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Communication interventions in adult and pediatric oncology: A scoping review and analysis of behavioral targets

  • Bryan A. Sisk ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Department of Pediatrics, Division of Hematology/Oncology, Washington University School of Medicine, St. Louis, Missouri, United States of America

  • Ginny L. Schulz,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Writing – review & editing

    Affiliation Department of Pediatrics, Division of Hematology/Oncology, Washington University School of Medicine, St. Louis, Missouri, United States of America

  • Jennifer W. Mack,

    Roles Conceptualization, Methodology, Supervision, Writing – review & editing

    Affiliation Pediatric Oncology and Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts; and Division of Pediatric Hematology/Oncology, Boston Children’s Hospital, Boston, Massachusetts, United States of America

  • Lauren Yaeger,

    Roles Data curation, Investigation, Methodology, Writing – review & editing

    Affiliation Becker Library, Washington University School of Medicine, St. Louis, MO, United States of America

  • James DuBois

    Roles Conceptualization, Methodology, Supervision, Visualization, Writing – review & editing

    Affiliation Department of Medicine, Division of General Medical Sciences, Washington University School of Medicine, St. Louis, Missouri, United States of Ameica

Communication interventions in adult and pediatric oncology: A scoping review and analysis of behavioral targets

  • Bryan A. Sisk, 
  • Ginny L. Schulz, 
  • Jennifer W. Mack, 
  • Lauren Yaeger, 
  • James DuBois



Improving communication requires that clinicians and patients change their behaviors. Interventions might be more successful if they incorporate principles from behavioral change theories. We aimed to determine which behavioral domains are targeted by communication interventions in oncology.


Systematic search of literature indexed in Ovid Medline, Embase, Scopus, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, (2000–October 2018) for intervention studies targeting communication behaviors of clinicians and/or patients in oncology. Two authors extracted the following information: population, number of participants, country, number of sites, intervention target, type and context, study design. All included studies were coded based on which behavioral domains were targeted, as defined by Theoretical Domains Framework.


Eighty-eight studies met inclusion criteria. Interventions varied widely in which behavioral domains were engaged. Knowledge and skills were engaged most frequently (85%, 75/88 and 73%, 64/88, respectively). Fewer than 5% of studies engaged social influences (3%, 3/88) or environmental context/resources (5%, 4/88). No studies engaged reinforcement. Overall, 7/12 behavioral domains were engaged by fewer than 30% of included studies. We identified methodological concerns in many studies. These 88 studies reported 188 different outcome measures, of which 156 measures were reported by individual studies.


Most communication interventions target few behavioral domains. Increased engagement of behavioral domains in future studies could support communication needs in feasible, specific, and sustainable ways. This study is limited by only including interventions that directly facilitated communication interactions, which excluded stand-alone educational interventions and decision-aids. Also, we applied stringent coding criteria to allow for reproducible, consistent coding, potentially leading to underrepresentation of behavioral domains.


Effective communication is essential to optimize the experiences of patients with cancer. However, “effective communication” ca be defined in many ways. In 2007, a National Cancer Institute consortium defined the following six core functions of patient-centered communication in oncology: exchanging information, enabling self-management, making decisions, fostering a healing relationship, responding to emotions, and managing uncertainty.[1] Effectively fulfilling these communication functions has been associated with better mental health and lower healthcare expenditures,[2] as well as improved hope,[3] trust in the oncologist,[4] satisfaction with medical care,[5] and peace of mind.[6] However, a large body of evidence shows that clinicians often fail to fulfill many of these communication functions.[716]

Fulfilling all of these communication functions, however, is a difficult task. It is no surprise that many clinical teams might struggle to effectively communicate with patients and their families. Improving communication in medicine requires that clinicians and patients change their behaviors, sometimes in ways that are unfamiliar or uncomfortable. Many interventions to improve communication have been tested, but with variable success. To develop more successful communication interventions, we propose that investigators begin to view communication as a complex clinician behavior influenced by cognitive, social, economic, and cultural factors.[17, 18]. If viewed in this way, investigators can use the lens of behavioral change domains to identify novel targets for communication interventions, as we have previously argued.[19]

In psychology, models of behavioral change have sought to understand how individuals will behave in certain circumstances by evaluating multiple determinants that affect the behavior of interest. Other complex clinician behaviors, like prescribing practices and compliance with antibiotic stewardship, have been amenable to behavioral change theories.[20, 21] However, investigators have not rigorously or specifically applied these concepts to communication behaviors. We propose that investigators should further incorporate principles from the psychology of behavior change into the conceptualization and design of communication interventions.

