Felt Age and its Psychological Correlates in Dementia Spousal Caregiving Dyads: Findings from the IDEAL Programme.

OBJECTIVES: Evidence suggests spouses influence each other's subjective views on aging. Aligned with the Theory of Dyadic Illness Management, we investigated for the first time similarities in felt age (how old people feel relative to their chronological age) between people with dementia and their spousal caregivers, and how each partner's felt age was related to psychological correlates in the other partner. METHODS: We used baseline (2014-2016) data from 1,001 people with dementia and their spousal caregivers who participated in the British IDEAL study. We ran linear regressions to analyze the extent to which the felt age of people with dementia and their caregivers were similar, and whether relationship quality was associated with the similarity. We utilized Actor-Partner Interdependence Models to analyze whether the felt age of people with dementia and their caregivers were associated with each other's well-being, satisfaction with life, and self-efficacy. RESULTS: The felt age of people with dementia was associated with the felt age of their caregivers (ß=.10; p=.001). Caregivers and people with dementia reported a more similar felt age when caregivers rated the caregiving relationship more positively (ß=.07; p=.043). Caregivers' felt age was associated with well-being (ß=.07; p=.024) and satisfaction with life (ß=.06; p=.044), but not with self-efficacy, in people with dementia. DISCUSSION: Felt age in caregivers and people with dementia may be interwoven, and important psychological variables in people with dementia are related to caregivers' felt age. Findings offer empirical evidence on dementia caregiving dynamics and how family relationships are related to views on aging.

Unpacking the process of developing South Africa's national drug policy - lessons for universal health coverage.

Background: South Africa's National Drug Policy (NDP) was first issued in 1996, at a time of considerable political change. Objectives: To revisit the lessons learned from the process of development and initial implementation of the NDP. Methods: Six in-depth face-to-face interviews were held with purposively-selected key actors. Interviews, which followed pre-determined semi-structured questions, but were allowed to explore additional areas, were recorded and transcribed, and then subjected to abductive thematic analysis, informed by the Walt and Gilson model. Results: Three key themes emerged, described as 'evidence', 'trust' and 'looking forward'. A paucity of evidence backed some of the key concepts in the NDP, and these have not been addressed as evidence has matured. The lack of trust which characterised the policy process impacted on the ways in which actors were able to or not able to engage, and therefore on the resultant content and the choices exercised. The coherence of the policy, its articulation with other health reforms, and its contribution to subsequent efforts to ensure universal health coverage in South Africa have all been weakened by the failure to revise the document over time. Conclusion: As South Africa advances its plans for universal health coverage, there is an urgent need to revisit key components of the NDP which are no longer fit for purpose.

A priority experience replay actor-critic algorithm using self-attention mechanism for strategy optimization of discrete problems.

In the dynamic field of deep reinforcement learning, the self-attention mechanism has been increasingly recognized. Nevertheless, its application in discrete problem domains has been relatively limited, presenting complex optimization challenges. This article introduces a pioneering deep reinforcement learning algorithm, termed Attention-based Actor-Critic with Priority Experience Replay (A2CPER). A2CPER combines the strengths of self-attention mechanisms with the Actor-Critic framework and prioritized experience replay to enhance policy formulation for discrete problems. The algorithm's architecture features dual networks within the Actor-Critic model-the Actor formulates action policies and the Critic evaluates state values to judge the quality of policies. The incorporation of target networks aids in stabilizing network optimization. Moreover, the addition of self-attention mechanisms bolsters the policy network's capability to focus on critical information, while priority experience replay promotes training stability and reduces correlation among training samples. Empirical experiments on discrete action problems validate A2CPER's adeptness at policy optimization, marking significant performance improvements across tasks. In summary, A2CPER highlights the viability of self-attention mechanisms in reinforcement learning, presenting a robust framework for discrete problem-solving and potential applicability in complex decision-making scenarios.

Factors effecting on health-promoting behaviors in iranian pregnant women and their husbands: the actor-partner interdependence model (APIM).

