Fear of cancer recurrence in breast cancer: A moderated serial mediation analysis of a prospective international study.

OBJECTIVE: Women dealing with breast cancer (BC) face many challenges, one of which is the fear of cancer recurrence (FCR). This study examined whether disease severity predicts FCR 6 months after cancer diagnosis through psychological distress and whether cognitive-emotion regulation moderates this effect. METHOD: The study sample included 656 women from Italy (27.5%), Finland (31.9%), Israel (19.8%), and Portugal (20.8%) diagnosed with Stages I-III of BC. Participants' age ranged between 40 and 70 years (M = 54.92, SD = 8.22). Participants were tracked following BC diagnosis and at 3 and 6 months follow-up. Participants filled out self-report questionnaires, including the FCR inventory-short form, the Hospital Anxiety and Depression Scale, and the cognitive-emotion regulation questionnaire along with medical-social-demographic data. RESULTS: Greater disease severity at baseline indicated by higher cancer stage predicted greater psychological distress, which in turn predicted greater psychological distress at 3 months. The latter predicted greater FCR at 6 months. This serial mediation model was moderated by negative cognitive-emotion regulation. The mediating effect of disease severity on FCR through psychological distress was significant only in women with mean or higher levels of negative cognitive-emotion regulation. CONCLUSION: This study suggests that facilitating psychological well-being and effective cognitive-emotion regulation in the early stages after a cancer diagnosis may protect women from FCR. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Quality of Life and Incidence of Clinical Signs and Symptoms among Caregivers of Persons with Mental Disorders: A Cross-Sectional Study.

BACKGROUND: Caring for individuals with mental disorders poses significant challenges for caregivers, often leading to compromised quality of life and mental health issues such as stress, anxiety, and depression. This study aims to assess the extent of these challenges among caregivers in Greece, identifying which demographic factors influence their well-being. METHOD: A total of 157 caregivers were surveyed using the SF-12 Health Survey for quality-of-life assessment and the DASS-21 questionnaire for evaluating stress, anxiety, and depression symptoms. t-tests, Kruskal-Wallis tests, Pearson's correlation coefficients, and regression analyses were applied to understand the associations between demographics, quality of life, and mental health outcomes. RESULTS: The study found that caregivers, especially women and younger individuals, faced high levels of mental health challenges. Marital status, educational level, and employment status also significantly influenced caregivers' well-being. Depression was the most significant factor negatively correlating with the mental component of quality of life. The magnitude of the burden experienced by caregivers highlighted the urgency for targeted social and financial support, as well as strategic treatment programs that consider caregiver well-being. CONCLUSIONS: Caregivers of individuals with mental disorders endure significant stress, anxiety, and depression, influencing their quality of life. Demographic factors such as age, gender, marital status, education, and employment status have notable impacts. Findings emphasize the need for society-wide recognition of caregivers' roles and the creation of comprehensive support and intervention programs to alleviate their burden, particularly in the context of the COVID-19 pandemic.

Psychosocial interventions on the posttraumatic growth of adults with cancer: A systematic review and meta-analysis of clinical trials.

BACKGROUND: It has been increasingly recognized that some people experience post-traumatic growth (PTG) as a result of struggling with cancer. OBJECTIVE: This systematic review aims to identify psychosocial interventions that might facilitate PTG in adults with cancer. METHODS: A search was conducted in PsycINFO, PubMed, Scopus, the Cochrane Library, and ProQuest up to 16 September 2022. The PRISMA guidelines were followed; all included interventional studies had to comprise 30 or more adults with cancer, using the Posttraumatic Growth Inventory, from 1994 forward. RESULTS: A total of 2731 articles were retrieved, 1028 of those were screened and 37 unique trials were included (46 articles). A large number of studies were published since 2018 (52.4%), were randomized controlled trials (43.2%), and had group interventions (34.8%), including mainly female participants (83.8%) with a single cancer type (54.1%). Most interventions (75.7%) were moderately to highly effective in increasing PTG (d = 0.65, 95% CI 0.39-0.91) with the most effective interventions using Cognitive Behavioral Therapy (d = 1.24, 95% CI: 0.05-2.44), Mindfulness-based (d = 0.54, 95% CI = 0.14-0.94) and Education, Peer Support and Health Coaching interventions (d = 0.28, 95% CI: 0.1-0.46). Expression-based and Positive Psychology-based approaches also showed promising results. Notably, the majority of studies had a high risk of bias. CONCLUSIONS: PTG facilitation is a promising field that should be pursued as it not only allows people with cancer to overcome their trauma but also results in them going over and above their pre-cancer state, enhancing resilience, health, and well-being.