More than 80 theories of behavioral change have been published, each with different strengths and weaknesses.[22] The Theoretical Domains Framework (TDF) was developed to consolidate multiple theories and theoretical constructs into a single framework with 14 domains. As described by Atkins, et al., TDF resulted from “a collaboration of behavioral scientists and implementation researchers who identified theories relevant to implementation and grouped constructs from these theories into domains. The collaboration aimed to provide a comprehensive, theory-informed approach to identify determinants of behavior.”[23] TDF is a theoretical framework that “provides a theoretical lens through which to view the cognitive, affective, social and environmental influences on behavior.”[23] TDF has been applied to several areas of clinical practice, including adherence to surgical best practices,[24] opioid prescription,[25] and reporting of medication errors by clinicians,[26] among many others. TDF can also serve as a lens for identifying potential levers for changing communication behaviors.

In this article, we report the results of a scoping review focused on recent communication interventions in pediatric and adult oncology, posing the question “Which domains of behavioral change are targeted by communication intervention studies in oncology?” While several previously published review articles have focused on specific modalities of communication interventions, no review has broadly evaluated the full field of communication interventions, nor has any review evaluated which behavioral domains are targeted by interventions. By identifying these behavioral domains, we aimed to highlight areas for further innovation in the development of communication interventions.


We conducted a systematic search and scoping review following recently published Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for scoping reviews.[27] We did not register a review protocol. For the PRSMA scoping review checklist, see S1 Checklist.

Data sources and searches

A medical librarian (LHY) searched published literature for the concepts of ‘oncology patients’, ‘clinical communication’, ‘communication skills’, and ‘training interventions’. Due to the broad nature of search terms used to capture these concepts the search was built for specificity using major focus controlled vocabulary terms, proximity searching, and keywords in Ovid Medline 1946-, Embase 1947-, Scopus 1823-, Cochrane Database of Systematic Reviews (CDSR), Cochrane Central Register of Controlled Trials (CENTRAL), 1997-, The Cumulative Index to Nursing and Allied Health Literature (CINAHL) 1937-, and PsycINFO 1800s -. Fully reproducible search strategies for each database are presented in Table 1.

Study selection

This review was inclusive of research articles presenting original data on interventions to facilitate communication between clinicians and patients (or parents of pediatric patients) in oncology. Exclusion criteria included: manuscripts published in non-English language; not an intervention; not focused on communication related to cancer; not focused on actual or potential clinical encounter (i.e. cancer scenario used for training with non-oncology professionals or students); abstract or conference presentation; protocol only without results; no pre/post assessment or control comparison pertinent to communication functions or outcomes; secondary analysis of previously published intervention; published prior to year 2000; not targeting either patients or clinicians who primarily see cancer patients; study sample with fewer than 30 participants. We focused on articles published after 2000 to narrow focus to the current state of the field. We utilized the cutoff of 30 participants as an initial screen of quality, anticipating that studies with fewer than 30 participants would be pilot studies with limited external validity. If a study included clinicians and patients, we used the larger number to determine eligibility. For example, if a study included 10 clinicians, but assessed outcomes of 40 patients, we included this study in analysis. One author (BAS) screened study titles and abstracts prior to detailed review of full text. After full text review, this author excluded studies that did not meet the inclusion/exclusion criteria.

