Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

BACKGROUND: Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. OBJECTIVE: The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. METHODS: Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. RESULTS: Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. CONCLUSIONS: Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness.

Obesity - a social and physical risk.

Overweight and obesity are an accepted cause of numerous metabolic disorders. The obvious strategies for prevention and therapy of increased fat body mass (reduction of energy intake, increase of physical activity) fail in most cases, especially with respect to their sustainability. The lack of success of programs developed so far for prevention and therapy of obesity suggests the existence of poorly-understood regulatory mechanisms leading to the imbalance between energy uptake and energy expenditure. Besides physiological factors,such as dysregulated levels of hunger-controlling or satiation-mediating hormones, the composition of the intestinal flora and synthetic compounds with hormone-like activity have been suggested as triggers of the development of obesity. Along with biological and metabolic parameters, scientists have focused more and more on psychological and sociological factors in the development of a strategy for the prevention of obesity. Important factors in this context are the motivation and ability to self-regulation and aspects of the socio-cultural context. Consequently, the real challenge in reducing the prevalence of obesity is not only the identification of relevant parameters but also the assessment of proportionality of these factors. To achieve this goal, borders of disciplines dealing with obesity development (nutrition, medicine, kinematics, psychology, sociology) need to be overcome. Common models must be developed that facilitate the assessment of both the importance of single factors and their relationship to each other.