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Prostate cancer ranks high in mortality. Only 18% of men entitled for screenings take advantage of this. Social-cognitive models of health psychology describe and predict health behavior. This study investigates what barriers men perceive that impede the utilization of cancer screenings. Semistructured interviews were conducted in 2 general practices and 3 hospital wards. One hundred and seventy-eight men over 45 years were addressed; 64 utilized cancer screenings regularly, 3 had a diagnosis of prostate cancer, and 18 declined participation. Content analyses were conducted with 83 interviews. The interview tapped into the following domains: barriers, risk perception, outcome expectancies, self-efficacy, and intentions. 57 men regarded their health as very important, while 47 had never utilized cancer screenings. Barriers were divided into emotional/cognitive versus organizational/structural. Sixty-four men did not utilize cancer screenings because of lack of symptoms, 22 feared a positive result, 20 had more pertinent health issues, and 18 assumed that their physicians would screen for cancer 'automatically.' Mainly emotional/cognitive barriers were seen as important for nonutilization, especially the absence of symptoms. Following the reasoning of social-cognitive models, a first step to enhance utilization rates would be to enhance risk perception. [ABSTRACT FROM AUTHOR]

The aim of the study was to test the effectiveness of a postpartum smoking cessation and relapse prevention intervention. Structural equation modeling techniques were applied to evaluate the impact of the intervention on smoking behavior and on non- behavioral variables derived from the Transtheoretical Model (TTM). Women were randomized to an intervention (I) and control group (C). Smoking status, TTM-variables, and control variables were assessed four weeks, six and 12 months postpartum. Membership in the intervention group significantly predicted non-smoking and higher self-efficacy six months, but not one year postpartum, after controlling for demographic, smoking, and postpartum risk variables. [ABSTRACT FROM AUTHOR]

Little is known about the motivational background of smoking after a period of nicotine abstinence during pregnancy. The study examines the intention to resume smoking (IRS) in the post-partum period and its predictive value for smoking within 12 months post-partum. In a sample of 301 women recruited from obstetric wards who reported having stopped smoking during pregnancy, data on IRS, sociodemo- graphic variables, recent smoking behaviour and smoking in the social network were collected. Smoking status was assessed 6 and 12 months after pregnancy. Among all formerly smoking women, 39 (13%) intended to resume smoking and 262 (87%) intended to maintain abstinence. Women with IRS returned to smoking more often than women without IRS [77 versus 45%, odds ratio (OR) = 4.1, 95% confidence interval (CI): 1.89-9.05]. In a logistic regression model, IRS (OR = 3.7,95% CI: 1.51- 9.01) and number of months currently abstinent (OR = 0.9, 95% CI: 0.76-0.96) attained statistical significance. IRS proved to be the main predictor for relapse; yet, women with no IRS are at risk to restart smoking again, too. IRS offers a cue for tailoring interventions. [ABSTRACT FROM AUTHOR]

Effectiveness studies among pregnant and postpartum women indicate that pregnancy and the postpartum period provide a window of opportunity to promote smoking cessation and smoke-free families. Yet, there is a lack of information about interventions that are portable to routine care. The goal of this article is to describe the structure, basic strategies, and the application of a smoking cessation and relapse prevention intervention for postpartum women in the general population. By using the stages of change concept and motivational interviewing, a classification of current and former smokers is given, and basic strategies and techniques are described to counsel women postpartum with regard to smoking. [ABSTRACT FROM AUTHOR]

To bridge the gap between science and practice in mental health care, scientific methods need to be developed that have direct applications in clinical practice. Studies that report ‘average’ effects document the efficacy of psychotherapy but have limited implications for decision making in clinical practice. Although it is very unlikely that statistical models will ever perfectly predict treatment outcomes, models that identify and describe changes in a patient's risk of treatment failure may be developed to support decisions during ongoing treatment. In the current study, the classification and regression tree (CART) method was applied to data from the German multicenter study on the relationship between treatment duration/intensity and outcome in inpatient treatment of eating disorders (Project TR-EAT). Within a sample of patients diagnosed with bulimia nervosa (n = 630), data on admission, treatment strategy, and treatment response were used to develop a CART decision tree. This has potential for treatment decision support because the tree structure identifies changes in risk status associated with available treatment options and is sensitive to a patient's unique presenting characteristics and observed treatment response. [ABSTRACT FROM PUBLISHER]