Data synthesis and analysis

All included articles were coded based on (1) which core functions of patient-clinician communication each study addressed, and (2) which behavioral domains each intervention directly engaged, using definitions provided in Table 2. Coding definitions for communication functions were based on definitions initially described by Epstein and Street in 2007,[1] and previously modified and employed by our group in two prior publications.[28, 29] Definitions for behavioral domains were based on the refined Theoretical Domains Framework definitions published in 2012.[30] Of the 14 total domains listed in the Theoretical Domains Framework, we excluded “memory, attention, and decision process” and “optimism” after the authorship group determined that these domains were less relevant to communication. Definitions were refined after coding the first 10 articles by two reviewers (BAS and GLS). These final definitions were agreed upon by all authors. For each article, these reviewers assigned one or more codes for communication functions and behavioral domains targeted by the intervention, meaning that one article could be coded as targeting multiple communication functions and behavioral domains. Agreement was good for all categories of communication functions (mean kappa for agreement = 0.82, range 0.72 to 0.89) and behavioral domains (mean kappa for agreement = 0.87, range 0.78 to 0.93). Discrepancies were resolved by consensus between the two reviewers.

Table 2. Definitions of communication functions and behavioral domains.

Two authors (BAS and GLS) extracted the following information from included studies: population, whose behavior was targeted by interventions, number of study participants, type of intervention, study design, context of clinical communication, country, and number of sites. One author (BAS) subsequently extracted the following additional information: outcome measures utilized, positive and null outcomes reported, whether primary outcome was defined within article, and technology utilized by interventions. Notably, if an article performed statistical analyses on every question within a scale, we still counted the entire scale as a single outcome measure. We applied the same approach to studies that performed statistical analyses on the coding of multiple individual behaviors in recorded interactions. All data was charted independently in Excel spreadsheets by two authors (BAS and GLS).

Role of the funding source

Financial support for this study was provided in part by grants from National Center for Advancing Translational Sciences of the National Institutes of Health and the American Society of Clinical Oncology Young Investigator’s Award. The funding agreements ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.


All search strategies were created and run in October 2018 finding a total of 3,692 records. Using Endnote’s automatic duplication finder 1,416 records were removed. An additional 97 duplications were removed leaving a total of 2,179 unique citations included in the project library. This search was supplemented by manual searching through reference lists and review articles, which yielded an additional 10 articles. (Fig 1) After exclusions, 88 articles remained for analysis.

Study characteristics

Complete details of study characteristics are presented in Table 3. Eighty percent (70/88) of studies were performed in North America or Western Europe, with another 12% (11/88) in Australia/New Zealand, and 8% (7/88) in Asia. We did not identify any studies from Eastern Europe, South America, Latin America, or Africa. While 34% (30/88) of these studies were performed at a single institution, at least 22% (20/88) included 5 or more institutions. Notably, 25% (22/88) of studies reported “multiple” institutions in the methods, but did not specify the number of participating institutions. The number of clinician participants ranged from 7 to 518, with a median of 57. The number of patient participants ranged from 32 to 2314, with a median of 206. Notably, studies almost exclusively targeted adult oncology clinicians and patients (97%, 85/88). Only 3/88 studies included pediatric and adult oncology clinicians, and no studies specifically targeted communication in pediatric or adolescent oncology.

Fifty-nine percent (52/88) of studies employed randomized controlled trial (RCT) study designs, with most of the remainder employing quasi-experimental pre/post assessment methodology (38%, 33/88). The majority of studies (68%, 59/88) employed communication skills training/communication educational curricula. Only 7% (6/88) of studies employed multimodal interventions (e.g. communication skills training and question prompt lists utilized in the same study), with the remaining 93% (82/88) of studies employing unimodal interventions. Only 17 studies (19%) utilized technology to facilitate communication, beyond utilizing audio- and video-recordings to evaluate interventions. Most of these interventions targeted patients: video preparation for patients prior to consultation,[38, 41, 81, 102] providing patients with recordings of consultations,[73, 81] computer-assisted needs assessment, symptom monitoring, and/or question prompt sheet,[37, 50, 55, 59, 67, 71, 81] web-based decision-support intervention,[56] communication coaching via telephone,[108] and integration of interventions into the electronic medical record.[59] Some technological interventions also targeted clinicians: computer-assisted communication training for clinicians [40, 72, 74] or delivering communication skills training via teleconference.[107]

The context of communication in all included articles was mostly “general” communication without further specification within the article (50%, 43/88). The remainder were distributed among the following topics: end of life/palliative care (14%, 13/88), cancer treatment/decision making (12%, 11/88), new diagnosis/prognosis (9%, 8/87), pain/symptom management (8%, 7/88), clinical trial enrollment (7%, 6/88).

