Sex, race, and the role of relationships in diabetes health: intersectionality matters.

Previous research has seldom used an intersectionality framework to consider how sex and race affect diabetes health, nor has it examined the role of sex and race in the well-established link between romantic relationship quality and health. This study targeted 200 adults with type 2 diabetes (46% Black; 45% female) and examined whether sex, race, and the interaction between sex and race predicted behavioral and psychological health, or moderated the link between relationship quality and health outcomes. Black women reported poorer diabetes self-care and lower self-efficacy compared to other groups. Relationship quality was associated with better self-care, increased self-efficacy, and lower depressive symptoms. The association between relationship quality and medication adherence was stronger for Black women, and the association between relationship quality and self-efficacy was stronger for both Black women and White men. Results suggest that Black women with diabetes experience more health disadvantages than other groups, but some of these disadvantages might be attenuated by supportive romantic relationships.

An examination of the communal coping process in recently diagnosed diabetes.

Communal coping, which involves a shared illness appraisal and engaging in collaboration when illness-related problems arise, is likely beneficial for individuals with type 2 diabetes. The purpose of this work was to examine the process by which communal coping may lead to such benefits. First, we hypothesized that illness-related interactions characterized by more communal coping would involve greater spouse support provision and greater patient receptivity to support. Second, we hypothesized that such interactions would lead to greater perceived problem resolution and more positive perceptions of the interaction. Third, we expected communal coping to predict changes in long-term diabetes outcomes-increased self-efficacy, improved self-care, and reduced diabetes distress-6 months later. Finally, we predicted that these long-term links would be partially explained by the immediate interaction outcomes. We tested these hypotheses in a sample of 123 persons with recently diagnosed type 2 diabetes and their spouses. Patient and spouse communal coping was observed in the laboratory during a diabetes stressor discussion, and patients reported outcomes immediately after the discussion and 6 months later. Results were largely consistent with hypotheses, but spouse communal coping was more consistently linked to support outcomes, and only patient communal coping was linked to changes in long-term outcomes. This work contributes to the literature indicating communal coping is beneficial for individuals with chronic illness and provides insight into the process by which communal coping exerts these effects.

Communally coping with diabetes: An observational investigation using the actor-partner interdependence model.

Communal coping is a form of interpersonal coping that involves a shared illness appraisal and collaborating to address illness-related issues. We hypothesized that communal coping among couples in which one person is recently diagnosed with Type 2 diabetes would be related to better diabetes problem-solving, better mood, greater relationship quality, and less psychological distress for both partners. Communal coping was coded from videotaped interactions in which 119 heterosexual couples discussed difficulties in managing diabetes. Actor-partner interdependence models were performed to isolate associations of actor communal coping and partner communal coping with outcomes, and examined whether the couple-member had diabetes and sex as moderator variables. We expected that communal coping would be more beneficial for women than men, and that partner communal coping would be more strongly linked to outcomes than actor communal coping. Results were largely consistent with hypotheses, suggesting that communal coping is beneficial to couples coping with diabetes. (PsycINFO Database Record

Daily Communal Coping in Couples With Type 2 Diabetes: Links to Mood and Self-Care.

Background: Adjusting to the challenges of a chronic illness does not affect patients alone but also influences social network members-most notably spouses. One interpersonal framework of coping with a chronic illness is communal coping, described as when a problem is appraised as joint and the couple collaborates to manage the problem. Purpose: We sought to determine whether daily communal coping was linked to daily mood and self-care behavior and examined one potential mechanism that may explain these links: perceived emotional responsiveness. Methods: Patients who had been diagnosed with diabetes less than 5 years ago and their spouses (n = 123) completed a daily diary questionnaire that assessed communal coping and mood for 14 consecutive days. The patients also reported daily self-care behaviors. We used multilevel modeling to examine the links of communal coping to patient and spouse mood and patient self-care. Because both patients and spouses reported their mood, the actor-partner interdependence model (APIM) was employed to examine mood. Results: Multilevel APIM showed that actor communal coping was associated with lower depressed mood, higher happy mood, and lower angry mood and partner communal coping was linked to higher happy mood. Patient communal coping was related to better dietary and medication adherence, and spouse communal coping was linked to better medication adherence. Perceived emotional responsiveness partially mediated the relations of communal coping to mood but not to self-care behaviors. Conclusions: Communal coping on a daily basis may help both patients and spouses adjust psychologically to the illness as well as enhance patient self-care behaviors.

A Bayesian model of psychosis symptom trajectory in Alzheimer's disease.

OBJECTIVE: Psychosis, like other neuropsychiatric symptoms of dementia, has many features that make predictive modeling of its onset difficult. For example, psychosis onset is associated with both the absolute degree of cognitive impairment and the rate of cognitive decline. Moreover, psychotic symptoms, while more likely than not to persist over time within individuals, may remit and recur. To facilitate predictive modeling of psychosis for personalized clinical decision making, including evaluating the role of risk genes in its onset, we have developed a novel Bayesian model of the dual trajectories of cognition and psychosis symptoms. METHODS: Cognition was modeled as a four-parameter logistic curve with random effects for all four parameters and possible covariates for the rate and time of fall. Psychosis was modeled as a continuous-time hidden Markov model with a latent never-psychotic class and states for pre-psychotic, actively psychotic and remitted psychosis. Covariates can affect the probability of being in the never-psychotic class. Covariates and the level of cognition can affect the transition rates for the hidden Markov model. RESULTS: The model characteristics were confirmed using simulated data. Results from 434 AD patients show that a decline in cognition is associated with an increased rate of transition to the psychotic state. CONCLUSIONS: The model allows declining cognition as an input for psychosis prediction, while incorporating the full uncertainty of the interpolated cognition values. The techniques used can be used in future genetic studies of AD and are generalizable to the study of other neuropsychiatric symptoms in dementia.

