Effects of intervention stage completion in an integrated behavioral health and primary care randomized pragmatic intervention trial.

Purpose: A pragmatic, cluster-randomized controlled trial of a comprehensive practice-level, multi-staged practice transformation intervention aimed to increase behavioral health integration in primary care practices and improve patient outcomes. We examined association between the completion of intervention stages and patient outcomes across a heterogenous national sample of primary care practices. Methods: Forty-two primary care practices across the U.S. with co-located behavioral health and 2,426 patients with multiple chronic medical and behavioral health conditions completed surveys at baseline, midpoint and two year follow-up. Effects of the intervention on patient health and primary care integration outcomes were examined using multilevel mixed-effects models, while controlling for baseline outcome measurements. Results: No differences were found associated with the number of intervention stages completed in patient health outcomes were found for depression, anxiety, fatigue, sleep disturbance, pain, pain interference, social function, patient satisfaction with care or medication adherence. The completion of each intervention stage was associated with increases in Practice Integration Profile (PIP) domain scores and were confirmed with modeling using multiple imputation for: Workflow 3.5 (95% CI: 0.9-6.1), Integration Methods 4.6 (95% CI: 1.5-7.6), Patient Identification 2.9 (95% CI: 0.9-5.0), and Total Integration 2.7 (95% CI: 0.7-4.7). Conclusion: A practice-centric flexible practice transformation intervention improved integration of behavioral health in primary care across heterogenous primary care practices treating patients with multiple chronic conditions. Interventions that allow practices to flexibly improve care have potential to help complex patient populations. Future research is needed to determine how to best target patient health outcomes at a population level.

A Cluster Randomized Trial of Primary Care Practice Redesign to Integrate Behavioral Health for Those Who Need It Most: Patients With Multiple Chronic Conditions.

PURPOSE: Patient outcomes can improve when primary care and behavioral health providers use a collaborative system of care, but integrating these services is difficult. We tested the effectiveness of a practice intervention for improving patient outcomes by enhancing integrated behavioral health (IBH) activities. METHODS: We conducted a pragmatic, cluster randomized controlled trial. The intervention combined practice redesign, quality improvement coaching, provider and staff education, and collaborative learning. At baseline and 2 years, staff at 42 primary care practices completed the Practice Integration Profile (PIP) as a measure of IBH. Adult patients with multiple chronic medical and behavioral conditions completed the Patient-Reported Outcomes Measurement Information System (PROMIS-29) survey. Primary outcomes were the change in 8 PROMIS-29 domain scores. Secondary outcomes included change in level of integration. RESULTS: Intervention assignment had no effect on change in outcomes reported by 2,426 patients who completed both baseline and 2-year surveys. Practices assigned to the intervention improved PIP workflow scores but not PIP total scores. Baseline PIP total score was significantly associated with patient-reported function, independent of intervention. Active practices that completed intervention workbooks (n = 13) improved patient-reported outcomes and practice integration (P ≤ .05) compared with other active practices (n = 7). CONCLUSION: Intervention assignment had no effect on change in patient outcomes; however, we did observe improved patient outcomes among practices that entered the study with greater IBH. We also observed more improvement of integration and patient outcomes among active practices that completed the intervention compared to active practices that did not. Additional research is needed to understand how implementation efforts to enhance IBH can best reach patients.

Employee Group Coaching Program for University and Hospital Employees During COVID-19: A Feasibility Study.