Communication functions targeted

We found evidence that all 6 communication functions were targeted by studies included in this review. The frequency with which these studies targeted the 6 communication functions ranged from 77% (68/88) for exchanging information to 15% (13/88) for enabling self-management. (Fig 2) Notably, 8% (7/88) articles did not provide sufficient methodological information to determine which communication functions were targeted.

Fig 2. Percentage of interventions targeting each communication function.

Each study was considered a single intervention; therefore, percentage represents percentage of total studies included in this review.

Behaviors and behavioral domains

Interventions targeted the behaviors of individuals with a wide variety of roles, with 31% targeting physicians (23/88 attending physicians and 4/88 fellows), 20% (18/88) targeting nurses, 15% (13/88) targeting multiple healthcare team members, 15% (13/88) targeting members of the healthcare team and the patient, and 18% (16/88) targeting the patient.

Interventions varied widely in which behavioral domains they engaged. (Fig 3) While knowledge and skills were engaged most frequently (85%, 75/88 and 73%, 64/88, respectively), fewer than 5% of studies engaged social influences (3%, 3/88) or environmental context/resources (5%, 4/88). No studies engaged reinforcement. Overall, 7 of these 12 behavioral domains were engaged by fewer than 30% of included studies.

Fig 3. Percentage of interventions targeting each behavioral domain.

Each study was considered a single intervention; therefore, percentage represents percentage of total studies included in this review.

Complete details regarding communication functions, behavioral domains, and study outcomes for each study are available in Table 4.

Characteristics of study outcomes

In total, these 88 studies reported on 188 different outcome measures. Of these 188 outcome measures, 156 measures were only used by individual studies, 14 were used by 2 studies, 9 were used by 3 studies. Four outcome measures were used by more than 5 studies, including Hospital Anxiety and Depression Scale (used in 13 studies), State-Trait Anxiety scale (used in 11 studies), EORTC Quality of Life questionnaire (used in 8 studies), and Cancer Research Campaign Workshop Evaluation Manual for coding strategies (used in 6 studies). For most studies, outcomes were assessed at a single time point immediately after the intervention (61%, 54/88). The remaining thirty-nine percent (34/88) of studies evaluated outcomes at least 1 week after the intervention (ranging from 1 week to 6 years post-intervention). Twenty-six percent (23/88) of studies evaluated outcomes at multiple time points beyond the baseline assessment– 19% (17/88) evaluated outcomes at 2 time points beyond baseline, and 7% (6/88) evaluated at 3 time points beyond baseline.

Eleven studies (13%) reported all null outcomes. Of these 11 studies, 6 employed communication skills training interventions,[66, 88, 93, 94, 96, 101] one provided patients with their medical records,[100] one engaged thought leaders at institutions to institute changes in communication behaviors of surgeons,[36] one utilized patient needs assessments prior to clinic encounters,[108] one employed a patient-directed educational intervention,[81] and one employed a multimodal intervention with communication skills training, value elicitation, and a clinical question guide.[59] The remaining 77 studies (87%) reported at least 1 positive outcome, and 70 studies (79%) reported at least 1 null outcome. However, only 42 articles (48%) identified a primary outcome of the study. Of 52 randomized-controlled trials, only 17 (33%) explicitly identified a single primary outcome of the study. Furthermore, several studies performed hypothesis testing on individual questions from measures or individual skills that were observed, often without alpha-correction for multiple comparisons. This resulted in as many as 42 separate hypothesis tests in a single study, of which some were statistically significant.[61]


This extensive scoping review has highlighted two generalizable lessons for the broader field of communication research in medicine. First, there is a need for further innovation in the development of interventions. For example, 7 of 12 behavioral domains were infrequently targeted by studies included in this review. “Environmental context/resources” and “social influences” were targeted by 3% of studies, and “reinforcement” was not targeted by any studies. These untapped domains represent additional behavioral levers that future interventions could target. For example, an intervention that engaged administrators in modifying performance evaluation based on communication outcomes (though practically challenging) could strongly target “reinforcement.” Open reporting of patients’ evaluations of communication might target “social and professional role/identity.” Utilizing cultural liaisons to facilitate communication with minority patients might engage the “social” domain of behavioral change. By considering these behavioral domains when developing interventions, investigators stand a better chance of supporting durable changes in communication behavior.

