SMART STEP – SMARTphone-driven exercise and pedometer-based STEP intervention to promote physical activity among desk-based employees: Study protocol for a three-arm cluster randomized controlled trial

Abstract

BACKGROUND:

Prolonged sitting in desk-based office workers is found to be associated with increased cardiometabolic risk and poor cognitive performance. Technology-based physical activity (PA) interventions using smartphone applications (SmPh app) to promote PA levels might be effective in reducing cardiometabolic risk among sedentary population but the evidence remains inconclusive.

OBJECTIVE:

The objective is to investigate the effects of a technology-based PA intervention compared to PA education with a worksite manual or no intervention on PA levels, cardiometabolic risk, cognitive performance, and work productivity among desk-based employees.

METHOD:

A three-arm clustered randomized trial will be conducted. The study will be conducted among various administrative offices of a multifaceted university in India. Desk-based employees aged between 30 and 50 years (n = 159; 53 in each arm) will be recruited. Employees from various constituent institutions (clusters) of the university will be randomized into one of the three following groups - SMART: SmPh app-driven break reminders (visual exercise prompts) plus pedometer-based step intervention, TRADE: worksite PA education with a manual plus American College of Sports Medicine guided PA prescription, or CONTROL: usual work group. At baseline and after the 1st, 3rd and 6th month of the trial period, accelerometer-measured sitting time and PA levels, cardiometabolic risk (fasting blood glucose, triglycerides, insulin, blood pressure, heart rate variability, functional capacity, and subcutaneous fat), cognitive performance (executive function), sickness absenteeism and work limitations will be assessed by a blinded assessor. Therapist delivering interventions will not be blinded.

CONCLUSION:

This trial will determine whether a combined SmPh-app and pedometer-based intervention is more effective than education or no intervention in altering PA levels, cardiometabolic risk and cognitive performance among desk-based employees in India. This study has the potential to foster institutional recommendations for using SmPh-based technology and pedometers to promote PA and reduce sedentary behavior at work.

Keywords

M-health physical activity office workers worksite education cardiometabolic risk cognition work productivity musculoskeletal discomfort

1 Introduction

Due to industrialization and subsequent computerization of work in recent years, office employees spend 65%–75% of their wake hours by sitting at the office and home [1 –3]. Desk-based employees sit 77% of their (work) time accrued in prolonged bouts of >30 minutes [4]. Sedentary behavior, including uninterrupted sitting, is associated with increased cardiometabolic disease risk and reduced cognitive performance of individuals at office settings [5, 6]. Moreover, continuous sitting at work is related to work limitation and decreased productivity [7]. Impaired physiological function and cognitive performance, and musculoskeletal discomfort would lead to sickness absenteeism at work [8]. Reducing sedentary behavior by breaking sitting or promoting physical activity may be hypothesized to reverse the physiological derangements, and thereby improve work productivity and sickness presenteeism [9].

A qualitative study revealed that employees and their supervisors perceived a simple 10-minute physical activity break (using videos) to be feasible and enjoyable during their working hours [10]. A field-based randomized controlled trial (RCT) found that desk-based employees engaged in short-burst physical activities and increased their energy expenditure when passively prompted with a software installed in their desktop computers [11]. In fact, a systematic review by Bennati et al. concluded that acute breaks in sitting either through standing or low-intensity exercises, lowered postprandial glucose (by 43%) and improved stepping time (by 1–1.5 hours). However, they recommended that future trials need to objectively quantify the breaks (frequency and duration) to counteract the detrimental effects of prolonged sitting [5].

A pedometer-driven increase in step count has been recommended along with break reminders to improve physical activity (PA) among different populations, including office employees [12]. In a Spanish worksite wellness randomized trial, web-based break reminders and a pedometer-based step intervention improved step count by 446 (±126) steps compared to active control (pedometer alone) group that had a reduction in step count by 388 (±120) steps following a five-month intervention period. Even so, the study did not investigate the effects of the intervention on any cardiometabolic disease risk factors [12]. Significant compliance with a gradual increase in step count to achieve 10,000 steps over 7–8 weeks was found in sedentary desk-based employees when pedometers were used [12, 13].

Although pedometer-driven PA and e-health interventions are in practice, smartphone (SmPh) based interventions to promote PA have gained attention in the recent years [14 –16]. SmPh-based exercise programs have been found to reduce cardiometabolic disease risk in a sedentary population, and promote compliance to the PA in office employees and healthy individuals [17, 18]. An RCT has found an increase in low-to-moderate activity (by 22.8 to 26.7%) and moderate-to-vigorous activity (by 5 to 7%) in obese subjects when SmPh-app directed break reminders were administered via three counterbalanced approaches’ (3 minutes break for every 30 minutes, 6 minutes for every 60 minutes, and 12 minutes for every 120 minutes of sedentary time) [16]. In a recent systematic review, 14 of 25 included studies (60%) found that SmPh-apps improve PA and reduce sedentary time [19]. However, another systematic review found that active workstations (treadmill or cycle desks) improved recall abilities and affected work performance but did not improve the findings of selective attention tests [20]. There is a need for more robust RCTs to substantiate the beneficial effects of the SmPh-based interventions to improve PA levels, work performance, and cognitive function [21].

The theory of planned behavior elaborates the impact of behavioral change after a sedentary behavior intervention [22]. Action planning and coping strategies are crucial for inducing behavioral change and addressing long-term compliance with the interventions [23]. It is essential to monitor behavioral change in desk-based employees receiving the interventions to break sedentary behavior and, at the same time, assess their long-term compliance to such interventions [22].

To our knowledge, there are barely any studies investigating the effects of a technology-assisted PA program (a combination of SmPh app-based break reminders and a pedometer-driven step-based intervention) compared to a traditional exercise program or no intervention on sitting time, PA levels, cardiometabolic disease risk, cognitive performance and work productivity among desk-based employees in low-middle income countries.

