Skip to main content

Effectiveness of workplace interventions with digital elements to reduce sedentary behaviours in office employees: a systematic review and meta-analysis



Digital interventions are potential tools for reducing and limiting occupational sedentary behaviour (SB) in sedentary desk-based jobs. Given the harmful effects of sitting too much and sitting for too long while working, the aim of this systematic review and meta-analysis was to examine the effectiveness of workplace interventions, that incorporated digital elements, to reduce the time spent in SB in office workers.


Randomised control trials that evaluated the implementation of workplace interventions that incorporated digital elements for breaking and limiting SB among desk-based jobs were identified by literature searches in six electronic databases (PubMed, Web of Science, Scopus, CINAHL, PsycINFO and PEDro) published up to 2023. Studies were included if total and/or occupational SB were assessed. Only studies that reported pre- and postintervention mean differences and standard deviations or standard errors for both intervention arms were used for the meta-analysis. The meta-analysis was conducted using Review Manager 5 (RevMan 5; Cochrane Collaboration, Oxford, UK). Risk of bias was assessed using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields QUALSYST tool.


Nineteen studies were included in the systematic review. The most employed digital elements were information delivery and mediated organisational support and social influences. Multicomponent, information, and counselling interventions measuring total and/or occupational/nonoccupational SB time by self-report or via device-based measures were reported. Multicomponent interventions were the most represented. Eleven studies were included in the meta-analysis, which presented a reduction of 29.9 (95% CI: -45.2, -14.5) min/8 h workday in SB (overall effect: Z = 3.81).


Multicomponent interventions, using a wide range of digital features, have demonstrated effectiveness in reducing time spent in SB at the workplace among desk-based employees. However, due to hybrid work (i.e., work in the office and home) being a customary mode of work for many employees, it is important for future studies to assess the feasibility and effectiveness of these interventions in the evolving work landscape.

Trial registration

The review protocol was registered in the Prospero database (CRD42022377366).


Recent advancements in technology have led to a significant increase in sedentary behaviour (SB) in the workplace [1]. Office workers who have a desk-based occupation spend the majority of their daily time (68%) in workplace sitting [2, 3]. High levels of workplace SB has a significant impact on employees’ physical and mental health, along with work-related outcomes, such as work performance and presenteeism [4,5,6,7]. Moreover, breaking up prolonged sedentary periods and replacing them with physical activity (PA) of any intensity has been shown to provide health benefits [8,9,10]. Given that work is the primary domain where SB commonly occurs in office workers, it is crucial to prioritise interventions that target this behaviour to improve desk-based workers’ health, as well as work-related outcomes [8, 11,12,13,14].

Several systematic reviews have been conducted in recent years to assess workplace interventions targeting SB [15,16,17]. These studies, including 34 [15], 26 [16] and 40 [17] studies respectively, have described a wide variety of interventions, including physical changes in the workplace design and environment (e.g., sit-stand desks), policies to change the organisation of work (e.g., breaks to sit less), provision of information and counselling (e.g., distribution of leaflets), and multicomponent interventions [15]. The interventions reviewed, rating the quality of evidence of the most included studies as low or very low [15], fair [16] or non-reported [17], demonstrated a broad range of levels of effectiveness on SB measured by self-reported or via device-measures. However, none of them focused on examining what specific elements of the intervention were most effective. Additionally, many of the interventions required substantial investment (i.e., sit-to-stand desks), while the effectiveness of more cost-efficient and scalable interventional approaches, such as digital interventions [18], were not determined.

Recent evidence has highlighted the potential of technology to enhance behavioural change interventions [19], especially to promote PA and reduce SB [20]. A scoping review classified the digital features that may help to reduce SB among office workers, such as information delivery, digital log, passive data collection, connected device, scheduled prompts, automated tailored feedback, and mediated organisational support and social influences [21]. However, to our knowledge, no previous reviews have analysed the effectiveness of workplace digital interventions to reduce time spent in SB in office workers as the target population.

In this context, it is essential to acknowledge the technological elements that have the potential to facilitate workplace interventions to influence employees’ behaviours. Therefore, the aim of this systematic review and meta-analysis was to examine the effectiveness of workplace interventions that incorporated digital elements to reduce SB in office workers.


The current systematic review was performed following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. The review protocol was registered in the Prospero database (CRD42022377366).

Search strategy

Six electronic databases (PubMed, Web of Science, Scopus, CINAHL, PsycINFO and PEDro) were searched for relevant articles published from 2017 (date of the most recent studies included in the last review on the topic) to October 2023. The reference lists of the included studies were then reviewed. The search included terms related to office work, SB, and digital technology (Table 1).

Table 1 Search strategy

Eligibility criteria

Eligible study designs included, randomised controlled trials (RCTs), crossover RCTs, cluster-RCTs, and quasi-RCTs. The Population, Intervention, Comparison, and Outcomes (PICO) characteristics were: office workers (i.e., ≥ 18 years) whose occupations involved spending most of their working time sitting at a desk; a digital element as part of the intervention to reduce SB (i.e., mobile technologies, computers software, messages, wearable devices such as activity trackers for self-monitoring activity patterns, providing feedback or prompts, social media, or websites for improving health, sharing experiences, changing perceptions and cognitions around health, assess and monitoring SB); against a control, comparison and/or other intervention group; and duration of time spent in SB during working hours or on work days measured either by self-report or using device-based measures.

Study selection

Initially, a single reviewer (FMB) screened titles and abstracts for inclusion. Duplicates were eliminated using reference management software (Zotero, Corporation for Digital Scholarship, George Mason University). Full texts of the remaining articles were independently assessed by two researchers (FMB, IPS), and in case of any disagreements, a discussion with a third reviewer (JBR) took place.

Data extraction

For selected articles, the following data were extracted: article characteristics (i.e., authors, year, and country), study population (i.e., job type, age, gender, and sample size), study design, intervention characteristics (i.e., type of intervention, general description including the dose and theoretical basis if used, duration and digital features), SB measurement tool (i.e., self-report or device-based measures), primary and secondary outcome measures, and main statistical findings (Table 3). The type of intervention was classified into four categories: physical changes in the workplace design and environment (e.g., height-adjustable desk), policies to change the organisation of work (e.g., active breaks), provision of information and counselling (e.g., educational e-booklet), and multicomponent interventions (i.e., combining at least two of the three above) [15]. Digital elements (i.e., information delivery, digital log, passive data collection, connected device, scheduled prompts, automated tailored feedback, and mediated organisational support and social influences, see Table 2) of the interventions were also documented specifying what digital element of the intervention covers each category [21]. The outcome extracted was time spent in SB at work or in a working day. For missing information, corresponding authors were contacted by email using a template. One reviewer (IPS) extracted the relevant information, and a second reviewer (JBR) checked/confirmed the data.

