A systematic review of the facilitators and barriers to rapid response team activation.

BACKGROUND: Outcomes associated with rapid response teams (RRTs) are inconsistent. This may be due to underlying facilitators and barriers to RRT activation that are affected by team leaders and health systems. AIMS: The aim of this study was to synthesize the published research about facilitators and barriers to nurse-led RRT activation in the United States (U.S.). METHODS: A systematic review was conducted. Four databases were searched from January 2000 to June 2023 for peer-reviewed quantitative, qualitative, and mixed methods studies reporting facilitators and barriers to RRT activation. Studies conducted outside the U.S. or with physician-led teams were excluded. RESULTS: Twenty-five studies met criteria representing 240,140 participants that included clinicians and hospitalized adults. Three domains of facilitators and barriers to RRT activation were identified: (1) hospital infrastructure, (2) clinician culture, and (3) nurses' beliefs, attributes, and knowledge. Categories were identified within each domain. The categories of perceived benefits and positive beliefs about RRTs, knowing when to activate the RRT, and hospital-wide policies and practices most facilitated activation, whereas the categories of negative perceptions and concerns about RRTs and uncertainties surrounding RRT activation were the dominant barriers. LINKING EVIDENCE TO ACTION: Facilitators and barriers to RRT activation were interrelated. Some facilitators like hospital leader and physician support of RRTs became barriers when absent. Intradisciplinary communication and collaboration between nurses can positively and negatively impact RRT activation. The expertise of RRT nurses should be further studied.

Revision and Psychometric Evaluation of the Diabetes Knowledge Questionnaire for People With Type 2 Diabetes.

Objective: Diabetes knowledge is associated with health, including lower A1C levels. The Diabetes Knowledge Questionnaire (DKQ-24), developed 30 years ago for Mexican Americans with type 2 diabetes and since used with diverse samples in many countries, contains outdated items that no longer accurately assess current knowledge needed for diabetes self-management. We revised the DKQ-24 and tested psychometric properties of the DKQ-Revised (DKQ-R) with a diverse sample. Methods: We conducted a five-phase instrumentation study as follows: 1) DKQ-24 items were revised to reflect current diabetes care standards; 2) the Delphi method was used to evaluate the DKQ-R's content validity (n = 5 experts); 3) cognitive interviews were conducted with people with type 2 diabetes (n = 5) to assess their interpretations of DKQ-R items; 4) cross-sectional administration of the DKQ-R to adults with type 2 diabetes was carried out to assess internal consistency reliability and convergent validity; and 5) an item analysis was conducted using discrimination index and point biserial analysis. Results: After receiving the experts' feedback and conducting the cognitive interviews, 39 items were administered to 258 participants with type 2 diabetes (42.2% women; 29.1% Latino, 42.6% Asian, mean age 55.7 years). To select the final items, we considered the item discrimination index, as well as item-to-total correlations, content area, and participant feedback. The final 22-item DKQ-R uses the same yes/no/I don't know response format as the DKQ-24. The DKQ-R is strongly correlated with the DKQ-24 (r = 0.71, P <0.01) and is weakly correlated with diabetes numeracy (r = 0.23, P <0.01), indicating adequate convergent validity; a Kuder-Richardson-20 coefficient of 0.77 indicated good reliability. Conclusion: The DKQ-R is a reliable and valid updated measure of diabetes knowledge for diverse populations with type 2 diabetes.

Who needs what (features) when? Personalizing engagement with data-driven self-management to improve health equity.