Well-being trajectories in breast cancer and their predictors: A machine-learning approach.

OBJECTIVE: This study aimed to describe distinct trajectories of anxiety/depression symptoms and overall health status/quality of life over a period of 18 months following a breast cancer diagnosis, and identify the medical, socio-demographic, lifestyle, and psychological factors that predict these trajectories. METHODS: 474 females (mean age = 55.79 years) were enrolled in the first weeks after surgery or biopsy. Data from seven assessment points over 18 months, at 3-month intervals, were used. The two outcomes were assessed at all points. Potential predictors were assessed at baseline and the first follow-up. Machine-Learning techniques were used to detect latent patterns of change and identify the most important predictors. RESULTS: Five trajectories were identified for each outcome: stably high, high with fluctuations, recovery, deteriorating/delayed response, and stably poor well-being (chronic distress). Psychological factors (i.e., negative affect, coping, sense of control, social support), age, and a few medical variables (e.g., symptoms, immune-related inflammation) predicted patients' participation in the delayed response and the chronic distress trajectories versus all other trajectories. CONCLUSIONS: There is a strong possibility that resilience does not always reflect a stable response pattern, as there might be some interim fluctuations. The use of machine-learning techniques provides a unique opportunity for the identification of illness trajectories and a shortlist of major bio/behavioral predictors. This will facilitate the development of early interventions to prevent a significant deterioration in patient well-being.

The dyadic regulation approach of coping and illness representations in female cancer patients and their partners.

Purpose: Adjustment to any illness is a 'dyadic' process whereby patients and their partners mutually determine each other's perceptions, behaviours, and well-being. The present study explored the association between dyadic coping strategies and illness representations in newly diagnosed female cancer patients and their partners. Methods: The sample consisted of 92 female cancer patient-partner pairs from 3 oncology hospitals in Greece and Cyprus. The Actor Partner Interdependence Model was applied to test for dyadic regulation effects. Results: The findings revealed that patients' evaluations of dyadic coping were related to their own illness representations and, in some cases, to partners' illness representations of control. However, partner evaluations of dyadic coping were not associated with either patients' or their own illness representations. Relationship satisfaction did not moderate the relationship between dyadic coping and illness representations. Implications: The study suggests that patients' perceptions of support provided by themselves and their partners play a significant role in shaping their illness representations. Future research could delve into the underlying reasons for the observed differences in the impact of dyadic coping on illness representations between patients and partners, considering factors such as gender roles and specific gender-related issues.

Protective Factors against Fear of Cancer Recurrence in Breast Cancer Patients: A Latent Growth Model.

The current study aimed to examine the fear of cancer recurrence (FCR) trajectory and protective predictors in women coping with breast cancer (BC). The study's model investigated whether a higher coping self-efficacy and positive cognitive-emotion regulation at the time of the BC diagnosis would lead to reduced levels of FCR at six months and in later stages (12 and 18 months) post-diagnosis. The sample included 494 women with stages I to III BC from Finland, Italy, Portugal, and Israel. They completed self-report questionnaires, including the Fear of Cancer Recurrence Inventory (FCRI-SF), the Cancer Behavior Inventory-Brief Version (CBI-B), the Cognitive-Emotion Regulation Questionnaire (CERQ short), and medical-social-demographic data. Findings revealed that a higher coping self-efficacy at diagnosis predicted lower FCR levels after six months but did not impact the FCR trajectory over time. Surprisingly, positive cognitive-emotion regulation did not predict FCR levels or changes over 18 months. FCR levels remained stable from six to 18 months post-diagnosis. This study emphasizes the importance of developing specific cancer coping skills, such as coping self-efficacy. Enhancing coping self-efficacy in the first six months after BC diagnosis may lead to lower FCR levels later, as FCR tends to persist in the following year.