Table 2 Digital elements description

Data analysis

The meta-analysis was conducted using Review Manager 5 (RevMan 5; Cochrane Collaboration, Oxford, UK) and following the general recommendations in the Cochrane handbook for Systematic Reviews of Interventions [22].

The adjusted mean difference (AMD) and standard deviation (SD) of the intervention and control groups were extracted for studies reporting these measures. For studies that reported the AMD and 95% confidence interval (CI) instead of SD, the AMD was extracted, and the standard error (SE) was calculated, which was entered in RevMan 5 to calculate the SD. For studies that did not report the AMD, the unadjusted mean difference (UMD) was calculated from the means at baseline and postintervention in each group. For missing information, authors were contacted via email.

The mean differences were combined using time spent in SB in minutes per eight-hour workday (min/8 h workday) as a standard unit as this was the most prevalent unit presented in the included interventions. Studies which reported min/8 h workday were combined with studies which reported other units, such as hours per week, hours per workday or minutes per day. The latter units were firstly converted to minutes if this was necessary, and then scaled from week to day, and subsequently converted to min/8 h, considering a day as 24 h or a workday as 8 h. One study presented SB in minutes per shift, the shift was assumed as eight hours. Studies with multiple intervention arms were included as two separate studies, while studies with multiple time points, the baseline and “postintervention” measures (collected at the end of the intervention) were included as one study in the meta-analysis, no follow-up measures outside the specified intervention time were used. The sensitivity of the pooled intervention effects was assessed. The overall combined intervention effect was estimated using the random effect model and the inverse variance. Heterogeneity was assessed by I2, and significance was set at p < 0.05. Inverse variance weighting was used to compensate for heterogeneity of sample sizes between studies. The sensitivity of the pooled intervention effects was assessed after the exclusion of one study through the leave-one-out method.

The meta-analysis was performed for all studies together and for the following subgroups: 1) studies that applied device-based measures for measuring SB, 2) studies that compared a workplace intervention that included digital elements with another workplace intervention that included digital elements, 3) studies that compared a workplace intervention that included digital elements with a usual care group, and 4) studies in which the core elements of the intervention were digital. Additionally, a sub-analysis was conducted comprising of subgroups two and three.

Risk of bias assessment

Risk of bias was assessed using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields QUALSYST tool. The QUALSYST consists of a 14-item checklist, where every item is scored depending on adherence to the specific criterion (“yes” = 2, “partial” = 1, “no” = 0, and “n/a” = not applicable). Included articles were assessed independently by two reviewers (AC, IPS). Discrepancies were discussed with two additional reviewers (KD, JBR). A summary score was calculated for each paper by summing the total score obtained across relevant items and dividing it by the total possible score.


Selected studies

Figure 1 provides a flow diagram of the article selection criteria for the systematic review. The search in six databases yielded 1403 unique articles. After duplicate review and initial screening of titles and abstracts, 225 full articles were retrieved. A total of 68 full-text articles were critically appraised for eligibility. Fifty articles did not meet the inclusion criteria, and the main reasons were as follows: a) the study design was not a RCT, b) the intervention did not include digital technology features, c) participants were not office workers, and d) the outcome under study did not include SB measures. After reviewing the reference lists of the included studies, one additional article was selected for inclusion in the systematic review [23]. A total of 19 studies were included in the qualitative synthesis.

Fig. 1
figure 1

Flow diagram of the study selection process

Characteristics of the studies

The 19 included studies, which are summarised in Table 3, comprise cluster-RCTs (n = 10) [24,25,26,27,28,29,30,31,32,33], RCTs (n = 5) [23, 34,35,36,37], crossover-RCTs (n = 2) [38, 39], and quasi-RCTs (n = 2) [40, 41]. Studies evaluating workplace interventions that included digital elements to reduce SB ranged from 2 weeks to 12 months in duration. The most common duration of included interventions was between 8 and 13 weeks (n = 11) [26, 27, 29, 30, 32,33,34, 36, 38, 40, 41]. Of the 19 studies, nine included an intervention and a control group (i.e., no intervention elements) [24, 26, 27, 30, 33, 37,38,39, 41], five included an intervention group and a comparison group (i.e., lighter variant intervention than intervention group) [25, 28, 29, 31, 32], and two included three groups, intervention, comparison and control [25, 31]. Four studies included two intervention groups [23, 34, 35, 40], and one of them also had a third control group [40].

Table 3 Characteristics of the studies

Studies have been undertaken in a wide range of countries. The most represented countries were the United Kingdom (n = 8) [24,25,26,27, 34, 35, 38, 40] and Australia (n = 2) [28, 41]. European countries such as Spain [29], Denmark [30], Belgium [31], Italy [36], the Netherlands [32], and Ireland [39] were also represented.

A total of 3529 participants were included in the 19 studies, with samples sizes ranging from 18 to 756. All the participants were adult office workers, and most of them were women who represented a mean of 61.7% in the included studies. Two studies solely focused on men [35, 39].

Measurement methods

Occupational and nonoccupational SB outcomes were measured by self-report questionnaires (n = 7) [25, 31,32,33,34, 36, 37] or via device-based measures (n = 14) [23,24,25,26,27,28,29,30, 35, 36, 38,39,40,41], with two studies utilising both approaches [25, 36]. Self-reported tools included were the Global Physical Activity Questionnaire (GPAQ) [34], Workforce Sitting Questionnaire (WSQ) [31], International Physical Activity Questionnaire (IPAQ) [36], Occupational Sitting and Physical Activity Questionnaire (OSPAQ) [25, 37], and unvalidated or adapted questions [32, 33]. Fourteen studies employed thigh-based accelerometers, with the activPAL (PAL Technologies, Glasgow, UK) being the most employed (n = 10) [23,24,25,26,27,28,29, 35, 38,39,40], and three studies used ActiGraph GT3X + (ActiGraph, Shalimar, FL, USA) [30, 41]; only one study applied a wrist-based accelerometer, the Axivity AX3 (Axivity, Newcastle upon Tyne, UK, 2013) [36].

Table 4 shows the measurement unit of SB, presented in a wide range of ways, such as in hours, minutes, or proportions of time spent in SB during the day, workday, or work hours. Some of the studies reported the data in more than one measurement unit [24, 25, 27, 29, 36, 38,39,40].

