Keywords: unwanted habits; habit change; habit discontinuity; context change; vigilant monitoring; implementation intentions; replacement behaviour

Abstract

Background. Advice on breaking a bad habit usually appeals to willpower. Habit research describes a habit as a response cued by a familiar context, which points to strategies that act on the cue or on the response it triggers.

Aims. This review asks which strategies weaken or override an unwanted everyday habit in adults, and under what conditions each one fails.

Method. A single-reviewer narrative review of peer-reviewed journal articles found through Crossref, Europe PMC, Semantic Scholar and extended web searches in October 2026. Eighteen sources were included and appraised with the CRAAP test.

Results. Habits were disrupted when their context changed, as after a move to a new university or home, and in some studies intentions or interventions then had more influence; two recent studies found no such effect for New Year or for the start of university. In diary studies, watching for slips was the strategy most associated with controlling strong habits. If-then plans naming a replacement response reduced the advantage of the habitual response, whereas plans phrased as "if X, then not Y" produced ironic rebound. Plans helped less, or not at all, against strong habits, and a 2025 meta-analysis of 642 tests found substantial publication bias.

Conclusions. The evidence favours acting on the cue where possible and pairing it with a named alternative behaviour. Most studies used self-report over short periods, so durations and effect sizes remain uncertain.

1. Introduction

People who want to stop a habit, such as reaching for the phone on waking, are commonly told to try harder. That advice treats the behaviour as a choice made afresh each time. Research by Wendy Wood, David Neal and colleagues at Duke University and the University of Southern California describes habits differently: a response repeated often in one setting comes to be triggered by the setting, and current goals play a smaller part (Neal et al., 2011; Quinn et al., 2010).

In two field experiments, Neal, Wood, Wu and Kurlander (2011) found that people with a strong habit of eating popcorn at the cinema were barely affected by hunger or liking, and ate as much stale popcorn as fresh. The pattern appeared in the cinema and not in a different setting, and it did not appear when participants ate with their non-dominant hand. A habit, on this evidence, persists despite contrary motives and is bound to a context that can be changed.

Bas Verplanken of the University of Bath and Sheina Orbell of the University of Essex argue that campaigns based on information and attitude change take insufficient account of habits, which set boundary conditions on what such campaigns achieve (Verplanken & Orbell, 2022). Their proposed alternatives include capitalising on habit discontinuities and on strategic planning. This review examines the evidence for those strategies as tools an individual can use, and asks one question: which strategies weaken or override an unwanted everyday habit in adults, and under what conditions do they fail?

2. Method

2.1 Search strategy

Searches were run on 14 October 2026. OpenAlex and the Semantic Scholar search endpoint returned rate-limit errors throughout, so records were retrieved from Crossref, Europe PMC and Semantic Scholar paper records, supplemented by WebSearch in extended mode. Search strings combined "bad habit", "unwanted habit", "breaking habits", "habit discontinuity", "context change", "relocation", "vigilant monitoring", "implementation intention", "negation" and "replacement". Reference lists of Verplanken and Orbell (2022) and Quinn et al. (2010) were checked, and forward searches were run from Wood et al. (2005).

2.2 Eligibility criteria

Sources were included when they (a) appeared in a peer-reviewed journal, (b) reported an experiment, longitudinal or diary study, survey analysis, meta-analysis or review, (c) concerned the weakening or override of an existing habit, or a strategy proposed for that purpose, and (d) studied non-clinical adults. Books, chapters, preprints, theses, popular writing and clinical treatments such as habit reversal training were excluded, as was any source whose abstract or full text could not be read in this session. That rule removed a field experiment on implementation intentions in an office (Holland et al., 2006) and an earlier survey on moving house and car use (Verplanken et al., 2008), whose abstracts could be seen only in summary. Every included record was checked in Crossref for retraction or correction notices, and none was found.