Personalized Risk Analysis to Improve the Psychological Resilience of Women Undergoing Treatment for Breast Cancer: Development of a Machine Learning-Driven Clinical Decision Support Tool.

BACKGROUND: Health professionals are often faced with the need to identify women at risk of manifesting poor psychological resilience following the diagnosis and treatment of breast cancer. Machine learning algorithms are increasingly used to support clinical decision support (CDS) tools in helping health professionals identify women who are at risk of adverse well-being outcomes and plan customized psychological interventions for women at risk. Clinical flexibility, cross-validated performance accuracy, and model explainability permitting person-specific identification of risk factors are highly desirable features of such tools. OBJECTIVE: This study aimed to develop and cross-validate machine learning models designed to identify breast cancer survivors at risk of poor overall mental health and global quality of life and identify potential targets of personalized psychological interventions according to an extensive set of clinical recommendations. METHODS: A set of 12 alternative models was developed to improve the clinical flexibility of the CDS tool. All models were validated using longitudinal data from a prospective, multicenter clinical pilot at 5 major oncology centers in 4 countries (Italy, Finland, Israel, and Portugal; the Predicting Effective Adaptation to Breast Cancer to Help Women to BOUNCE Back [BOUNCE] project). A total of 706 patients with highly treatable breast cancer were enrolled shortly after diagnosis and before the onset of oncological treatments and were followed up for 18 months. An extensive set of demographic, lifestyle, clinical, psychological, and biological variables measured within 3 months after enrollment served as predictors. Rigorous feature selection isolated key psychological resilience outcomes that could be incorporated into future clinical practice. RESULTS: Balanced random forest classifiers were successful at predicting well-being outcomes, with accuracies ranging between 78% and 82% (for 12-month end points after diagnosis) and between 74% and 83% (for 18-month end points after diagnosis). Explainability and interpretability analyses built on the best-performing models were used to identify potentially modifiable psychological and lifestyle characteristics that, if addressed systematically in the context of personalized psychological interventions, would be most likely to promote resilience for a given patient. CONCLUSIONS: Our results highlight the clinical utility of the BOUNCE modeling approach by focusing on resilience predictors that can be readily available to practicing clinicians at major oncology centers. The BOUNCE CDS tool paves the way for personalized risk assessment methods to identify patients at high risk of adverse well-being outcomes and direct valuable resources toward those most in need of specialized psychological interventions.

Trajectories of Quality of Life among an International Sample of Women during the First Year after the Diagnosis of Early Breast Cancer: A Latent Growth Curve Analysis.

The current study aimed to track the trajectory of quality of life (QoL) among subgroups of women with breast cancer in the first 12 months post-diagnosis. We also aimed to assess the number and portion of women classified into each distinct trajectory and the sociodemographic, clinical, and psychosocial factors associated with these trajectories. The international sample included 699 participants who were recruited soon after being diagnosed with breast cancer as part of the BOUNCE Project. QoL was assessed at baseline and after 3, 6, 9, and 12 months, and we used Latent Class Growth Analysis to identify trajectory subgroups. Sociodemographic, clinical, and psychosocial factors at baseline were used to predict latent class membership. Four distinct QoL trajectories were identified in the first 12 months after a breast cancer diagnosis: medium and stable (26% of participants); medium and improving (47%); high and improving (18%); and low and stable (9%). Thus, most women experienced improvements in QoL during the first year post-diagnosis. However, approximately one-third of women experienced consistently low-to-medium QoL. Cancer stage was the only variable which was related to the QoL trajectory in the multivariate analysis. Early interventions which specifically target women who are at risk of ongoing low QoL are needed.

Personalized prediction of one-year mental health deterioration using adaptive learning algorithms: a multicenter breast cancer prospective study.

