How are habits formed: Modelling habit formation in the real world

Lally, Phillippa; van Jaarsveld, Cornelia H.M.; Potts, Henry; Wardle, Jane · 2009 · OpenAlex-citations

DOI: 10.1002/ejsp.674

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Summary

This study investigates the process of habit formation in real-world settings, addressing the lack of empirical data on how long it takes for behaviors to become automatic. While previous theories suggested that habit strength follows an asymptotic curve—where automaticity increases with repetition until reaching a plateau—this relationship had not been systematically tested at the individual level for everyday behaviors. The researchers aimed to determine if an asymptotic model accurately describes habit formation, how many repetitions are required to reach a plateau, whether behavior type influences this process, and if missing a single opportunity to perform a behavior compromises habit development. The study involved 96 volunteers who selected a healthy eating, drinking, or exercise behavior to perform daily in a consistent context for 12 weeks (84 days). Participants logged their performance and completed the Self-Report Habit Index (SRHI) daily. The researchers used a subset of SRHI items to create an automaticity subscale. Nonlinear regressions based on Mitscherlich’s law of diminishing returns were applied to fit an asymptotic curve to each individual’s automaticity scores over time. The analysis focused on 82 participants who provided sufficient data, examining the model fit, the time to reach 95% of the automaticity asymptote, and the impact of missed opportunities. The results indicated that for 39 participants (48% of those with sufficient data), the asymptotic model provided a good fit, significantly outperforming linear models. The median time to reach 95% of the automaticity plateau was 66 days, with a wide range from 18 to 254 days, highlighting substantial individual variation. There were no significant differences in the time to asymptote or the asymptote value between eating, drinking, and exercise behaviors, although exercise participants showed lower compliance rates. Crucially, missing a single opportunity to perform the behavior did not materially affect the habit formation process; automaticity scores decreased by less than half a point following an omission, and recovery was rapid if the behavior was resumed. The study concludes that habit formation in real-world contexts follows an asymptotic trajectory, where early repetitions yield larger gains in automaticity than later ones. The finding that it can take up to 254 days to reach a plateau suggests that interventions aiming to establish healthy habits must provide sustained support over extended periods. Furthermore, the resilience of the habit formation process to single missed opportunities implies that perfection is not required for habit acquisition, offering practical guidance for behavioral change strategies. The research validates the idiographic approach to modeling habit strength and confirms that intrinsic rewards are sufficient for habit development without extrinsic reinforcement.

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• automaticity skill acquisition