Table 4 Measurement units according to the different studies

Digital element of the intervention characteristics

Multicomponent interventions were used in 16 studies [23,24,25,26, 28,29,30, 32, 33, 35,36,37,38,39,40,41], seven of which included elements from design and environmental changes (e.g., sit-stand desks) [23,24,25, 30, 36, 39, 41], and 15 of which comprised policies to change the organisation (e.g., SB breaks) [23,24,25,26, 28,29,30, 32, 33, 35, 37,38,39,40,41]. All of them included information and counselling interventions (e.g., prompts, distribution of leaflets or counselling). Three studies only included information and counselling interventions [27, 31, 34].

All studies combined different digital features. Information delivery was included in 18 of the studies [23,24,25, 27,28,29,30,31,32,33,34,35,36,37,38,39,40,41]. Digital media forms of information delivery cover educational and informational materials to increase knowledge and awareness in a range of ways, such as e-booklets [38], e-newsletters [23, 24], website [30, 31, 33, 34], online sessions [25], videos [33, 41], Toolkit [23], Garmin watch [35], and gamification tools [32]. Two of the studies did not specify what type of channel was used to distribute text messages [30, 37]. Text messages sent through emails [23, 30, 32, 38, 41], mobile phone application [28, 29], or computer software [27] were also covered by the information delivery digital element.

Automated tailored feedback (n = 11) comprised periodical feedback of the individual or team behaviours and progress, as well as goal accomplishment, sent in a variety of ways (i.e., emails [32, 38, 41], uploaded in a mobile phone application [24, 28, 36], website [29, 31, 39], and visually via the wearable device [35]). One study did not specify what channel was used to send text messages [37].

Scheduled prompts, such as reminders to break SB [24,25,26,27, 29, 35, 38,39,40] and/or to participate in PA [26, 33, 34, 39], as well as to use environmental strategies (i.e., change sit-stand desk position) [41] were implemented in 12 studies [24,25,26,27, 29, 33,34,35, 38,39,40,41]. Prompts were delivered visually [29, 33, 34, 38, 39], audibly [29, 39,40,41] and/or by vibration [24, 35, 39, 40] through computer screens [25,26,27, 33, 38, 41], emails [34], mobile phone applications [25, 26, 29, 40], SMS [34], wearables (i.e., smartwatches [39], or bracelets [35]) and/or seat cushions [24]. Three studies did not report the delivery method of the reminder [25,26,27]. The frequency and duration of the prompts and breaks differed in each intervention, being either selected by the intervention administrator or self-selected by the workers themselves.

Ten studies reported passive data collection of time spent in SB through applications [24, 25, 28, 32, 36], websites [29, 39], wearables [35], and software [25, 38, 41]. Seven of them used an external connected device, such as mobile phones [29, 36], computers [38], wearables [28, 32, 39], or cushions [24]. One study combined an external device (i.e., Garmin watch) and a digital log to self-report manual pedalling time [39]. Three studies used a digital self-monitoring log of the behaviour through a mobile phone diary [40], a virtual board [26], and a questionnaire [26, 31, 40].

The mediated organisational support and social influences were represented in seven studies covering e-newsletter from the managers’ [24], support emails from employees’ leader [23], organisation signed prompt messages [27], telephone support [23], and challenges [26, 32, 37] allowing (or not) social comparison [32].

Effectiveness of the intervention with digital elements in reducing SB

Six out of 16 multicomponent interventions [23, 24, 30, 33, 37, 40], including information delivered through e-newsletters [23, 24], website [30, 33], video demonstrations [33], or text messages [37, 40]; non-digital physical changes (i.e., height adjustable desks [23, 24, 30]); prompts to break SB or participate in PA delivered through a cushion [24], computer screen notifications [33] or mobile phone application notifications [40]; support from the organisation and social influences demonstrated through emails [23], e-newsletters [24], or challenges [37]; feedback on the behaviour [24, 37]; and/or behaviour data collected through a device or manually entered [24, 40], reported significant changes in time spent in SB at work. Ten multicomponent interventions reported reductions, although they were not statistically significant on daily, workday, or working SB [25, 26, 28, 29, 32, 35, 36, 38, 39, 41]. These interventions comprised informational and educational material delivered through online sessions [25], emails or app messages [29, 38, 41], e-booklets [38]; feedback on behaviour [28, 32, 35, 39, 41] collected passively [25, 28, 29, 32, 35, 38, 39, 41] (i.e., through a wearable [28, 32, 39], mobile phone app [29] or computer [38] connected to an application [28, 32], website [29], computer software [38] or platform [39]) or manually [26, 39] (i.e., entering data onto a virtual board [26] or onto a platform [39]); organisational support and social influences illustrated through challenges [26, 32], or social competition [39], prompts delivered through the computer [25, 26, 38, 41], mobile phone app [25, 29] and/or wearables [35, 39]. Only one of them, characterized by a mobile phone application including real-time data and self-monitoring, prompts, daily summary messages and weekly motivational messages, automated strategies and goals, showed higher reductions, but not statistically significant, in the comparison group, which used a partial application including self-monitoring features, compared to the intervention group [29].

Ten of the 16 multicomponent interventions were developed based on theories of behaviour change [23,24,25, 30, 33, 36,37,38,39,40]. Three of these interventions were grounded in multiple theories [24, 25, 30], while the other studies were based only on one theory. The Behaviour Change Wheel (BCW) [24, 25, 33] and socio-ecological model [23, 39, 40], as well as the habit formation model/theory [24, 25, 38] and social cognitive theory [24, 25, 30] were the most commonly employed theories. Other theories employed for the development of interventions were organisation development theory [24, 25], self-regulation theory [24, 25], relapse prevention theory [24, 25], Roger’s diffusion of innovations theory [30], goal-setting theory [30], self-determination theory [36], and the health action process approach [37]. The six multicomponent interventions, which demonstrated significant changes, used theories to develop their interventions [23, 24, 30, 33, 37, 40].

Two of the three studies that comprised information and counselling interventions, including prompting positive messages on the computer screen [27] and web-based computer-tailored advice, feedback messages and action planning [31], showed higher reductions, although not statistically significant, for intervention groups compared to control groups in time spent in SB during work [27, 31]. One information and counselling intervention, which had two intervention groups and no control group and implemented website educational materials and messages via SMS or email. The two groups showed reductions that were not statistically significant in daily SB at 12 weeks [34]. Two of the three information and counselling interventions were based on theories, such as the theory of planned behaviour [31, 34] and self-regulation theory [31], to develop their interventions. One of the two studies followed two theories to develop the intervention and showed reductions in SB time, but these changes were not statistically significant [31]. One study did not use a theory to develop the intervention, and showed non statistically significant reductions in SB [27].