Identifying individual patient characteristics that contribute to long-term mental health deterioration following diagnosis of breast cancer (BC) is critical in clinical practice. The present study employed a supervised machine learning pipeline to address this issue in a subset of data from a prospective, multinational cohort of women diagnosed with stage I-III BC with a curative treatment intention. Patients were classified as displaying stable HADS scores (Stable Group; n = 328) or reporting a significant increase in symptomatology between BC diagnosis and 12 months later (Deteriorated Group; n = 50). Sociodemographic, life-style, psychosocial, and medical variables collected on the first visit to their oncologist and three months later served as potential predictors of patient risk stratification. The flexible and comprehensive machine learning (ML) pipeline used entailed feature selection, model training, validation and testing. Model-agnostic analyses aided interpretation of model results at the variable- and patient-level. The two groups were discriminated with a high degree of accuracy (Area Under the Curve = 0.864) and a fair balance of sensitivity (0.85) and specificity (0.87). Both psychological (negative affect, certain coping with cancer reactions, lack of sense of control/positive expectations, and difficulties in regulating negative emotions) and biological variables (baseline percentage of neutrophils, thrombocyte count) emerged as important predictors of mental health deterioration in the long run. Personalized break-down profiles revealed the relative impact of specific variables toward successful model predictions for each patient. Identifying key risk factors for mental health deterioration is an essential first step toward prevention. Supervised ML models may guide clinical recommendations toward successful illness adaptation.

The Role of Attachment Styles on Quality of Life and Distress Among Early-Stage Female Breast Cancer Patients: A Systematic Review.

Cancer patients' quality of life (QoL) and distress are affected by dispositional factors such as attachment anxiety or avoidance. In this review, we aimed to provide a thorough overview of the relationship between attachment dimensions and QoL and distress among early-stage breast cancer patients. Following PRISMA guidelines, we conducted a systematic search using PubMed, PsycINFO, Scopus, Cinahl, Google Scholar, and PMC Europe. We reviewed 8 eligible studies describing 1180 patients. Insecure attachment appeared to be related to poorer QoL and higher distress levels. Avoidant attachment was more frequent and was more often associated with more negative outcomes. Healthcare providers should consider investigating modifiable personality traits in the immediate post diagnosis period to identify patients more vulnerable to mental health problems, deliver personalized care, and reduce emotional burden.

COVID-19 pandemic-related representations, self-efficacy, and psychological well-being in the general population during lockdown.

The aim of this study was to examine the association among representations of the COVID-19 pandemic, self-efficacy to cope with the anti-pandemic measures (e.g., general lockdown), and psychological distress in the Greek general population. The study was conducted online, during the general lockdown in the country, and 358 individuals (239 females) participated (mean age = 36.89; SD = 12.15). A perception of personal control over the condition, negative emotions towards the pandemic, and self-efficacy to cope with the current anti-pandemic measures were related to psychological distress. Also, a significant interaction between representation clusters and self-efficacy to cope with potential future difficulties (i.e., after the anti-pandemic measures are ended), was found. Specifically, the association between this type of self-efficacy and psychological distress was significant only for the 'low-impact' representations cluster (i.e., a perception of the pandemic as less burdensome and more controllable). The findings indicate that the factors which, according to previous research and theory, are significantly related to psychological distress during a health threat, are important also in times of a pandemic. They also suggest a potential adaptation-promoting synergy between pandemic-related self-efficacy and a more positive representation of COVID-19, as far as psychological distress is conerned. Thus, these factors may serve as the basis for the development of pandemic-related health behavior promotion programs.

Psychological and somatic symptoms among breast cancer patients in four European countries: A cross-lagged panel model.

Psychological and physical health among women with breast cancer are linked. However, more research is needed to test the interrelations between psychological and somatic symptoms, over time and throughout the different phases of breast cancer treatment, to determine when and which interventions should be prioritized. Six hundred and eighty nine women from four countries (Finland, Israel, Italy and Portugal) completed questionnaires during their first clinical consultation following diagnosis with breast cancer, and again after 3 and 6 months. The questionnaires included self-reported measures of psychological symptoms (Hospital Anxiety and Depression Scale; the Positive and Negative Affect Schedule Short Form) and somatic symptoms [selected items from the International European Organization for Research and Treatment of Cancer (EORTC) questionnaires]. Psychological and somatic symptoms were relatively stable across the three time-points. Cross-lagged paths leading from somatic to psychological symptoms (beta coefficients of 0.08-0.10), as well as vice-versa (beta 0.11-0.12), were found to be significant. No evidence was found for cross-cultural differences in mutual effects of psychological and somatic symptoms. The findings of this study call for tailoring personal interventions for breast cancer patients-either from a somatic perspective or a psychological perspective-and adjust them to the specific experiences of the individual patient.