1.1 Primary and secondary objectives

The primary objective is to compare the effects of combined SmPh-based break reminders (with audio-visual prompts demonstrating exercises) and pedometer-based step intervention (SMART group), a traditional exercise program (TRADE group), and uninterrupted sitting (CONTROL group) on 1) prolonged sitting time (>30 minutes continuous bouts) per day during weekdays at work, 2) total daily sitting time in minutes, 3) total stepping time, and 4) total step count (cpm). The secondary objective is to compare the SMART, TRADE, and CONTROL groups for changes in cardiometabolic disease risk factors (fasting blood glucose [FBG], triglycerides, blood pressure [BP], heart rate variability [HRV], functional capacity [VO2 max], and body fat percentage), cognitive performance (attention and episodic memory), work productivity, musculoskeletal symptoms and sickness absenteeism among desk-based employees; in addition, behavior change associated with the interventions and maintenance over time will be investigated only for the SMART and TRADE groups.

2 Methods

The protocol is written according to the guidelines of SPIRIT 2013 guidelines and TiDieR checklist (Supplementary Tables 1 and 2). Table 1 provides an overview of randomization, intervention, and outcome measurement.

Table 1
Schedule for allocation and intervention based on the SPIRIT 2013 checklist

Enrolment Allocation Intervention period Close-out

TIMEPOINT -t₁ t₀ t_{1 (1st month)} t_{2 (3rd month)} t_{3 (6th month)} t_{x (2 weeks)}

ENROLMENT: X

Eligibility screen X

Informed consent/Familiarization X

Allocation X

INTERVENTIONS:

SMART ⟸ ⇒

TRADE ⟸ ⇒

CONTROL

Assessments Baseline Anthropometry X

Sitting time, step count, prolonged sitting X

Biochemistry - FBG, HOMA-IR, LDL X

Blood pressure X

Heart rate variability X

Maximal aerobic capacity X

Cognitive performance –attention, memory X

Musculoskeletal discomfort X

Work productivity and limitation X

Sickness presenteeism X

Outcome Measures Anthropometry X X X

Sitting time, step count, prolonged sitting bout X X X

Biochemistry - FBG, HOMA-IR, LDL X X X

Blood pressure X X X

Heart rate variability X X X

Maximal aerobic capacity X X X

Cognitive performance –attention, memory X X X

Musculoskeletal discomfort X X X

Work productivity and limitation X X X

Sickness presenteeism X X X

Behavioral change and coping strategy X X X

Preference to the intervention X X X

			Allocation	Intervention period	Close-out
ENROLMENT:	X
Eligibility screen	X
Informed consent/Familiarization	X
Allocation		X
INTERVENTIONS:
SMART		⟸ ⇒
TRADE		⟸ ⇒
CONTROL
Assessments	Baseline	Anthropometry	X
		Sitting time, step count, prolonged sitting	X
		Biochemistry - FBG, HOMA-IR, LDL	X
		Blood pressure	X
		Heart rate variability	X
		Maximal aerobic capacity	X
		Cognitive performance –attention, memory	X
		Musculoskeletal discomfort	X
		Work productivity and limitation	X
		Sickness presenteeism	X
	Outcome Measures	Anthropometry		X	X	X
		Sitting time, step count, prolonged sitting bout		X	X	X
		Biochemistry - FBG, HOMA-IR, LDL		X	X	X
		Blood pressure		X	X	X
		Heart rate variability		X	X	X
		Maximal aerobic capacity		X	X	X
		Cognitive performance –attention, memory		X	X	X
		Musculoskeletal discomfort		X	X	X
		Work productivity and limitation		X	X	X
		Sickness presenteeism		X	X	X
		Behavioral change and coping strategy			X	X	X
		Preference to the intervention			X	X	X

CONTROL –group that will continue their usual work; FBG –Fasting blood glucose; HOMA-IR - Homeostatic Model Assessment of Insulin Resistance; LDL –Low density lipoproteins; SMART –Intervention group receiving smartphone-driven exercise break reminders and pedometer-based step intervention; TRADE –intervention group receiving worksite exercise education and American College of Sports Medicine guided physical activity prescription; -t1 –period specifying enrollment period; t0–time of allocation or immediately before intervention; t1–end of 1st month of the trial period; t2 –end of 3rd month of the trial period; t3 –end of 6th month of the trial period; tx –at the two weeks after the 6 months trail period.

2.1 Study design

Our study is a three-arm cluster RCT. The constituent institutions (communication, management, technology, dental, allied health, and medicine) with desk-based employees across a large University, Manipal Academy of Higher Education (Karnataka, India) will be identified as potential clusters after seeking necessary permissions from the administrators of the institutions. Departments will be matched based on size and work nature, and randomized into one of the three groups after baseline measurements. Follow-up measurements will be done at one month, three months and six months after baseline measurements. The flow of the participants through the study is illustrated in the CONSORT flow diagram (Fig. 1).

Fig. 1

CONSORT flow diagram of the cluster randomized controlled trial.

2.2 Sample size

The sample size for this cluster randomised controlled trial is based on recent recommendations by Daniel Ribeiro et al. [24]. Sample Size_cluster _RCT = Sample Size_standardRCT×Design effect (DE _{Unequalclustersize}) where the design effect specific to variance in the cluster sample is calculated from $D E_{unequal} = 1 + [(1 + cv 2) + \bar{x} - 1] ρ$ . We assumed a ρ of 0.5 and a cv of 0.05 based on an earlier cluster RCT (SMArT Work trial) [6] and estimated design effect to be 1.136. Thirty-two desk-based employees per intervention arm will be needed to reduce daily sitting time at 3 and 6 months by at least 37 minutes/day (with an effect size of 0.43) and standard deviation of 32 min at a power of 80% and a significance level of 95%. Accounting for a 30% dropout $[n * = \frac{n}{1 - dropout}]$ and skewed outcome data, 53 employees per each intervention arm would be needed. Hence, the total sample size estimated for three groups (SMART, TRADE and CONTROL) will be 159 employees.

2.3 Instrumental procedure

The study will be executed in two phases: 1) SmPh-app and worksite manual development and 2) administration of three-arm cluster RCT.

2.3.1 SmPh-app development

An app compatible with the SmPh will be custom-developed to incorporate the following features: a break reminder every one hour for two minutes with exercise videos demonstrating six strengthening and six stretching exercises (Supplementary Table 3) appearing in a randomized order [25]. The exercises will be administered based on frequency, duration, and type of exercise (FITT) principle: a strengthening exercise of one muscle for 3 seconds/repetition, ten repetitions for one set, two set/hour, for leg curls and hip raises two sets of strengthening sets will be done ten repetitions per side (left and right) and a stretching exercise of one muscle for 15 seconds/repetition, two repetitions/set for one side during work time.

