Skip to content
#software testing Meta-analysis Open access

Behavior plan and the intention–behavior gap in physical activity among adolescents and college students: a systematic review and meta-analysis

Sep 2026 · Frontiers in Public Health · Vol 14 · 0 citations · 62 references
Medicine

Abstract

Objectives (1) To conduct a meta-analysis on the structure of the TPB extended model to examine the predictive effects of its components on physical activity participation among adolescents and college students; (2) To investigate the moderating effects of key research dimensions, including participant groups, cultural backgrounds, physical activity measurement methods, study designs, and gender composition (proportion of females), on the relationships between variables in the TPB extended model and behavioral models for adolescents and college students physical activity; (3) To test the mediating effects of the TPB extended model; (4) To examine the direct effect of perceived behavioral control on adolescents’ and college students’ behavior. Methods A systematic literature search was conducted across multiple databases to identify studies applying the extended Theory of Planned Behavior (TPB) model to physical activity (PA) in adolescents and college students (approximately 10–24 years). A total of 28 articles (including 31 independent samples, with a total of 19,652 unique participants) met the inclusion criteria. Pairwise meta-analyses were performed using random-effects models in CMA 3.0 software. Meta-analytic structural equation modeling (MASEM) was conducted in Amos 24.0, with covariance matrix and harmonic mean constructed based on the summarized correlation matrix. Moderation analyses were conducted to examine the moderating effects of participant group, cultural background, physical activity measurement method, study design, and gender composition. Publication bias was assessed using funnel plots and Egger’s regression tests, and methodological quality was evaluated using the adapted Newcastle-Ottawa Scale (NOS-xs). Results The TPB extended model explained 54.7% of intention differences, 29.2% of behavior differences, and 28.9% of behavior plan differences. Behavioral intention was found to be a significant statistical mediator variable connecting the three major factors of TPB with behavior, and additional indirect effects have been observed through the sequential pathway of behavioral intention and behavior plan. Moderator analyses revealed that the strength of several TPB relationships was contingent upon participant characteristics (adolescents and college students), cultural background, measurement methods, and study design. Conclusion The TPB extended model demonstrates predictive utility for adolescents and college student’s physical activities at the aggregate level and can explain, on average, substantial variations in behavioral intention, behavior, and behavior plan across the diverse studies synthesized here. Nevertheless, the extreme heterogeneity (I2 > 90% for many pairwise associations) indicates that effect sizes vary considerably across populations, instruments, and study designs, limiting the generalizability of any single pooled estimate to specific subgroups or settings. In this cross-sectional synthesis, Perceived Behavioral Control (PBC) showed the strongest statistical association with behavioral intention. Behavior plan was also statistically associated with the relationship between behavioral intention and action, and may represent a potential explanatory pathway; however, the predominantly cross-sectional design precludes any causal or temporal inferences. The action path of this model is moderated by participant group, cultural background, measurement method, and study design, highlighting its contextual sensitivity. These findings underscore that PBC and behavior plan may be key variables for inclusion in future intervention designs, although their causal impact on behavior change still remains to be established via controlled trials.

Read PDF

Similar papers

#computer vision Review Sep 2017

Agile Software Development Methods: Review and Analysis

This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.

P. Abrahamsson, O. Salo, Jussi Ronkainen et al. · 727 citations · ⚡54
#computer vision Jun 2008

The impact of agile practices on communication in software development

The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.

M. Pikkarainen, Jukka Haikara, O. Salo et al. · 401 citations · ⚡48
#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54
#computer vision Review Mar 2008

Agile methods in European embedded software development organisations: a survey on the actual use and usefulness of Extreme Programming and Scrum

The results show that the embedded industry has been able to apply agile methods in its development processes and that the appreciation of the agile methods and their individual practices appears to increase once adopted and applied in practice.

O. Salo, P. Abrahamsson · 238 citations · ⚡9
#computer vision Open access Jul 2017

What happens when software developers are (un)happy

Consequences of happiness and unhappiness that are beneficial and detrimental for developers' mental well-being, the software development process, and the produced artifacts are found.

D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al. · 236 citations · ⚡13
#computer vision Open access Oct 2004

Mobile-D: an agile approach for mobile application development

The Mobile-D approach is briefly outlined here and the experiences gained from four case studies are discussed, which helped develop an agile development approach for mobile application development.

P. Abrahamsson, Antti Hanhineva, H. Hulkko et al. · 225 citations · ⚡18

Related blog posts

Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.