The narrow behavioral focus reflects the predominant utilization of unimodal interventions, primarily communication skills training sessions. While education is important, it is often insufficient to lead to persistent behavioral change. The need for additional levers of change beyond education is the conceptual basis for all behavioral change models, quality improvement scholarship, and the field of dissemination and implementation science.[30, 119] Even motivated clinicians will falter if institutional norms and practices create barriers to effective communication, such as clinic scheduling practices, large patient volumes, and clinicians’ time constraints.[120124] To overcome these barriers, future interventions should use multimodal approaches to target multiple behavioral domains. For example, an intervention might address clinic workflow issues that waste time, while also providing communication skills training and question prompt lists.

The second generalizable lesson from this review is that methodological features of this communication literature make it challenging to compare studies or determine best practices. For example, these 88 studies utilized 188 different outcome measures, of which 156 were only utilized by individual studies. This great variability in outcome measures makes it difficult to compare results of studies, to interpret the clinical significance of small but statistically significant changes on non-validated measures, and ultimately to determine which studies are truly successful.

These challenges to interpretation are exacerbated by the variability in statistical methods employed by studies; most studies evaluated multiple outcome measures, some of which improved after the intervention. In some cases, every item on a measure or coding scheme was subjected to individual hypothesis testing, with the potential for numerous statistical comparisons within a single study. Alpha correction was seldom employed to account for multiple comparisons. While 11 studies in this review reported all null outcomes, only 18 studies reported all positive outcomes and the remaining 59 studies reported a mix of positive and null outcomes. Given the multiple comparisons, many of the positive findings could be merely results of chance, or could be erroneously positive because of flaws in the non-validated instruments that were employed. Furthermore, most outcomes were also assessed immediately after the intervention with only one comparison time point, thus calling to question the durability of these responses.

For some studies, it is reasonable to develop novel outcome measures, especially if the target of communication is not well represented in other areas of clinical communication (e.g. discussion of complementary and alternative medicine). However, some studies utilized novel measures where validated measures were available (e.g. quality of life, self-efficacy, decision-making preferences). Other methodological problems might be a result of limited resources and funding for such studies. For example, longitudinal follow up is essential to determining the sustainability of improvements in communication, but such follow up can require an infrastructure that exceeds the funding available for such studies.

However, our review has also highlighted several methodological strengths of this literature. First, these studies targeted a broad array of participants in the healthcare encounter, including nurses, doctors, patients, trainees, and combinations of all these. Furthermore, more than half of these interventions were evaluated in randomized controlled trials (RCTs), which provide a higher level of evidence for evaluating communication interventions. Also, greater than two-thirds of studies were multisite trials, which supports generalizability. However, no studies were reported from Eastern Europe, Latin America, South America, or Africa, highlighting a disparity in global communication research.

In terms of methodology and behavioral approach, a small number of exemplar studies stand out. The VOICE trial, for example, employed multimodal interventions including question prompt lists, physician communication training, and patient communication coaching in an RCT.[35] This multimodal intervention targeted 6 of 12 behavioral domains and 5 of 6 communication functions. Similarly, Paladino et al. published another exemplar study that employed multimodal interventions including question prompt lists and communication skills training in an RCT.[59] These interventions targeted 6 of 12 behavioral domains and 4 of 6 communication functions. Furthermore, this study repeated assessments every 2 months for 2 years or until the participant’s death. Despite the high quality of these studies, the results are underwhelming. The VOICE trial resulted in an improvement in a composite communication score that served as the primary outcome. However, this multimodal intervention did not lead to a difference in quality of life, clinicians’ responses to emotions, or provision of prognostic or treatment information. The study by Paladino et al. failed to improve the co-primary outcomes of goal-concordant care and peacefulness at the end of life, as well as the secondary outcomes of therapeutic alliance, depression, or survival. This study did find an improvement in patient-reported of anxiety.

We believe there are several ways to interpret these mostly negative results. First, targeting multiple domains might be ineffective in communication interventions. While this is a possibility, the failure of two studies certainly does not prove this point. Alternatively, characteristics of these studies might explain these negative results. These two studies employed rigorous methodologies and validated outcome measures. As such, these studies did not benefit from surrogate outcome measures or questionable statistical methodologies that might have provided positive outcomes, but little meaning. However, these studies might have failed simply because they did not target the right mix of behavioral levers. As we discussed earlier, workflow challenges might trump the best of intentions.