The app development process consists of 1) deciding on the specifications with the developer, 2) selecting the appropriate platform (Android), 3) creating the design, and 4) testing the prototype. The specifications of the SmPh application are specified in the later part of the proposal. The app is developed on the JAVA platform and easily saved as an .apk file. The SmPh-app is compatible with all the android processors (version 4.0 and above) and will run both offline and online for data synchronization. The data will be stored offline and server protected by a password accessible only by the investigators.

2.3.2 Worksite physical activity education

The manual being developed will consist of three modules: 1) the ill-effects of sitting, 2) the benefits of breaking sitting on sedentarism, cardiometabolic disease risk and cognition, and 3) the exercises recommended during work: six strengthening and six stretching exercises (Supplementary Table 3; Reproduced after obtaining permission from Taylor & Francis Group for the author’s work: Patel AK, Banga C, Chandrasekaran B. Effect of an education-based workplace intervention (move in office with education) on sedentary behaviour and well-being in desk-based workers: a cluster randomized controlled trial. Int J Occup Saf Ergon. 2021 May 18:1-9. doi: 10.1080/10803548.2021.1916221) similar to the SmPh app focusing on two minutes of exercise every hour. The participants will be requested to do the six body-supported strengthening exercises, and self-stretching exercises durng their work hours as shown in the illustrated handouts of the worksite manual.

2.4 Participants

Potential desk-based employees aged between 30 and 50 years will be recruited through adverts (posters and flyers) placed on the university notice boards, word of mouth, and emails after necessary permissions are sought from the corresponding authorities in the respective institutional clusters. To promote the study to the university employees, we will set up advertisement standees and a desk manned by the primary investigator (BC) in the institution for a week duration during lunchtime. Those who are interested will be provided with the information leaflet and will be screened for eligibility criteria as specified in Table 2.

Table 2
Eligibility criteria for recruiting desk-based employees

Inclusion criteria Exculsion criteria

•Permanent day shift desk-based employees (office secretaries) •Any pre-existing musculoskeletal injury or disorder

•Both genders •Pregnancy

•Age 30–50 years •Known coronary artery disease (CAD)

•Full-time desk-based job •Unstable metabolic disorders

•Not going on for any planned leave for more than 6 months or planning to shift the work •Any surgeries < 8 weeks

•Self reporting a sitting time more than 6 hrs/day [34] •Acute systemic illness

•At least 2 bouts of 60 minutes of uninterrupted sitting [35] •Diabetes mellitus (diagnosed with a fasting blood glucose value of >125 mg/dL), hypertensive (diagnosed with a pressure of 130/89)

•Physically less active as determined through the International Physical Activity Questionnaire (IPAQ)-short-form with a score < 600 metabolic equivalents (MET) minutes/week will be recruited. •psychological disorders/cognitive impairments

•The participants to be recruited in the SMART group must have the knowledge of handling a SmPh with an android version 4.0 and above (compatible with the Google play store) •Currently taking medications such as cardiac depressants or stimulants

•Participants in all three groups should be willing to undergo blood investigations (FBG and lipids) •Planning to quit or shift the job in the next six months

•Participants in all three groups need to be willing to wear a triaxial accelerometer (Activpal 3^™, PAL technologies, Glasgow, UK) on the thigh for 7 consecutive days •Those who are contraindicated for moderate-vigorous PA (MVPA)

Inclusion criteria	Exculsion criteria
•Permanent day shift desk-based employees (office secretaries)	•Any pre-existing musculoskeletal injury or disorder
•Both genders	•Pregnancy
•Age 30–50 years	•Known coronary artery disease (CAD)
•Full-time desk-based job	•Unstable metabolic disorders
•Not going on for any planned leave for more than 6 months or planning to shift the work	•Any surgeries < 8 weeks
•Self reporting a sitting time more than 6 hrs/day [34]	•Acute systemic illness
•At least 2 bouts of 60 minutes of uninterrupted sitting [35]	•Diabetes mellitus (diagnosed with a fasting blood glucose value of >125 mg/dL), hypertensive (diagnosed with a pressure of 130/89)
•Physically less active as determined through the International Physical Activity Questionnaire (IPAQ)-short-form with a score < 600 metabolic equivalents (MET) minutes/week will be recruited.	•psychological disorders/cognitive impairments
•The participants to be recruited in the SMART group must have the knowledge of handling a SmPh with an android version 4.0 and above (compatible with the Google play store)	•Currently taking medications such as cardiac depressants or stimulants
•Participants in all three groups should be willing to undergo blood investigations (FBG and lipids)	•Planning to quit or shift the job in the next six months
•Participants in all three groups need to be willing to wear a triaxial accelerometer (Activpal 3^™, PAL technologies, Glasgow, UK) on the thigh for 7 consecutive days	•Those who are contraindicated for moderate-vigorous PA (MVPA)

2.5 Randomization and allocation

Randomization will be done at an institutional level (15 institutions) to minimize the risk of contamination of interventions between groups (Supplementary Figure 1). A statistician, blinded to the study protocol, will perform a computer-generated randomization (including random permuted blocks of varying sizes to account for the number of desk-based employees <10, 10–30 and >30 in institutions) and prepare sequentially numbered, opaque, sealed envelopes to conceal allocation. One of the coinvestigators other than primary investigator (CR) will open the sealed envelope to reveal the assignment for each cluster.

The various constituent institutions (clusters) of the university will be randomized into three groups: 1) SMART group, 2) TRADE group and 3) CONTROL group. Possible contamination of intervention will be avoided as much as possible (e.g. employees need to refrain from discussing about interventions with other departments). The result of the randomization will not be shared with any of the heads of institutions as this may bias the intervention results.

2.6 Blinding

Since the baseline assessment of PA levels, cardiometabolic risk factors and cognitive functions will take place before randomization, participants will not be aware of group allocation at baseline. An independent researcher will randomize clusters to intervention arms. Outcome assessor will be blinded to group allocation and interventions.