Background: Workplace wellbeing programs can be beneficial but range widely in approach. A group coaching model offers numerous benefits. Objective: To evaluate feasibility of group coaching for employees during COVID-19. Methods: Employees (n = 29) at a university and university hospital underwent a 12-week group coaching program. Measurements of feasibility -- including enrollment, attendance at sessions goal attainment and satisfaction -- and exploratory outcomes including perceived physical and mental health and stress were administered at beginning, middle, and end of the program, plus 2 follow-ups. Results: Twenty-six of the 29 program enrollees (96% women; 65% university employees) opted to complete surveys at 1 or more time points, and 9 individuals completed surveys at all 5 time points. Median attendance was 9 sessions. Participants opted to focus on movement, nutrition and mind/body goals and all participants reported making progress toward their goal during the program. Exploratory wellness outcomes showed meaningful improvements in perceived physical and mental health and reduced stress during the program, with return to near baseline 12 weeks after program completion. Perceptions of workplace wellness culture varied by employer. Conclusion: Despite pandemic-related disruptions to life, work, and health, online group coaching is feasible and acceptable to participants. The program should be replicated to evaluate whether the improvements in exploratory wellness outcomes observed during the program are statistically significant. The apparent return to baseline levels by 24 weeks suggests that post-program maintenance support may be helpful.

Practice-Level Documentation of Alcohol-Related Problems in Primary Care.

Importance: Rates of alcohol-associated deaths increased over the past 20 years, markedly between 2019 and 2020. The highest rates are among individuals aged 55 to 64 years, primarily attributable to alcoholic liver disease and psychiatric disorders due to use of alcohol. This study investigates potential geographic disparities in documentation of alcohol-related problems in primary care electronic health records, which could lead to undertreatment of alcohol use disorder. Objective: To identify disparities in documentation of alcohol-related problems by practice-level social deprivation. Design, Setting, and Participants: A cross-sectional study using secondary data from the Integrating Behavioral Health and Primary Care clinical trial (September 21, 2017, to January 8, 2021) was performed. A national sample of 44 primary care practices with co-located behavioral health services was included in the analysis. Patients with 2 primary care visits within 2 years and at least 1 chronic medical condition and 1 behavioral health condition or at least 3 chronic medical conditions were included. Exposure: The primary exposure was practice-level Social Deprivation Index (SDI), a composite measure based on county income, educational level, employment, housing, single-parent households, and access to transportation (scores range from 0 to 100; 0 indicates affluent counties and 100 indicates disadvantaged counties). Main Outcomes and Measures: Documentation of an alcohol-related problem in the electronic health record was determined by International Classification of Diseases, 9th Revision, Clinical Modification and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Clinical Modification codes or use of medications for alcohol use disorder in past 2 years. Multivariable models adjusted for alcohol consumption, screening for a substance use disorder, urban residence, age, sex, race and ethnicity, income, educational level, and number of chronic health conditions. Results: A total of 3105 participants (mean [SD] age, 63.7 [13.0] years; 64.1% female; 11.5% Black, 7.0% Hispanic, 76.7% White, and 11.9% other race or chose not to disclose; 47.8% household income <$30 000; and 80.7% urban residence). Participants had a mean (SD) of 4.0 (1.7) chronic conditions, 9.1% reported higher-risk alcohol consumption, 4% screened positive for substance use disorder, and 6% had a documented alcohol-related problem in the electronic health record. Mean (SD) practice-level SDI score was 45.1 (20.9). In analyses adjusted for individual-level alcohol use, demographic characteristics, and health status, practice-level SDI was inversely associated with the odds of documentation (odds ratio for each 10-unit increase in SDI, 0.89; 95% CI, 0.80 to 0.99; P = .03). Conclusions and Relevance: In this study, higher practice-level SDI was associated with lower odds of documentation of alcohol-related problems, after adjusting for individual-level covariates. These findings reinforce the need to address primary care practice-level barriers to diagnosis and documentation of alcohol-related problems. Practices located in high need areas may require more specialized training, resources, and practical evidence-based tools that are useful in settings where time is especially limited and patients are complex.

The Association Between Depression and Substance Use Among Primary Care Patients With Comorbid Medical and Behavioral Health Conditions.

