Network Psychometrics of the 10-Item Perceived Stress Scale Among Patients With High Cardiovascular and Type 2 Diabetes Risk Using Exploratory Graph Analysis.

BACKGROUND: No studies have explored the internal structure of the 10-item Perceived Stress Scale in patients with high cardiovascular and diabetes risk. OBJECTIVE: We scrutinized the dimensionality of the scale in this patient group using exploratory graph analysis, a technique within the developing field of network psychometrics. METHODS: Analyses were conducted on 200 primary care patients. A bootstrap version of exploratory graph analysis assessed the stability of the dimensions based on structural consistency, item stability, and network loadings. RESULTS: Exploratory graph analysis revealed a 2-dimensional structure; structural consistency of the first dimension was high (0.863), whereas that for the second was low (0.667). Items belonging to the latter dimension did not cluster consistently with each other (ie, low item stability) and were not strongly associated with any particular dimension (ie, weak network loadings). CONCLUSION: Exploratory graph analysis offers unique outputs, making it easy to assess the dimensional integrity of scales. Further research is warranted regarding the second dimension of the Perceived Stress Scale.

Latent Class Analysis of Depressive Symptom Phenotypes Among Black/African American Mothers.

BACKGROUND: Depression is a growing global problem with significant individual and societal costs. Despite their consequences, depressive symptoms are poorly recognized and undertreated because wide variation in symptom presentation limits clinical identification-particularly among African American (AA) women-an understudied population at an increased risk of health inequity. OBJECTIVES: The aims of this study were to explore depressive symptom phenotypes among AA women and examine associations with epigenetic, cardiometabolic, and psychosocial factors. METHODS: This cross-sectional, retrospective analysis included self-reported Black/AA mothers from the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure study (data collected in 2015-2020). Clinical phenotypes were identified using latent class analysis. Bivariate logistic regression examined epigenetic age, cardiometabolic traits (i.e., body mass index ≥ 30 kg/m 2 , hypertension, or diabetes), and psychosocial variables as predictors of class membership. RESULTS: All participants were Black/AA and predominantly non-Hispanic. Over half of the sample had one or more cardiometabolic traits. Two latent classes were identified (low vs. moderate depressive symptoms). Somatic and self-critical symptoms characterized the moderate symptom class. Higher stress overload scores significantly predicted moderate-symptom class membership. DISCUSSION: In this sample of AA women with increased cardiometabolic burden, increased stress was associated with depressive symptoms that standard screening tools may not capture. Research examining the effect of specific stressors and the efficacy of tools to identify at-risk AA women are urgently needed to address disparities and mental health burdens.

Perceptions of Using Multiple Mobile Health Devices to Support Self-Management Among Adults With Type 2 Diabetes: A Qualitative Descriptive Study.

PURPOSE: This study identified facilitators and barriers pertaining to the use of multiple mobile health (mHealth) devices (Fitbit Alta® fitness tracker, iHealth® glucometer, BodyTrace® scale) that support self-management behaviors in individuals with type 2 diabetes mellitus (T2DM). DESIGN: This qualitative descriptive study presents study participants' perceptions of using multiple mobile devices to support T2DM self-management. Additionally, this study assessed whether participants found visualizations, generated from each participant's health data as obtained from the three separate devices, useful and easy to interpret. METHODS: Semistructured interviews were completed with a convenience sample of participants (n = 20) from a larger randomized control trial on T2DM self-management. Interview questions focused on participants' use of three devices to support T2DM self-management. A study team member created data visualizations of each interview participant's health data using RStudio. RESULTS: We identified two themes from descriptions of study participants: feasibility and usability. We identified one theme about visualizations created from data obtained from the mobile devices. Despite some challenges, individuals with T2DM found it feasible to use multiple mobile devices to facilitate engagement in T2DM self-management behaviors. DISCUSSION: As mHealth devices become increasingly popular for diabetes self-management and are integrated into care delivery, we must address issues associated with the use of multiple mHealth devices and the use of aggregate data to support T2DM self-management. CLINICAL RELEVANCE: Real-time patient-generated health data that are easily accessible and readily available can assist T2DM self-management and catalyze conversations, leading to better self-management. Our findings lay an important groundwork for understanding how individuals with T2DM can use multiple mHealth devices simultaneously to support self-management.

