Psychology & Methods

Objective: Planning has been hypothesized to operate as a mediator linking intentions to health behaviors. To explore the temporal variation of these constructs and their interrelationships, a long-term study of intentions, planning, and physical activity was conducted. Method: A sample of 328 individuals in orthopedic rehabilitation provided data at five measurement occasions over 3 years after their discharge from rehabilitation. A process-oriented approach combining mediation analysis and latent growth curve (LGC) modeling was applied. Results: The orthopedic rehabilitation led to an initial increase in planning and behavior, followed by a decrease after 6 months and stabilization for the next 2.5 years. Intention revealed a slight but constant decrease for 6 months and remained stable up to 3 years after rehabilitation. The mediation model confirmed planning as mediator between intention and physical activity in former rehabilitation participants. Conclusions: Prior evidence on the mediating role of planning in the intention-behavior relation is corroborated and extended by the present findings at the level of long-term processes. Planning can and should be integrated in rehabilitation treatment programs to facilitate sustainable recovery.

Stage theories propose that individuals pass through different stages on their way toward behavior change. The present study examines stage-specific prediction patterns of socialcognitive variables (risk perception, outcome expectancies, perceived self-efficacy, action planning and social support) regarding transitions between the three stages of the Health Action Process Approach (HAPA; preintention, intention and action stage). In an online study (n 5 494) on fruit and vegetable intake, socialcognitive variables and stages were assessed at baseline and stage transitions 4 weeks later. Transitions between the preintention, intention and action stage were predicted by social-cognitive variables using binary and multinomial logistic regression analyses. Stage-specific prediction patterns emerged for stage progression and stage regression. Outcome expectancies predicted progression from the preintention stage, whereas social support predicted progression to the action stage. Low levels of planning were associated with relapse to the preintention and the intention stage. Self-efficacy emerged as a universal predictor of stage transitions. Findings support not only the usefulness of the stage construct for describing health behavior change but also the validity of the HAPA variables as predictors of stage transi-tions. Stage-matched interventions targeting the variables identified as stage-specific predictors might support stage progression toward the goal behavior.

Objective: To compare the predictive power of goal intentions and implementation intentions. Design: Both constructs were expected to explain physical exercise at 3 points in time (with follow-ups at 6 and 12 months) in a sample of 368 persons participating in orthopedic rehabilitation. Results: Goal intentions and implementation intentions predicted exercise during rehabilitation. In contrast, goal intentions failed to predict exercise at later points in time, whereas implementation intentions continued to be associated with exercise 12 months later. Conclusions: Implementation intentions rather than goal intentions predict behavior as it becomes routine. As automatic processes such as behavior elicited by planning are largely age invariant, strengthening those processes might help to overcome volitional problems across all age groups represented in rehabilitation settings.

Health behavior change is seen as a self-regulatory process that consists of a motivation phase of goal setting and a volition phase of goal pursuit. Previous studies suggest that the intention–behavior association is mediated by planning. However, evidence is based on observational studies rather than on experimental designs. To validate the causal assumptions, an experimental-causal-chain design was employed. Study 1 (n= 145) examined whether changing dietary intentions by a motivational intervention engenders changes in planning activities 1 month later. Study 2 (n= 115) examined, in a different sample, whether a volitional planning intervention engenders changes in dietary behavior 1 month later. In both studies, repeated measures ANOVAs revealed a significant Time × Condition interaction. Changes in intention mediated the effects of the motivational intervention on planning activities (Study 1). Changes in planning mediated the effect of a planning intervention on dietary behavior (Study 2). Previous observational findings on planning as a mediator in the intention–behavior association were supported by the two experiments. The findings might help to identify points of intervention in the process underlying health behavior change.Le changement de comportement au plan de la santé est considéré comme un processus d’auto-régulation qui se compose d’une phase de motivation (fixation des buts) et d’une phase de volition (poursuite des buts). Des études précédentes suggèrent que le passage de l’intention au comportement est médiatisé par la planification. Ces résultats sont obtenus par voie d’observations plutôt que par expérimentations. Pour valider les hypothèses de causalité, un modèle de chaîne-causale-expérimentale a été employé. L’étude 1 examine si, en changeant les intentions alimentaires par une intervention motivationnelle, on obtient des changements dans la planification des activités un mois après (n= 145). L’étude 2 examine, sur un échantillon différent, si la planification d’une intervention engendre des changements du comportement alimentaire un mois plus tard (n= 115). Pour ces deux études, des ANOVA à mesures répétées révèlent une interaction significative entre le temps et la condition étudiée. Les changements de l’intention influencent les effets de l’intervention motivationnelle sur la planification des activités (étude 1). Les changements de la planification influencent les effets de l’intervention de la volition sur le comportement alimentaire (Etude 2). Les résultats obtenus par observation sur la planification comme lien entre l’intention et le comportement sont confirmés par les expérimentations. Les résultats peuvent permettre d’identifier les modalités d’interventions relatives au processus sous-tendant le changement du comportement de santé.