INTRODUCTION: Pregnancy is an important period of life for women and their husbands as the couple's health is essential. The present study evaluated the impact of some factors (marital adjustment with depressive symptoms) on health-promoting behaviors in pregnant women and their husbands based on the actor-partner interdependence model (APIM). MATERIALS AND METHODS: This descriptive study examined 211 couples (pregnant women and their husbands) in pregnancy clinics of Babol University of Medical Sciences using a convenience sampling method. The participants completed Spanier's Dyadic Adjustment Scale (DAS) (1979), Edinburgh Postnatal Depression Scale (EPDS) (1987), and Walker's Health Promoting Lifestyle Profile II (HPLPII) questionnaire (1997). The relationships between women and their husbands were also evaluated using structural equation modeling with R software according to the Lavaan (latent variable analysis) package based on APIM-SEM. RESULTS: The pregnant women's marital adjustment positively affected their health-promoting behaviors (ß = 0.456, 95% Cl: 0.491-0.998, p < 0.001) and their husbands' (ß = 0.210, 95% Cl: 0.030-0.726, p = 0.048). Pregnant woman's depressive symptoms also negatively affected their health-promoting behaviors (ß=-0.088, 95% Cl: -0.974-0.074, P = 0.236) and their husbands' health-promoting behaviors (ß=-0.177, 95% Cl: -0.281 - -0.975, P = 0.011). Furthermore, the husband's marital adjustment only positively affected his studied behaviors (ß = 0.323, 95% Cl: 0.0303-0.895, P < 0.001) but did not affect the pregnant woman's health behaviors. The husband's depressive symptoms had a negative impact on his studied behaviors (ß = 0.219, 95% Cl: -0.122 - -0.917, P = 0.001) and did not affect the pregnant woman's depressive symptoms. Our findings confirmed the mediating role of depressive symptoms in pregnant women and their husbands on the association of marital adjustment and health-promoting behaviors. According to the actor-partner study, a pregnant woman's marital adjustment scores positively affected her studied behaviors and her husband (ß = 0.071, 95% Cl: 0.042-0.278, P = 0.015) by decreasing her depression score. Therefore, the husband's marital adjustment score positively affected his studied behaviors by decreasing his depression score (ß = 0.084, 95% Cl: -0.053 -0.292, P = 0.005), and it did not affect his wife's health-promoting behaviors. DISCUSSION AND CONCLUSION: These findings suggest healthcare providers, obstetricians, and psychologists evaluate the husbands' symptoms of depression and health-promoting behaviors in the routine pregnancy care of pregnant women. They also pay great attention to marital adjustment as a determinant of reducing depressive symptoms in pregnant women and their husbands.

Reassembling nursing in the digital age: An actor-network theory perspective.

This article explores the application of actor-network theory (ANT) to the nursing profession, proposing a novel perspective in understanding nursing in the context of modern digital healthcare. Traditional grand nursing theories, while foundational, often fail to encapsulate the dynamic and complex nature of nursing, particularly in an era of rapid technological advancements and shifting societal dynamics. ANT, with its emphasis on the relationships between human and nonhuman actors, offers a framework to understand nursing beyond traditional paradigms. This article makes two key arguments: first, that nursing can be viewed as a highly organised social assemblage, where both human (nurses, patients and policymakers) and nonhuman actors (technologies, medical equipment, institutional policies) play a crucial role, and second, that ANT can be used to enhance existing nursing theory to better understand the role of technology in nursing practice. The article considers how ANT can provide a more holistic and adaptable model for describing the nursing profession, particularly in an era where technology plays an integral role in healthcare delivery. It discusses the implications of viewing nursing through ANT, highlighting the need for nursing education and practice to adapt to the interconnected and technologically advanced nature of modern healthcare. The article also acknowledges the limitations of ANT, particularly its potential oversimplification of the complex ethical dimensions inherent in nursing and its focus on observable phenomena.

Unveiling Influence in Networks: A Novel Centrality Metric and Comparative Analysis through Graph-Based Models.