Place of Residence and Cognitive Function among the Adult Population in India.

BACKGROUND: The place of residence has been linked to cognitive function among adults in developed countries. This study examined how urban and rural residence was associated with cognitive function among adults in India. METHODS: The World Health Organization Study on Global AGEing and Adult Health data was used to examine cognition among 6,244 community-residing adults age 50+ in 6 states in India. Residential status was categorized as urban, rural, urban-to-urban, rural-to-urban, rural-to-rural, and urban-to-rural. Cognition was assessed by immediate and delayed recall tests, digit span test, and verbal fluency test. Multilevel models were used to account for state-level differences and adjusted for individual-level sociodemographic, psychosocial, and health-related factors. RESULTS: Urban residents and urban-to-urban migrants had the highest levels of cognition, whereas rural residents and those who migrated to (or within) rural areas had the lowest cognition. The differences largely persisted after adjustment for multiple covariates; however, rural-to-urban migrants had no difference in cognition from urban residents once socioeconomic factors were taken into account. CONCLUSION: Cognition among adults in India differed significantly according to their current and past place of residence. Socioeconomic factors played an important role in the cognitive function of adults in urban areas.

Type 2 Diabetes Education and Support in a Virtual Environment: A Secondary Analysis of Synchronously Exchanged Social Interaction and Support.

BACKGROUND: Virtual environments (VEs) facilitate interaction and support among individuals with chronic illness, yet the characteristics of these VE interactions remain unknown. OBJECTIVE: The objective of this study was to describe social interaction and support among individuals with type 2 diabetes (T2D) who interacted in a VE. METHODS: Data included VE-mediated synchronous conversations and text-chat and asynchronous emails and discussion board posts from a study that facilitated interaction among individuals with T2D and diabetes educators (N=24) in 2 types of sessions: education and support. RESULTS: VE interactions consisted of communication techniques (how individuals interact in the VE), expressions of self-management (T2D-related topics), depth (personalization of topics), and breadth (number of topics discussed). Individuals exchanged support more often in the education (723/1170, 61.79%) than in the support (406/1170, 34.70%) sessions or outside session time (41/1170, 3.50%). Of all support exchanges, 535/1170 (45.73%) were informational, 377/1170 (32.22%) were emotional, 217/1170 (18.55%) were appraisal, and 41/1170 (3.50%) were instrumental. When comparing session types, education sessions predominately provided informational support (357/723, 49.4%), and the support sessions predominately provided emotional (159/406, 39.2%) and informational (159/406, 39.2%) support. CONCLUSIONS: VE-mediated interactions resemble those in face-to-face environments, as individuals in VEs engage in bidirectional exchanges with others to obtain self-management education and support. Similar to face-to-face environments, individuals in the VE revealed personal information, sought information, and exchanged support during the moderated education sessions and unstructured support sessions. With this versatility, VEs are able to contribute substantially to support for those with diabetes and, very likely, other chronic diseases.

Improving Diabetes Self-Management Support: Goal-Setting Across the Continuum of Care.

IN BRIEF Goal-setting has consistently been promoted as a strategy to support behavior change and diabetes self-care. Although goal-setting conversations occur most often in outpatient settings, clinicians across care settings need to better understand and communicate about the priorities, goals, and concerns of those with diabetes to develop collaborative, person-centered partnerships and to improve clinical outcomes. The electronic health record is a mechanism for improved communication and collaboration across the continuum of care. This article describes a quality improvement project that was intended to improve the person-centeredness of care for adults with diabetes by offering goal-setting and self-management support during and after hospitalization.

Diabetes Learning in Virtual Environments: Testing the Efficacy of Self-Management Training and Support in Virtual Environments (Randomized Controlled Trial Protocol).