OBJECTIVES: To examine the feasibility of promoting engagement with data-driven self-management of health among individuals from minoritized medically underserved communities by tailoring the design of self-management interventions to individuals' type of motivation and regulation in accordance with the Self-Determination Theory. METHODS: Fifty-three individuals with type 2 diabetes from an impoverished minority community were randomly assigned to four different versions of an mHealth app for data-driven self-management with the focus on nutrition, Platano; each version was tailored to a specific type of motivation and regulation within the SDT self-determination continuum. These versions included financial rewards (external regulation), feedback from expert registered dietitians (RDF, introjected regulation), self-assessment of attainment of one's nutritional goals (SA, identified regulation), and personalized meal-time nutrition decision support with post-meal blood glucose forecasts (FORC, integrated regulation). We used qualitative interviews to examine interaction between participants' experiences with the app and their motivation type (internal-external). RESULTS: As hypothesized, we found a clear interaction between the type of motivation and Platano features that users responded to and benefited from. For example, those with more internal motivation reported more positive experience with SA and FORC than those with more external motivation. However, we also found that Platano features that aimed to specifically address the needs of individuals with external regulation did not create the desired experience. We attribute this to a mismatch in emphasis on informational versus emotional support, particularly evident in RDF. In addition, we found that for participants recruited from an economically disadvantaged community, internal factors, such as motivation and regulation, interacted with external factors, most notably with limited health literacy and limited access to resources. CONCLUSIONS: The study suggests feasibility of using SDT to tailor design of mHealth interventions for promoting data-driven self-management to individuals' motivation and regulation. However, further research is needed to better align design solutions with different levels of self-determination continuum, to incorporate stronger emphasis on emotional support for individuals with external regulation, and to address unique needs and challenges of underserved communities, with particular attention to limited health literacy and access to resources.

A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors.

PURPOSE: The purpose of this study is to use text-mining methods to examine the dominant sources of online information and content about continuous glucose monitors (CGMs). Because the internet is the most popular source for health information, it is important to understand what is being said about CGMs in online sources of information. METHODS: A text miner, algorithmic-driven statistical program was used to identify the main sources of online information and topics on CGMs. Content was limited to English and was posted from August 1, 2020, to August 4, 2022. Using Brandwatch software, 17 940 messages were identified. After cleaning, there were 10 677 messages in final analyses conducted using SAS Text Miner V.12.1 software. RESULTS: The analysis identified 20 topics that formed 7 themes. Results show that most online information comes from news sources and focuses on the general benefits of CGM use. Beneficial aspects ranged from improvements in self-management behaviors, cost, and glucose levels. None of the themes mentioned changes to practice, research, or policies related to CGM. CONCLUSIONS: To improve diffusion of information and innovations going forward, novel ways of information sharing should be explored, such as diabetes specialist, provider, and researcher engagement in social media and digital storytelling.

Redesigning culturally tailored intervention in the precision health era: Self-management science context.

BACKGROUND: Nurse scientists have significantly contributed to health equity and ensuring cultural tailoring of interventions to meet unique needs of individuals. Methodologies for cultural tailoring of self-mangament interventions among marginalized populations have limitedly accommodated intersectionality and group heterogeneity when addressing health needs. PURPOSE: Identify methodological limitations in cultural tailoring of interventions among priority populations and issue recommendations on cultural elements that researchers can target to ensure valid cultural tailoring approaches. METHODS: Synthesis of literature on health equity, self-management, and implementation and dissemination research. FINDINGS: Among priority populations, intersectionality and group heterogeneity has made group-based cultural tailoring approaches less effective in eliciting desirable health outcomes. Precision health methodology could be useful for cultural tailoring of interventions due to the methodology's focus on individual-level tailoring approaches. DISCUSSION: We offer ways to advance health equity research using precision health approaches in cultural tailoring through targeting unique elements of culture and relevant psychosocial phenotypes.

Social justice informatics: A critical approach for the future.

Given the longstanding inequities clarified by the pandemic, the time has come for nursing informatics to adopt the goals of social justice and equity as its primary focus. Social justice informatics (SJI) is an emerging field that leverages the power of data, information, and technology in pursuit of advancing equity through collaboration with diverse communities. We propose that an SJI orientation should be adopted to change the paradigms of power by placing communities at the center of the work and ensuring future informatics work is free from unintended consequences. However, to support this, legacy practices and policies will need to be replaced, which is discussed using the exemplar of academic systems. While this process will not be easy, it is hoped that by committing to and refining the vision presented here we will create a society that more accurately reflects our shared values of equity and prosperity.