Identifying influential actors within social networks is pivotal for optimizing information flow and mitigating the spread of both rumors and viruses. Several methods have emerged to pinpoint these influential entities in networks, represented as graphs. In these graphs, nodes correspond to individuals and edges indicate their connections. This study focuses on centrality measures, prized for their straightforwardness and effectiveness. We divide structural centrality into two categories: local, considering a node's immediate vicinity, and global, accounting for overarching path structures. Some techniques blend both centralities to highlight nodes influential at both micro and macro levels. Our paper presents a novel centrality measure, accentuating node degree and incorporating the network's broader features, especially paths of different lengths. Through Spearman and Pearson correlations tested on seven standard datasets, our method proves its merit against traditional centrality measures. Additionally, we employ the susceptible-infected-recovered (SIR) model, portraying virus spread, to further validate our approach. The ultimate influential node is gauged by its capacity to infect the most nodes during the SIR model's progression. Our results indicate a notable correlative efficacy across various real-world networks relative to other centrality metrics.

Intelligent control of self-driving vehicles based on adaptive sampling supervised actor-critic and human driving experience.

Due to the complexity of the driving environment and the dynamics of the behavior of traffic participants, self-driving in dense traffic flow is very challenging. Traditional methods usually rely on predefined rules, which are difficult to adapt to various driving scenarios. Deep reinforcement learning (DRL) shows advantages over rule-based methods in complex self-driving environments, demonstrating the great potential of intelligent decision-making. However, one of the problems of DRL is the inefficiency of exploration; typically, it requires a lot of trial and error to learn the optimal policy, which leads to its slow learning rate and makes it difficult for the agent to learn well-performing decision-making policies in self-driving scenarios. Inspired by the outstanding performance of supervised learning in classification tasks, we propose a self-driving intelligent control method that combines human driving experience and adaptive sampling supervised actor-critic algorithm. Unlike traditional DRL, we modified the learning process of the policy network by combining supervised learning and DRL and adding human driving experience to the learning samples to better guide the self-driving vehicle to learn the optimal policy through human driving experience and real-time human guidance. In addition, in order to make the agent learn more efficiently, we introduced real-time human guidance in its learning process, and an adaptive balanced sampling method was designed for improving the sampling performance. We also designed the reward function in detail for different evaluation indexes such as traffic efficiency, which further guides the agent to learn the self-driving intelligent control policy in a better way. The experimental results show that the method is able to control vehicles in complex traffic environments for self-driving tasks and exhibits better performance than other DRL methods.

Prognostic understanding among advanced heart failure patients and their caregivers: A longitudinal dyadic study.

OBJECTIVES: To examine heart failure patients' and caregivers' prognostic understanding (PU) over time, and patient and caregiver factors associated with their own and each other's PU. METHODS: We used longitudinal dyadic data from Singapore, involving surveys with 95 heart failure patient-caregiver dyads every 4 months for up to 4 years. We assessed the association of PU with patient health status, caregiver psychological distress and caregiving hours using random effects multinomial logistic models, controlling for patient and caregiver characteristics. RESULTS: At baseline, half of patients and caregivers reported correct PU. Patient and caregiver variables were associated with their own and each other's PU. Patients with poorer functional well-being were less likely to report correct PU [Average Marginal Effects (95 % CI) 0.008 (0.002, 0.015)] versus incorrect PU. Greater caregiver psychological distress was associated with a lower likelihood of caregivers reporting a correct PU [- 0.008 (-0.014, -0.002)]. Higher caregiving hours reduced the likelihood of patients reporting correct [- 0.002 (-0.003, -0.001)] and increased the likelihood of patients reporting uncertain [0.001 (0, 0.002)] PU. CONCLUSIONS: We found PU among patients and caregivers was influenced by their own and each other's experience. Our findings highlight the importance of ongoing communication to enhance PU of patients and caregivers.

Testing the Associations Between Attachment Anxiety, Relational Aggression and Depressive Symptoms in Romantic Relationships: Actor-Partner Interdependence Model and Actor-Partner Interdependence Mediator Model.