2.7 Procedure

A research graduate assistant, blinded to the interventions will assess the employees of the three groups before, during and after intervention for the following outcome measures: prolonged uninterpreted sitting time >30 minutes, PA levels (step count, step time, energy expenditure (Kcal), MVPA levels, cardiometabolic disease risk (FBG, triglycerides, insulin, heart rate variability, resting BP and maximal aerobic capacity [VO_2max]), and cognitive performance (simple reaction times, response inhibition and memory). The details of the outcome measures are explained in Table 3. All desk-based employees will be given an information brochure recommending a regular healthy diet of 2200–2300 Kcal (based on dietary guidelines for Indians) [26] and the recommended calorie diet will be based on the patient’s choice of food. The overall experimental design is depicted in Fig. 2.

Table 3
Outcome measures assessed at the baseline and follow-up time-points during the trial

Outcome variable Outcome variable Instrument Procedure Psychometric properties Special considerations

Primary outcome measure

Physical activity and sedentary levels •Prolonged sitting time (>30 minutes continuous) in minutes Triaxial accelerometer – activPAL^™ (PAL technologies, Glasgow, UK) or Fibion® (Fibion Inc, Jyväskylä, Finland) Sedentary time (including sitting time), light PA and MVPA during work and leisure hours will be monitored continuously throughout for seven days. Accelerometer will be attached to volunteer’s anterior midline of the right thigh, halfway between the hip and knee joints by a hypoallergic waterproof adhesive tape. The data files will be imported to data analysis software or manufacturer’s website and data will be processed. •Accuracy: 96.2% in 18–60 years •] The PA levels can be classified as].

•Sitting time/day (mins) ICC: 0.96 [95% CI:0.8–0.9] [36 •‘Active’ (≥1 hour of MVPA per day)

•Total sitting time (mins) •‘Moderately active’ (30–59 min of MVPA per day)

•Average sitting time/day (mins) •‘Inactive’ (<30 min of MVPA per day) and energy expenditure in METs will be quantified [37

•Average energy expenditure/week (KCal)

•Total stepping time (mins)

•Standing time (mins)

Secondary outcome measures

Cardiometabolic risk factors Blood biochemistry: Insulin enzyme linked immunosorbent assay (Insulin-ELISA) kit [Cryochem, USA] [39] Fasting blood samples will be collected in blood collection tubes at the worksite by an experienced phlebotomist in aminopolycarboxylic acid (EDTA) filled tubes and immediately transferred to NABL accredited central laboratory at the University Hospital, India and analysed by insulin enzyme linked immunosorbent assay (Insulin-ELISA) kit [Cryochem, USA] [39] Accuracy: 85.3% in healthy population [40] Desk-based workers will be requested in fasting state for 12 hours prior to the lab investigations. FBG < 125 mg/dL will be an inclusion criterion.

•Fasting Blood Glucose (FBG),

•Fasting insulin levels,

•Homeostatic model

•Insulin resistance (HOMA–IR; plasma glucose [mg/dL]×insulin [IRI; μU/L] ÷ 405) [38].

•Low-density lipoproteins

•High-density lipoproteins

•Triglycerides

Heart rate variability (HRV): Polar H7 (Sensor), Polar-V800 (emitter) watch and Kubios software (MATLABS, MathWorks, Natick, Massachusetts, USA) A Polar H7 sensor (Polar Electro Oy, Kempele, Finland) will be secured to the chest and heart rate variability in the supine lying position will be taken for 10 minutes. The 10 minutes beat-beat RR interval.csv files from the Polar-V800 (emitter) watch will be transferred to the Kubios software (MATLABS, MathWorks, Natick, Massachusetts, USA) as Polar.hrm files. Identical 256-segment RR interval will be selected and analyzed for the time (SDNN, RMSSD, NN50, pNN50), frequency domain (VLF, LF, HF, LF/HF index) and non-linear components (SD₁, SD₂, SD₁/SD₂) analyses •Intraclass correlation (ICC) of time domain > 0.99 (95% CI: 0.86–0.99) with a small standard error mean (0.086%) in young athletes [41] Person should arrive 30 minutes earlier to the test and will be asked to rest for next 30 minutes. Last 10 minutes, HRV will be measured.

•Time (SDNN, RMSSD, NN50, pNN50) •Concurrent validity of SDNN, pNN50 is high (r≥0.96 with SEM less than 1 ms) when compared to Polar V800 with Holter monitor in measuring heartrate variability [42]

•Frequency domain (VLF, LF, HF, LF/HF index) and non-linear components (SD₁, SD₂, SD₁/SD₂) analyses

Ambulatory blood pressure (mmHg) Aneroid sphyghmanometer (Diamond, India) •Measurement will be standardised according to the recommendations of European Health Examination Survey (EHES) [43] A recent study by Climie et al. revealed a strong intra-test (ICC 0.97; 95 CIs 0.84–0.99) and inter-test reliability (ICC 0.89) for BP measurement using the auscultatory method [44] Mean BP, systolic and diastolic BP and rate pressure product will be estimated from the pressure measured

•BP will be measured thrice with one minute interval between trials from the right arm in the sitting posture

•The desk-based employees will be sitting in the chair with their back supported and their feet placed firmly on the floor

•The aneroid sphyghmanometer, used for BP measurement, will be calibrated every month at the Department of Biomedical Engineering (MAHE, India) for near 2 mmHg accuracy. The highest of three readings will be considered for the analysis

•The cuff selection and positioning of the arm will be standardised, and the auscultatory method will be followed for measuring BP (Littmann, USA)

•Maximal aerobic capacity (VO2 max) ml/kg/min Portable calorimeter (K5, COSMED, Italy) and a treadmill ergometer (h/p/Cosmos, Quasar, Germany) •The employees will be administered treadmill-based exercise testing (using the modified Bruce Protocol) comprising of 2.7 kmh^-1 at 0%, 5% and 10% inclination levels, 4 kmh^-1 at 12% inclination level, and 5.5 kmh^-1 at 14% inclination level for 3 minutes at every stage •Excellent intra- and inter-rater reliability (ICCs > 0.99) at 95% confidence intervals) [45] The volunteers will be familiarized with the treadmill protocol one week before the baseline measurement. Prerequisites of exercise testing shall be strictly followed as per ACSM standards

•Peak aerobic capacity (VO₂ max) will be quantified through the portable telemetric calorimeter. Variables such as maximal oxygen consumption (VO₂ max), METs, ventilatory equivalents of carbon dioxide and oxygen (V_E/VCO₂, VE/VO₂), anaerobic threshold, work pulse (ΔHR), minute ventilation (V_E) and peak heart rate will be measured