INTRODUCTION: The scope of primary care increasingly encompasses patient behavioral health problems, manifest typically through depression screening and treatment. Although substance use is highly comorbid with depression, it is not commonly identified and addressed in the primary care context. This study aimed to examine the association between the likelihood of substance use disorder and increased depression severity, both cross-sectionally and longitudinally, among a sample of 2409 patients from 41 geographically dispersed and diverse primary care clinics across the US. METHODS: This is secondary analysis of data obtained from a multi-site parent study of integrated behavioral health in primary care, among patients with both chronic medical and behavioral health conditions. Patient reported outcome surveys were gathered from patients at 3 time points. The primary care practices were blind to which of their patients completed surveys. Included were standardized measures of depression severity (Patient Health Questionnaire-9) [PHQ-9] and substance use disorder likelihood (Global Appraisal of Individual Needs-Short Screener [GSS]). RESULTS: Four percent of the study population screened positive for substance use disorder. PHQ-9 scores indicated depression among 43% of all patients. There was a significant association between the likelihood of substance use disorder and depression initially, at a 9-month follow-up, and over time. These associations remained significant after adjusting for age, gender, race, ethnicity, education, income, and other patient and contextual characteristics. CONCLUSIONS: The findings suggest that substance use disorder is associated with depression severity cross-sectionally and over time. Primary care clinics and health systems might consider implementing substance use screening in addition to the more common screening strategies for depression. Especially for patients with severe depression or those who do not respond to frontline depression treatments, the undermining presence of a substance use disorder should be explored.

Practice integration profile revised: Improving item readability and completion.

INTRODUCTION: The Practice Integration Profile (PIP) is a reliable, valid, and broadly used measure of the integration of behavioral health (BH) into primary care. The PIP assesses operational and procedural elements that are grounded in the AHRQ Lexicon for Behavioral Health and Primary Care Integration. Prior analyses of PIP data and feedback from users suggested the measure was in need of revisions. This article describes the process used to improve readability, clarity, and pragmatic utility of the instrument. METHOD: Two rounds of structured cognitive interviews were conducted with clinicians in primary care settings. After each round, interview transcripts were coded by an analytic team using an iterative and consensus-driven process. Themes were identified based on codes. Themes and recommendations for revisions were reviewed and modified by committee. RESULTS: Based on feedback and a prior factor analysis of the PIP, revisions were undertaken to: (a) eliminate redundant or overlapping items; (b) clarify the meaning of items; (c) standardize the response categories, and (d) place items in the most appropriate domains. The resulting measure has 28 items in five domains. DISCUSSION: PIP 2.0 will need further examination to confirm its continuing use as a foundational tool for evaluating integrated care. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Urban-Rural Differences in Mental and Physical Health among Primary Care Patients with Multiple Chronic Conditions: A Secondary Analysis from a Randomized Clinical Trial.

PURPOSE: Rural health disparities are largely attributable to access to healthcare, socioeconomic status, and health behaviors. Little is known about the persistence of these disparities when differences in access to care are eliminated. We sought to investigate urban-rural differences in physical and mental health in primary care patients with demonstrated access to primary care. METHODS: We obtained cross-sectional survey responses from a multicenter randomized controlled trial on 2726 adult primary care patients with multiple chronic medical or behavioral conditions from 42 primary care practices in 13 states. Study outcomes include measures of mental health including: The Patient-Reported Outcomes Measurement Information System (PROMIS-29®), General Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire-9 (PHQ-9), as well as physical health including: the PROMIS-29® and the Duke Activity Status Index (DASI). Urban-rural residence was indicated by census-tract Rural Urban Commuting Areas of the participant's home address. Differences in mental and physical health outcomes attributable to rurality were assessed using multilevel models with a random intercept for census-tract. RESULTS: After adjustment for demographic and neighborhood characteristics, urban residents had significantly worse generalized anxiety disorder (GAD-7) (ß = 0.7; 95% CI = 0.1, 1.3; p = 0.027), depression (PHQ-9) (ß = 0.7; 95% CI = 0.1, 1.4; p = 0.024), and functional capacity (DASI) (ß = -0.4; 95% CI = -0.5, -0.2; p < 0.001) compared to rural residents. Urban residents also had significantly worse anxiety and depression as measured by the PROMIS-29® compared to their rural counterparts. There were no urban-rural differences in the other PROMIS-29® subdomains. CONCLUSIONS: Among adults with demonstrated access to care and multiple diagnosed chronic conditions, rural residents had better mental health and functional capacity than their urban counterparts. This finding is not consistent with prior research documenting rural health disparities and should be confirmed.