Emerging adulthood is a pivotal period for romantic relationships, yet the specific mechanisms through which attachment anxiety influences relationship dynamics and psychological outcomes in this phase are poorly understood. Particularly, in the context of romantic dyads, understanding how partners' behaviors and emotional patterns reciprocally influence each other remains underexplored. This study utilizes the Actor-Partner Interdependence Model and Actor-Partner Interdependence Mediator Model to explore the relationship between attachment anxiety,relational aggression (both perpetration and victimization), and depressive symptoms among emerging adults. A sample of 138 mixed-sex emerging adulthood couples from China, was recruited (Mage = 21.40, SD = 2.54; 50% female, 62.6% reporting that this relationship was ongoing for more than a year). Attachment anxiety significantly predicted relational aggression in both partners, with male attachment anxiety also significantly predicted female relational aggression. Significant indirect effects of both partners' relational aggression perpetration and victimization on their own and each other's relationship between attachment anxiety and depressive symptoms. These findings contribute to understanding the intricate dynamics of attachment anxiety and relational aggression in romantic relationships during emerging adulthood, emphasizing the need for targeted interventions to mitigate these risks.

Dyadic effects of financial toxicity and social support on the fear of cancer recurrence in breast cancer patients and caregivers: an actor-partner interdependence mediation model.

PURPOSE: In this study, the actor-partner interdependence mediation model (APIMeM) was applied to breast cancer patients and their caregivers to assess the factors that affect the fear of cancer recurrence. In particular, the purpose of this study was to evaluate the mediating effect of social support on financial toxicity and the fear of cancer recurrence, providing an effective basis for developing plans to reduce the level of fear of cancer recurrence. METHODS: This study employed a cross-sectional design, and 405 dyads of breast cancer patients and their caregivers were enrolled. Financial toxicity, social support, and fear of cancer recurrence were assessed by computing comprehensive scores for financial toxicity based on patient-reported outcome measures, the Social Support Rating Scale, and the Fear of Cancer Recurrence Inventory Short Form, respectively. The data were analysed using SPSS 24.0 and AMOS 23.0. RESULTS: The results showed that the fear of cancer recurrence of breast cancer patients and their caregivers was significantly related to dyadic financial toxicity and social support. In addition, the financial toxicity of breast cancer patients and their caregivers had significant actor effects and partner effects on the fear of cancer recurrence through dyadic social support. CONCLUSIONS: The financial toxicity of breast cancer patients and their caregivers could produce actor and partner effects on the fear of cancer recurrence through the mediation of social support, which provided empirical support for improving reducing the level of fear of cancer recurrence among patients and caregivers at the dyadic level.

Constant force grinding controller for robots based on SAC optimal parameter finding algorithm.

Since conventional PID (Proportional-Integral-Derivative) controllers hardly control the robot to stabilize for constant force grinding under changing environmental conditions, it is necessary to add a compensation term to conventional PID controllers. An optimal parameter finding algorithm based on SAC (Soft-Actor-Critic) is proposed to solve the problem that the compensation term parameters are difficult to obtain, including training state action and normalization preprocessing, reward function design, and targeted deep neural network design. The algorithm is used to find the optimal controller compensation term parameters and applied to the PID controller to complete the compensation through the inverse kinematics of the robot to achieve constant force grinding control. To verify the algorithm's feasibility, a simulation model of a grinding robot with sensible force information is established, and the simulation results show that the controller trained with the algorithm can achieve constant force grinding of the robot. Finally, the robot constant force grinding experimental system platform is built for testing, which verifies the control effect of the optimal parameter finding algorithm on the robot constant force grinding and has specific environmental adaptability.

Is passion contagious in coach-athlete dyads? A dyadic exploration of the association between passion, affective and need-based experiences in individual sports.