2.3 Appraisal with the CRAAP test

Each source was rated on the five CRAAP criteria. Currency weighed the publication date against later work, keeping older reference studies. Relevance assessed how closely the behaviour resembles an everyday personal habit. Authority required a peer-reviewed journal and authors with a record in the field. Accuracy considered design, sample size, measurement and whether the reported statistics allow the claim to be judged. Purpose checked for commercial or advocacy aims. The full texts of three sources were read (Adriaanse, Gollwitzer, et al., 2011; Sheeran et al., 2025; Thomas et al., 2016); for the other 15, figures come from abstracts and bibliographic records.

2.4 Appraisal results

Source	Design	Appraisal notes	Decision
Sheeran et al. (2025)	Meta-analysis, 642 tests	Full text read; not habit-specific; publication bias.	Included
Adriaanse, Vinkers, et al. (2011)	Meta-analysis, 23 studies	Separates adding from reducing eating behaviours.	Included
Wood et al. (2005)	Longitudinal study of transferring students	Reference study for context change.	Included
Neal et al. (2011)	Two field experiments	Habits persisting against motives.	Included
Verplanken & Roy (2016)	Field experiment, n = 800	Randomised; self-reported behaviour.	Included
Thomas et al. (2016)	Survey analysis, n = 18,053	Full text read; cross-sectional; small effects.	Included
Walker et al. (2015)	Panel study around an office move	Measures habit decay directly; one organisation.	Included
Maltagliati et al. (2021)	Three-wave survey, n = 283	Lockdown as a context change; retrospective self-report.	Included
Haggar et al. (2025)	Retail sales and survey data, n = 12,968	Current; null result for New Year; pro-environmental purchases.	Included as counter-evidence
Mitev et al. (2024)	Intervention study with new students	Current; timing showed no effect.	Included as counter-evidence
Quinn et al. (2010)	Two diary studies and an experiment	Compares strategies for habits and temptations.	Included
Sonnentag et al. (2022)	Daily diary study, n = 145, follow-up n = 126	Workplace habits; correlational, multilevel.	Included
Adriaanse, Gollwitzer, et al. (2011)	Three experiments, female students	Full text read; cognitive accessibility only; small samples.	Included
Adriaanse, van Oosten, et al. (2011)	Experiments	Tests negation plans against replacement plans.	Included
Webb et al. (2009)	Laboratory experiment and field test with smokers	Tests habit strength as a moderator.	Included
Gardner et al. (2015)	Prospective survey, n = 239	Challenges habit-over-intention claim.	Included as counter-evidence
Lin et al. (2016)	Two laboratory studies	Trained habits; depletion manipulation.	Included
Verplanken & Orbell (2022)	Annual review	Theory and framing; no new data.	Included as theory
Holland et al. (2006)	Field experiment	Abstract and full text could not be opened.	Excluded
Verplanken et al. (2008)	Survey	Abstract seen only in summary.	Excluded

3. Findings

3.1 Intentions and habits

The case for cue-based strategies rests on the claim that habits override intentions. Benjamin Gardner and colleagues at University College London tested it with 239 adults who reported their snacking habits and their intention to avoid unhealthy snacks, and then their intake two weeks later (Gardner et al., 2015). Habit and intention each predicted intake, but the expected interaction did not appear: people with strong habits could still act on their intentions. The authors suggest that earlier evidence for the interaction may be unreliable and that habitual tendencies can be inhibited, with difficulty. The result tempers the strong form of the habit account, while habit still predicted intake independently of intention.

3.2 Changing the context

If a habit is triggered by its context, a change of context should weaken it. Wood, Tam and Witt (2005) followed students' exercise, newspaper reading and television habits across a transfer between universities. The habits survived when relevant features of the setting stayed the same, such as reading the paper with other people, and were disrupted when those features changed. In some cases the disruption placed the behaviour under intentional control, so that participants acted on their current intentions.

This prediction is known as the habit discontinuity hypothesis (Verplanken & Roy, 2016). Gregory Thomas, Wouter Poortinga and Elena Sautkina at Cardiff University tested it in the UK Understanding Society survey with 18,053 employed adults (Thomas et al., 2016). Car commuting was lower among people with stronger environmental attitudes, and the gap was widest soon after a move: the predicted probability of commuting by car was .60 for people with weak attitudes and .47 for those with strong attitudes one month after moving, narrowing to .66 and .61 after ten years. The authors describe the effects as small and note that cross-sectional data cannot show behaviour before the move.