Planning interventions have proven effective to change behaviour. However, less is known about their underlying mechanisms. To better understand the processes by which planning interventions unfold their effects, a combined action planning and coping planning intervention was tested in a field setting, with the focus on mediating and moderating effects of theory-derived social-cognitive variables. In a randomized controlled trial, 374 employees of a logistics company were asked to participate in either a combined action planning and coping planning intervention or an active control group. Four weeks later, self-reported changes in fruit and vegetable intake, action planning, coping planning, intentions and self-efficacy were measured. Single and simultaneous mediating effects on behaviour were tested with intention-to-treat analyses, along with interaction effects between planning processes. Action planning and coping planning mediated intervention effects on fruit and vegetable intake not only separately, but also simultaneously (multiple mediation). Action planning and coping planning had main and interactive effects on behaviour change (moderation). Action planning and coping planning may exert both additive and synergistic effects on health behaviour change. Volitional interventions should include both action planning and coping planning components and stimulate the use of planning in everyday life. Copyright © 2009 John Wiley & Sons, Ltd.

Exercise-related strategy use and planning were investigated in younger (18-49 years) and older individuals (50-80 years) in orthopedic rehabilitation who were supposed to adhere to a strict exercise regimen. As part of a longitudinal study, N = 368 individuals completed questionnaires assessing the amount of physical activities performed pre-rehabilitation and 6 and 12 months after discharge. In addition, the extent of strategy use (selection, optimization, and compensation) and planning after discharge was assessed. Planning was subdivided into two constructs: action planning (planning when, where, and how to exercise) and coping planning (planning how to exercise in the face of barriers). Two-sample structural equation modeling was used. For both age groups, strategy use improved prediction of exercise goal attainment on top of planning, while strategy use mediated the relationship between coping planning and goal attainment. Interventions fostering strategy use as well as planning might enhance exercise adherence across age groups.

Background: Adoption and maintenance of health behaviors are often poorly predicted by behavioral intentions. To bridge the gap between intentions and behavior, strategic planning and recovery self-efficacy have been suggested as proximal predictors. Purpose: The aim was to examine the usefulness of a prediction model that includes planning and self-efficacy as postintentional mediator variables. Methods: Four longitudinal studies were conducted on dental flossing (Study I, N ¼ 157), seat belt use (Study II, N ¼ 298), dietary behaviors (Study III, N ¼ 700), and physical activity (Study IV, N ¼ 365).Dental flossing and seat belt use were assessed in students by paper-and-pencil questionnaires, whereas dietary behavior and physical activity inventories were presented to the general public in the internet. Results: By structural equation modeling, it was found that one common model fits all four data sets well. Results differed in terms of variance accounted for, but the overall patterns of estimated parameters were similar across samples. Conclusions: Self-efficacy and planning seemed to be functional as proximal predictors of health behaviors, whereas health risk perception appeared to be a negligible factor. When predicting health behaviors, self-regulatory variables should be used in addition to the behavioral intention. (Ann Behav Med 2007, 33(2):156-166)

Objective: Levels of physical exercise adherence are not predicted well by behavioral intentions. Therefore, action planning and recovery self-efficacy were specified as proximal predictors to bridge the gap between intentions and adherence. The prediction model was examined in 3 studies with participants who were enrolled in cardiac rehabilitation (Study 1, N ϭ 353; Study 2, N ϭ 114) or orthopedic rehabilitation (Study 3, N ϭ 368). Main Outcome Measure: Each study included 3 measurement points in time, covering a period between 4 and 12 months. Intentions, planning, self-efficacy, and exercise levels were assessed. Results: Structural equation modeling revealed that 1 common model fit all 3 data sets well. Results differed in terms of variance accounted for, but the overall patterns of estimated parameters were similar. Conclusions: Although health risk perception appeared to be a negligible factor, action planning and recovery self-efficacy were effective predictors of physical exercise adherence.