Outcomes of Delay of Care After the Onset of COVID-19 for Patients Managing Multiple Chronic Conditions.

PURPOSE: Many patients delayed health care during COVID-19. We assessed the extent to which patients managing multiple chronic conditions (MCC) delayed care in the first months of the pandemic, reasons for delay, and impact of delay on patient-reported physical and behavioral health (BH) outcomes. METHODS: As part of a large clinical trial conducted April 2016-June, 2021, primary care patients managing MCC were surveyed about physical and behavioral symptoms and functioning. Surveys administered between September 3, 2020, and March 16, 2021, included questions about the extent of and reasons for any delayed medical and BH care since COVID-19. Multivariable linear regression was used to assess health outcomes as a function of delay of care status. RESULTS: Among patients who delayed medical care, 58% delayed more than once. Among those who delayed behavioral health care, 63% delayed more than once. Participants who delayed multiple times tended to be younger, female, unmarried, and reported food, financial, and housing insecurities and worse health. The primary reasons for delaying care were lack of availability of in-person visits and perceived lack of urgency. Participants who delayed care multiple times had significantly worse outcomes on nearly every measure of physical and mental health, compared with participants who delayed care once or did not delay. CONCLUSIONS: Delay of care was substantial. Patients who delayed care multiple times were in poorer health and thus in need of more care. Effective strategies for reengaging patients in deferred care should be identified and implemented on multiple levels. TRIAL REGISTRATION: ClinicalTrials.gov NCT02868983. Registered on August 16, 2016.

Co-creating the Patient Partner Guide by a Multiple Chronic Conditions Team of Patients, Clinicians, and Researchers: Observational Report.

BACKGROUND: Engaging patients as partners can influence research, with rewards and deterrents. The authors are researchers and patient co-investigators who collaborated on a comparative effectiveness, randomized controlled study of a structured quality improvement (QI) process to improve behavioral health and primary care integration for people managing multiple chronic conditions (MCC). Patient co-investigators responded to a gap in available resources to support study clinics in partnering with their own patients in QI and co-created the Patient Partner Guide (PPG). OBJECTIVE: Describe the development of the PPG, its use by clinics undertaking the QI project, and research team partnerships. DESIGN: Observational report of study intervention component. PARTICIPANTS: Diverse patients and family members managing MCC and members of their primary care clinics. INTERVENTION: The PPG component of the study intervention is a five-step workbook providing practical tools and resources to sustain partnerships across clinic QI team members, including patient partners. The process of developing the PPG relied on relationship-building tools that were iteratively assessed, practiced, improved, and incorporated into the PPG under the leadership of patient co-investigators. MAIN MEASURES: Observations related to PPG use and patient partner inclusion in clinic QI; impact on the research team. KEY RESULTS: Of 20 clinics, 6 engaged patients as full partners on QI teams. Clinics found resistance in partnering and challenges in using the PPG but valued the material and their partners' contributions. Similarly, engagement of patient co-investigators in research brought a shift in perspective to team members. The PPG is available and was adapted for use by research teams. CONCLUSIONS: Engagement of patients and other stakeholders in research can be transformative and productive. Building relationships through meaningful work benefits others, and in turn, the research process. This approach can enhance clinical care QI and may result in substantial contributions to the conduct of research. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT02868983.

Development and validation of the patient centeredness index for primary care.