Verplanken and Deborah Roy supplied a field experiment, assigning 800 households, half of which had recently moved, to an intervention promoting 25 sustainable behaviours or to no intervention (Verplanken & Roy, 2016). After eight weeks, and controlling for past behaviour, habit strength and intentions, the intervention was more effective among recently relocated participants, with a window of opportunity of about three months.

The old habit does not vanish at the moment of change. Ian Walker, Gregory Thomas and Bas Verplanken surveyed staff at a charity 19 months before its headquarters moved to another town, and one and four weeks after (Walker et al., 2015). Travel habit weakened immediately after the move, equally among staff who changed mode and those who did not. Among those who switched, habit strength for the old mode decayed over the post-move period while that for the new mode grew. Silvio Maltagliati and colleagues surveyed 283 adults in France and Switzerland about physical activity around the spring 2020 COVID-19 lockdown (Maltagliati et al., 2021). Habits declined from before to mid-lockdown, more steeply among people with strong prior habits, and pre-lockdown habit no longer predicted mid-lockdown activity (β = −.02, p = .837). The ratings were collected retrospectively.

Two recent studies found no advantage for moments of change. Paul Haggar and colleagues at Cardiff University linked 35 months of sales data from a UK health retailer to a survey of 12,968 customers (Haggar et al., 2025). Sales of self-improvement health products rose in January, but there was no evidence of a habit discontinuity at New Year in purchases of greener products. Kaloyan Mitev and colleagues at the University of Bath gave students who had recently moved into university housing information, an if-then plan and a shower timer (Mitev et al., 2024). Self-reported water saving increased relative to controls, measured shower times and water use did not change, and how recently a student had started university was unrelated to the effect. In these data, a calendar landmark did not behave like a physical change of setting, and a recent transition did not enhance the intervention.

3.3 Watching for slips

When the context cannot be changed, the cue has to be met as it occurs. Jeffrey Quinn and Anthony Pascoe at Duke University, with Wood and Neal, compared the strategies people used in daily life against bad habits and against temptations (Quinn et al., 2010). In two diary studies, vigilant monitoring, which meant telling oneself not to do it and watching for slip-ups, was the most effective strategy against bad habits, and no other strategy helped with strong habits, although removing the tempting item worked against temptations. A follow-up experiment indicated that monitoring helps by strengthening inhibitory control, leaving the habit's memory trace intact. On that account, monitoring is likely to demand effort, because the habit remains and each episode calls for inhibition.

Sabine Sonnentag and colleagues extended the finding to work with a daily survey of 145 employees about workplace habits they regarded as unwanted (Sonnentag et al., 2022). On days when employees formed implementation intentions or monitored themselves vigilantly, they reported less habitual behaviour and more of the alternative. In a follow-up with 126 participants, the change in habit strength held over two months, particularly for task-related habits and consistent monitoring. The design was correlational.

3.4 If-then plans: replacement and negation

Implementation intentions take the form "if situation X arises, then I will do Y". Marieke Adriaanse and colleagues at Utrecht University, with Peter Gollwitzer of New York University and the University of Konstanz, tested such plans against snacking and drinking habits in three experiments with 61, 30 and 75 female students (Adriaanse, Gollwitzer, et al., 2011). Plans that replaced the habitual response with an alternative removed the habitual response's speed advantage in a lexical decision task, without making the alternative faster than the habit. The authors conclude that such plans give people a choice at the critical moment, and that behaviour changes to the extent that people strongly intend the alternative. Eating itself was not observed.

The wording of the plan mattered. Plans phrased as "if X, then I will not do Y" produced ironic rebound in thought and in behaviour, compared with an intention alone or a replacement plan, most clearly when the habit was strong (Adriaanse, van Oosten, et al., 2011). The authors draw on ironic process theory and the processing of negations: a plan that names the unwanted response may strengthen the link it is meant to break.

