How do I feel about the behavior? The interplay of affective associations with behaviors and cognitive beliefs as influences on physical activity behavior.

Individuals have affective associations with health behaviors. In other domains such associations have been shown to influence behavior, but affective associations with health behaviors are not included in current health decision-making models. The authors examined whether affective associations with exercise predicted individuals' activity behavior and, if so, how they interfaced with other decision-making constructs to influence behavior. Adult participants (N = 433) reported their current physical activity behavior and affective associations with physical activity. Health belief model and theory of planned behavior constructs were also assessed. More positive affective associations with activity significantly predicted greater activity behavior. Moreover, the influence of the health belief model and theory of planned behavior constructs on activity behavior was mediated through affective associations. Affective associations were shown to play a central role in individuals' activity behavior, both as a mediator of the effects of cognitively based decision-making factors and as an independent predictor of activity behavior. The results suggest the need to include affective influences on behavior in formal models of health decision making and, potentially, to explore affectively based intervention routes to change behaviors.     

Klaus-Uwe Adam,Therapeutisches Arbeiten mit Träumen. Theorie und Praxis der Traumarbeit

Ohne Zusammenfassung     

Reasoning about curvilinear motion: Using principles or analogy

People possess implicit theories about the motion of objects, theories that are often incorrect. When asked to predict the path of an object emerging from a curved tube, for example, people often say that the object will continue to follow a curved path. However, when solving a problem that reminds them of a familiar previous instance, people often reason by analogy to the instance. In this study, we show that a previous instance must be very superficially similar to a problem in order to be used as an analogy; otherwise, people will use their implicit theories as the basis of their reasoning.     

Opportunism in Memory: Preparing for Chance Encounters

Recognizing opportunities to achieve pending goals is an important cognitive ability. But when and how do we recognize that a current situation is especially suited to resuming a past goal? The predictive encoding model suggests pending goals are encoded into memory in association with anticipated environmental features. Optimally, these features are (a) necessary for successful goal satisfaction, (b) distinctive preconditions for expecting a plan to achieve the goal, and (c) described so as to be readily identified in the environment. Later, ordinary perception of features in the environment leads to automatic recognition of opportunities already prepared in memory. Evidence from experimental studies supports this theory, and demonstrates that general preparation can produce apparently novel opportunism. These findings suggest ways to facilitate the recognition of opportunities to satisfy pending goals.     

First-order factor structure of the Personality Research Form

To establish the first-order factor structure of the Personality Research Form, a high school sample of 327 boys and a college sample of 215 men and women were administered Form AA. Principal component analyses were made, in both samples, of the 20 scales subdivided into two subsets. Nine factors were found to be equivalent in the college and high school data. Comparison with Edwards and Abbott analyses revealed substantial agreement. It was concluded that 12 scales could be used to measure the constructs embodied in the Personality Research Form.     

Swimming constraints and arm coordination

Following Newell's concept of constraint (1986), we sought to identify the constraints (organismic, environmental and task) on front crawl performance, focusing on arm coordination adaptations over increasing race paces. Forty-two swimmers (15 elite men, 15 mid-level men and 12 elite women) performed seven self-paced swim trials (race paces: as if competitively swimming 1500m, 800m, 400m, 200m, 100m, 50m, and maximal velocity, respectively) using the front crawl stroke. The paces were race simulations over 25m to avoid fatigue effects. Swim velocity, stroke rate, stroke length, and various arm stroke phases were calculated from video analysis. Arm coordination was quantified in terms of an index of coordination (IdC) based on the lag time between the propulsive phases of each arm. This measure quantified three possible coordination modes in the front crawl: opposition (continuity between the two arm propulsions), catch-up (a time gap between the two arm propulsions) and superposition (an overlap of the two arm propulsions). With increasing race paces, swim velocity, stroke rate, and stroke length, the three groups showed a similar transition in arm coordination mode at the critical 200m pace, which separated the long- and mid-pace pattern from the sprint pace pattern. The 200m pace was also characterized by a stroke rate close to 40strokemin(-1). The finding that all three groups showed a similar adaptation of arm coordination suggested that race paces, swim velocity, stroke rate and stroke length reflect task constraints that can be manipulated as control parameters, with race paces (R(2)=.28) and stroke rate (R(2)=.36) being the best predictors of IdC changes. On the other hand, only the elite men reached a velocity greater than 1.8ms(-1) and a stroke rate of 50strokemin(-1). They did so using superposition of the propulsion phases of the two arms, which occurred because of the great forward resistance created when these swimmers achieved high velocity, i.e., an environmental constraint. Conversely, the elite women and mid-level men had shorter stroke lengths and maintained a time gap between the propulsions of the two arms throughout the increase in paces, with gender and expertise explaining 9% and 8.3% of the IdC changes, respectively. These results indicate that arm coordination cannot be interpreted solely from the IdC value but should be considered from the perspective of task, environmental, and organismic constraints. These constraints can serve as control parameters in experiments aimed at gaining insight into changes in arm coordination during the front crawl. In this context, catch-up coordination, which is often considered as a mistake, was seen to be an adaptation to a relative constraint.