Stress is nearly ubiquitous in everyday life; however, it imposes a tremendous burden worldwide by acting as a risk factor for most physical and mental diseases. The effects of geographic environments on stress are supported by multiple theories acknowledging that natural environments act as a stress buffer and provide deeper and quicker restorative effects than most urban settings. However, little is known about how the temporalities of exposure to complex urban environments (duration, frequency and sequences of exposures) experienced in various locations – as shaped by people’s daily activities – affect daily and chronic stress levels. The potential modifying effect of activity patterns (ie, time, place, activity type and social company) on the environment–stress relationship also remains poorly understood. Moreover, most observational studies relied quasi-exclusively on self-reported stress measurements, which may not accurately reflect the individual physiological embodiment of stress. The FragMent study aims to assess the extent to which the spatial and temporal characteristics of exposures to environments in daily life, along with individuals’ activity patterns, influence physiological and psychological stress.

A sample of 2000 adults aged 18–65 and residing in the country of Luxembourg completed a traditional and a map-based questionnaire to collect data on their perceived built, natural and social environments, regular mobility, activity patterns and chronic stress at baseline. A subsample of 200 participants engaged in a 15-day geographically explicit ecological momentary assessment (GEMA) survey, combining a smartphone-enabled global positioning system (GPS) tracking and the repeated daily assessment of the participants’ momentary stress, activities and environmental perceptions. Participants further complete multiple daily vocal tasks to collect data on vocal biomarkers of stress. Analytical methods will include machine learning models for stress prediction from vocal features, the use of geographic information systems (GIS) to quantify dynamic environmental exposures in space and time, and statistical models to disentangle the environment–stress relationships.

Ethical approval (LISER REC/2021/024.FRAGMENT/4-5-9-10) was granted by the Research Ethics Committee of the Luxembourg Institute of Socio-Economic Research (LISER), Luxembourg. Results will be disseminated via conferences, peer-review journal papers and comic strips. All project outcomes will be made available at https://www.fragmentproject.eu/.

Reducing sedentary behaviour (SB) in older adults is a promising strategy to promote healthy ageing. However, to develop more effective interventions, more in-depth information is needed on how existing interventions work. The present realist review aims to identify the working mechanisms and contextual preconditions to guide the development of future interventions.

A realist review was conducted following the iterative process of Pawson and Tilley and reported following the RAMESES publication standards.

Evidence was searched in four databases: EMBASE, PubMed, Web of Science and Scopus, and in the grey literature.

All study types and designs were included. Studies conducted in older adults with a mean age of 60 years or older, providing information on the context, mechanisms and/or outcomes of interventions aimed at the reduction of SB were eligible for inclusion and appraised for relevance and rigour.

All data were coded by two independent reviewers. Sections that contained relevant information to refine, refute or confirm the initial programme theory were given a code. Based on these codes, context-mechanism-outcome configurations were made, and a final programme theory was developed.

In total, 58 studies, from 61 articles, were eligible. The review revealed three important contexts for changes in SB: the (1) motivation, (2) opportunities and (3) capabilities of older adults. Depending on the context, other behaviour change techniques should be used to trigger specific mechanisms and, in turn, reduce SB. Especially, the impact of the underlying automatic processes of SB on the effectiveness of SB interventions became clear. Existing interventions primarily focus on the reflective processes guiding SB, without taking into account that SB is often an automatic response that occurs unconsciously, with little reasoning.

The effectiveness of SB interventions in older adults highly depends on the context in which the interventions occur. In particular, the context of automatic motivation should receive more attention to break the ingrained habit of SB in older adults.

Regular physical activity (PA) and reduced sedentary behaviour (SB) have been associated with positive health outcomes, but many older adults do not comply with the current recommendations. Sensor-triggered ecological momentary assessment (EMA) studies allow capturing real-time data during or immediately after PA or SB, which can yield important insights into these behaviours. Despite the promising potential of sensor-triggered EMA, this methodology is still in its infancy. Addressing methodological challenges in sensor-triggered EMA studies is essential for improving protocol adherence and enhancing validity. Therefore, this study aimed to examine (1) the patterns in sensor-triggered EMA protocol adherence (eg, compliance rates), (2) the impact of specific settings (eg, event duration) on the number of prompted surveys, and (3) participants’ experiences with engaging in a sensor-triggered EMA study.

Two longitudinal, sensor-triggered EMA studies—one focused on PA and the other on SB—were conducted using similar methodologies from February to October 2022. Participants’ steps were monitored for seven days using a Fitbit activity tracker, which automatically prompted an EMA survey through the HealthReact smartphone application when specified (in)activity thresholds were reached. After the monitoring period, qualitative interviews were conducted. Data from both studies were merged.

The studies were conducted among community-dwelling Belgian older adults.

The participants had a median age of 72 years, with 54.17% being females. The PA study included 88 participants (four dropped out), while the SB study included 76 participants (seven dropped out).

Descriptive methods and generalised logistic mixed models were employed to analyse EMA adherence patterns. Simulations were conducted to assess the impact of particular settings on the number of prompted EMA surveys. Additionally, qualitative interview data were transcribed verbatim and thematically analysed using NVivo.

Participants responded to 81.22% and 79.10% of the EMA surveys in the PA and SB study, respectively. The confirmation rate, defined as the percentage of EMA surveys in which participants confirmed the detected behaviour, was 94.16% for PA and 72.40% for SB. Logistic mixed models revealed that with each additional day in the study, the odds of responding to the EMA survey increased significantly by 1.59 times (OR=1.59, 95% CI: 1.36 to 1.86, p

This study demonstrates the potential of sensor-triggered EMA to capture real-time data on PA and SB among older adults, showing strong adherence potential with compliance rates of approximately 80%. The SB study had lower confirmation rates than the PA study, due to technical issues and discrepancies between self-perception and device-based measurements. Practical recommendations were provided for future studies, including improvements in survey timing, technical reliability and strategies to reduce latency.