Habit strength limits what plans can do. Thomas Webb of the University of Sheffield, with Paschal Sheeran and Aleksandra Luszczynska, found that if-then plans reduced the cost of a trained habit in a laboratory task, but less for participants with strong habits (Webb et al., 2009). In a field test, plans reduced smoking among people with weak or moderate smoking habits and had no effect among those with strong habits.

Meta-analyses point the same way. Across 23 studies of eating, implementation intentions had a medium effect for adding healthy foods (d = .51) and a smaller one for reducing unhealthy eating (d = .29), and weaker control conditions tended to inflate effects (Adriaanse, Vinkers, et al., 2011). Sheeran, Olivia Listrom and Gollwitzer pooled 642 tests (Sheeran et al., 2025). The weighted average was d = .36 (95% CI .33 to .40), with similar effects for avoidance and approach responses (d = .38 and .40) and smaller ones for reducing unhealthy food intake (d = .27), alcohol (d = .21) and smoking (d = .20). The authors report strong evidence of publication bias; a robust Bayesian model reduced the average to d = .15. The search ended in September 2019, and habit strength was not coded.

3.5 Building the replacement

If the old habit fades slowly, a competing habit has to take over the cue. Pei-Ying Lin, Wendy Wood and John Monterosso at the University of Southern California trained participants to choose healthy or unhealthy foods in response to a cue (Lin et al., 2016). Those trained with a healthy habit resisted chocolate when their self-control was depleted, and those trained to choose carrots in response to a picture resisted sweets while the picture was present. The habits were trained in one laboratory session, and the effect depended on a manipulation of self-control resources.

4. Discussion

4.1 Synthesis

A habit's link to its cue changes slowly and outlasts a change in behaviour (Walker et al., 2015; Quinn et al., 2010). The cue and its response can nonetheless be acted on. Changes of physical context disrupted habits and were associated with a wider opening for intentions (Wood et al., 2005; Verplanken & Roy, 2016; Thomas et al., 2016). At the moment of the cue, monitoring and a plan naming the alternative were associated with less habitual behaviour (Quinn et al., 2010; Sonnentag et al., 2022; Adriaanse, Gollwitzer, et al., 2011), while plans that merely forbade the habit risked rebound (Adriaanse, van Oosten, et al., 2011).

The negative findings set boundaries. A calendar landmark showed no discontinuity in retail data (Haggar et al., 2025), and the timing of a real transition did not change an intervention's effect in one student sample (Mitev et al., 2024). Strong habits weakened, and in one field test eliminated, the effect of if-then plans (Webb et al., 2009). Intentions continued to predict behaviour alongside habit (Gardner et al., 2015), consistent with larger plan effects among motivated participants (Sheeran et al., 2025).

4.2 Limitations of the evidence

Most studies measured habit and behaviour by self-report, and several used single sessions or follow-ups of eight weeks or less. The experiments on if-then plans relied largely on students, three samples entirely female, and on cognitive measures. The context-change studies concerned mostly travel and environmental behaviour, and the largest was cross-sectional. The diary findings on monitoring are correlational, and the 2025 meta-analysis reported substantial publication bias. No included study tracked how long an unwanted habit takes to fade, and none examined digital habits such as phone checking.

5. Practical implications

The recommendations below are graded by the strength of the evidence behind them.

Change the setting where you can. Habits were disrupted when relevant features of their context changed, and behaviour change efforts worked better soon after a move (Wood et al., 2005; Verplanken & Roy, 2016; Thomas et al., 2016). Strength: moderate, mainly travel and environmental behaviour.
Use a real transition promptly, and do not rely on the calendar alone. The window after relocation appeared to last about three months (Verplanken & Roy, 2016), while New Year showed no discontinuity in retail data (Haggar et al., 2025) and recency did not matter in one student sample (Mitev et al., 2024). Strength: limited, mixed results.
Write the if-then plan around a replacement. Plans naming an alternative response reduced the advantage of the habit, while plans phrased as "then I will not" produced rebound (Adriaanse, Gollwitzer, et al., 2011; Adriaanse, van Oosten, et al., 2011). Strength: moderate for the cognitive effect, limited for behaviour.
Watch for the cue while the habit is strong. Vigilant monitoring was the strategy most associated with controlling strong habits in daily life (Quinn et al., 2010; Sonnentag et al., 2022). Strength: moderate, diary designs.
Expect an overlap period. The old habit decayed gradually while the new one grew (Walker et al., 2015). Strength: limited, one organisation.
Expect less from a plan when the habit is very strong. Plans did not reduce smoking among strong-habit smokers (Webb et al., 2009), and effects for reducing unhealthy behaviours were small (Adriaanse, Vinkers, et al., 2011; Sheeran et al., 2025). Strength: moderate.