AIMS AND OBJECTIVES: To describe the development of the Patient Centeredness Index (PCI), evaluate its psychometric characteristics and evaluate the relationships between scores on the PCI and an established measure of empathy. BACKGROUND: Patient centeredness helps patients manage multiple chronic conditions with their providers, nurses and other team members. However, no instrument exists for evaluating patient centeredness within primary care practices treating this population. DESIGN: Multi-site instrument development and validation. STROBE reporting guidelines were followed. METHODS: To identify themes, we consulted literature on patient centeredness and engaged stakeholders who had or were caring for people with multiple chronic conditions (n = 7). We composed and refined items to represent those themes with input from clinicians and researchers. To evaluate reliability and convergent validity, we administered surveys to participants (n = 3622) with chronic conditions recruited from 44 primary care practices for a large-scale cluster randomised clinical trial of the effects of a practice-level intervention on patient and practice-level outcomes. Participants chose to complete the 16-item survey online, on paper or by phone. Surveys assessed demographics, number of chronic conditions and ratings of provider empathy. We conducted exploratory factor analysis to model the interrelationships among items. RESULTS: A single factor explained 93% of total variance. Factor loadings ranged from 0.55-0.85, and item-test correlations were ≥.67. Cronbach's alpha was .93. A moderate, linear correlation with ratings of provider's empathy (r = .65) supports convergent validity. CONCLUSIONS: The PCI is a new tool for obtaining patient perceptions of the patient centeredness of their primary care practice. The PCI shows acceptable reliability and evidence of convergent validity among patients managing chronic conditions. RELEVANCE TO CLINICAL PRACTICE: The PCI rapidly identifies patients' perspectives on patient centeredness of their practice, making it ideal for administration in busy primary care settings that aim to efficiently address patient-identified needs. TRIAL REGISTRATION: Clinicaltrials.org Protocol ID: WLPS-1409-24372. TITLE: Integrating Behavioural Health and Primary Care for Comorbid Behavioural and Medical Problems (IBHPC).

Integrating behavioral health & primary care for multiple chronic diseases: Clinical trial of a practice redesign toolkit.

Context: Most patients in need of behavioral health (BH) care are seen in primary care, which often has difficulty responding. Some practices integrate behavioral health care (IBH), with medical and BH providers at the same location, working as a team. However, it is difficult to achieve high levels of integration. Objective: Test the effectiveness of a practice intervention designed to increase BH integration. Study Design: Pragmatic, cluster-randomized controlled trial. Setting: 43 primary care practices with on-site BH services in 13 states. Population: 2,460 adults with multiple chronic medical and behavioral conditions. Intervention: 24-month practice change process including an online curriculum, a practice redesign and implementation workbook, remote quality improvement coaching services, and an online learning community. Outcomes: Primary outcomes were changes in the 8 Patient-Reported Outcomes Measurement Information System (PROMIS-29) domain scores. Secondary outcomes were changes in medication adherence, self-reported healthcare utilization, time lost due to disability, cardiovascular capacity, patient centeredness, provider empathy, and several condition-specific measures. A sample of practice staff completed the Practice Integration Profile at each time point to estimate the degree of BH integration in that site. Practice-level case studies estimated the typical costs of implementing the intervention. Results: The intervention had no significant effect on any of the primary or secondary outcomes. Subgroup analyses showed no convincing patterns of effect in any populations. COVID-19 was apparently not a moderating influence of the effect of the intervention on outcomes. The intervention had a modest effect on the degree of practice integration, reaching statistical significance in the Workflow domain. The median cost of the intervention was $18,204 per practice. In post-hoc analysis, level of BH integration was associated with improved patient outcomes independent of the intervention, both at baseline and longitudinally. Conclusions: The specific intervention tested in this study was inexpensive, but had only a small impact on the degree of BH integration, and none on patient outcomes. However, practices that had more integration at baseline had better patient outcomes, independent of the intervention. Although this particular intervention was ineffective, IBH remains an attractive strategy for improving patient outcomes.

Telemedicine in Neurology: A Scoping Review of Key Outcomes in Movement Disorders.