Four studies had an intervention and treatment active-comparison group, including prompts and feedback on SB time vs no prompts and no feedback [29]; action plan vs no action plan [31]; and different goals vs the same goal across the intervention [28, 32]. One of these studies had three groups: intervention, comparison and control [31]. All the studies showed reductions in SB, but none of them were statistically significant. Additionally, the study with three intervention arms showed higher reductions between the intervention and comparison groups than studies that included two intervention arms. Five studies had two intervention groups, including height-adjustable desk vs no desk [25]; prompts every 30 min vs 60 min [40]; feedback on SB time vs feedback on upright time [35]; increased standing (with height-adjustable desk) vs increased moving time (no desk) [23]; and messages via SMS vs via email [34]. Two of them included three groups, two intervention and one control group [25, 40]. The five studies showed reductions in SB; three of them showed favourable differences between groups in favour of the height-adjustable desk and prompts every 60 min [23, 25, 40], while two others reported higher reductions in intervention groups that included messages via SMS and feedback on SB time [34, 35]. However, in only two of the five studies were these changes statistically significant [23, 40].

Of eleven studies using activPAL as the measurement tool [23,24,25,26,27,28,29, 35, 38,39,40], ten revealed reductions in SB time in intervention groups compared to control groups [23,24,25,26,27,28, 35, 38,39,40]. Three of these were statistically significant [23, 24, 40]. Only one study showed higher reductions in the comparison group than in the intervention group [29]. Two studies used the ActiGraph accelerometer as a device-based measure, and both reported higher reductions in SB during work in favour of the intervention groups [30, 41]. One study using Axivitiy as a device-based measure and the IPAQ as a self-reported measure did not find significant differences in either measurement method [36]. Those studies employing the WFQ and OSPAQ showed reductions in SB time in the two groups, with higher reductions in the intervention group [25, 31, 37]. Measuring SB with GPAQ also showed reductions in SB time from baseline to postintervention, although these findings were not statistically significant [34]. Studies that used unvalidated self-reported measures did not find associations between digital interventions and SB reductions [32, 33].


Nine of the 19 studies were included in the meta-analysis [23,24,25,26, 29, 33, 35, 38, 40]. Two of the nine studies were considered as two independent studies due to the inclusion of three intervention arms [25, 40]. The reason for exclusion of the eight other studies was missing data (see Fig. 2).

Fig. 2
figure 2

Total sedentary behaviour reductions (min/8 h workday)

The total change in workplace SB was -29.9 (95% CI: -45.3, -14.5) min/8 h workday (Z = 3.81; I2 = 81%) (see Fig. 2). The leave-one-out sensitivity analysis showed that the strength of the pooled estimate was robust and did not significantly differ when one study was omitted at a time (see Additional file 1). No changes in the pool estimated and confidence intervals were significant by exclusion of any one study. Removing the largest study [33] did not substantially change the point estimate (-31.4 (95% CI: -49.5, 13.4) min/8 h workday).

Figure 3 shows the results from the digital interventions subgroup, which covers interventions that were entirely digital interventions [29, 33, 35, 40], or digital interventions that included a unique non-digital element (i.e., an educational session) [26]. In this subgroup, SB was reduced by 15.28 (95% CI: -28.5, -2.07) min/8 h workday.

Fig. 3
figure 3

Digital interventions (min/8 h workday)

Figure 4 illustrates the pooled results from the sub-analysis. Four studies comprised the intervention vs intervention group [23, 25, 35, 40], eight studies comprised the intervention vs control [24,25,26, 33, 38, 40], and four of them belonged to two studies [25, 40]. Intervention arm subgroups identified a change of -35.6 (95% CI: -48.6, -22.6) min/8 h workday in SB.

Fig. 4
figure 4

Sub-analysis sedentary behaviour reductions (min/8 h workday)

The results of the device-based measures subgroup are presented in Fig. 5, which includes 10 studies [23,24,25,26, 29, 35, 38, 40], four of which correspond to two studies [25, 40]. In this subgroup analysis, changes of -31.4 (95% CI: -49.3, -13.5) min/8 h workday were observed in SB.

Fig. 5
figure 5

Device-based measures of sedentary behaviour reductions (min/8 h workday)

Risk of bias assessment

The mean quality score for 19 articles was 74.3%, ranging from 50% [36] to 92.9% [24]. The main reasons for lower scores were the lack of blinding of investigators and subjects (21.1% and 39.5%, respectively), and small sample sizes (44.7%). The higher scores included appropriate study design to respond to research questions and described and presented appropriate analysis (100%). The detailed quality score for each study can be found in Additional file 2.


The aim of this systematic review and meta-analysis was to explore the effectiveness of workplace interventions that incorporated digital elements to reduce SB in office workers. A total of 19 studies published between 2017 and 2023 met the inclusion criteria. In the identified studies, the most effective interventions were multicomponent and included a wide variety of digital features, with the delivery of information and educational materials the most common, followed by scheduled prompts to break SB or participate in PA and behaviour feedback. Text messages, e-newsletters, websites, and videos were the most common way to deliver information for increasing knowledge and awareness, while computer screens and mobile phone apps were the most typical way to deliver visual prompts.

Our meta-analysis highlights that workplace interventions that include digital elements (ranging from 8 weeks to 12 months) reduced SB by an average of 30 min/8 h workday, which is similar to a previous meta-analysis, demonstrating a reduction of 32.6 min/8 h workday [42], and slightly lower compared to other two meta-analyses with 40 min/8 h workday and 41 min/day [19] reductions. Two of these meta-analyses included studies with digital elements, although they did not focus on them in their analyses, combining the results of multiple intervention arms and time points into a standardised single result or included non-RCTs, which may indicate its higher result [16, 42]. The other study considered computer, mobile and wearable technology interventions to reduce SB across the whole day and the results were presented in minutes per day, which would explain our lower reductions presented in minutes per 8 h of workday [19]. The intervention effects seen in the present study may be clinically relevant, with evidence showing that a decrease in SB of 30 min or more per day had a favourable effect on body weight, body mass index, as well as significantly increased energy and social functioning and reduced pain and sleep disturbance [43, 44]. Additionally, replacing SB time of 30 min per day with low intensity PA or moderate-to-vigorous PA was associated with lower all-cause mortality risk [45], and reduced blood cholesterol [46].