Associations between Physical Exercise, Quality of Life, Psychological Symptoms and Treatment Side Effects in Early Breast Cancer.

Background: Identifying and understanding modifiable factors for the well-being of cancer patients is critical in survivorship research. We studied variables associated with the exercise habits of breast cancer patients and investigated if the achievement of exercise recommendations was associated with enhanced quality of life and/or psychological well-being. Material and Methods. 311 women from Finland, Portugal, Israel, and Italy receiving adjuvant therapy for stage I-III breast cancer answered questions about sociodemographic factors and physical exercise. Quality of life was assessed by the EORTC C30 and BR23 questionnaires. Anxiety and depression were evaluated using the HADS scale. Results: At the beginning of adjuvant therapy and after twelve months, 32% and 26% of participants were physically inactive, 27% and 30% exercised between 30 and 150 minutes per week, while 41% and 45% exercised the recommended 150 minutes or more per week. Relative to other countries, Finnish participants were more likely to be active at baseline and at twelve months (89% vs. 50%, p < 0.001 and 87% vs. 64%, p < 0.001). Participants with stage I cancer were more likely to be active at twelve months than those with a higher stage (80% vs. 70%,p < 0.05). The inactive participants reported more anxiety (p < 0.05) and depression (p < 0.001), lower global quality of life (p < 0.001), and more side effects (p < 0.05) than the others at twelve months. Accordingly, those who remained inactive or decreased their level of exercise from baseline to twelve months reported more anxiety (p < 0.01) and depression (p < 0.001), lower global quality of life (p < 0.001), and more side effects (p < 0.05) than those with the same or increased level of exercise. Conclusion: For women with early breast cancer, exercise was associated with a better quality of life, less depression and anxiety, and fewer adverse events of adjuvant therapy. Trial registration number: NCT05095675. Paula Poikonen-Saksela on behalf of Bounce consortium (https://www.bounce-project.eu/).

Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE Back: Protocol for a Multicenter Clinical Pilot Study.

BACKGROUND: Despite the continued progress of medicine, dealing with breast cancer is becoming a major socioeconomic challenge, particularly due to its increasing incidence. The ability to better manage and adapt to the entire care process depends not only on the type of cancer but also on the patient's sociodemographic and psychological characteristics as well as on the social environment in which a person lives and interacts. Therefore, it is important to understand which factors may contribute to successful adaptation to breast cancer. To our knowledge, no studies have been performed on the combination effect of multiple psychological, biological, and functional variables in predicting the patient's ability to bounce back from a stressful life event, such as a breast cancer diagnosis. Here we describe the study protocol of a multicenter clinical study entitled "Predicting Effective Adaptation to Breast Cancer to Help Women to BOUNCE Back" or, in short, BOUNCE. OBJECTIVE: The aim of the study is to build a quantitative mathematical model of factors associated with the capacity for optimal adjustment to cancer and to study resilience through the cancer continuum in a population of patients with breast cancer. METHODS: A total of 660 women with breast cancer will be recruited from five European cancer centers in Italy, Finland, Israel, and Portugal. Biomedical and psychosocial variables will be collected using the Noona Healthcare platform. Psychosocial, sociodemographic, lifestyle, and clinical variables will be measured every 3 months, starting from presurgery assessment (ie, baseline) to 18 months after surgery. Temporal data mining, time-series prediction, sequence classification methods, clustering time-series data, and temporal association rules will be used to develop the predictive model. RESULTS: The recruitment process stared in January 2019 and ended in November 2021. Preliminary results have been published in a scientific journal and are available for consultation on the BOUNCE project website. Data analysis and dissemination of the study results will be performed in 2022. CONCLUSIONS: This study will develop a predictive model that is able to describe individual resilience and identify different resilience trajectories along the care process. The results will allow the implementation of tailored interventions according to patients' needs, supported by eHealth technologies. TRIAL REGISTRATION: ClinicalTrials.gov NCT05095675; https://clinicaltrials.gov/ct2/show/NCT05095675. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34564.