A planning tool can help by placing the replacement behaviour in the time slot where the old cue usually occurs, so that the alternative is rehearsed in the same context. In Flowo, a replacement routine can be added as a habit and placed in that slot; the app does not detect cues or monitor behaviour, and its effect on habit change has not been studied. For forming a new routine, see how long habit formation takes and what a missed day costs.

6. Limitations of this review

This is a narrative review with structured appraisal, carried out by a single reviewer. It was not preregistered, only English-language sources were searched, and publication bias was not assessed beyond what the included meta-analyses reported. OpenAlex and the Semantic Scholar search service were unavailable, which may have reduced coverage, and two relevant studies were excluded because they could not be read. The full texts of three sources were read; data for the other 15 come from abstracts and bibliographic records. The author has a commercial interest in planning software.

7. Conclusion

In the studies reviewed, unwanted habits gave way most readily when their cues changed, as after a move to a new home or workplace, and that opening appeared to last weeks to months. Where the cue stayed in place, watching for it and planning a specific replacement were associated with less habitual behaviour, while plans that merely forbade the habit could strengthen it. Strong habits blunted the effect of if-then plans, and the old link faded slowly even after behaviour changed.

Frequently asked questions

What is the most effective way to break a bad habit?

The evidence favours changing the context that triggers the habit where possible, and otherwise planning a specific replacement for the moment the cue appears (Wood et al., 2005; Adriaanse, Gollwitzer, et al., 2011).

Does moving house help break habits?

Habits weakened after relocations, and behaviour change efforts worked better in the following months (Verplanken & Roy, 2016; Walker et al., 2015). The effects were small in a large UK survey (Thomas et al., 2016).

Does telling yourself "don't do it" work?

Watching for slips in the moment was associated with better control of habits (Quinn et al., 2010), but written plans of the form "then I will not" produced rebound in experiments (Adriaanse, van Oosten, et al., 2011).

How long does it take to break a habit?

No included study measured this directly. After an office move, the old travel habit decayed over several weeks as the new one grew (Walker et al., 2015).

References

Adriaanse, M. A., Gollwitzer, P. M., De Ridder, D. T. D., de Wit, J. B. F., & Kroese, F. M. (2011). Breaking habits with implementation intentions: A test of underlying processes. Personality and Social Psychology Bulletin, 37(4), 502-513. https://doi.org/10.1177/0146167211399102
Adriaanse, M. A., van Oosten, J. M. F., de Ridder, D. T. D., de Wit, J. B. F., & Evers, C. (2011). Planning what not to eat: Ironic effects of implementation intentions negating unhealthy habits. Personality and Social Psychology Bulletin, 37(1), 69-81. https://doi.org/10.1177/0146167210390523
Adriaanse, M. A., Vinkers, C. D. W., De Ridder, D. T. D., Hox, J. J., & De Wit, J. B. F. (2011). Do implementation intentions help to eat a healthy diet? A systematic review and meta-analysis of the empirical evidence. Appetite, 56(1), 183-193. https://doi.org/10.1016/j.appet.2010.10.012
Gardner, B., Corbridge, S., & McGowan, L. (2015). Do habits always override intentions? Pitting unhealthy snacking habits against snack-avoidance intentions. BMC Psychology, 3, 8. https://doi.org/10.1186/s40359-015-0065-4
Haggar, P., Sachdev, Y., Whitmarsh, L., Goulding, J., Smith, A., & Smith, G. (2025). New year as a moment of change in pro-environmental product consumption: Evaluating the habit discontinuity and self-activation hypotheses using a large UK retail dataset. Frontiers in Psychology, 16, 1550091. https://doi.org/10.3389/fpsyg.2025.1550091
Lin, P.-Y., Wood, W., & Monterosso, J. (2016). Healthy eating habits protect against temptations. Appetite, 103, 432-440. https://doi.org/10.1016/j.appet.2015.11.011
Maltagliati, S., Rebar, A., Fessler, L., Forestier, C., Sarrazin, P., Chalabaev, A., Sander, D., Sivaramakrishnan, H., Orsholits, D., Boisgontier, M. P., Ntoumanis, N., Gardner, B., & Cheval, B. (2021). Evolution of physical activity habits after a context change: The case of COVID-19 lockdown. British Journal of Health Psychology, 26(4), 1135-1154. https://doi.org/10.1111/bjhp.12524
Mitev, K., Rennison, F., Haggar, P., Hafner, R., Lowe, A., & Whitmarsh, L. (2024). Encouraging water-saving behavior during a "moment of change": The efficacy of implementation intentions on water conservation during the transition to university. Frontiers in Psychology, 15, 1465696. https://doi.org/10.3389/fpsyg.2024.1465696
Neal, D. T., Wood, W., Wu, M., & Kurlander, D. (2011). The pull of the past: When do habits persist despite conflict with motives? Personality and Social Psychology Bulletin, 37(11), 1428-1437. https://doi.org/10.1177/0146167211419863
Quinn, J. M., Pascoe, A., Wood, W., & Neal, D. T. (2010). Can't control yourself? Monitor those bad habits. Personality and Social Psychology Bulletin, 36(4), 499-511. https://doi.org/10.1177/0146167209360665
Sheeran, P., Listrom, O., & Gollwitzer, P. M. (2025). The when and how of planning: Meta-analysis of the scope and components of implementation intentions in 642 tests. European Review of Social Psychology, 36(1), 162-194. https://doi.org/10.1080/10463283.2024.2334563
Sonnentag, S., Wehrt, W., Weyers, B., & Law, Y. C. (2022). Conquering unwanted habits at the workplace: Day-level processes and longer term change in habit strength. Journal of Applied Psychology, 107(5), 831-853. https://doi.org/10.1037/apl0000930
Thomas, G. O., Poortinga, W., & Sautkina, E. (2016). Habit discontinuity, self-activation, and the diminishing influence of context change: Evidence from the UK Understanding Society survey. PLOS ONE, 11(4), e0153490. https://doi.org/10.1371/journal.pone.0153490
Verplanken, B., & Orbell, S. (2022). Attitudes, habits, and behavior change. Annual Review of Psychology, 73, 327-352. https://doi.org/10.1146/annurev-psych-020821-011744
Verplanken, B., & Roy, D. (2016). Empowering interventions to promote sustainable lifestyles: Testing the habit discontinuity hypothesis in a field experiment. Journal of Environmental Psychology, 45, 127-134. https://doi.org/10.1016/j.jenvp.2015.11.008
Walker, I., Thomas, G. O., & Verplanken, B. (2015). Old habits die hard: Travel habit formation and decay during an office relocation. Environment and Behavior, 47(10), 1089-1106. https://doi.org/10.1177/0013916514549619
Webb, T. L., Sheeran, P., & Luszczynska, A. (2009). Planning to break unwanted habits: Habit strength moderates implementation intention effects on behaviour change. British Journal of Social Psychology, 48(3), 507-523. https://doi.org/10.1348/014466608X370591
Wood, W., Tam, L., & Witt, M. G. (2005). Changing circumstances, disrupting habits. Journal of Personality and Social Psychology, 88(6), 918-933. https://doi.org/10.1037/0022-3514.88.6.918

Conflict of interest: the author is a co-founder of Flowo, a planning app. None of the studies cited was funded by or connected to the company.

Flowo is free to download on the App Store for iPhone and on Google Play for Android, with optional in-app purchases.

How Do You Break a Bad Habit? A Review of the Evidence on Changing Cues and Replacement Plans