•The portable telemetric calorimeter will be calibrated for flow, reference gas (cylinder of 16% oxygen and 0.08% carbon dioxide) and delay as per the manufacturer guidelines (COSMED, Italy 2013)

•Body fat percentage (%) Lange skinfold calliper (Beta Technology Inc., Cambridge, MA) •The subcutaneous body fat is calculated by measuring skinfold thickness at four sites (triceps, infrascapular, suprailiac and mid-thigh regions) [46] using a Lange skinfold calliper (Beta Technology Inc., Cambridge, MA) by an assessor experienced in skinfold measurements (a postgraduate in exercise science) blinded to the interventions •The root mean square error (RMSE), related to interrater reliability, for the calculation of subcutaneous fat percentage has been found to be 4.6% [46] Subcutaneous fat measurement by skin fold will be standardized as per the manufacturer standards and earlier guidelines [46]

•Body fat percentage (% BF) will be estimated from the sum of four skinfolds with following gender specific equations as designed by Peterson et al. [46].

Cognitive performance •Response inhibition (ms) The stimulus presentation by Eriksen Flanker Paradigm and response registration are controlled by Inquisit 2.0 (Millisecond, Seattle, USA) •The participants will be presented with 40 sets of trial arrays with each trial having a congruent (↑↑↑ ↑↑ or ↓↓↓ ↓↓) and a non-congruent “flanker” stimuli ↓↓ ↑ ↓↓ or ↑↑ ↓ ↑↑) at an inter-stimulus interval of 2000 ms and a rest period of 1500 ms between the array sets •Excellent ICC (95 CIs: 0.81–0.94) for the Eriksen flanker task to pick error-related negativity (ERN) in the employees [47] The tests will be administered during the earliest part of the day before beginning their day’s work. The tests will be repeated after one month, third and sixth month of the trial

•Amongst congruent or non-congruent flankers, the employees will be required to press the button to the direction of centrally presented target arrow through the Eriksen flanker paradigm with controlled stimulus presentation of ↓↓ ↑ ↓↓ or ↑↑ ↓ ↑↑ through mouse computer interaction (Intel 64-bit processor, HP, USA) as shown in Fig. 3 •Correlation of conflict monitoring performance of Simon task to Eriksen Flanker using Inquisit software is 0.49 [48]

•The up and down flanker stimuli will be presented in 500 ms difference and the employee will be asked to press the target stimulus in the centre amidst of the flankers presented

•The reaction times (ms) or the latency for reaction will be measured and logged for the correct and non-correct flanker responses

Dietary intake •Daily calorie intake (Kcal) •“Track –Calorie Counter” SmPh-app (Nutritionix, Washington DC, USA) [49] •Both south and north Indian food calorie estimates are fed in the software by each employee and weekly/daily average calorie intake will be assessed •Nutritionix app is found to be moderately valid across the globe [50] compared to Edamam and Yummly SmPh app [50] but at present Indian data are not available Desk-based office workers included will install this application and they will be familiarized to enter the daily diet intake for next 7 days

•Customized to estimate calories associated with south and north Indian food consumption. •The calorie intake will be documented by an observer, blinded to the interventions, through an interview mode for allowing homogeneity of the employees

Motivation and behavior change •Intention •Intention, action and coping planning questionnaire by Sneihotta et al. [23] •This outcome deals with identifying one’s limitation, planning for actions and self-regulation of identifying barriers and facilitators of behavioural change •Risk- perception, action self-efficacy, outcome expectancies, maintenance self-efficacy, action and coping planning, behavioral intention, and recovery self-efficacy) explains 82.23% of the variation •Self-administered

•Action planning •The tool has 16 questions summarized in three domains: intentions (6 questions), action planning (5 questions) and coping planning (5 questions) with 4 choices for each question (totally disagree, disagree, agree or totally disagree) •Cronbach alpha = 0.63 to 0.97; ICC = 0.862 to 0.988 [23].

•Coping •Maximum score determines the behavioral change if documented before and after interventions [23]

Work-related sickness presenteeism and limitation/productivity •Sickness presenteeism •Stanford Sickness Presenteeism Scale 6-item questionnaire, developed by Koopman et al. [51] inquiring about stress, accomplishment and disability during sitting at work •Valid (r = 0.78–84) and reliable (interrater reliability ICC > 0.99; 95 CI = 0.86–1) [52] •Self-administered 6 item questionnaire

•Sickness absenteeism •Bradford Score •Bradford Factor (B) = Individual occurrences (S²) x individual absent days (D) •Not yet validated

•For example, if the person is taking 3 days leave at one single instance, occurrence is one where the number of absent days is three •It will be administered at the end of 3rd and 6th month

•Tool commonly employed by administrative offices to check absenteeism

•Work limitation •Work Limitation Questionnaire •Was developed by Learner et al. [53] •It has been found to have good interrater reliability (kappa 79% agreement (range: 0.88–0.91) [53] Self-administered questionnaire (5–8 minutes to fill)

•Measures 5 domains of work limitation: time management, physical demands, mental and output demands through 25 questions (self-administered or interview-based)