The World Health Organisation (WHO) recommends breaking and limiting the time spent in SB in any context, including work, and replacing it with PA [47]. Although performing PA breaks involves working time, productivity is not affected, in fact it improves by improving other outcomes, such as health [48, 49]. This suggests that the use of technology, such as activity trackers and mobile phone applications, has great potential for measuring and encouraging PA [50] and has been shown to be effective in behavioural change interventions [19, 20] since these digital elements, aimed at health and PA, incorporate established behaviour change techniques [50]. Furthermore, digital elements may provide a crucial intervention tool as it provides information such as self-monitoring progress, individual goal progress, and real-time information at low cost, and usually is an acceptable tool according to workers’ opinions [20, 50]. Hence, our findings may show that technology is a great element to fulfil WHO recommendations, specifically in the workplace, where workers spend the most of their SB time.

Multicomponent interventions with two groups (i.e., intervention, and control groups) were the most represented among the studies, followed by information and counselling interventions. There was no representation of interventions only including physical changes in the workplace design and environment, and policies to change the organisation of work as intervention techniques alone. Our results of the meta-analysis suggest that multicomponent interventions including environmental changes (e.g. sit-stand desks) as the core element of the interventions, but were complemented by digital elements, reported the highest SB reductions (-59.2 (95% CI: -74.4, -44.) and -58.6 (95% CI: -74.1, -43.1)) [23, 25]. Interventions with environmental changes as core elements in the intervention have been shown to reduce SB and increase standing time, but not PA time. In addition, they showed difficulties in maintaining utilisation over time [51, 52]. Digital multicomponent interventions which only include digital elements, show the higher reductions in SB present prompts as the core component of the interventions (-49.7 (95% CI: -93.7, -5.72) and -38.2 (95% CI: -85.6, 9.22)) [38, 40]. Therefore, digital elements, such as prompts, may complement interventions with physical changes for maintaining and encouraging its use. Although the evidence shows the benefits of breaking SB time at work on health and work-related outcomes, the frequency and duration of the breaks are uncertain [53, 54]. Hence, future research should examine the most effective duration and frequency of SB breaks to reduce that behaviour.

Despite reductions in SB, multicomponent interventions, given their nature, have a large heterogeneity in the intervention’s components, as well as in the digital elements, making it difficult to compare them to determine the most effective intervention. Due to the lack of data, it was impossible in our meta-analysis to compare specific intervention types. Even though there is no conclusive evidence about the effectiveness of multicomponent interventions, the literature indicates that multicomponent interventions based on behavioural change theories, such as the BCW, theory of planned behaviour, and the socioecological model tend to be more effective [55]. Our results of the systematic review and meta-analysis suggest that interventions based on theories, including organisational strategies or policy components, environmental changes and educational or informational material reported higher SB reductions (-59.2 (95% CI: -74.4, -44.0) and -58.6 (-74.1, -43.1) min/8 h workday) [23, 25], than studies that have not been based on theories (5.4 (95% CI: -12.9, 23.7), -2.17 (95% CI: -63.1, 58.7), and -16.6 (95% CI: -45.0, 11.8) min/8 h workday) [26, 29, 35]. This finding may contribute to a better understanding of what components a behaviour change intervention should include to be effective.

The advancement of wearable technologies has made possible the device-based determination of activities based on body posture. The studies included in the present systematic review mainly reported the time spent in SB using device-based measures, especially through the activPAL device, which showed significant reductions of -31.4 (95% CI: -49.3, -13.5) min/8 h workday. Given the heterogeneity in unit measurement and the lack of data, effectiveness was not compared with other measurement tools, but evidence suggests that thigh-worn devices showed higher levels of accuracy to measure SB compared with wrist-worn devices [56]. Furthermore, self-report tools showed low correlation with device-based data and low precision [57]. A previous meta-analysis showed smaller reductions in time spent in SB for self-reported measures than device-based measures [16], which may be due to difficulties in recalling this behaviour, and therefore the difficulty to recollect the data accurately. These smaller reductions may be likely a result of the measurement method, rather than the intervention.

Strengths and limitations

A key strength of this study is that, to our knowledge, it is the first systematic review that comprehensively assesses how workplace interventions that incorporated digital elements, affect office workers’ SB reductions, who are the most sedentary work sectors. Additionally, it is the first study that quantifies these findings through a meta-analysis and sub-analysis and present a mid-high quality (74.3%) of the included studies. However, the study includes acceptability and feasibility studies, as well as pilot studies presenting small sample sizes, lack of control of confounding and the lack of the assessment of statistically significant changes in the results.

This study has several limitations. One such limitation was the lack of opportunity to assess one intervention, using digital elements in one group and non-digital elements in the other group, to examine the effectiveness of the digital elements in the workplace interventions. The variety in SB unit measurement was a limitation of the current study. We standardised all the data to min/8-h workdays for the meta-analysis. That fact may have influenced our results, given lower reductions since not knowing whether total SB in the studies covered all day or only waking hours, we transformed the data from 24 to 8 h. The lack of data (i.e., mean differences from baseline to postintervention) and the nonresponse from the authors were other limitations for the meta-analysis, as the absence of data resulted in the removal of some studies. Overall, the meta-analysis showed greater heterogeneity (Chi2 = 53.82; I2 = 81%); hence, caution should be taken when interpreting these results.

Future implications

Although the evidence supports the effectiveness of workplace interventions using digital elements in reducing SB in the traditional office setting, the hybrid work model (i.e., work in office and home) has become the customary mode of working for many employees since the COVID-19 pandemic [58]. This new paradigm of work has been associated with even more drastic increases in SB patterns [59, 60]. Therefore, future research should prioritise exploring how these theory-driven digital-based interventions, can be feasible for breaking and limiting SB when working from home. Additionally, it is important to investigate the adoption and maintenance of this behaviour change on employees' health and work performance. Recent evidence has identified digital interventions as complex interventions [20], and it is recommended to involve multiple stakeholders in the development process of these interventions to ensure their effectiveness in future studies [20, 61].


This review provided evidence for the effectiveness of workplace interventions using digital elements to reduce SB among office workers. Our findings indicated an approximate reduction of 30 min per 8-h work day, suggesting that multicomponent interventions incorporating a wide variety of technological features (i.e., information delivery and mediated organisational support and social influences) may be effective approaches to reduce SB in workplaces. Considering the emerging evidence indicating an increase in SB in the hybrid work mode, future studies need to adapt these interventions in the home-office environment to evaluate their feasibility and effectiveness.

Availability of data and materials

All data generated or analysed during this study are included in this published article [and Additional files 1 and 2].



