This research examined the degree to which meaning in life explained the association between dispositional mindfulness and psychological symptoms. This was a survey research study with 292 patients with gastrointestinal cancer. Meaning in Life, dispositional mindfulness, psychological symptoms, and perceived stress were assessed. Results showed that consistent with theory and prior research, greater dispositional mindfulness was associated with less psychological symptoms and perceived stress. In addition, the results of the structural equation model verify that meaning in life mediates the association between dispositional mindfulness and perceived stress and psychological symptoms. Findings are consistent with logotheory and suggest that psychological symptoms may be reduced by addressing the impact of meaning in life.

Mindfulness has been garnering increased attention within the area of clinical psychology due to its theorized and empirical associations with psychological well-being. Using a sample of patients diagnosed with digestive tract cancer ( N = 292), we examined the relationship between perceived stress and psychological symptoms at varying levels of dispositional mindfulness. Results showed significant associations between perceived stress and psychological symptoms. More importantly, the relationship between perceived stress and psychological symptoms was only significant for patients with low, but not high, levels of dispositional mindfulness. Implications and future research directions were discussed.

Based on the Vulnerability Stress Adaptation model, this study examined the relationship between forgiveness and marital stability, and provides a first look at the mediating role of marital quality in this association during the first 3 years of marriage based on three annual waves of data collected from 268 Chinese couples. Tests of actor–partner interdependence mediation models revealed direct effects of decisional forgiveness and emotional forgiveness on the concurrent levels of marital stability for husbands, and indirect effects of emotional forgiveness on the concurrent and longitudinal levels of marital stability through marital quality for both husbands and wives. There was also an indirect effect of wives’ emotional forgiveness on concurrent and longitudinal levels of husbands’ marital stability through their wives’ marital quality. Thus, emotional forgiveness, rather than decisional forgiveness, contributes to longitudinal levels of marital stability through marital quality. Theoretical implications and future directions for research are discussed.

IntroductionPerinatal complications, such as perinatal depression and preterm birth, are major causes of morbidity and mortality for the mother and the child. Prediction of high risk can allow for early delivery of existing interventions for prevention. This ongoing study aims to use digital phenotyping data from the Mom2B smartphone application to develop models to predict women at high risk for mental and somatic complications.Methods and analysisAll Swedish-speaking women over 18 years, who are either pregnant or within 3 months postpartum are eligible to participate by downloading the Mom2B smartphone app. We aim to recruit at least 5000 participants with completed outcome measures. Throughout the pregnancy and within the first year postpartum, both active and passive data are collected via the app in an effort to establish a participant’s digital phenotype. Active data collection consists of surveys related to participant background information, mental and physical health, lifestyle, and social circumstances, as well as voice recordings. Participants’ general smartphone activity, geographical movement patterns, social media activity and cognitive patterns can be estimated through passive data collection from smartphone sensors and activity logs. The outcomes will be measured using surveys, such as the Edinburgh Postnatal Depression Scale, and through linkage to national registers, from where information on registered clinical diagnoses and received care, including prescribed medication, can be obtained. Advanced machine learning and deep learning techniques will be applied to these multimodal data in order to develop accurate algorithms for the prediction of perinatal depression and preterm birth. In this way, earlier intervention may be possible.Ethics and disseminationEthical approval has been obtained from the Swedish Ethical Review Authority (dnr: 2019/01170, with amendments), and the project fully fulfils the General Data Protection Regulation (GDPR) requirements. All participants provide consent to participate and can withdraw their participation at any time. Results from this project will be disseminated in international peer-reviewed journals and presented in relevant conferences.