Introduction: Telemedicine for neurological care has been researched and practiced in various ways over the past three decades, but the recent COVID-19 pandemic has rapidly expanded its use and highlighted the need for a synthesis of the existing literature. We aimed to review the methodology and outcomes of previous studies that have evaluated the use of telemedicine in movement disorders. Methods: This scoping review was performed by searching PubMed, Ovid MEDLINE, and CINAHL databases from 1946 to November 2020. Studies that assessed the application of telemedicine for delivering care to patients with a movement disorder were included. We reported the aims and employed methodologies and categorized the outcomes from each study. Results: The search retrieved 228 articles, and 41 studies met the criteria for inclusion in the review. The majority of telemedicine studies were case series or randomized controlled pilot trials, investigating feasibility and acceptability in Parkinson's disease. Even with heterogeneity among outcome measures, they can be categorized into themes, such as feasibility, satisfaction, and efficacy. Conclusions: Telemedicine use has grown rapidly, due to the demands of providing care during a global pandemic. This application of telemedicine has been considered a promising way to expand care in Neurology, although research evaluating the dissemination of its use is dilatory. This review highlights the number of studies that have found telemedicine to be an acceptable and feasible way to deliver care for movement disorders. Further research is needed to expand on harmonization of outcomes, reach, adoption, and long-term use of telemedicine.

Differences in Occupational Burnout Among Primary Care Professionals.

BACKGROUND: Occupational burnout is a major concern for personal well-being and patient care. We examined burnout among primary care providers (PCPs), medical residents, behavioral health providers (BHPs), nurses, and other clinical and nonclinical primary care team members. METHODS: This was a cross-sectional study, nested within a larger randomized trial. Participants completed a validated 9-item burnout measure with 3 domains: depersonalization, emotional exhaustion, and personal accomplishment. Multivariable multilevel linear regression with a random intercept for each practice was used to determine mean differences in burnout across professional roles. RESULTS: Overall burnout rates varied by professional role: PCPs 70%, medical residents 89%, BHPs 59%, nurses 66%, other clinicians 68%, and nonclinical professionals 70%. Compared with nonclinical professionals, residents experienced more burnout in more domains, followed by PCPs. PCPs, residents, and nurses reported significantly worse depersonalization and exhaustion scores. Nonclinical professionals had worse accomplishment scores than all clinical professionals except for residents. This study revealed moderate-to-high levels of burnout among primary care professionals. DISCUSSION: Clinicians may be experiencing aspects of burnout more intensely than their nonclinical colleagues, and this may be most true for residents and PCPs. Based on these variations, interventions to mitigate burnout may need to be tailored by professional role.

Integrating Behavioral Health and Primary Care (IBH-PC) to improve patient-centered outcomes in adults with multiple chronic medical and behavioral health conditions: study protocol for a pragmatic cluster-randomized control trial.

BACKGROUND: Chronic diseases that drive morbidity, mortality, and health care costs are largely influenced by human behavior. Behavioral health conditions such as anxiety, depression, and substance use disorders can often be effectively managed. The majority of patients in need of behavioral health care are seen in primary care, which often has difficulty responding. Some primary care practices are providing integrated behavioral health care (IBH), where primary care and behavioral health providers work together, in one location, using a team-based approach. Research suggests there may be an association between IBH and improved patient outcomes. However, it is often difficult for practices to achieve high levels of integration. The Integrating Behavioral Health and Primary Care study responds to this need by testing the effectiveness of a comprehensive practice-level intervention designed to improve outcomes in patients with multiple chronic medical and behavioral health conditions by increasing the practice's degree of behavioral health integration. METHODS: Forty-five primary care practices, with existing onsite behavioral health care, will be recruited for this study. Forty-three practices will be randomized to the intervention or usual care arm, while 2 practices will be considered "Vanguard" (pilot) practices for developing the intervention. The intervention is a 24-month supported practice change process including an online curriculum, a practice redesign and implementation workbook, remote quality improvement coaching services, and an online learning community. Each practice's degree of behavioral health integration will be measured using the Practice Integration Profile. Approximately 75 patients with both chronic medical and behavioral health conditions from each practice will be asked to complete a series of surveys to measure patient-centered outcomes. Change in practice degree of behavioral health integration and patient-centered outcomes will be compared between the two groups. Practice-level case studies will be conducted to better understand the contextual factors influencing integration. DISCUSSION: As primary care practices are encouraged to provide IBH services, evidence-based interventions to increase practice integration will be needed. This study will demonstrate the effectiveness of one such intervention in a pragmatic, real-world setting. TRIAL REGISTRATION: ClinicalTrials.gov NCT02868983 . Registered on August 16, 2016.