BACKGROUND: Ongoing self-management improves outcomes for those with Type 2 diabetes (T2D); however, there are many barriers to patients receiving assistance in this from the healthcare system and peers. Findings from our pilot study showed that a virtual diabetes community on the Internet with real-time interaction among peers with T2D-and with healthcare professionals-is feasible and has the potential to influence clinical and psychosocial outcomes. OBJECTIVE: The purpose of this article is to present the protocol for the Diabetes Learning in Virtual Environments (LIVE) trial. PROTOCOL: Diabetes LIVE is a two-group, randomized controlled trial to compare effects of a virtual environment and traditional Web site on diet and physical activity. Our secondary aims will determine the effects on metabolic outcomes; effects of level of engagement and social network formation in LIVE on behavioral outcomes; potential mediating effects of changes in self-efficacy; and diabetes knowledge, diabetes-related distress, and social support on behavior change and metabolic outcomes. We will enroll 300 subjects at two sites (Duke University/Raleigh-Durham, NC and New York University/New York, NY) who have T2D and do not have serious complications or comorbidities. Those randomly assigned to the intervention group have access to the LIVE site where they can find information, synchronous classes with diabetes educators, and peer support to enhance self-management. Those in the control group have access to the same informational and educational content in a traditional asynchronous Web format. Measures of self-management, clinical outcomes, and psychosocial outcomes are assessed at baseline and 3, 6, 12, and 18 months. DISCUSSION: Should LIVE prove effective in improved self-management of diabetes, similar interventions could be applied to other prevalent chronic diseases. Innovative programs such as LIVE have potential for improving healthcare access in an easily disseminated alternative model of care that potentially improves the reach of self-management training and support.

Virtual worlds in nursing education: a synthesis of the literature.

Although the literature has highlighted the use of virtual worlds in teaching-learning, little is known about the concepts associated with this technology in nursing education. Moreover, the application of virtual worlds to education has been underdeveloped theoretically, with much of the work being exploratory. Thus, the aim of this integrative review was to identify the current evidence on the use of virtual worlds in the education of nursing and other health professional students and to describe emerging themes surrounding this phenomenon. We searched seven electronic databases for relevant articles and used Whittemore's and Knafl's integrative review method to synthesize the literature. Twelve articles met the selection criteria for this review, from which three overarching themes emerged: (a) critical reasoning skills, (b) student-centered learning, and (c) instructional design considerations. This integrative review extends our understanding of virtual worlds in nursing education and the potential barriers and facilitators of their use.

Associations Between DNA Methylation Age Acceleration, Depressive Symptoms, and Cardiometabolic Traits in African American Mothers From the InterGEN Study.

Background: African American women (AAW) have a high risk of both cardiometabolic (CM) illness and depressive symptoms. Depressive symptoms co-occur in individuals with CM illness at higher rates than the general population, and accelerated aging may explain this. In this secondary analysis, we examined associations between age acceleration; depressive symptoms; and CM traits (hypertension, diabetes mellitus [DM], and obesity) in a cohort of AAW. Methods: Genomic and clinical data from the InterGEN cohort (n = 227) were used. Age acceleration was based on the Horvath method of DNA methylation (DNAm) age estimation. Accordingly, DNAm age acceleration (DNAm AA) was defined as the residuals from a linear regression of DNAm age on chronological age. Spearman's correlations, linear and logistic regression examined associations between DNAm AA, depressive symptoms, and CM traits. Results: DNAm AA did not associate with total depressive symptom scores. DNAm AA correlated with specific symptoms including self-disgust/self-hate (-0.13, 95% CI -0.26, -0.01); difficulty with making decisions (-0.15, 95% CI -0.28, -0.02); and worry over physical health (0.15, 95% CI 0.02, 0.28), but were not statistically significant after multiple comparison correction. DNAm AA associated with obesity (0.08, 95% CI 1.02, 1.16), hypertension (0.08, 95% CI 1.01, 1.17), and DM (0.20, 95% CI 1.09, 1.40), after adjustment for potential confounders. Conclusions: Associations between age acceleration and depressive symptoms may be highly nuanced and dependent on study design contexts. Factors other than age acceleration may explain the connection between depressive symptoms and CM traits. AAW with CM traits may be at increased risk of accelerated aging.

Health coaching and genetic risk testing in primary care: Randomized controlled trial.