Future studies might also aim to incorporate advanced technology to facilitate communication. In this review, only 19% of studies incorporated any technology, and most of these uses were rudimentary (i.e. using a telephone to call a patient outside of the clinical encounter). The communication needs of patients can vary widely and may surpass the abilities of any single healthcare team member. As such, future studies should evaluate how some of these needs can be appropriately supported by technological interventions ranging from facilitative technologies (e.g. telemedicine or interactive patient portals) to stand-alone technologies (e.g. adaptive teaching modules or chatbots). For example, perhaps an interactive needs assessment identifies that a patient has many technical questions. But this patient also has concerns about which treatment will best fit his values and preferred lifestyle. If a computer interface can provide sufficient information and education to address the technical issues, then the patient will have more time discuss his values and preferences to appropriately support a shared decision. It is uncertain whether advancing technologies will help or hinder the clinician-patient relationship; this question should be answered with future studies.

Lastly, this scoping review only identified 3 studies that included pediatric clinicians, and no study specifically targeted pediatric or adolescent oncology. Children can vary widely in their cognitive and emotional development, which can affect their communication needs. Also, communication might serve different purposes for parents that are unique from their needs as patients.[28] Given these unique aspects of communicating with children and their parents, future work should aim to develop communication interventions specific to this population.

The results of this review should be considered in light of its limitations. First, we only included interventions that aimed to directly facilitate a communication interaction between a patient/parent and a clinician. As a result, many educational interventions and decision-aids were excluded from analysis. While these stand-alone interventions can be valuable, we were specifically interested in interventions that reinforced and supported the centrality of the clinical encounter. A second limitation was the potential overlap of behavioral domains and communication functions used in coding articles. To maximize consistency, we aimed to limit coding to the domains or functions most directly and explicitly targeted by the intervention without extrapolating to possible downstream effects of the intervention. For example, an educational seminar on communication skills with active practice sessions could potentially bolster “beliefs about capabilities” via “knowledge” and “skills”, however, we determined that availability of feedback for participants was an integral component of understanding one’s capabilities. Therefore, such a communication intervention would only be coded as targeting “beliefs about capabilities” if the workshop included feedback to participants. Similarly, if a training workshop included passive learning but no opportunity for active practicing of skills, we coded such interventions as targeting “knowledge” but not “skills.” These stringent criteria allowed for reproducible, consistent coding, but it is possible that more behavioral domains were engaged than we reported. Furthermore, we intentionally coded behavioral domains based on the description of the intervention provided in the manuscripts or supporting materials. In other words, we strove to avoid making assumptions about what domains an intervention was targeting when detail in the manuscript was insufficient. To illustrate, consider the domain “social/professional role and identity.” Some manuscripts provided sufficient details about the contents of the communication skills training sessions to facilitate coding of this domain. The communication skills workshop described by Liu, et al. in 2007,[118] for example, clearly targeted social/professional role and identity. In this intervention, they provided managerial support aimed at providing “nurses [with] positive feedback, establishing a peer-supportive atmosphere, implementing teaching rounds, building up role models, and conducting roleplaying within small groups in their workplace.” Many other interventions provided scant details about the content of their skills training sessions, and we suspect that few of these studies were as intentional about targeting the professional role and identity of clinicians. In the absence of compelling data from the manuscripts, we did not code communication skills training sessions as targeting this domain. Lastly, we excluded studies with fewer than 30 participants in the hopes of identifying studies that are more likely to have generalizable findings. However, some of these smaller studies might have had interesting findings to contribute.

In conclusion, changing communication behaviors is a challenging but essential goal in order to meet the needs of patients with serious illness. In this review, we have identified the need for further innovation in developing multimodal communication interventions that aim to engage multiple behavioral domains. In addition, we have identified methodological concerns with this body of communication intervention literature. In the future, we recommend that investigators view clinician-patient communication through the lens of behavioral change theories in order to develop interventions that can fulfill communication needs in feasible, specific, and sustainable ways.

Supporting information


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