Newborn Resuscitation Device: Human Factors Approach to Understanding Cognitive User Requirements.

BackgroundA novel medical device has been developed to address an unmet need of standardizing and facilitating heart rate recording during neonatal resuscitation. In a time-critical emergency resuscitation, where failure can mean death of an infant, it is vital that clinicians are provided with information in a timely, precise, and clear manner to capacitate appropriate decision making. This new technology provides a hands-free, wireless heart rate monitoring solution that easily fits the clinical pathway and procedure for neonatal resuscitation.ObjectiveThis study aimed to understand the requirements of the interface design for a new device by using a human factors approach. This approach combined a traditional user-centered design approach with an applied cognitive task analysis to understand the tasks involved, the cognitive requirements, and the potential for error during a neonatal resuscitation scenario.MethodsFourteen clinical staff were involved in producing the final design requirements. Two pediatric doctors supported the development of a visual representation of the activities associated with neonatal resuscitation. This design was used to develop a scenario-based workshop. Two workshops were carried out in parallel and involved three pediatric doctors, three neonatal nurses, two advance neonatal practitioners, and four midwives. Both groups came together at the end to reflect on the findings from the separate sessions.ResultsThe outputs of this study have provided a comprehensive description of information requirements during neonatal resuscitation and enabled product developers to understand the preferred requirements of the user interface design for the device. The study raised three key areas for the designers to consider, which had not previously been highlighted: (1) interface layout and information priority, as heart rate should be central and occupy two-thirds of the screen; (2) size and portability, to enable positioning of the product local to the baby’s head and allow visibility from all angles; and (3) auditory feedback, to support visual information on heart rate rhythm and reliability of the trace with an early alert for intervention while avoiding parental distress.ConclusionsThis study demonstrates the application of human factors and the applied cognitive task analysis method, which identified previously unidentified user requirements. This methodology provides a useful approach to aid development of the clinical interface for medical devices.

PARTICIPATORY BULLSEYE TOOLKIT INTERVIEW: IDENTIFYING PHYSICIANS' RELATIVE PRIORITIZATION OF DECISION FACTORS WHEN ORDERING RADIOLOGIC IMAGING IN A HOSPITAL SETTING.

Critical Decision Method (CDM), a popular cognitive task analysis (CTA) method, is an in-depth retrospective interview that uses a historical non-routine incident to identify experts' decision-making factors in complex socio-technical settings with high consequences for failure. However, it is challenging to use CDM to make comparisons, including those between experts and trainees. We describe an alternative CTA method used to study physicians' decision making for ordering diagnostic imaging. After being primed with 11 simulated patient scenarios, nine attending and 11 resident physicians were asked to map out and present their decision-making process with a bullseye participatory design toolkit. Interviews were analyzed qualitatively, revealing four common decision factors: diagnostic efficacy, patient safety, organizational constraints, and patient comfort. The bullseye maps were used to quantitatively measure priority differences between these decision factors. Attending and resident physicians both prioritized diagnostic efficacy over the other factors (2.38 vs. 3.71, p <.01, and 2.59 vs. 3.52, p<.01, respectively), but attending physicians' decisions had a higher proportion of non-diagnostic items (65% vs. 50%, p = .008). Our results demonstrate the usefulness of this method in eliciting decision factors for a complex, face-valid task and for identifying differences due to levels of expertise and training.

Incorporating Guideline Adherence and Practice Implementation Issues into the Design of Decision Support for Beta-Blocker Titration for Heart Failure.

The recognition of and response to undertreatment of heart failure (HF) patients can be complicated. A clinical reminder can facilitate use of guideline-concordant β-blocker titration for HF patients with depressed ejection fraction. However, the design must consider the cognitive demands on the providers and the context of the work. This study's purpose is to develop requirements for a clinical decision support tool (a clinical reminder) by analyzing the cognitive demands of the task along with the factors in the Cabana framework of physician adherence to guidelines, the health information technology (HIT) sociotechnical framework, and the Promoting Action on Research Implementation in Health Services (PARIHS) framework of health services implementation. It utilizes a tool that extracts information from medical records (including ejection fraction in free text reports) to identify qualifying patients at risk of undertreatment. We conducted interviews with 17 primary care providers, 5 PharmDs, and 5 Registered Nurses across three Veterans Health Administration outpatient clinics. The interviews were based on cognitive task analysis (CTA) methods and enhanced through the inclusion of the Cabana, HIT sociotechnical, and PARIHS frameworks. The analysis of the interview data led to the development of requirements and a prototype design for a clinical reminder. We conducted a small pilot usability assessment of the clinical reminder using realistic clinical scenarios. We identified organizational challenges (such as time pressures and underuse of pharmacists), knowledge issues regarding the guideline, and information needs regarding patient history and treatment status. We based the design of the clinical reminder on how to best address these challenges. The usability assessment indicated the tool could help the decision and titration processes. Through the use of CTA methods enhanced with adherence, sociotechnical, and implementation frameworks, we designed a decision support tool that considers important challenges in the decision and execution of β-blocker titration for qualifying HF patients at risk of undertreatment.