OBJECTIVE: Accessible interventions are needed to prevent coronary heart disease (CHD) and Type 2 diabetes (T2D). This prospective, randomized, controlled trial evaluated remote health coaching (HC), genetic risk testing (GRT), or both added to standardized risk assessment (SRA) in at-risk military primary care patients. METHOD: Using a 2 × 2 factorial longitudinal design, 200 Air Force at-risk participants provided primary outcomes at baseline, 3-, 6- (HC endpoint), and 12-months. Secondary measures were taken less often. Per protocol analyses used linear models and logistic regression; intent-to-treat (ITT) analyses used mixed models. RESULTS: Compared with those not receiving HC, the HC group was 3.6 times more likely to report moderate to intense physical activity at 6-months (p = .0009), and 2.9 times more likely to report such at 12-months (p = .0065). ITT longitudinal model did not reach significance (p = .0885). The HC group reported lower emotional representations of illness at 6-weeks and lower depression at 6 months. There were no other significant findings. HC and GRT interacted; higher T2D risk participants receiving HC were 4.7 times more likely to report higher stage of change for exercise at 6-months, and lost 2.2 kg more by 12-months. Lower T2D risk participants receiving HC perceived greater control over CHD risk at 6-weeks, and averaged lower 6-month depression. CONCLUSIONS: Remote HC after SRA increased physical activity, which was sustained 6-months later. Incorporating GRT into SRA warrants further exploration regarding the potential to leverage HC for weight loss in elevated T2D risk participants, and for depression in lower T2D risk participants. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Exchanges in a Virtual Environment for Diabetes Self-Management Education and Support: Social Network Analysis.

BACKGROUND: Diabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes-specific virtual communities. OBJECTIVE: The objective of this study was to examine social support exchanges from a type 2 diabetes self-management education and support intervention that was delivered via a virtual environment. METHODS: Data comprised virtual environment-mediated synchronous interactions among participants and between participants and providers from an intervention for type 2 diabetes self-management education and support. Network data derived from such social interactions were used to create networks to analyze patterns of social support exchange with the lens of social network analysis. Additionally, network correlations were used to explore associations between social support networks. RESULTS: The findings revealed structural differences between support networks, as well as key network characteristics of supportive interactions facilitated by the intervention. Emotional and appraisal support networks are the larger, most centralized, and most active networks, suggesting that virtual communities can be good sources for these types of support. In addition, appraisal and instrumental support networks are more connected, suggesting that members of virtual communities are more likely to engage in larger group interactions where these types of support can be exchanged. Lastly, network correlations suggest that participants who exchange emotional support are likely to exchange appraisal or instrumental support, and participants who exchange appraisal support are likely to exchange instrumental support. CONCLUSIONS: Social interaction patterns from disease-specific virtual environments can be studied using a social network analysis approach to better understand the exchange of social support. Network data can provide valuable insights into the design of novel and effective eHealth interventions given the unique opportunity virtual environments have facilitating realistic environments that are effective and sustainable, where social interactions can be leveraged to achieve diverse health goals.

Unpacking Peer Conversations in a Virtual Communitiy for Diabetes Self-Management Education and Support: Behavior Science and Linguistics Perspective.

Diabetes is a chronic disease that can be effectively managed and controlled using strategies such as self-management education and ongoing support. Virtual environments offer innovative and realistic settings where patients can achieve self-management education and obtain ongoing self-management support from peers and healthcare professionals. Transcribed real-time conversations in an innovative virtual community were analyzed using qualitative and linguistic analysis. These virtual interactions were manually coded to identify embedded behavior change techniques and linguistic features. Results showed 13 behavior change techniques were manifested. Further, language differences were observed between behavior change techniques and social support types. Our research can provide valuable insights into the design of effective digital health interventions that maximize sustained use of virtual environments, subsequently impacting self-management of chronic conditions such as diabetes.

Residential Mobility and Cognitive Function Among Middle-Aged and Older Adults in China.

OBJECTIVES: To assess the association between rural and urban residential mobility and cognitive function among middle-aged and older adults in China. METHOD: We used data from the World Health Organization Study on global AGEing and adult health that included adults age 50+ from China ( N = 12,410). We used multivariate linear regressions to examine how residential mobility and age at migration were associated with cognitive function. RESULTS: Urban and urban-to-urban residents had the highest level of cognitive function, whereas rural and rural-to-rural residents had the poorest cognitive function. Persons who migrated to/within rural areas before age 20 had poorer cognitive function than those who migrated during later adulthood. Socioeconomic factors played a major role in accounting for the disparities in cognition; however, the association remained significant after inclusion of all covariates. DISCUSSION: Residential mobility and age at migration have significant implications for cognitive function among middle-aged and older adults in China.

Developing Methods That Facilitate Coding and Analysis of Synchronous Conversations via Virtual Environments.