Does e-pain plan improve management of sickle cell disease associated vaso-occlusive pain crisis? a mixed methods evaluation.

PURPOSE: There is limited application and evaluation of health information systems in the management of vaso-occlusive pain crises in sickle cell disease (SCD) patients. This study evaluates the impact of digitization of paper-based individualized pain plans on process efficiency and care quality by examining both objective patient data and subjective clinician insights. METHODS: Retrospective, before and after, mixed methods evaluation of digitization of paper documents in Children's Hospital of Pittsburgh of UPMC. Subjective perceptions are analyzed using surveys completed by 115 clinicians in emergency department (ED) and inpatient units (IP). Objective effects are evaluated using mixed models with data on 1089 ED visits collected via electronic chart review 28 months before and 22 months after the digitization. RESULTS: Surveys indicate that all clinicians perceived the digitization to improve the efficiency and quality of pain management. Physicians overwhelmingly preferred using the digitized plans, but only 44% of the nurses had the same response. Analysis of patient records indicates that adjusted time from analgesic order to administration was significantly reduced from 35.50 to 26.77 min (p<.05). However, time to first dose and some of the objective quality measures (time from administration to relief, relief rate, admission rate, and ED re-visit rate) were not significantly affected. DISCUSSION: The relatively simple intervention, high baseline performance, and limited accommodation of nurses' perspectives may account for the marginal improvements in process efficiency and quality outcomes. Additional efforts, particularly improved communication between physicians and nurses, are needed to further enhance quality of pain management. CONCLUSION: This study highlights the important role of health information technology (HIT) on vaso-occlusive pain management for pediatric patients with sickle cell disease and the critical challenges in accommodating human factor considerations in implementing and evaluating HIT effects.

Trajectories of cognitive decline in Alzheimer's disease.

BACKGROUND: Late-onset Alzheimer disease (LOAD) is a clinically heterogeneous complex disease defined by progressively disabling cognitive impairment. Psychotic symptoms which affect approximately one-half of LOAD subjects have been associated with more rapid cognitive decline. However, the variety of cognitive trajectories in LOAD, and their correlates, have not been well defined. We therefore used latent class modeling to characterize trajectories of cognitive and behavioral decline in a cohort of AD subjects. METHODS: 201 Caucasian subjects with possible or probable Alzheimer's disease (AD) were evaluated for cognitive and psychotic symptoms at regular intervals for up to 13.5 years. Cognitive symptoms were evaluated serially with the Mini-mental State Examination (MMSE), and psychotic symptoms were rated using the CERAD behavioral rating scale (CBRS). Analyses undertaken were latent class mixture models of quadratic trajectories including a random intercept with initial MMSE score, age, gender, education, and APOE 4 count modeled as concomitant variables. In a secondary analysis, psychosis status was also included. RESULTS: AD subjects showed six trajectories with significantly different courses and rates of cognitive decline. The concomitant variables included in the best latent class trajectory model were initial MMSE and age. Greater burden of psychotic symptoms increased the probability of following a trajectory of more rapid cognitive decline in all age and initial MMSE groups. APOE 4 was not associated with any trajectory. CONCLUSION: Trajectory modeling of longitudinal cognitive and behavioral data may provide enhanced resolution of phenotypic variation in AD.

Functional brain maturation in neonates as measured by EEG-sleep analyses.

OBJECTIVE: Seven measures of neonatal EEG-sleep behavior were evaluated using multivariate analyses to ascertain if physiologic differences exist between healthy full- and preterm cohorts. METHODS: A total of 381 24-channel EEG-sleep studies were analyzed, including 125 recordings on 50 healthy fullterm and 256 recordings on 59 asymptomatic preterm infants between 28 and 70.6 weeks post-conceptional age. One EEG study for each subject was randomly assigned (109 studies) within the time window of 38-44 weeks post-conceptional age. A multivariate analytic procedure was applied to the data sets, by which a 'dysmaturity index' was assigned for each infant, based on 7 EEG-sleep measures. This index was defined in terms of the distance from the fullterm group's centroid (i.e. Mahalanobis distance). Receiver-operating characteristic curves (ROCs) were calculated for several different combinations of 7 EEG-sleep measures to describe differences between neonatal cohorts. RESULTS: The ROC curve corresponding to all 7 EEG-sleep measures covered the substantially largest area among the curves for the sets of variables considered, suggesting that all 7 measures of sleep behavior were required to best discriminate between cohorts. CONCLUSIONS: This methodology exemplifies how EEG-sleep analyses can be applied to the study of functional brain maturation of infants at risk for neurodevelopment problems. SIGNIFICANCE: Changes in EEG-sleep behavior in the preterm infant may represent altered activity-dependent development of neural circuitry, resulting in remodeling of the immature brain as a reflection of adaptation to conditions of prematurity.