Clinical use of coping in affective disorder, a critical review of the literature

BACKGROUND: The relationship between life stressors, coping and affective disorder is interesting when predicting onset of a affective disorder and relapse of mood episodes. METHODS: A litteratur review of cross-sectional and longitudinal studies concerning coping and affective disorder in adults including a Medline and Embase search was conducted. RESULTS: 11 cross-sectional studies and 17 longitudinal studies concerning affective disorder and coping were found, among these, two studies include patients with bipolar disorder exclusively. Only four studies elucidate whether emotion-oriented and/or avoidance coping styles are associated with a higher risk of developing affective disorder, so this hypothesis remains unclear. Most studies shows that emotion-oriented and avoidance coping strategies are associated with relapse of depressive episodes. Conversely, problem-focused and task-oriented coping seem to be associated with a good outcome. CONCLUSION: There is a gap between coping theory and clinical use of coping and the clinical relevance of coping is, though promising, still unclear. In future research it is recommended to concentrate on development of a semi-structured interview combining coping style, life events and personality traits

Smartphone-Based Self-Assessment of Stress in Healthy Adult Individuals:A Systematic Review

BACKGROUND: Stress is a common experience in today’s society. Smartphone ownership is widespread, and smartphones can be used to monitor health and well-being. Smartphone-based self-assessment of stress can be done in naturalistic settings and may potentially reflect real-time stress level. OBJECTIVE: The objectives of this systematic review were to evaluate (1) the use of smartphones to measure self-assessed stress in healthy adult individuals, (2) the validity of smartphone-based self-assessed stress compared with validated stress scales, and (3) the association between smartphone-based self-assessed stress and smartphone generated objective data. METHODS: A systematic review of the scientific literature was reported and conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. The scientific databases PubMed, PsycINFO, Embase, IEEE, and ACM were searched and supplemented by a hand search of reference lists. The databases were searched for original studies involving healthy individuals older than 18 years, measuring self-assessed stress using smartphones. RESULTS: A total of 35 published articles comprising 1464 individuals were included for review. According to the objectives, (1) study designs were heterogeneous, and smartphone-based self-assessed stress was measured using various methods (e.g., dichotomized questions on stress, yes or no; Likert scales on stress; and questionnaires); (2) the validity of smartphone-based self-assessed stress compared with validated stress scales was investigated in 3 studies, and of these, only 1 study found a moderate statistically significant positive correlation (r=.4; P<.05); and (3) in exploratory analyses, smartphone-based self-assessed stress was found to correlate with some of the reported smartphone generated objective data, including voice features and data on activity and phone usage. CONCLUSIONS: Smartphones are being used to measure self-assessed stress in different contexts. The evidence of the validity of smartphone-based self-assessed stress is limited and should be investigated further. Smartphone generated objective data can potentially be used to monitor, predict, and reduce stress levels

Attitudes and beliefs among patients treated with mood stabilizers

BACKGROUND: There is increasing evidence that attitudes and beliefs are important in predicting adherence in depressive and bipolar disorders. However, such attitudes and beliefs on mood stabilizers have not been analysed by socio-demographic and clinical variables. METHODS: The Mood Stabilizer Compliance Questionnaire (MSQC) was mailed to a large population of patients with depressive or bipolar disorder representative of patients treated at their first contacts to hospital settings in Denmark. RESULTS: Of the 1005 recipients, 49.9 % responded to the letter and among these 256 indicated that they previously had been or currently were in treatment with a mood stabilizer. A large proportion of the patients (40 to 80 %) had non-correct views on the effect of mood stabilizers. Older patients consistently had a more negative view on the doctor-patient relationship, more non-correct views on the effect of mood stabilizers and a more negative view on mood stabilizers. There was no difference in the attitudes and beliefs according to the type of disorder (depressive or bipolar), the number of psychiatric hospitalisations or according to the type of the current doctor (general practitioner, private psychiatrist, community psychiatry doctor, hospital doctor, other doctor). CONCLUSION: There is a need of improving knowledge and attitudes toward diagnosis and treatment especially among elder patients as this may add to improve the prognosis of depressive and bipolar disorders

Smartphone-based objective monitoring in bipolar disorder:status and considerations

Abstract In 2001, the WHO stated that: “The use of mobile and wireless technologies to support the achievement of health objectives (mHealth) has the potential to transform the face of health service delivery across the globe”. Within mental health, interventions and monitoring systems for depression, anxiety, substance abuse, eating disorder, schizophrenia and bipolar disorder have been developed and used. The present paper presents the status and findings from studies using automatically generated objective smartphone data in the monitoring of bipolar disorder, and addresses considerations on the current literature and methodological as well as clinical aspects to consider in the future studies

Data-Driven Learning in High-Resolution Activity Sampling From Patients With Bipolar Depression: Mixed-Methods Study.

BackgroundBehavioral activation is a pen and paper-based therapy form for treating depression. The patient registers their activity hourly, and together with the therapist, they agree on a plan to change behavior. However, with the limited clinical personnel, and a growing patient population, new methods are needed to advance behavioral activation.ObjectiveThe objectives of this paper were to (1) automatically identify behavioral patterns through statistical analysis of the paper-based activity diaries, and (2) determine whether it is feasible to move the behavioral activation therapy format to a digital solution.MethodsWe collected activity diaries from seven patients with bipolar depression, covering in total 2,480 hours of self-reported activities. A pleasure score, on a 1-10 rating scale, was reported for each activity. The activities were digitalized into 6 activity categories, and statistical analyses were conducted.ResultsAcross all patients, movement-related activities were associated with the highest pleasure score followed by social activities. On an individual level, through a nonparametric Wilcoxon Signed-Rank test, one patient had a statistically significant larger amount of spare time activities when feeling bad (z=–2.045, P=.041). Through a within-subject analysis of covariance, the patients were found to have a better day than the previous, if that previous day followed their diurnal rhythm (ρ=.265, P=.029). Furthermore, a second-order trend indicated that two hours of daily social activity was optimal for the patients (β2=–0.08, t (63)=–1.22, P=.23).ConclusionsThe data-driven statistical approach was able to find patterns within the behavioral traits that could assist the therapist in as well as help design future technologies for behavioral activation.</jats:sec