Alternative Constructions of Partner Relationships in Chronic Illness: A Qualitative Study Exploring Concurrent Relationships

Chronic illness can have a profound impact on couples’ relationships. In dealing with relational changes, new constructions and forms of relationships may arise. In the context of a larger grounded theory study on relational processes and practices in couples faced with chronic illness, this article focuses on concurrent relationships as an alternative form of relationship construction which embodies an additional relationship existing parallel to that of the couple confronted with chronic illness. Based on qualitative interviews with a subsample of five persons within the larger study, conditions for the development and characteristics of concurrent relationships are presented. From an individual and shared life questioned by chronic illness, concurrent relationships are formed in the attempt to be able to live on together in a new partner relationship and a continued care relationship. This can lead to new constructions of relationships, family life, and social relations in everyday life.

Personality traits predicting different aspects of subjective well-being in elderly adults

The study examined unique predictive relations of personality traits with three components of subjective well-being (WB) in a normative sample (N = 272; 70% females) of Slovene elderly (M = 71.82 years, SD = 6.03). Investigating the concurrent relationships, we relied on the Big Five personality model and the Keyes’s model of WB, which entails emotional well-being (EWB), psychological well-being (PWB), and social well-being (SoWB). We also considered the participants’ background characteristics (age, gender, marital status and educational level), and their subjective health status in predicting the components of WB. The respondents filled-in a scale of subjective health, constructed for the purpose of the study, the Big Five Inventory and the Mental Health Continuum – Short Form. The demographic characteristics did not significantly contribute to any aspect of WB, whereas self-reported health significantly improved the prediction of EWB and PWB. The Big Five uniquely predicted all of the components of WB, over and above demographics and subjective health. Agreeableness was a significant single predictor across the components of WB. Higher levels of conscientiousness and lower levels of neuroticism contributed to EWB. Conscientiousness, extraversion, and openness predicted PWB, and openness predicted SoWB.

A rapid, accurate approach to inferring pedigrees in endogamous populations

Accurate reconstruction of pedigrees from genetic data remains a challenging problem. Pedigree inference algorithms are often trained only on urban European-descent families, which are comparatively ‘outbred’ compared to many other global populations. Relationship categories can be difficult to distinguish (e.g. half-sibships versus avuncular) without external information. Furthermore, published software cannot accommodate endogamous populations where there may be reticulations within a pedigree or elevated haplotype sharing. We design a simple, rapid algorithm which initially uses only high-confidence first degree relationships to seed a machine learning step based on the number of identical by descent segments. Additionally, we define a new statistic to polarize individuals to ancestor versus descendant generation. We test our approach in a sample of 700 individuals from northern Namibia, sampled from an endogamous population. Due to a culture of concurrent relationships in this population, there is a high proportion of half-sibships. We accurately identify first through third degree relationships for all categories, including half-sibships, half-avuncular-ships etc. We further validate our approach in the Barbados Asthma Genetics Study (BAGS) dataset. Accurate reconstruction of pedigrees holds promise for tracing allele frequency trajectories, improved phasing and other population genomic questions.

Cognitive Response Styles and the Construction of Personal Narratives: Implications for Psychopathology in Young Adults

We investigated the concurrent relationships among life story variables (autobiographical reasoning), cognitive variables (negative explanatory style, cognitive reappraisal strategies, and rumination), and psychopathology (symptoms of depression and anxiety). Narratives of life story high, low, and turning points were collected from 164 young adults. Findings for negative self-event connections are reported here. Young adults who made some, as opposed to no, negative self-event connections reported greater symptoms of depression and anxiety and were more likely to report higher levels of ruminative thinking and less likely to use adaptive cognitive reappraisal strategies. Whether participants drew negative self-event connections predicted depression over and above the variance explained by negative explanatory style and cognitive reappraisal strategies and interacted with explanatory style to predict depression. In contrast, negative self-event connections did not incrementally predict anxiety over and above the cognitive variables. Results are discussed in terms of our current understanding of the factors that predict psychological distress.

Reliability, Concurrent Validity, and Minimal Detectable Change for iPhone Goniometer App in Assessing Knee Range of Motion

Much of the published works assessing the reliability of smartphone goniometer apps (SG) have poor generalizability since the reliability was assessed in healthy subjects. No research has established the values for standard error of measurement (SEM) or minimal detectable change (MDC) which have greater clinical utility to contextualize the range of motion (ROM) assessed using the SG. This research examined the test–retest reproducibility, concurrent validity, SEM, and MDC values for the iPhone goniometer app (i-Goni; June Software Inc., v.1.1, San Francisco, CA) in assessing knee ROM in patients with knee osteoarthritis or those after total knee replacement. A total of 60 participants underwent data collection which included the assessment of active knee ROM using the i-Goni and the universal goniometer (UG; EZ Read Jamar Goniometer, Patterson Medical, Warrenville, IL), knee muscle strength, and assessment of pain and lower extremity disability using quadruple numeric pain rating scale (Q-NPRS) and lower extremity functional scale (LEFS), respectively. Intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of the knee ROM assessed using the i-Goni and UG. Bland and Altman technique examined the agreement between these knee ROM. The SEM and MDC values were calculated for i-Goni assessed knee ROM to characterize the error in a single score and the index of true change, respectively. Pearson correlation coefficient examined concurrent relationships between the i-Goni and other measures. The ICC values for the knee flexion/extension ROM were superior for i-Goni (0.97/0.94) compared with the UG (0.95/0.87). The SEM values were smaller for i-Goni assessed knee flexion/extension (2.72/1.18 degrees) compared with UG assessed knee flexion/extension (3.41/1.62 degrees). Similarly, the MDC values were smaller for both these ROM for the i-Goni (6.3 and 2.72 degrees) suggesting smaller change required to infer true change in knee ROM. The i-Goni assessed knee ROM showed expected concurrent relationships with UG, knee muscle strength, Q-NPRS, and the LEFS. In conclusion, the i-Goni demonstrated superior reproducibility with smaller measurement error compared with UG in assessing knee ROM in the recruited cohort. Future research can expand the inquiry for assessing the reliability of the i-Goni to other joints.

Modeling disease spread in populations with birth, death, and concurrency

The existence of sexual partnerships that overlap in time (concurrent relationships) is believed by some to be a significant contributing factor to the spread of HIV, although this is controversial. We derive an analytic model which allows us to investigate and compare disease spread in populations with and without concurrency. We can identify regions of parameter space in which its impact is negligible, and other regions in which it plays a major role. We also see that the impact of concurrency on the initial growth phase can be much larger than its impact on the equilibrium size. We see that the effect of concurrency saturates, which leads to the perhaps surprising conclusion that interventions targeting concurrency may be most effective in populations with low to moderate levels of concurrency.Author SummaryWe consider the spread of an infectious disease through a population modeled by a dynamic network with demographic turnover. We develop a stochastic model of the disease and derive governing equations that exactly predict the large population (deterministic) limit of the stochastic model. We use this to investigate the role of concurrency and find that interventions targeting concurrency may be most effective in populations with lower levels of concurrency.Our model is not intended to be an accurate representation of any single population. Rather it is intended to give general insights for intervention design and to provide a framework which can be further specialized to particular populations.This model is the first model to allow for analytic investigation of the impact of concurrent partnerships in a population exhibiting demographic turnover. Thus it will be useful for investigating the “concurrency hypothesis.”