Trajectories and Predictors of Depression After Breast Cancer Diagnosis: A 1-year longitudinal study.

Being diagnosed with breast cancer (BC) can be a traumatic experience for patients who may experience symptoms of depression. In order to facilitate the prevention of such symptoms, it is crucial to understand how and why depressive symptoms emerge and evolve for each individual, from diagnosis through treatment and recovery. In the present work, data from a multicentric study of 706 BC patients followed for 12 months are analyzed. First, a trajectory-based unsupervised clustering based on K-means is performed to capture the dynamic patterns of change in patients' depressive symptoms after BC diagnosis and to identify distinct trajectory clusters. Then a supervised learning approach was employed to build a classification model of depression progression and to identify potential predictors. Patients were clustered into 4 groups: stable low, stable high, improving, and worsening depressive symptoms. In a nested cross-validation pipeline, the performance of the Support Vector Machine model for discriminating between "good" and "poor" progression was 0.78±0.05 in terms of AUC. Several psychological variables emerged as highly predictive of the evolution of depressive symptoms with the most important ones being negative affectivity and anxious preoccupation. Clinical Relevance-The findings of the present study may help clinicians tailor individualized psychological interventions aiming at alleviating the burden of these symptoms in women with breast cancer and improving their overall well-being.

Perceived Discrimination and Psychological Well-Being Among Immigrants Living in Greece: Separation as Mediator and Interdependence as Moderator.

The present study was based on the rejection-identification model regarding migrants acculturation. Personal perceived discrimination, acculturation attitudes, self-construal, and psychological well-being were examined simultaneously in Albanian and Indian immigrants residing in Greece (N = 233). It was hypothesized that perceived discrimination would be related negatively to immigrants' psychological well-being, both directly and indirectly. A positive relationship was expected between perceived discrimination and separation and a negative relationship between discrimination and integration, or assimilation. It was, also, expected a positive relationship of perceived discrimination to interdependent self-construal and a negative relationship to independent self-construal. Furthermore, it was examined the mediating role of separation in the association of perceived discrimination with psychological well-being and the moderating role of interdependent self-construal in the association of perceived discrimination with psychological well-being. According to the results, perceived discrimination was positively related to separation and negatively to integration, but was related neither to independent nor to interdependent self-construal. Perceived discrimination was, also, positively related to depression directly and indirectly. Fewer depressive symptoms were reported by those immigrants who face discrimination but also select separation. Immigrants with high levels of interdependence, also, do seem to be protected from depression and anxiety. The interpretation of these findings signifies that, when immigrants who perceive discrimination choose separation from the host country, they may reduce their depression feelings, by fitting into relationships with in-group members. Interdependence and the perception of immigrants self as a social unit, also, may act protectively for their psychological well-being, enhancing the identification with the in-group, as well.

Mechanisms of change in acceptance and commitment therapy for primary headaches.