Sedentary Behaviour


Physical Activity


Preferred Reporting Items for Systematic reviews and Meta-Analyses


Randomised Controlled Trial


Population, Intervention, Comparison and Outcomes


Adjusted Mean Differences


Standard Deviations


Confidence Interval


Standard Error


Unadjusted Mean Difference


Global Physical Activity Questionnaire


Workforce Sitting Questionnaire


International Physical Activity Questionnaire


Occupational Sitting and Physical Activity Questionnaire


World Health Organization


Behaviour Change Wheel


  1. Hendriksen IJM, Bernaards CM, Steijn WMP, Hildebrandt VH. Longitudinal relationship between sitting time on a working day and vitality, work performance, presenteeism, and sickness absence. J Occup Environ Med. 2016;58(8):784–9.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Clemes SA, O’Connell SE, Edwardson CL. Office workers’ objectively measured sedentary behavior and physical activity during and outside working hours. J Occup Environ Med. 2014;56(3):298–303.

    Article  PubMed  Google Scholar 

  3. Waters CN, Ling EP, Chu AHY, Ng SHX, Chia A, Lim YW, et al. Assessing and understanding sedentary behaviour in office-based working adults: a mixed-method approach. BMC Public Health. 2016;16:360.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Puig-Ribera A, Martínez-Lemos I, Giné-Garriga M, González-Suárez ÁM, Bort-Roig J, Fortuño J, Muñoz-Ortiz L, McKenna J, Gilson ND. Self-reported sitting time and physical activity: interactive associations with mental well-being and productivity in office employees. BMC Public Health. 2015;15:72.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Oakman J, Kinsman N, Stuckey R, Graham M, Weale V. A rapid review of mental and physical health effects of working at home: how do we optimise health? BMC Public Health. 2020;20(1):1825.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Saunders TJ, McIsaac T, Douillette K, Gaulton N, Hunter S, Rhodes RE, Prince SA, Carson V, Chaput JP, Chastin S, Giangregorio L, Janssen I, Katzmarzyk PT, Kho ME, Poitras VJ, Powell KE, Ross R, Ross-White A, Tremblay MS, Healy GN. Sedentary behaviour and health in adults: an overview of systematic reviews. Appl Physiol Nutr Metab. 2020;45(10 (Suppl. 2)):S197–217.

    Article  PubMed  Google Scholar 

  7. Brown HE, Ryde GC, Gilson ND, Burton NW, Brown WJ. Objectively measured sedentary behavior and physical activity in office employees: relationships with presenteeism. J Occup Environ Med. 2013;55(8):945–53.

    Article  PubMed  Google Scholar 

  8. Muniswamy P, Gorhe V, Parashivakumar L, Chandrasekaran B. Short-term effects of a social media-based intervention on the physical and mental health of remotely working young software professionals: a randomised controlled trial. Appl Psychol Health Well Being. 2022;14(2):537–54.

    Article  PubMed  Google Scholar 

  9. Lin YP, Hong O, Lin CC, Lu SH, Chen MM, Lee KC. A “sit less, walk more” workplace intervention for office workers: long-term efficacy of a quasi-experimental study. J Occup Environ Med. 2018;60(6):e290.

    Article  PubMed  Google Scholar 

  10. Buffey AJ, Herring MP, Langley CK, Donnelly AE, Carson BP. The acute effects of interrupting prolonged sitting time in adults with standing and light-intensity walking on biomarkers of cardiometabolic health in adults: a systematic review and meta-analysis. Sports Med. 2022;52(8):1765–87.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Podrekar N, Kozinc Ž, Šarabon N. The effects of cycle and treadmill desks on work performance and cognitive function in sedentary workers: a review and meta-analysis. Work. 2020;65(3):537–45.

    Article  PubMed  Google Scholar 

  12. Sui W, Smith ST, Fagan MJ, Rollo S, Prapavessis H. The effects of sedentary behaviour interventions on work-related productivity and performance outcomes in real and simulated office work: a systematic review. Appl Ergon. 2019;75:27–73.

    Article  PubMed  Google Scholar 

  13. Commissaris DACM, Könemann R, Hiemstra-van Mastrigt S, Burford EM, Botter J, Douwes M, Ellegast RP. Effects of a standing and three dynamic workstations on computer task performance and cognitive function tests. Appl Ergon. 2014;45(6):1570–8.

    Article  PubMed  Google Scholar 

  14. Ma J, Ma D, Li Z, Kim H. Effects of a workplace sit-stand desk intervention on health and productivity. Int J Environ Res Public Health. 2021;18(21):11604.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Shrestha N, Kukkonen-Harjula KT, Verbeek JH, Ijaz S, Hermans V, Pedisic Z. Workplace interventions for reducing sitting at work. Cochrane Database Syst Rev. 2018;6(6):CD010912.

    PubMed  Google Scholar 

  16. Chu AHY, Ng SHX, Tan CS, Win AM, Koh D, Müller-Riemenschneider F. A systematic review and meta-analysis of workplace intervention strategies to reduce sedentary time in white-collar workers. Obes Rev. 2016;17(5):467–81.

    Article  CAS  PubMed  Google Scholar 

  17. Commissaris DACM, Huysmans MA, Mathiassen SE, Srinivasan D, Koppes LLJ, Hendriksen IJM. Interventions to reduce sedentary behavior and increase physical activity during productive work: a systematic review. Scand J Work Environ Health. 2016;42(3):181–91.

    PubMed  Google Scholar 

  18. Murray E, Hekler EB, Andersson G, Collins LM, Doherty A, Hollis C, et al. Evaluating digital health interventions: key questions and approaches. Am J Prev Med. 2016;51(5):843–51.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Stephenson A, McDonough SM, Murphy MH, Nugent CD, Mair JL. Using computer, mobile and wearable technology enhanced interventions to reduce sedentary behaviour: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14(1):105.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Buckingham SA, Williams AJ, Morrissey K, Price L, Harrison J. Mobile health interventions to promote physical activity and reduce sedentary behaviour in the workplace: a systematic review. Digit Health. 2019;5:2055207619839883.