Self-management of the Dual Diagnosis of HIV/AIDS and Diabetes During COVID-19: A Qualitative Study.

The purpose of this qualitative secondary analysis research was to describe the impact of the COVID-19 pandemic on self-management behaviors and practices for people living with the dual diagnoses of HIV/AIDS and type 2 diabetes mellitus and to identify early pandemic-specific disruptions or changes to their self-management practices. In-depth interviews conducted in May-June 2020 with 9 participants, and analyzed using content analysis, revealed 5 themes: adjusting to living with HIV/AIDS and diabetes impacts beliefs about COVID-19 risks; COVID-19 information seeking and accuracy; trade-offs in self-managing multiple chronic conditions; balance between safety, relationships, and the society at large; and discordant perceptions and actions. Some participants were resilient from previous experiences. Many received mixed messages about their risk for COVID-19, resulting in inaccurately or inconsistently applying guidelines for social isolation.

Psychosocial phenotyping as a personalization strategy for chronic disease self-management interventions.

BACKGROUND: As the U.S. population grows older and more diverse, self-management needs are increasingly complicated. In order to deliver effective personalized interventions to those suffer from chronic conditions social determinants of health must be considered. Therefore, psychosocial phenotyping holds strong promise as a tool for tailoring interventions based on precision health principles. PURPOSE: To define psychosocial phenotyping and develop a research agenda that promotes its integration into chronic disease management as a tool for precision self-management interventions. METHODS: Since psychosocial phenotyping is not yet used in interventions for self-management support, we conducted a literature review to identify potential phenotypes for chronic disease self-management. We also reviewed policy intervention case reports from the Centers for Medicare and Medicaid Services to examine factors related to social determinants of health in people with chronic illnesses. Finally, we reviewed methodological approaches for identifying patient profiles or phenotypes. RESULTS: The literature review revealed areas within which to collect data for psychosocial phenotyping that can inform personalized interventions. The findings of our exemplar cases revealed that several environmental or key SDOH such as factors realted with economic stability and neighborhood environment have been closely linked with the success of chronic disease management interventions. We elucidated theory, definitions, and pragmatic conceptual boundaries related to psychosocial phenotyping for precision health. CONCLUSIONS: Our literature review with case example analysis demonstrates the potential usefulness of psychosocial phenotyping as a tool to enhance personalized self-management interventions for people with chronic diseases, with implications for future research.

Preparing Teaching Assistants in Nursing: A Mixed-Methods Evaluation.

BACKGROUND: Teaching assistants (TAs) serve an important role in schools of nursing, but their educational needs are poorly understood. PURPOSE: To better prepare TAs, our School of Nursing identified and evaluated current TA practices to create tailored educational materials. METHODS: A 16-item survey captured how faculty used TAs. Focus groups with current faculty and former TAs explored the TA role and identified areas to target for future training. Focus groups were analyzed using thematic content analysis. RESULTS: Survey response rate was high (88%). Most faculty meet with TAs before the semester, and typical TA duties included attending lecture (71%) and facilitating examination review sessions (64%). Qualitative themes focused on faculty/TA communication, faculty guidance, knowing the policies, and TA/student boundary negotiation. CONCLUSIONS: Findings demonstrate the importance of preparing TAs. Since this study, the university and school of nursing have each developed educational materials to better prepare TAs and faculty.

From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations.

Self-tracking can help personalize self-management interventions for chronic conditions like type 2 diabetes (T2D), but reflecting on personal data requires motivation and literacy. Machine learning (ML) methods can identify patterns, but a key challenge is making actionable suggestions based on personal health data. We introduce GlucoGoalie, which combines ML with an expert system to translate ML output into personalized nutrition goal suggestions for individuals with T2D. In a controlled experiment, participants with T2D found that goal suggestions were understandable and actionable. A 4-week in-the-wild deployment study showed that receiving goal suggestions augmented participants' self-discovery, choosing goals highlighted the multifaceted nature of personal preferences, and the experience of following goals demonstrated the importance of feedback and context. However, we identified tensions between abstract goals and concrete eating experiences and found static text too ambiguous for complex concepts. We discuss implications for ML-based interventions and the need for systems that offer more interactivity, feedback, and negotiation.