Objectives: To examine a parsimonious three-stage model of health behavior change that makes a distinction between non-intenders, intenders, and actors in terms of physical activity. It was hypothesized that intention formation, action planning, and behavior change were at different levels in these three stages, and that these were differentially predicted by self-efficacy, outcome expectancies, and risk perception.

Objective: Planning has been hypothesized to operate as a mediator linking intentions to health behaviors. To explore the temporal variation of these constructs and their interrelationships, a long-term study of intentions, planning, and physical activity was conducted. Method: A sample of 328 individuals in orthopedic rehabilitation provided data at five measurement occasions over 3 years after their discharge from rehabilitation. A process-oriented approach combining mediation analysis and latent growth curve (LGC) modeling was applied. Results: The orthopedic rehabilitation led to an initial increase in planning and behavior, followed by a decrease after 6 months and stabilization for the next 2.5 years. Intention revealed a slight but constant decrease for 6 months and remained stable up to 3 years after rehabilitation. The mediation model confirmed planning as mediator between intention and physical activity in former rehabilitation participants. Conclusions: Prior evidence on the mediating role of planning in the intention-behavior relation is corroborated and extended by the present findings at the level of long-term processes. Planning can and should be integrated in rehabilitation treatment programs to facilitate sustainable recovery.

Objective: To examine the putative moderating role of self-efficacy in the intention-planningbehavior relationship. Methods: In N=812 individuals, intentions (independent variable) were assessed at baseline, whereas action plans (mediator), self-efficacy (moderator), and physical activity (dependent variable) were measured again 4 weeks later. We examined a moderated-mediation model. Results: Self-efficacy moderates the mediation process: the strength of the mediated effect increased along with levels of selfefficacy. The results remain valid after accounting for baseline physical activity. Conclusions: For plans to mediate the intentionbehavior relation, people must hold sufficiently high levels of self-efficacy. If they lack selfefficacy, planning may be in vain.

Objective: Stage assessments are examined to develop and test refined measurements that can be used for classifying individuals. Design: Stages were assessed in 1,850 persons in terms of their physical activity and dietary behaviors. Main Outcome Measures: Stages for both behaviors were compared to behavior and other test variables. Misclassification, sensitivity, specificity, receiver-operation-curves, and discontinuity patterns were computed. Discontinuity patterns were tested with trends across stages and planned contrasts between adjacent stages. Results: In comparison to previous studies, sensitivity (70% to 80%) and specificity (80% to 87%) were high. When using lower level criteria (such as less intensive activity), sensitivity was lower, whereas specificity was higher. When behavioral maintenance was assessed, results suggested that the temporal cut-off point between action and maintenance was equally optimal at different cut-off points. Applying contrast analyses, nonlinear trends across the stages and a match of 87% of predictions of stage differences resulted. Conclusion: Stage assumptions are supported in general, and refined stage assessment in particular. Levels of psychological variables (e.g., easiness, habit) may discriminate stages as well as or even better than temporal stage definitions.

Stage theories propose that individuals pass through different stages on their way toward behavior change. The present study examines stage-specific prediction patterns of socialcognitive variables (risk perception, outcome expectancies, perceived self-efficacy, action planning and social support) regarding transitions between the three stages of the Health Action Process Approach (HAPA; preintention, intention and action stage). In an online study (n 5 494) on fruit and vegetable intake, socialcognitive variables and stages were assessed at baseline and stage transitions 4 weeks later. Transitions between the preintention, intention and action stage were predicted by social-cognitive variables using binary and multinomial logistic regression analyses. Stage-specific prediction patterns emerged for stage progression and stage regression. Outcome expectancies predicted progression from the preintention stage, whereas social support predicted progression to the action stage. Low levels of planning were associated with relapse to the preintention and the intention stage. Self-efficacy emerged as a universal predictor of stage transitions. Findings support not only the usefulness of the stage construct for describing health behavior change but also the validity of the HAPA variables as predictors of stage transi-tions. Stage-matched interventions targeting the variables identified as stage-specific predictors might support stage progression toward the goal behavior.