Relationship between Magnesium Intake and Chronic Pain in U.S. Adults.

Chronic pain is a public health concern and additional treatment options are essential. Inadequate magnesium intake has been associated with chronic pain in some populations. We sought to examine the relationship between dietary magnesium intake and chronic pain in a large, representative cohort of U.S. adults (NHANES). Of the 13,434 eligible adults surveyed between 1999 and 2004, 14.5% reported chronic pain while 66% reported inadequate magnesium intake. The univariate analysis showed a protective effect of increased magnesium intake adjusted for body weight (odds ratio 0.92; 95%; CI 0.88, 0.95; p < 0.001). It remained so even after correcting for socioeconomic and clinical factors as well as total calorie intake (odds ratio 0.93; 95% CI 0.87, 0.99; p = 0.02). The association was stronger in females (odds ratio 0.91; 95% CI 0.85, 0.98; p = 0.01) than males (odds ratio 0.96; 95% CI 0.89, 1.04; p = 0.32). The potential protective effect of magnesium intake on chronic pain warrants further investigation.

A Machine Learning Approach to Identification of Unhealthy Drinking.

INTRODUCTION: Unhealthy drinking is prevalent in the United States, and yet it is underidentified and undertreated. Identifying unhealthy drinkers can be time-consuming and uncomfortable for primary care providers. An automated rule for identification would focus attention on patients most likely to need care and, therefore, increase efficiency and effectiveness. The objective of this study was to build a clinical prediction tool for unhealthy drinking based on routinely available demographic and laboratory data. METHODS: We obtained 38 demographic and laboratory variables from the National Health and Nutrition Examination Survey (1999 to 2016) on 43,545 nationally representative adults who had information on alcohol use available as a reference standard. Logistic regression, support vector machines, k-nearest neighbor, neural networks, decision trees, and random forests were used to build clinical prediction models. The model with the largest area under the receiver operator curve was selected to build the prediction tool. RESULTS: A random forest model with 15 variables produced the largest area under the receiver operator curve (0.78) in the test set. The most influential predictors were age, current smoker, hemoglobin, sex, and high-density lipoprotein. The optimum operating point had a sensitivity of 0.50, specificity of 0.86, positive predictive value of 0.55, and negative predictive value of 0.83. Application of the tool resulted in a much smaller target sample (75% reduced). CONCLUSION: Using commonly available data, a decision tool can identify a subset of patients who seem to warrant clinical attention for unhealthy drinking, potentially increasing the efficiency and reach of screening.

Best practices in research mentoring in clinical science.

The growth of clinical science as a field depends on the work of engaged mentors nurturing future generations of scientists. Effective research mentoring has been shown to predict positive outcomes, including greater scholarly productivity, reduced attrition, and increased satisfaction with training and/or employment, which ultimately may enhance the quality of the clinical-science research enterprise. Barriers to effective research mentoring, however, pose significant challenges for both mentees and mentors, as well as for labs, training programs, and/or departments. We discuss some key issues as they apply to clinical-science mentoring and note how they are affected across different developmental levels (undergraduate, postbaccalaureate, doctoral, internship, postdoctoral associates, and early career faculty). Although we do not proclaim expertise on these issues-and have struggled with them in our own careers-we believe an open discussion around best mentoring practices will enhance our collective effectiveness and help mentees and our field to flourish. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The Association between Serum Magnesium Levels and Depression in an Adult Primary Care Population.