Designing for engagement with self-monitoring: A user-centered approach with low-income, Latino adults with Type 2 Diabetes.

BACKGROUND AND SIGNIFICANCE: Data-driven interventions for health can help to personalize self-management of Type 2 Diabetes (T2D), but lack of sustained engagement with self-monitoring among disadvantaged populations may widen existing health disparities. Prior work developing approaches to increase motivation and engagement with self-monitoring holds promise, but little is known about applicability of these approaches to underserved populations. OBJECTIVE: To explore how low-income, Latino adults with T2D respond to different design concepts for data-driven solutions in health that require self-monitoring, and what features resonate with them the most. MATERIAL AND METHODS: We developed a set of mockups that incorporated different design features for promoting engagement with self-monitoring in T2D. We conducted focus groups to examine individuals' perceptions and attitudes towards mockups. Multiple interdisciplinary researchers analyzed data using directed content analysis. RESULTS: We conducted 14 focus groups with 25 English- and Spanish-speaking adults with T2D. All participants reacted positively to external incentives. Social connectedness and healthcare expert feedback were also well liked because they enhanced current social practices and presented opportunities for learning. However, attitudes were more mixed towards goal setting, and very few participants responded positively to self-discovery and personalized decision support features. Instead, participants wished for personalized recommendations for meals and other health behaviors based on their personal health data. CONCLUSION: This study suggests connections between individuals' degree of internal motivation and motivation for self-monitoring in health and their attitude towards designs of self-monitoring apps. We relate our findings to the self-determination continuum in self-determination theory (SDT) and propose it as a blueprint for aligning incentives for self-monitoring to different levels of motivation.

An intersectional approach to examine sleep duration in sexual minority adults in the United States: findings from the Behavioral Risk Factor Surveillance System.

OBJECTIVES: Investigate sexual identity differences in sleep duration and the multiplicative effect of sexual identity and race/ethnicity among US adults. DESIGN: Cross-sectional. PARTICIPANTS: The sample consisted of 267,906 participants from the Behavioral Risk Factor Surveillance System. MEASUREMENTS: Sleep duration was categorized as very short (≤4 hours), short (5-6 hours), adequate (7-8 hours), or long (≥9 hours). Sex-stratified multinomial logistic regressions were used to examine sexual identity differences in sleep duration. We then examined sleep duration by comparing sexual minorities to (1) same-race/-ethnicity heterosexuals and (2) White participants with the same sexual identity. RESULTS: Sexual minority women had higher odds of very short sleep compared to heterosexual women, regardless of race/ethnicity. Black gay men had higher rates of very short sleep but lower rates of long sleep relative to Black heterosexual men. Latino and Asian/Pacific Islander bisexual men reported higher rates of short sleep than their heterosexual counterparts. Black lesbian and other-race bisexual women were more likely to have very short sleep than their heterosexual peers. Black lesbian women also had higher rates of long sleep. Analyses examining racial/ethnic differences by sexual identity found that Black and Latino gay men reported higher rates of very short sleep compared to White gay men. Black bisexual women had higher rates of short sleep duration than White bisexual women. CONCLUSIONS: More research is needed to understand how to promote sleep health among sexual minorities, particularly racial/ethnic minorities, and the impact of inadequate sleep duration on health outcomes in this population.

Personal discovery in diabetes self-management: Discovering cause and effect using self-monitoring data.