    PubMed  PubMed Central  Google Scholar 

  21. Huang Y, Benford S, Blake H. Digital interventions to reduce sedentary behaviors of office workers: scoping review. J Med Internet Res. 2019;21(2):e11079.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors. Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane; 2022. Available from

  23. Pereira MA, Mullane SL, Toledo MJL, Larouche ML, Rydell SA, Vuong B, Feltes LH, Mitchell NR, de Brito JN, Hasanaj K, Carlson NG, Gaesser GA, Crespo NC, Oakes JM, Buman MP. Efficacy of the ‘Stand and Move at Work’ multicomponent workplace intervention to reduce sedentary time and improve cardiometabolic risk: a group randomized clinical trial. Int J Behav Nutr Phys Act. 2020;17(1):133.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Edwardson CL, Yates T, Biddle SJH, Davies MJ, Dunstan DW, Esliger DW, Gray LJ, Jackson B, O’Connell SE, Waheed G, Munir F. Effectiveness of the Stand More AT (SMArT) work intervention: cluster randomised controlled trial. BMJ. 2018;363:k3870.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Edwardson CL, Biddle SJH, Clemes SA, Davies MJ, Dunstan DW, Eborall H, Granat MH, Gray LJ, Healy GN, Jaicim NB, Lawton S, Maylor BD, Munir F, Richardson G, Yates T, Clarke-Cornwell AM. Effectiveness of an intervention for reducing sitting time and improving health in office workers: three arm cluster randomised controlled trial. BMJ. 2022;378:e069288.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Maylor BD, Edwardson CL, Zakrzewski-Fruer JK, Champion RB, Bailey DP. Efficacy of a multicomponent intervention to reduce workplace sitting time in office workers: a cluster randomized controlled trial. J Occup Environ Med. 2018;60(9):787–95.

    Article  PubMed  Google Scholar 

  27. O’Dolan C, Grant M, Lawrence M, Dall P. A randomised feasibility study to investigate the impact of education and the addition of prompts on the sedentary behaviour of office workers. Pilot Feasibility Stud. 2018;15:433.

    Google Scholar 

  28. Thogersen-Ntoumani C, Quested E, Smith BS, Nicholas J, McVeigh J, Fenton SAM, Stamatakis E, Parker S, Pereira G, Gucciardi DF, Ntoumanis N. Feasibility and preliminary effects of a peer-led motivationally-embellished workplace walking intervention: a pilot cluster randomized trial (the START trial). Contemp Clin Trials. 2020;91:105969.

    Article  CAS  PubMed  Google Scholar 

  29. Bort-Roig J, Chirveches-Pérez E, Giné-Garriga M, Navarro-Blasco L, Bausà-Peris R, Iturrioz-Rosell P, Gónzalez-Suárez AM, Martínez-Lemos I, Puigoriol-Juvanteny E, Dowd K, Puig-Ribera A. An mHealth workplace-based “sit less, move more” program: impact on employees’ sedentary and physical activity patterns at work and away from work. Int J Environ Res Public Health. 2020;17(23):1–10.

    Article  Google Scholar 

  30. Danquah IH, Kloster S, Holtermann A, Aadahl M, Bauman A, Ersbøll AK, Tolstrup JS. Take a Stand!-A multi-component intervention aimed at reducing sitting time among office workers-a cluster randomized trial. Int J Epidemiol. 2017;46(1):128–40.

    CAS  PubMed  Google Scholar 

  31. De Cocker K, De Bourdeaudhuij I, Cardon G, Vandelanotte C. What are the working mechanisms of a web-based workplace sitting intervention targeting psychosocial factors and action planning? BMC Public Health. 2017;17(3):382.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Mamede A, Noordzij G, Jongerling J, Snijders M, Schop-Etman A, Denktas S. Combining web-based gamification and physical nudges with an app (MoveMore) to promote walking breaks and reduce sedentary behavior of office workers: field study. JJ Med Internet Res. 2021;23(4):e19875.

    Article  Google Scholar 

  33. Blake H, Lai B, Coman E, Houdmont J, Griffiths A. Move-It: a cluster-randomised digital worksite exercise intervention in China: outcome and process evaluation. Int J Environ Res Public Health. 2019;16(18):3451.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Blake H, Suggs LS, Coman E, Aguirre L, Batt ME. Active8! technology-based intervention to promote physical activity in hospital employees. Am J Health Promot. 2017;31(2):109–18.

    Article  PubMed  Google Scholar 

  35. Martin A, Adams JM, Bunn C, Gill JMR, Gray CM, Hunt K, et al. Feasibility of a real-time self-monitoring device for sitting less and moving more: a randomised controlled trial. BMJ Open Sport Exerc Med. 2017;3(1):e000285.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Invernizzi PL, Signorini G, Scurati R, Michielon G, Benedini S, Bosio A, Staiano W. The UP150: a multifactorial environmental intervention to promote employee physical and mental well-being. Int J Environ Res Public Health. 2022;19(3):1175.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Rollo S, Prapavessis H. A combined health action process approach and mHealth intervention to reduce workplace sitting time in office-working adults: a secondary analysis examining health-related quality of life and work performance outcomes. Appl Psychol Health Well Being. 2020;12(3):660–86.

    Article  PubMed  Google Scholar 

  38. Carter SE, Draijer R, Maxwell JD, Morris AS, Pedersen SJ, Graves LEF, Thijssen DHJ, Hopkins ND. Using an e-Health intervention to reduce prolonged sitting in UK office workers: a randomised acceptability and feasibility study. Int J Environ Res Public Health. 2020;17(23):8942.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Nicolson GH, Hayes CB, Darker CD. A cluster-randomised crossover pilot feasibility study of a multicomponent intervention to reduce occupational sedentary behaviour in professional male employees. Int J Environ Res Public Health. 2021;18(17):9292.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Morris AS, Murphy RC, Shepherd SO, Healy GN, Edwardson CL, Graves LEF. A multi-component intervention to sit less and move more in a contact centre setting: a feasibility study. BMC Public Health. 2019;19(1):292.41.

    Article  Google Scholar 

  41. Engelen L, Drayton BA, Young S, Daley M, Milton K, Bauman A, et al. Impact and process evaluation of a co-designed «Move More, Sit Less» intervention in a public sector workplace. Work. 2019;64(3):587–99.

    Article  PubMed  Google Scholar 

  42. Zhou L, Deng X, Guo K, Hou L, Hui X, Wu Y, et al. Effectiveness of multicomponent interventions in office-based workers to mitigate occupational sedentary behavior: systematic review and meta-analysis. JMIR Public Health Surveill. 2023;9:e44745.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Saleh ZT, Lennie TA, Mudd-Martin G, Bailey AL, Novak MJ, Biddle M, Khalil AA, Darawad M, Moser DK. Decreasing sedentary behavior by 30 minutes per day reduces cardiovascular disease risk factors in rural Americans. Heart Lung. 2015;44(5):382–6.

    Article  PubMed  Google Scholar 

  44. Hergenroeder A, Quinn TD, Perdomo SJ, Kline CE, Gibbs BB. Effect of a 6-month sedentary behavior reduction intervention on well-being and workplace health in desk workers with low back pain. Work. 2022;71(4):1145–55.