The Dualistic Model of Passion distinguishes between harmonious and obsessive passion, which are associated with athletes' and coaches' adjustments. Whereas prior research sampled either athletes or coaches, the present study used a dyadic approach to explore the bidirectional influence of passion on affective experiences in coaches and athletes. Using a cross-sectional dyadic design, 198 coach-athlete dyads involved in an individual sport at different competition levels, reported on their passion, need-based, and affective experiences. Both actor effects (i.e., intrapersonal dynamics within athletes or coaches) and partner effects (i.e., interpersonal dynamics from coach to athlete and vice versa) were examined. Furthermore, dyadic mediation models were used to investigate the potential mediating role of need-based experiences in the association between passion and affective experiences. Results unveiled compelling evidence for actor effects, indicating that one's own harmonious passion was positively related to one's own more adaptive outcomes and negatively to one's own more maladaptive outcomes, whereas obsessive passion was positively related to maladaptive outcomes. Further, very limited evidence for partner effects, in which coaches' passion affected athletes' outcomes or vice versa, was found. The dyadic mediation models underscored the role of need-based experiences in mediating the association between passion and affective experiences, but only at the intrapersonal level. As such, one's own passion experiences were related to one's own need-based experiences, which in turn were related to one's own affective experiences. The study provided no evidence for interpersonal mediation effects.

Childcare sharing and family happiness: analyzing parental and child well-being in the actor-partner interdependence model.

Introduction: The exploration of the relationship between parental and child happiness, particularly in the context of shared childcare responsibilities, has not been examined in Korean families. Methods: Using a two-wave longitudinal design and data from 1,403 families from the Panel Study on Korean Children, this study employed the actor-partner interdependence model to examine the dynamics of childcare sharing between mothers and fathers in South Korea. Results: Mothers' childcare sharing was found to have no significant impact on their own and their partner's happiness, reflecting traditional gender norms that undervalue mothers' contributions. In contrast, fathers' childcare sharing had a positive impact on their own and their spouse's happiness, suggesting a growing recognition of fathers' involvement. Furthermore, fathers' active participation in childcare was found to promote their children's happiness through their own happiness. Discussion: This study reflects the complexity of evolving family roles and the covert persistence of traditional gender roles in modern Korean parenting. It suggests the importance of work and family policies that support changes in family dynamics by providing a more nuanced understanding of how changing family roles and responsibilities can enhance overall family well-being.

The dyadic associations among self-efficacy, dyadic coping, and health-related quality of life between high-risk pregnant women and spouses: a cross-sectional study.

AIM: Health-related quality of life(HRQoL) is essential for high-risk pregnant women and their spouses. This study aimed to explore the dyadic associations (including actor and partner effects) among self-efficacy, dyadic coping, and HRQoL of high-risk pregnant women and their spouses and examine the mediating effect of dyadic coping. METHODS: This cross-sectional study recruited participants from two Grade A tertiary hospitals in China from October 2022 to September 2023. A questionnaire including the Chinese version of the General Self-Efficacy Scale, Dyadic Coping Inventory, and 12 Short Form Health Survey Scales was used for the survey. The actor-partner interdependence mediation model was constructed to test dyadic associations and mediating effects. RESULTS: In the actor effects, self-efficacy was positively associated with dyadic coping and HRQoL (P < 0.05). Regarding partner effects, pregnant women's self-efficacy was positively associated with spouses' dyadic coping and physical health (P < 0.05). Dyadic coping partially mediated the relationship between self-efficacy and HRQoL for both groups(P < 0.05). CONCLUSION: The HRQoL of high-risk pregnant women and their spouses requires urgent attention. Enhancing self-efficacy and dyadic coping in these couples is related to their improved physical and mental health. Healthcare professionals should consider interactions between couples and include them together in perinatal care. Intervention programs for couples or families based on existing positive psychology and dyadic interventions may work together to improve the HRQoL of couples.

The Relationship between Addictive Use of Short-Video Platforms and Marital Satisfaction in Older Chinese Couples: An Asymmetrical Dyadic Process.