OBJECTIVE: To outline new design directions for informatics solutions that facilitate personal discovery with self-monitoring data. We investigate this question in the context of chronic disease self-management with the focus on type 2 diabetes. MATERIALS AND METHODS: We conducted an observational qualitative study of discovery with personal data among adults attending a diabetes self-management education (DSME) program that utilized a discovery-based curriculum. The study included observations of class sessions, and interviews and focus groups with the educator and attendees of the program (n = 14). RESULTS: The main discovery in diabetes self-management evolved around discovering patterns of association between characteristics of individuals' activities and changes in their blood glucose levels that the participants referred to as "cause and effect". This discovery empowered individuals to actively engage in self-management and provided a desired flexibility in selection of personalized self-management strategies. We show that discovery of cause and effect involves four essential phases: (1) feature selection, (2) hypothesis generation, (3) feature evaluation, and (4) goal specification. Further, we identify opportunities to support discovery at each stage with informatics and data visualization solutions by providing assistance with: (1) active manipulation of collected data (e.g., grouping, filtering and side-by-side inspection), (2) hypotheses formulation (e.g., using natural language statements or constructing visual queries), (3) inference evaluation (e.g., through aggregation and visual comparison, and statistical analysis of associations), and (4) translation of discoveries into actionable goals (e.g., tailored selection from computable knowledge sources of effective diabetes self-management behaviors). DISCUSSION: The study suggests that discovery of cause and effect in diabetes can be a powerful approach to helping individuals to improve their self-management strategies, and that self-monitoring data can serve as a driving engine for personal discovery that may lead to sustainable behavior changes. CONCLUSIONS: Enabling personal discovery is a promising new approach to enhancing chronic disease self-management with informatics interventions.

Baseline Characteristics and Technology Training of Underserved Adults With Type 2 Diabetes in the Mobile Diabetes Detective (MoDD) Randomized Controlled Trial.

Purpose The purpose of this study is to describe the characteristics and technology training needs of underserved adults with type 2 diabetes mellitus (T2DM) who participated in a health information technology (HIT) diabetes self-management education (DSME) intervention. Methods The baseline physiological, psychosocial, and technology use characteristics for 220 adults with poorly controlled T2DM were evaluated. Intervention participants received a 1-time intervention training, which included basic technology help, introduction to the Mobile Diabetes Detective (MoDD) website and text message features, and account activation that included subject-specific tailoring. Four additional on-site sessions for participants needing computer or Internet access or technology support were made available based on need. Data regarding on-site visits for usual care were collected. Data were analyzed using descriptive statistics and bivariate analysis. Results The participants were predominately Hispanic and female with a baseline mean A1C of 10% (86 mmol/mol). Only half of the participants regularly used computers or text messages in daily life. The average introductory MoDD training session lasted 73.6 minutes. Following training, approximately one-third (35%) of intervention participants returned for basic and MoDD-specific technology assistance at their federally qualified health center. The most frequently reported duration for the extra training sessions was 30 to 45 minutes. Conclusions Training and support needs were greater than anticipated. Diabetes educators should assess technology abilities prior to implementing health information technology (HIT) diabetes self-management education (DSME) in underserved adults. Future research must invest resources in technology access, anticipate subject training, and develop new training approaches to ensure HIT DSME use and engagement.

Do health information technology self-management interventions improve glycemic control in medically underserved adults with diabetes? A systematic review and meta-analysis.