Programs via the Internet are uniquely positioned to capture qualitative data. One reason is because the Internet facilitates the creation of a community of similar individuals who can exchange information and support related to living with a chronic illness. Synchronous conversations via the Internet can provide insight into real-time social interaction and the exchange of social support. One way to analyze interactions among individuals is by using qualitative methods such as content, conversation, or discourse analysis. This manuscript describes how we used content analysis with aspects from conversation and discourse analysis to analyze synchronous conversations via the Internet to describe what individuals talk about and how individuals talk in an Internet-mediated interaction. With the increase in Internet interventions that facilitate collection of real-time conversational data, this article provides insight into how combining qualitative methods can facilitate the coding and analysis of these complex data.

Gender differences in the association between migration and cognitive function among older adults in China and India.

OBJECTIVE: This study aims to examine gender differences in the association between migration and cognitive function among adults in China and India. METHODS: Data from the World Health Organization Study on global AGEing and adult health (SAGE) study were used that included adults aged 50 + from China (N = 12,937) and India (N = 6244). Migration status included: urban residents, rural residents, urban-to-urban, rural-to-urban, rural-to-rural, and urban-to-rural migrants. Cognitive function was assessed by immediate and delayed recall tests, digit span tests, and verbal fluency test. Ordinary least square regression models were used to adjust for sociodemographic characteristics, psychosocial factors, health behaviors, and physical health status. RESULTS: Controlling for multiple covariates, significant differences in cognitive function were found between men and women, and across migration groups. A consistent female disadvantage was found in China and India for cognitive function. Women who were rural residents or rural-to-rural migrants had the poorest cognitive function in both the Chinese and the Indian samples. Among males in China, rural residents had poorer cognitive function than urban residents, while urban-to-urban migrants had highest cognition scores; however, for male counterparts in India, rural-to-rural migrants had the poorest cognitive function. CONCLUSIONS: The results suggest that the association between migration and cognitive function differs by gender and country. In our study populations, major sociodemographic characteristics play a key role in accounting for the differences in cognitive function.

Participation of Racial and Ethnic Minorities in Technology-Based Interventions to Self-Manage Type 2 Diabetes: A Scoping Review.

PURPOSE: Strategies to decrease societal and cultural barriers for ethnic minorities to participate in health research are well established. However, limited data are available regarding participation of ethnic minorities in mobile and Internet technology-based interventions to self-manage type 2 diabetes where health disparities are predominant. Thus, the purpose was to understand the participation of ethnic minorities in technology-based intervention programs to manage type 2 diabetes. DESIGN/METHOD: A scoping review was used to review a total of 21 intervention studies containing participant information about ethnic minorities and one qualitative study discussing participation of ethnic minorities. FINDINGS: There was limited enrollment and participation of ethnic minorities. Technological barriers in addition to existing societal and cultural barriers were identified. Strategies to decrease the barriers were recommended. CONCLUSIONS: Technological barriers were identified on top of the societal and cultural barriers in traditional interventions. Further research to reduce the barriers is warranted.

Migration and cognitive function: a conceptual framework for Global Health Research.

BACKGROUND: Migration is a fundamental demographic process that has been observed globally. It is suggested that migration is an issue of global health importance that can have an immediate and lasting impact on an individual's health and well-being. There is now an increasing body of evidence linking migration with cognitive function in older adults. In this paper, we synthesized the current evidence to develop a general conceptual framework to understand the factors contributing to the association between migration and cognitive function. METHODS: A comprehensive review of the literature was conducted on the associations between migration and cognition among middle-aged and older adults. RESULTS: Five potential mechanisms were identified from the literature: 1) socioeconomic status-including education, occupation, and income; 2) psychosocial factors-including social networks, social support, social stressors, and discrimination; 3) behavioral factors-including smoking, drinking, and health service utilization; 4) physical and psychological health status-including chronic conditions, physical function, and depression; and 5) environmental factors-including both physical and social environment. Several underlying factors were also identified-including early-life conditions, gender, and genetic factors. CONCLUSIONS: The factors linking migration and cognitive function are multidimensional and complex. This conceptual framework highlights potential implications for global health policies and planning on healthy aging and migrant health. Additional studies are needed to further examine these mechanisms to extend and refine our general conceptual framework.