    Article  PubMed  Google Scholar 

  45. Diaz KM, Duran AT, Colabianchi N, Judd SE, Howard VJ, Hooker SP. Potential effects on mortality of replacing sedentary time with short sedentary bouts or physical activity: a national cohort study. Am J Epidemiol. 2019;188(3):537–44.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Camhi SM, Sisson SB, Johnson WD, Katzmarzyk PT, Tudor-Locke C. Accelerometer-determined moderate intensity lifestyle activity and cardiometabolic health. Prev Med. 2011;52(5):358–60.

    Article  PubMed  Google Scholar 

  47. World Health Organization. WHO guidelines on physical activity and sedentary behaviour. Geneva: World Health Organization; 2020. Licencia: CC BY-NC-SA 3.0 IGO.

  48. Welch A, Healy G, Straker L, Comans T, O’Leary S, Melloh M, Sjøgaard G, Pereira M, Chen X, Johnston V. Process evaluation of a workplace-based health promotion and exercise cluster-randomised trial to increase productivity and reduce neck pain in office workers: a RE-AIM approach. BMC Public Health. 2020;20(1):180.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Nakphet N, Chaikumarn M, Janwantanakul P. Effect of different types of rest-break interventions on neck and shoulder muscle activity, perceived discomfort and productivity in symptomatic VDU operators: a randomized controlled trial. Int J Occup Saf Ergon. 2014;20(2):339–53.

    Article  PubMed  Google Scholar 

  50. Sullivan AN, Lachman ME. Behavior change with fitness technology in sedentary adults: a review of the evidence for increasing physical activity. Front Public Health. 2017;4:289.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Edwardson CL, Abell L, Clarke-Cornwell A, Dunstan DW, Gray LJ, Healy GN, et al. Implementation and engagement of the SMART work & life sitting reduction intervention: an exploratory analysis on intervention effectiveness. Int J Behav Nutr Phys Act. 2023;20(1):148.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Riddell MF, Callaghan JP. Ergonomics training coupled with new Sit-Stand workstation implementation influences usage. Ergonomics. 2021;64(5):582–92.

    Article  PubMed  Google Scholar 

  53. Dempsey PC, Biddle SJH, Buman MP, Chastin S, Ekelund U, Friedenreich CM, et al. New global guidelines on sedentary behaviour and health for adults: broadening the behavioural targets. Int J Behav Nutr Phys Act. 2020;17(1):151.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Stamatakis E, Ekelund U, Ding D, Hamer M, Bauman AE, Lee IM. Is the time right for quantitative public health guidelines on sitting? A narrative review of sedentary behaviour research paradigms and findings. Br J Sports Med. 2019;53(6):377–82.

    Article  PubMed  Google Scholar 

  55. Taylor N, Conner M, Lawton R. The impact of theory on the effectiveness of worksite physical activity interventions: a meta-analysis and meta-regression. Health Psychol Rev. 2012;6(1):33–73.

    Article  Google Scholar 

  56. Montoye AHK, Pivarnik JM, Mudd LM, Biswas S, Pfeiffer KA. Validation and comparison of accelerometers worn on the hip, thigh, and wrists for measuring physical activity and sedentary behavior. AIMS Public Health. 2016;3(2):298–312.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Chastin SFM, Dontje ML, Skelton DA, Čukić I, Shaw RJ, Gill JMR, Greig CA, Gale CR, Deary IJ, Der G, Dall PM, Seniors USP team. Systematic comparative validation of self-report measures of sedentary time against an objective measure of postural sitting (activPAL). Int J Behav Nutr Phys Act. 2018;15(1):21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Gilson N, Coenen P, Hallman D, Holtermann A, Mathiassen SE, Straker L. Postpandemic hybrid work: opportunities and challenges for physical activity and public health. Br J Sports Med. 2022;56(21):1203–4.

    Article  PubMed  Google Scholar 

  59. Fukushima N, Machida M, Kikuchi H, Amagasa S, Hayashi T, Odagiri Y, et al. Associations of working from home with occupational physical activity and sedentary behavior under the COVID-19 pandemic. J Occup Health. 2021;63(1):e12212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Loef B, van Oostrom SH, van der Noordt M, Proper KI. Working from home during the COVID-19 pandemic and its longitudinal association with physical activity and sedentary behavior. Scand J Work Environ Health. 2022;48(5):380–90.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Dugstad J, Eide T, Nilsen ER, Eide H. Towards successful digital transformation through co-creation: a longitudinal study of a four-year implementation of digital monitoring technology in residential care for persons with dementia. BMC Health Serv Res. 2019;19:1–7.

    Article  Google Scholar 

Download references


Not applicable.


This research was funded by the Cooperation Partnerships Programme of the European Commission (101050490 – ERASMUS-SPORT-2021-SCP).

Author information

Authors and Affiliations



IPS screened the full texts for studies selection AND extracted the data of the included studies AND completed the checklist of the risk of bias assessment of all the included papers AND calculated their score AND developed the data analysis AND wrote the paper. ASM prepared the protocol of the research AND participated in the first part of the studies selection (title and abstract) AND revised the paper. FMB conducted the studies selection (screening titles, abstracts, and full texts). BL participated in the data analysis AND substantively revised the different versions of the paper. AC completed the checklist of the risk of bias assessment of all the included papers. KD conceptualized the review AND participated in the risk of bias assessment in case of disagreement AND revised the paper. GJC participated in the data analysis AND substantively revised the methods and results of the paper. KP conceptualized the review AND participated in the data analysis AND revised the paper. APR conceptualized the review AND prepared the protocol of the research AND revised the paper. JBR conceptualized of the review AND prepared the protocol of the research AND participated in the discussion of disagreements for studies selection (title, abstract, and full text) AND reviewed the data extraction AND participated in the risk of bias assessment in case of disagreements AND substantively revised the different versions of the paper. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Anna M. Señé-Mir.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no known competing financial interests or personal relationships that could influence the work reported in this article.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

Leave-one-out. The document shows the influence of each study on the overall effect-size estimate trough figures excluding every time one study.

Additional file 2.

Risk of bias assessment. The file shows on the first page the completed checklist of the QUALSYST for each study included in the systematic review. On the second page, the file presents the score of every item.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Parés-Salomón, I., Señé-Mir, A.M., Martín-Bozas, F. et al. Effectiveness of workplace interventions with digital elements to reduce sedentary behaviours in office employees: a systematic review and meta-analysis. Int J Behav Nutr Phys Act 21, 41 (2024).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: