Background: Healthy lifestyles depend on forming crucial habits through the process of habit formation, emphasising the need to establish positive habits and break negative ones for lasting behaviour changes. This systematic review aims to explore the time required for developing health-related habits. Methods: Six databases (Scopus, PsychINFO, CINAHL, EMBASE, Medline and PubMed) were searched to identify experimental intervention studies assessing self-report habit or automaticity questionnaires (e.g., the self-report habit index (SRHI) or the self-report behavioural automaticity index (SRBAI)), or the duration to reach automaticity in health-related behaviours. Habit formation determinants were also evaluated. Meta-analysis was performed to assess the change in the SRHI or SRBAI habit scores between pre- and post-intervention, and the study quality was assessed using the PEDro scale. Results: A total of 20 studies involving 2601 participants (mean age range: 21.5–73.5 years) were included. Most studies had a high risk of bias rating (n = 11). Health behaviours included physical activity (n = 8), drinking water (n = 2), vitamin consumption (n = 1), flossing (n = 3), healthy diet (n = 8), microwaving a dishcloth (for foodborne disease reduction, n = 2) and sedentary behaviour reduction (n = 1). Four studies reported the median or mean times to reach habit formation, ranging from 59–66 days (median) and 106–154 days (means), with substantial individual variability (4–335 days). The meta-analysis showed significant improvements in habit scores pre- to post-intervention across different habits (standardised mean difference: 0.69, 95% CI: 0.49–0.88). Frequency, timing, type of habit, individual choice, affective judgements, behavioural regulation and preparatory habits significantly influence habit strength, with morning practices and self-selected habits generally exhibiting greater strength. Conclusions: Emerging evidence on health-related habit formation indicates that while habits can start forming within about two months, the time required varies significantly across individuals. A limitation of this meta-analysis is the relatively small number of studies included, with flossing and diet having the most evidence among the behaviours examined. Despite this, improvements in habit strength post-intervention are evident across various behaviours, suggesting that targeted interventions can be effective. Future research should aim to expand the evidence base with well-designed studies to better understand and enhance the process of establishing beneficial health habits.

Background: Physical activity (PA), sleep and sedentary time are now recognised as mutually exclusive and exhaustive parts of the 24‐h day—if PA decreases, time spent sleeping, being sedentary or both must increase so that all components equate to 24 h. Recent advances in time‐use epidemiology suggest that we should not consider time‐use domains (PA, sleep and sedentary time) in isolation from each other, but in terms of a composition—the mix of time‐use domains across the 24‐h day. While interrelated daily activities are known to be important in the management of diabetes mellitus, few studies have investigated the interrelated daily activities in people with an active diabetes‐related foot ulcer (DFU) and their impact on important outcomes such as wound severity, blood glucose control and health‐related quality of life (HRQoL). This feasibility study aims to determine the acceptability and practicality of measuring 24‐h use of time data in people with a DFU and its associations on important outcome measures for this population.Methods: Participants wore a wrist‐worn accelerometer for two weeks and completed demographic and HRQoL questionnaires. Outcomes were participant engagement, reported levels of study burden and value and compositional data analysis as a methodological approach for evaluating 24‐h use of time data.Results: Twenty‐six participants reported low levels of study burden and rated the study value highly. The protocol appears feasible in terms of recruitment (81%) and retention rate (86%). On average, participants were relatively sedentary spending 747, 172 and 18 min in sedentary time, light physical activity and moderate‐to‐vigorous activity, respectively. Sleep appeared adequate with participants obtaining an average of 485 min, but quality of sleep was notably poor with average sleep efficiency of 75%. Compositional data analysis was able to quantify the integrated associations of 24‐h use of time with HRQoL.Conclusion: The protocol provides an acceptable method to collect 24‐h use of time data in people with a DFU. Efforts to consider and analyse PA as part of a 24‐h activity composition may provide holistic and realistic understandings of PA in this clinical population.