Outcome variable	Outcome variable	Instrument	Procedure	Psychometric properties	Special considerations
	Primary outcome measure
Physical activity and sedentary levels	•Prolonged sitting time (>30 minutes continuous) in minutes	Triaxial accelerometer – activPAL^™ (PAL technologies, Glasgow, UK) or Fibion® (Fibion Inc, Jyväskylä, Finland)	Sedentary time (including sitting time), light PA and MVPA during work and leisure hours will be monitored continuously throughout for seven days. Accelerometer will be attached to volunteer’s anterior midline of the right thigh, halfway between the hip and knee joints by a hypoallergic waterproof adhesive tape. The data files will be imported to data analysis software or manufacturer’s website and data will be processed.	•Accuracy: 96.2% in 18–60 years •]	The PA levels can be classified as].
	•Sitting time/day (mins)			ICC: 0.96 [95% CI:0.8–0.9] [36	•‘Active’ (≥1 hour of MVPA per day)
	•Total sitting time (mins)				•‘Moderately active’ (30–59 min of MVPA per day)
	•Average sitting time/day (mins)				•‘Inactive’ (<30 min of MVPA per day) and energy expenditure in METs will be quantified [37
	•Average energy expenditure/week (KCal)
	•Total stepping time (mins)
	•Standing time (mins)
Secondary outcome measures
Cardiometabolic risk factors	Blood biochemistry:	Insulin enzyme linked immunosorbent assay (Insulin-ELISA) kit [Cryochem, USA] [39]	Fasting blood samples will be collected in blood collection tubes at the worksite by an experienced phlebotomist in aminopolycarboxylic acid (EDTA) filled tubes and immediately transferred to NABL accredited central laboratory at the University Hospital, India and analysed by insulin enzyme linked immunosorbent assay (Insulin-ELISA) kit [Cryochem, USA] [39]	Accuracy: 85.3% in healthy population [40]	Desk-based workers will be requested in fasting state for 12 hours prior to the lab investigations. FBG < 125 mg/dL will be an inclusion criterion.
	•Fasting Blood Glucose (FBG),
	•Fasting insulin levels,
	•Homeostatic model
	•Insulin resistance (HOMA–IR; plasma glucose [mg/dL]×insulin [IRI; μU/L] ÷ 405) [38].
	•Low-density lipoproteins
	•High-density lipoproteins
	•Triglycerides
	Heart rate variability (HRV):	Polar H7 (Sensor), Polar-V800 (emitter) watch and Kubios software (MATLABS, MathWorks, Natick, Massachusetts, USA)	A Polar H7 sensor (Polar Electro Oy, Kempele, Finland) will be secured to the chest and heart rate variability in the supine lying position will be taken for 10 minutes. The 10 minutes beat-beat RR interval.csv files from the Polar-V800 (emitter) watch will be transferred to the Kubios software (MATLABS, MathWorks, Natick, Massachusetts, USA) as Polar.hrm files. Identical 256-segment RR interval will be selected and analyzed for the time (SDNN, RMSSD, NN50, pNN50), frequency domain (VLF, LF, HF, LF/HF index) and non-linear components (SD₁, SD₂, SD₁/SD₂) analyses	•Intraclass correlation (ICC) of time domain > 0.99 (95% CI: 0.86–0.99) with a small standard error mean (0.086%) in young athletes [41]	Person should arrive 30 minutes earlier to the test and will be asked to rest for next 30 minutes. Last 10 minutes, HRV will be measured.
	•Time (SDNN, RMSSD, NN50, pNN50)			•Concurrent validity of SDNN, pNN50 is high (r≥0.96 with SEM less than 1 ms) when compared to Polar V800 with Holter monitor in measuring heartrate variability [42]
	•Frequency domain (VLF, LF, HF, LF/HF index) and non-linear components (SD₁, SD₂, SD₁/SD₂) analyses
	Ambulatory blood pressure (mmHg)	Aneroid sphyghmanometer (Diamond, India)	•Measurement will be standardised according to the recommendations of European Health Examination Survey (EHES) [43]	A recent study by Climie et al. revealed a strong intra-test (ICC 0.97; 95 CIs 0.84–0.99) and inter-test reliability (ICC 0.89) for BP measurement using the auscultatory method [44]	Mean BP, systolic and diastolic BP and rate pressure product will be estimated from the pressure measured
			•BP will be measured thrice with one minute interval between trials from the right arm in the sitting posture
			•The desk-based employees will be sitting in the chair with their back supported and their feet placed firmly on the floor
			•The aneroid sphyghmanometer, used for BP measurement, will be calibrated every month at the Department of Biomedical Engineering (MAHE, India) for near 2 mmHg accuracy. The highest of three readings will be considered for the analysis
			•The cuff selection and positioning of the arm will be standardised, and the auscultatory method will be followed for measuring BP (Littmann, USA)
	•Maximal aerobic capacity (VO2 max) ml/kg/min	Portable calorimeter (K5, COSMED, Italy) and a treadmill ergometer (h/p/Cosmos, Quasar, Germany)	•The employees will be administered treadmill-based exercise testing (using the modified Bruce Protocol) comprising of 2.7 kmh^-1 at 0%, 5% and 10% inclination levels, 4 kmh^-1 at 12% inclination level, and 5.5 kmh^-1 at 14% inclination level for 3 minutes at every stage	•Excellent intra- and inter-rater reliability (ICCs > 0.99) at 95% confidence intervals) [45]	The volunteers will be familiarized with the treadmill protocol one week before the baseline measurement. Prerequisites of exercise testing shall be strictly followed as per ACSM standards
			•Peak aerobic capacity (VO₂ max) will be quantified through the portable telemetric calorimeter. Variables such as maximal oxygen consumption (VO₂ max), METs, ventilatory equivalents of carbon dioxide and oxygen (V_E/VCO₂, VE/VO₂), anaerobic threshold, work pulse (ΔHR), minute ventilation (V_E) and peak heart rate will be measured
			•The portable telemetric calorimeter will be calibrated for flow, reference gas (cylinder of 16% oxygen and 0.08% carbon dioxide) and delay as per the manufacturer guidelines (COSMED, Italy 2013)
	•Body fat percentage (%)	Lange skinfold calliper (Beta Technology Inc., Cambridge, MA)	•The subcutaneous body fat is calculated by measuring skinfold thickness at four sites (triceps, infrascapular, suprailiac and mid-thigh regions) [46] using a Lange skinfold calliper (Beta Technology Inc., Cambridge, MA) by an assessor experienced in skinfold measurements (a postgraduate in exercise science) blinded to the interventions	•The root mean square error (RMSE), related to interrater reliability, for the calculation of subcutaneous fat percentage has been found to be 4.6% [46]	Subcutaneous fat measurement by skin fold will be standardized as per the manufacturer standards and earlier guidelines [46]
			•Body fat percentage (% BF) will be estimated from the sum of four skinfolds with following gender specific equations as designed by Peterson et al. [46].
Cognitive performance	•Response inhibition (ms)	The stimulus presentation by Eriksen Flanker Paradigm and response registration are controlled by Inquisit 2.0 (Millisecond, Seattle, USA)	•The participants will be presented with 40 sets of trial arrays with each trial having a congruent (↑↑↑ ↑↑ or ↓↓↓ ↓↓) and a non-congruent “flanker” stimuli ↓↓ ↑ ↓↓ or ↑↑ ↓ ↑↑) at an inter-stimulus interval of 2000 ms and a rest period of 1500 ms between the array sets	•Excellent ICC (95 CIs: 0.81–0.94) for the Eriksen flanker task to pick error-related negativity (ERN) in the employees [47]	The tests will be administered during the earliest part of the day before beginning their day’s work. The tests will be repeated after one month, third and sixth month of the trial
			•Amongst congruent or non-congruent flankers, the employees will be required to press the button to the direction of centrally presented target arrow through the Eriksen flanker paradigm with controlled stimulus presentation of ↓↓ ↑ ↓↓ or ↑↑ ↓ ↑↑ through mouse computer interaction (Intel 64-bit processor, HP, USA) as shown in Fig. 3	•Correlation of conflict monitoring performance of Simon task to Eriksen Flanker using Inquisit software is 0.49 [48]
			•The up and down flanker stimuli will be presented in 500 ms difference and the employee will be asked to press the target stimulus in the centre amidst of the flankers presented
			•The reaction times (ms) or the latency for reaction will be measured and logged for the correct and non-correct flanker responses
Dietary intake	•Daily calorie intake (Kcal)	•“Track –Calorie Counter” SmPh-app (Nutritionix, Washington DC, USA) [49]	•Both south and north Indian food calorie estimates are fed in the software by each employee and weekly/daily average calorie intake will be assessed	•Nutritionix app is found to be moderately valid across the globe [50] compared to Edamam and Yummly SmPh app [50] but at present Indian data are not available	Desk-based office workers included will install this application and they will be familiarized to enter the daily diet intake for next 7 days
•Customized to estimate calories associated with south and north Indian food consumption.	•The calorie intake will be documented by an observer, blinded to the interventions, through an interview mode for allowing homogeneity of the employees
Motivation and behavior change	•Intention	•Intention, action and coping planning questionnaire by Sneihotta et al. [23]	•This outcome deals with identifying one’s limitation, planning for actions and self-regulation of identifying barriers and facilitators of behavioural change	•Risk- perception, action self-efficacy, outcome expectancies, maintenance self-efficacy, action and coping planning, behavioral intention, and recovery self-efficacy) explains 82.23% of the variation	•Self-administered
•Action planning	•The tool has 16 questions summarized in three domains: intentions (6 questions), action planning (5 questions) and coping planning (5 questions) with 4 choices for each question (totally disagree, disagree, agree or totally disagree)	•Cronbach alpha = 0.63 to 0.97; ICC = 0.862 to 0.988 [23].
•Coping	•Maximum score determines the behavioral change if documented before and after interventions [23]
Work-related sickness presenteeism and limitation/productivity	•Sickness presenteeism	•Stanford Sickness Presenteeism Scale	6-item questionnaire, developed by Koopman et al. [51] inquiring about stress, accomplishment and disability during sitting at work	•Valid (r = 0.78–84) and reliable (interrater reliability ICC > 0.99; 95 CI = 0.86–1) [52]	•Self-administered 6 item questionnaire
	•Sickness absenteeism	•Bradford Score	•Bradford Factor (B) = Individual occurrences (S²) x individual absent days (D)	•Not yet validated
			•For example, if the person is taking 3 days leave at one single instance, occurrence is one where the number of absent days is three	•It will be administered at the end of 3rd and 6th month
					•Tool commonly employed by administrative offices to check absenteeism
	•Work limitation	•Work Limitation Questionnaire	•Was developed by Learner et al. [53]	•It has been found to have good interrater reliability (kappa 79% agreement (range: 0.88–0.91) [53]	Self-administered questionnaire (5–8 minutes to fill)
			•Measures 5 domains of work limitation: time management, physical demands, mental and output demands through 25 questions (self-administered or interview-based)

ACSM –American College of Sports Medicine, CI –Confidence interval, MVPA –Moderate to Vigorous Physical Activity, PA –Physical activity. Formulas from Peterson et al are as follows: women: % BF = 22.18945 + (age×0.06368) + (BMI×0.60404) –(height×0.14520) + (sum4×0.30919) –(sum4x0.00099562); men: % BF = 20.94878 + (age×0.1166) –(height×0.11666) + (sum4×0.42696) –(sum4×0.00159). Measurement/investigation sites : 1) Central Lab of the Institutional Hospital - Blood biochemistry including fasting glucose, lipid profile and insulin levels; 2) Center for Sports Science Medicine and Research: Exercise Testing with indirect calorimeter, heart rate variability, subcutaneous fat percentage and ambulatory BP will be recorded. Cognitive assessment and work limitation will be done at the respective worksites of the desk-based employees

Fig. 2

Experimental design: desk-based employees will be randomized to three arms as follows: SMART (Smartphone driven break sitting + pedometer-based step); TRADE (Break sitting + ACSM walk prescription); CONTROL (uninterrupted sitting); Walking breaks are denoted by arrows in SMART and TRADE groups.

Fig. 3

Trial sequences of congruent and non-congruent stimuli in the Eriksen Flanker Paradigm.

2.8 Intervention

Once the baseline measures will be recorded, the assigned interventions will be carried out as follows:

2.8.1 SMART group

The customized SmPh-app, designed to auto-start at 8 AM, will be installed in each employee’s SmPh and exercise videos will be displayed for two minutes every hour during work hours (six times a day –9:30, 10:30, 11:30, 12:30, 14:30, and 15:30 hours). The app is set for six workdays (Monday to Saturday from 8:30–16:30 hours). The visual prompts (of exercise videos) (Supplementary Figure 2) will be demonstrated with the SmPh-app during the orientation session. In addition, each desk-based employee in the SMART group will receive a pedometer (Solar Powered Pedometer, Tiny Deal, India) (Supplementary Figure 3). The investigator (BC) will explain and demonstrate the employees how to use the pedometers and emphasize on achieving a target of 10,000 steps/day. The goal is to increase an average 700 steps/day by every week so that they achieve 10,000 steps per day as a weekly average in their pedometers by the 8th week. Then they will be instructed to maintain it or increase as per their comfort zone of walking for the remaining sixteen weeks of the intervention. The employees will wear the pedometers with a customized waist belt throughout the day except while using the washroom and sleeping.

At the end of every week of intervention, the average step count for seven days (at least three weekdays and one weekend day) will be inquired through a telephone call or a short message service (SMS) for six months. At the end of the third and sixth month of the intervention, the compliance towards exercise and the number of days in which the target step count has been achieved will be recorded. Further preference towards the intervention (in SMART and TRADE groups) will be scored with a dichotomous close ended-question: 0 –no; not preferred and 1 - yes; preferred.

2.8.2 TRADE group

This group will receive a formal education of physical exercises (six strengthening and six stretching exercises (Supplementary Table 3)), like those of the SMART group, demonstrated by an experienced physiotherapist (BC) during the familiarisation session. Employees will be requested to randomly choose and perform the exercises (one body support and one stretching exercise from the manual) every hour for two minutes during the work time. Each module will be clearly explained in both English and the regional language (Kannada). Besides work time break and exercise education, they will be educated to accumulate 150 minutes of walking with 30 minutes of continuous or intermittent exercise for almost five days a week as stated by the American College of Sports Medicine (ACSM) guidelines [27]. They will be instructed to cover this during their work hours and leisure time and will be asked to maintain an activity log.

2.8.3 CONTROL group

The employees of this group will be educated regarding the adverse effects of (uninterrupted) sitting and common exercises to break sitting at the desk side similar to the TRADE group during the familiarization session, but the manual will not be given to them. They will be requested to continue their routine work and leisure time activities as usual during the intervention phase. The outcome measures will be documented before and after 1st, 3rd and 6th month of recruitment in the study.

2.9 Statistical analysis

All desk-based employees initially allocated after randomization into one of the groups will be included for between-group comparisons by intention-to-treat analysis [28]. The data of the desk-based employees will be included only if they underwent all the baseline assessment and at least one follow-up assessment of all the outcome measures. Missing data will be treated by performing one or more appropriate methods such as replacing missing values with the mean of the observed values, the last measured values or multiple imputation analyses as required.

The continuous variables of >30 minutes of uninterrupted sitting time, step count, METs, MVPA, FBG, plasma insulin levels, triglycerides, body fat%, BP, VO₂ max, reaction times, accuracy of correct responses (and discrete variables of musculoskeletal discomfort, work limitation, sickness presenteeism and behavioural change recorded at the baseline and post-intervention (after 1st, 3rd and 6th months) will be analyzed using mixed ANOVA (time×group) with contrasts after checking for data normality with the Shapiro-Wilk test. Logarithmic transformations will be applied when there is a need to normalize skewed data. The treatment effect size will be estimated using Cohen’s ‘d’. Cohen’s d = (M₂ - M₁)/ SD_pooled where SD_pooled =√ ((SD₁² + SD₂²)/2) where M₂, M₁ and SD₁, SD₂ are mean differences and standard deviations among the intervention groups, respectively. Effect sizes are interpreted as follows – < 0.2: trivial, 0.2–0.5: small, 0.5–0.8: medium, and >0.8: large [29]. If assumptions of parametric tests are not met even with logarithmic transformations, Kruskal-Wallis ANOVA and/or Mann-Whitney U test will be used if appropriate. The significance level will be set at p < 0.050. All the statistical analyses will be done utilizing IBM SPSS 23.0 (Armonk NY, 2013).

2.10 Ethical approval

The research protocol was approved by the Kasturba Medical College and Hospital Institutional Ethics Committee (IEC:749/2019) and registered in the Clinical Trial Registry of India (CTRI/2020/03/024138). Any protocol amendments done by the investigators will be subjected to approval by IEC and CTRI. We do not anticipate any potential harm to employees based on the nature of the interventions employed; however, if any concerns arise from the trial, they will be recorded. Written informed consent will be obtained from each eligible employee before data collection. The smartphone data and the data related to the study will be stored for next five years in a password-protected computer accessed only by the investigators. All published data will remain anonymous and personal identities of employees will not be revealed.

3 Discussion

3.1 Potential impact and significance

To the best of our knowledge, this will be the first trial to test the effectiveness of an SmPh-app to increase PA levels among desk-based office employees with a 6-month follow-up in an Indian setting. Despite increasing studies on the m-health application and SmPh usage, whether the proposed app will be effective in promoting worksite PA and reducing cardiometabolic risk needs more substantiation. Though persuasive point-of-choice prompts have gained interest recently, their potential application in breaking sedentary behavior in an Indian worksite needs further investigation. We believe that creating favorable conditions for behavior change and the adoption of a healthy lifestyle will favor adherence and engagement of those involved in the study. Using the technology available on a SmPh to encourage the adoption of new ways of breaking prolonged sitting behavior can be a novel way of negating the ill-effects of sitting among the Indian population. In our study, we will be addressing functional capacity, HRV, behavior change and work limitation which have not addressed by the earlier studies [30]. If the SMART group is found to show significantly better outcomes compared to the TRADE and CONTROL groups in in desk-based employees, then the study results will aid in developing institutional recommendations and framing guidelines for using SmPh-based technology and pedometer-driven step intervention to promote PA at work for their employees.

3.2 Possible limitations of the study

As the trial is administered across administrative departments of various institutions of a single university, this may limit the generalization of research findings to global workplace settings due to environmental and cultural differences [31]. Similar to the findings of previous cluster RCTs [32, 33], contamination of the interventions across the groups may occur, especially between the TRADE and CONTROL groups. However, the administrative offices of the university are spread across various parts of the campus. We also anticipate an observational bias as the employees may modify their sedentary behavior while wearing the accelerometers due to the “Hawthorne effect” [6]. A drop-out of participants across all the groups may occur as there is no incentive or monetary compensation for participation in the study. We will document the reasons for drop-out and perform an “intention-to-treat” analysis.

Footnotes

Acknowledgments

The authors would like to thank the Manipal Academy of Higher Education for providing instruments and laboratory facilities for the study and for granting permission to conduct the study in its constituent institutions. The authors thank Dr Arto Pesola for his intellectual input on the outcomes related to behavioural change in the study.

Author contributions

BC and AA researched literature and conceived the study. BC, AA, CR and FD contributed to the study design and protocol development. BC and AA wrote the first draft of the manuscript. AA revised it critically for important intellectual content. CR and FD proofread the final draft of the manuscript. All authors reviewed, edited, and approved the final version of the manuscript.

Conflict of interest

There is no potential conflict of interest associated with the study, authorship and/or publication of this article.

Funding

No internal or external funding was received for the study.

The supplementary files are available from .

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