BACKGROUND: Despite the demonstrated effectiveness of behavioural headache interventions, it is not yet known which intervention processes account for treatment responses. Acceptance and commitment therapy (ACT), an emerging behavioural intervention for headaches, proposes psychological flexibility (PF) processes as the mechanisms via which intervention change occurs. This is the first study examining these processes of change variables on headache-related disability and quality of life (treatment outcome). METHODS: Data originated from a Randomized Clinical Trial evaluating the efficacy of ACT for primary headaches. Ninety-four individuals with primary headaches (M = 43 y; 84% females; M headache frequency/month = 9.30) were randomized to either an ACT-based or a Wait-list control group (N = 47 in each). Participants completed questionnaires related to their headache experiences and PF processes at pre- (T1), post-treatment (T2), and 3-month follow-up (T3). RESULTS: Following a bootstrapped cross product of coefficients approach, results demonstrated mediating effects of headache acceptance, cognitive defusion, avoidance of headache, and mindfulness in the ACT group compared to control on parameters of headache-related disability and quality of life at post and 3-month follow-ups. CONCLUSIONS: These findings demonstrate that changes in certain PF processes lower disability and improve quality of life in headache sufferers, supporting that ACT works via its proposed mechanisms of change. Interventions for headache management may be optimized if they target increases in headache acceptance, defusion from thoughts, and mindfulness. SIGNIFICANCE: Psychological flexibility (PF) guides the ACT approach, an emerging behavioral headache intervention that focuses on optimizing head pain adjustment via flexible responses to pain. It targets at increasing daily functioning rather than preventing or controlling headache episodes. Pain acceptance, cognitive defusion, and mindfulness act as processes of functional change in ACT, lowering disability and increasing daily functioning and quality of life. These components can upgrade the established effectiveness of behavioral headache interventions with personalized, modularized therapeutic targets that can help headache sufferers re-establish optimal daily functioning even in fluctuating and persistent headache episodes. TRIAL REGISTRATION: clinical trials.gov registry (NCT02734992).

Quality of life in patients with soft palate resection: The relationship between reported functional prosthetic outcomes and the patient's psychological adjustment.

STATEMENT OF PROBLEM: Tumors of the soft palate and the adjacent tissues often create considerable soft palate defects that are challenging for the maxillofacial prosthodontist. Soft palate obturator prostheses can usually address functional and esthetic concerns; however, the effectiveness of the prosthetic rehabilitation in improving the patient's well-being and overall quality of life (QOL) has not been extensively researched. PURPOSE: The purpose of the present research was to evaluate the function of the prosthesis, to review the interrelation between sociodemographic, medical, and treatment (SMT) characteristics, QOL, and prosthesis functioning, and to analyze the role of the prosthesis in how the patient represents the illness and the psychological coping response. MATERIAL AND METHODS: Thirty-three patients who underwent resection of the soft palate and had been using a technically successful soft palate obturator prosthesis for at least 1 year were interviewed by means of 5 questionnaires: European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Core Questionnaire (QLQ-C30), Head and Neck Cancer Module (QLQ-HN35), Obturator Functioning Scale (OFS), Illness Perceptions Questionnaire (IPQ-R), and Mental Adjustment to Cancer Scale (MAC). Data analysis was performed at α=.01. RESULTS: The QOL (r=-0.53, P=.001), personal control (r=-0.53, P=.001), negative adjustment to cancer (r=0.47, P=.005), treatment control (r=-0.55, P=.001), consequences (r=0.62, P<.001), and emotional representations (r=0.30, P=.009) were significantly related to prosthesis functioning. Better QOL was significantly related to prosthesis functioning (P=.006), age (P=.001), sex (P=.011), and type of soft palate defect (P=.009). The most important predictors of favorable soft palate obturator functioning were age (P<.001) and type of soft palate defect (P=.01). CONCLUSIONS: A patient-perceived effective soft palate obturator prosthesis was a significant predictor for advanced QOL, better adjustment to illness and illness-related disabilities, as well as the overall coping response to cancer.

A new perspective on dyadic regulation in chronic illness: the dyadic regulation connectivity model.

Several theoretical models have described the ways that patients and partners respond to a health problem. Most of these models are faced with limitations regarding the role of cognitive/emotional appraisals and coping behaviors, and the potential interactions between individual and dyadic variables. Therefore, new theoretical approaches are needed to capture the multiple processes that take place within dyadic adaptation to illness. Here, the major aspects of the dyadic adaptation/dyadic coping models are reviewed and their limitations are outlined. Moreover, a new theoretical approach to the dyadic-regulation processes that are important for adaptation to illness is proposed. The Dyadic-Regulation Connectivity Model emphasizes the concept of system connectivity and the role of central network hubs in dyadic regulation. Network hubs represent the common 'space' between intra- and inter-personal processes, and are closely connected to each other. The model posits that dyadic regulation processes evolve over time, all network hubs are fully responsive to changes in any part of the mechanism, while the entire mechanism is nested within the self- and the dyadic-system, the illness, and the broader socio-cultural contexts. The theoretical and research implications of the proposed model are also discussed.