Increasing evidence indicates that the addictive use of social media can have a detrimental effect on marital satisfaction, due mainly to the decrease in time and focus given to one's spouse. However, the impact of social media use among older couples remains under-investigated, and the research that does exist relies on individual-level data that do not allow the exploration of the dynamics between the dyadic partners. Therefore, the present study focused on older adults' use of short-video platforms, as these have been shown to be particularly addictive for older adults. A sample of 264 older couples was gathered (meanage = 68.02, SD = 8.68), and both spouses completed surveys reporting addictive use of short-video platforms, negative emotions, and marital satisfaction. Using an actor-partner interdependence model, we found an asymmetrical dyadic process in that the addictive use of short-video platforms by the wives was not only related to their own negative emotions, but also those of their spouse, as well as to decreased marital satisfaction. Meanwhile, addictive use by the husbands seemed to relate only to their own increased negative emotions, as well as to decreased marital satisfaction. Together, the findings from this study reveal dyadic dynamics with delineated pathways through which the addictive use of short-video platforms can damage older couples' interactive processes and marital satisfaction.

Decentralized multi-agent reinforcement learning based on best-response policies.

Introduction: Multi-agent systems are an interdisciplinary research field that describes the concept of multiple decisive individuals interacting with a usually partially observable environment. Given the recent advances in single-agent reinforcement learning, multi-agent reinforcement learning (RL) has gained tremendous interest in recent years. Most research studies apply a fully centralized learning scheme to ease the transfer from the single-agent domain to multi-agent systems. Methods: In contrast, we claim that a decentralized learning scheme is preferable for applications in real-world scenarios as this allows deploying a learning algorithm on an individual robot rather than deploying the algorithm to a complete fleet of robots. Therefore, this article outlines a novel actor-critic (AC) approach tailored to cooperative MARL problems in sparsely rewarded domains. Our approach decouples the MARL problem into a set of distributed agents that model the other agents as responsive entities. In particular, we propose using two separate critics per agent to distinguish between the joint task reward and agent-based costs as commonly applied within multi-robot planning. On one hand, the agent-based critic intends to decrease agent-specific costs. On the other hand, each agent intends to optimize the joint team reward based on the joint task critic. As this critic still depends on the joint action of all agents, we outline two suitable behavior models based on Stackelberg games: a game against nature and a dyadic game against each agent. Following these behavior models, our algorithm allows fully decentralized execution and training. Results and Discussion: We evaluate our presented method using the proposed behavior models within a sparsely rewarded simulated multi-agent environment. Although our approach already outperforms the state-of-the-art learners, we conclude this article by outlining possible extensions of our algorithm that future research may build upon.

Standardized patients' experience of participating in medical students' education: a qualitative content analysis.

BACKGROUND: Standardized patients are considered a significant educational method in medical sciences and have been successfully employed for many years. This study was conducted with the aim of explaining the experience of standardized patients participating in the education of medical student. METHOD: A qualitative content analysis approach was used. This study was conducted at Standardized Patient Center, Tehran University of Medical Sciences, Tehran, Iran, May to February 2022. Fifteen standard patients were selected through purposive sampling with maximum variation. Semi-structured, in-depth, face-to-face interviews were conducted with standard patients. The average duration of the interviews was 60 to 90 min. Data were transcribed and analyzed using the Graneheim and Lundman approach. RESULTS: A passport for the future and duality of feelings were the two main themes identified in this study with six subthemes. One of the main themes was passport for the future with subthemes creative, participation in educating future generation, reflection and another theme was duality of feeling with subthemes feeling of value, guilty conscience, and fear of judgment by others. CONCLUSION: The participants expressed having mixed feelings about their role as standard patients. They felt conflicted because they were compensated for their participation, which made them worry about being judged by others and feel guilty about taking the fee. Therefore, it is recommended to conduct further studies in this area.

Dyadic coping and associated factors in women with high-risk pregnancy and their spouses: Do they interact?