Depression is common, places a large burden on the patient, their family and community, and is often difficult to treat. Magnesium supplementation is associated with improved depressive symptoms, but because the mechanism is unknown, it is unclear whether serum magnesium levels act as a biological predictor of the treatment outcome. Therefore, we sought to describe the relationship between serum magnesium and the Patient Health Questionnaire (PHQ, a measure of depression) scores. A cross-sectional analysis of medical records from 3604 adults (mean age 62 years; 42% men) seen in primary care clinics between 2015 and 2018, with at least one completed PHQ were included. The relationship between serum magnesium and depression using univariate analyses showed a significant effect when measured by the PHQ-2 (-0.19 points/mg/dL; 95% CI -0.31, -0.07; P = 0.001) and the PHQ-9 (-0.93 points/mg/dL; 95% CI -1.81, -0.06; P = 0.037). This relationship was strengthened after adjusting for covariates (age, gender, race, time between serum magnesium and PHQ tests, and presence of diabetes and chronic kidney disease) (PHQ-2: -0.25 points/mg/dL; 95% CI -3.33, -0.09; P < 0.001 and PHQ-9: -1.09 95% CI -1.96 -0.21; P = 0.015). For adults seen in primary care, lower serum magnesium levels are associated with depressive symptoms, supporting the use of supplemental magnesium as therapy. Serum magnesium may help identify the biological mechanism of depressive symptoms and identify patients likely to respond to magnesium supplementation.

Measuring the integration of primary care and behavioral health services.

OBJECTIVE: To perform a factor analysis of the Practice Integration Profile (PIP), a 30-item practice-level measure of primary care and behavioral health integration derived from the Agency for Healthcare Research and Quality's Lexicon for Behavioral Health and Primary Care Integration. DATA SOURCES: The PIP was completed by 735 individuals, representing 357 practices across the United States. STUDY DESIGN: The study design was a cross-sectional survey. An exploratory factor analysis and assessment of internal consistency reliability via Cronbach's alpha were performed. DATA COLLECTION METHODS: Participant responses were collected using REDCap, a secure, web-based data capture tool. PRINCIPAL FINDINGS: Five of the PIP's six domains had factor loadings for most items related to each factor representing the PIP of 0.50 or greater. However, one factor had items from two PIP domains that had loadings >0.50. A five-factor model with redistributed items resulted in improved factor loadings for all domains along with greater internal consistency reliability (>0.80). CONCLUSIONS: Five of the PIP's six domains demonstrated excellent internal consistency for measures of health care resources. Although minor improvements to strengthen the PIP are possible, it is a valid and reliable measure of the integration of primary care and behavioral health.

Feasibility of an interactive voice response system for daily monitoring of illicit opioid use during buprenorphine treatment.

In-person retrospective timeline follow-back (TLFB) interviews are a well-established method for collecting self-reports of drug use from patients. However, this method can require significant staff and patient time. In the context of a randomized clinical trial evaluating interim buprenorphine dosing, we examined the feasibility of an interactive voice response (IVR) system for daily monitoring of illicit opioid use during buprenorphine treatment, with a focus on the agreement of illicit opioid use self-report data collected from the concurrent IVR methodology versus retrospective TLFB interviews. Participants (n = 24) received buprenorphine maintenance for 12 weeks and completed nightly IVR calls in which they reported illicit opioid use in the prior 24 hrs. At approximately weekly visits, they provided in-person TLFB reports of illicit opioid use. Levels of data collection were high for both IVR and TLFB methodologies (94.2% vs. 98.5%, respectively) and did not differ. Overall agreement between the 2 methods was high (97%), whereas Cohen's kappa was moderate (k = 0.60). When self-report data were compared with urinalysis results for illicit opioid use, IVR and TLFB approaches both showed high specificity (∼99%), although sensitivity was greater for the TLFB method (48% and 69% for IVR and TLFB, respectively; p = .003). These pilot data suggest that an automated IVR approach may offer an efficient alternative for monitoring self-reported opioid use, especially in rural or resource-constrained settings. Additional efforts to understand and improve IVR sensitivity are warranted. (PsycINFO Database Record (c) 2018 APA, all rights reserved).