OBJECTIVE: The purpose of this systematic review and meta-analysis was to examine the effect of health information technology (HIT) diabetes self-management education (DSME) interventions on glycemic control in medically underserved patients. MATERIALS AND METHODS: Following an a priori protocol, 5 databases were searched. Studies were appraised for quality using the Cochrane Risk of Bias assessment. Studies reporting either hemoglobin A1c pre- and post-intervention or its change at 6 or 12 months were eligible for inclusion in the meta-analysis using random effects models. RESULTS: Thirteen studies met the criteria for the systematic review and 10 for the meta-analysis and represent data from 3257 adults with diabetes (mean age 55 years; 66% female; 74% racial/ethnic minorities). Most studies ( n = 10) reflected an unclear risk of bias. Interventions varied by HIT type: computer software without Internet ( n = 2), cellular/automated telephone ( n = 4), Internet-based ( n = 4), and telemedicine/telehealth ( n = 3). Pooled A1c decreases were found at 6 months (-0.36 (95% CI, -0.53 and -0.19]; I 2 = 35.1%, Q = 5.0), with diminishing effect at 12 months (-0.27 [95% CI, -0.49 and -0.04]; I 2 = 42.4%, Q = 10.4). DISCUSSION: Findings suggest that medically underserved patients with diabetes achieve glycemic benefit following HIT DSME interventions, with dissipating but significant effects at 12 months. Telemedicine/telehealth interventions were the most successful HIT type because they incorporated interaction with educators similar to in-person DSME. CONCLUSION: These results are similar to in-person DSME in medically underserved patients, showing that well-designed HIT DSME has the potential to increase access and improve outcomes for this vulnerable group.

Impact of an electronic handoff documentation tool on team shared mental models in pediatric critical care.

OBJECTIVE: To examine the impact of the implementation of an electronic handoff tool (the Handoff Tool) on shared mental models (SMM) within patient care teams as measured by content overlap and discrepancies in verbal handoff presentations given by different clinicians caring for the same patient. MATERIALS AND METHODS: Researchers observed, recorded, and transcribed verbal handoffs given by different members of patient care teams in a pediatric intensive care unit. The transcripts were qualitatively coded and analyzed for content overlap scores and the number of discrepancies in handoffs of different team members before and after the implementation of the tool. RESULTS: Content overlap scores did not change post-implementation. The average number of discrepancies nearly doubled following the implementation (from 0.76 discrepancies per handoff group pre-implementation to 1.17 discrepancies per handoff group post-implementation); however, this change was not statistically significant (p=0.37). Discrepancies classified as related to dosage of treatment or procedure and to patients' symptoms increased in frequency post-implementation. DISCUSSION: The results suggest that the Handoff Tool did not have the desired positive impact on SMM within patient care teams. Future electronic tools for facilitating team handoff may need longer implementation times, complementary changes to handoff process and structure, and improved designs that integrate a common core of shared information with discipline-specific records. CONCLUSION: While electronic handoff tools provide great opportunities to improve communication and facilitate the formation of shared mental models within patient care teams, further work is necessary to realize their full potential.

Structured scaffolding for reflection and problem solving in diabetes self-management: qualitative study of mobile diabetes detective.

OBJECTIVE: To investigate subjective experiences and patterns of engagement with a novel electronic tool for facilitating reflection and problem solving for individuals with type 2 diabetes, Mobile Diabetes Detective (MoDD). METHODS: In this qualitative study, researchers conducted semi-structured interviews with individuals from economically disadvantaged communities and ethnic minorities who are participating in a randomized controlled trial of MoDD. The transcripts of the interviews were analyzed using inductive thematic analysis; usage logs were analyzed to determine how actively the study participants used MoDD. RESULTS: Fifteen participants in the MoDD randomized controlled trial were recruited for the qualitative interviews. Usage log analysis showed that, on average, during the 4 weeks of the study, the study participants logged into MoDD twice per week, reported 120 blood glucose readings, and set two behavioral goals. The qualitative interviews suggested that individuals used MoDD to follow the steps of the problem-solving process, from identifying problematic blood glucose patterns, to exploring behavioral triggers contributing to these patterns, to selecting alternative behaviors, to implementing these behaviors while monitoring for improvements in glycemic control. DISCUSSION: This qualitative study suggested that informatics interventions for reflection and problem solving can provide structured scaffolding for facilitating these processes by guiding users through the different steps of the problem-solving process and by providing them with context-sensitive evidence and practice-based knowledge related to diabetes self-management on each of those steps. CONCLUSION: This qualitative study suggested that MoDD was perceived as a useful tool in engaging individuals in self-monitoring, reflection, and problem solving.