Analyzing Unstructured Communication in a Computer-Mediated Environment for Adults With Type 2 Diabetes: A Research Protocol.

BACKGROUND: Individuals with type 2 diabetes have an increased risk for comorbidities such as heart disease, lower limb amputations, stroke, and renal failure. Multiple factors influence development of complications in a person living with type 2 diabetes; however, an individual's self-management behaviors may delay the onset of, or lessen the severity of, these complications. Social support provides personal, informal advice and knowledge that helps individuals initiate and sustain self-management and adherence. OBJECTIVE: Our aim was to gain an understanding of type 2 diabetes social interaction in a virtual environment, one type of computer-mediated environment (CME), and the social support characteristics that increase and sustain self-management in adults living with chronic illness. METHODS: This study is a secondary analysis of longitudinal data collected in a CME study, Second Life Impacts Diabetes Education & Self-Management (1R21-LM010727-01). This virtual environment replicated a real-life community where 6 months of naturalistic synchronous voice conversations, emails, and text chats were recorded among participants and providers. This analysis uses a mixed-methods approach to explore and compare qualitative and quantitative findings. This analysis is guided by two theories: Strong/Weak Ties Theory and Social Penetration Theory. Qualitative data will be analyzed using content analysis, and we will complete descriptive statistics on the quantified variables (eg, average number of ties). Institutional review board approval was obtained in June 2016. RESULTS: This study is in progress. CONCLUSIONS: Interventions provided through virtual environments are a promising solution to increasing self-management practices. However, little is known of the depth, breadth, and quality of social support that is exchanged and how interaction supports self-management and relates to health outcomes. This study will provide knowledge that will help guide clinical practice and policy to enhance social support for chronic illness via the Internet.

Nursing implications of personalized and precision medicine.

OBJECTIVES: Identify and discuss the nursing implications of personalized and precision oncology care. DATA SOURCES: PubMed, CINAHL. CONCLUSION: The implications in personalized and precision cancer nursing care include interpretation and clinical use of novel and personalized information including genetic testing; patient advocacy and support throughout testing, anticipation of results and treatment; ongoing chronic monitoring; and support for patient decision-making. Attention must also be given to the family and ethical implications of a personalized approach to care. IMPLICATIONS FOR NURSING PRACTICE: Nurses face increasing challenges and opportunities in communication, support, and advocacy for patients given the availability of advanced testing, care and treatment in personalized and precision medicine. Nursing education and continuing education, clinical decision support, and health systems changes will be necessary to provide personalized multidisciplinary care to patients, in which nurses play a key role.

Nurse practitioner management of type 2 diabetes.

CONTEXT: Multifactorial barriers prevent primary care clinicians from helping their adult patients with type 2 diabetes achieve good control of hemoglobin A1c (HbA1c) levels. Patients' depression and low self-efficacy can complicate diabetes management by impairing tasks needed for effective disease self-management. OBJECTIVES: To evaluate whether nurse practitioners in collaborative practices with primary care clinicians are effective in helping improve control of HbA1c, blood pressure (BP), and low-density lipoprotein cholesterol (LDL-C) in adults with uncontrolled hyperglycemia, and to assess whether nurse practitioner-guided care affects depression and self-efficacy in these patients. DESIGN: De-identified preintervention and postintervention data were collected from prospective review of medical charts of patients in a managed care organization's primary care clinics. MAIN OUTCOME MEASURES: Preintervention and postintervention HbA1c values were evaluated as the primary outcome measure. Preintervention and postintervention values for BP, LDL-C, body weight, and depression and self-efficacy scores were secondary outcome measures. RESULTS: After intervention, 50% of 26 patients achieved HbA1c benchmarks, 95.6% achieved systolic and diastolic BP benchmarks, and 57.8% achieved LDL-C benchmarks. Wilcoxon paired samples tests showed significantly increased self-efficacy (z = -3.42, p < 0.001) from preintervention to postintervention. Depression scores decreased slightly from preintervention (mean = 0.44, standard deviation = 1.34, median < 0.001) to postintervention values (mean = 0.18, standard deviation = 0.73, median < 0.001), but this decrease was not significant. CONCLUSION: Integrating nurse practitioners into primary care teams to provide innovative methods of support to adults with uncontrolled hyperglycemia improves clinical outcomes and self-efficacy for patients with type 2 diabetes.