OBJECTIVE: The objective of this study was to examine the present situation of dyadic coping in pregnant women with high-risk pregnancy and their spouses, as well as the relevant factors and the interactions between partners. METHODS: From October 2022 to September 2023, a cross-sectional survey was undertaken, involving 460 pairs of pregnant women with high-risk pregnancy who were hospitalized for childbirth and their accompanying spouses. These participants completed self-assessments on dyadic coping, marital satisfaction, perceived stress, and self-efficacy through the completion of paper questionnaires. The collected data was then subjected to analysis utilizing correlation analysis and multiple linear regression. The actor-partner interdependence model (APIM) was then developed using the structural equation modeling(SEM) to test the binary association. FINDINGS: Pregnant women preferred to utilize stressful communication, whereas their spouses employed supportive and delegated coping. Both external (such as education level, employment status, and medical insurance) and internal (such as marital satisfaction, perceived stress, and self-efficacy) factors were associated with pregnant women's dyadic coping. Education level and internal factors were also associated with the spouses' dyadic coping. In contrast to spouses, who can only have a partner effect on pregnant women through marriage satisfaction, all pregnant women's internal elements played the partner effect on the spouses' dyadic coping. IMPLICATIONS: The study's findings help identify populations with inadequate coping ability. Promoting marital satisfaction, self-efficacy, and reducing perceived stress are associated with enhancing the dyadic coping ability of pregnant women with high-risk pregnancy and their spouses. It also suggests that antenatal care should intervene with pregnant women with high-risk pregnancy and their spouses as a whole, and emphasize collaborative coping and effective mutual support between couples rather than spousal support alone.

Dyadic coping, resilience, and quality of life in young and middle-aged couples after gynecologic cancer: An actor-partner interdependence mediation model.

PURPOSE: To examine the effects of dyadic coping on quality of life (QoL) and the mediating role of resilience in these effects among young and middle-aged couples after gynecologic cancer (GC). METHODS: A cross-sectional study was conducted between July 2022 and June 2023 from one tertiary hospital in Wuhan, China. 240 pairs of young and middle-aged GC couples were recruited. The demographic and clinical characteristics questionnaire, the Dyadic Coping Inventory, the 10-item Connor-Davidson Resilience Scale, and the 12-item Short-Form Health Survey were used to collect data. The process of dyadic analysis was based on the actor-partner interdependence mediation model. RESULTS: GC patients' dyadic coping had an actor effect on both their own physical and mental QoL, while spouses' dyadic coping only exerted an actor effect on their own mental QoL. The mediating effects of resilience on the relationship between dyadic coping and QoL were identified in dyads. Moreover, spouses' dyadic coping could indirectly influence patients' QoL through their own and patients' resilience. CONCLUSION: The findings confirm the dyadic relationships between dyadic coping, resilience, and QoL among young and middle-aged couples facing GC. These results suggest that it is necessary to develop couple-based interventions to improve dyadic coping and resilience, thus enhancing the QoL of both members.

Examining the social and behavioral dynamics of substance use in a longitudinal network study in rural Appalachia.

BACKGROUND: Prior studies have shown that individuals and their peers often have similar substance use behaviors, but the mechanisms driving these similarities - particularly in rural settings, are not well understood. The primary objectives of this analysis are to (1) identify factors that contribute to relationship turnover and maintenance within a rural network of persons who use drugs (PWUD), (2) determine whether assimilation and/or homophily shape participants use of injection drugs, heroin, and stimulants (methamphetamine and cocaine), and (3) assess the extent that these mechanisms influence networks ties and/or behaviors and whether these effects vary across time. METHODS: Sociometric network data were collected from a cohort of PWUD in rural Eastern Kentucky at baseline (2008-2010) and at four follow-up visits conducted approximately semiannually. Stochastic actor-oriented models (SAOMS) were used to model network structure and participant behaviors as jointly dependent variables and to identify characteristics associated with the maintenance, dissolution, and formation of network ties and changes in drug use behaviors. RESULTS: Findings suggest (1) greater network stability over time for reciprocal and transitive relationships, (2) both homophily and assimilation played a greater role in shaping injection drug use (IDU) initiation and cessation than they did in shaping heroin and stimulant use, and (3) the importance of these mechanisms appeared consistent over time. CONCLUSION: Given the stability of particular network structures and evidence of both homophily and assimilation with respect to drug-use behaviors, interventions that leverage social networks could be used to motivate health-promoting behaviors.