Efficacy of a Tailored Communication Intervention Aimed At Increasing the Number of Daily Steps

NCT05620888 | Recruiting

• 1 other identifier: RM-2021-482
• Study Type: interventional
• Target: 255
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to evaluate the efficacy of a physical activity promotion intervention focused on walking behavior. The intervention is delivered via mobile application in a sample drawn from the healthy adult population.

Conditions

Physical Inactivity

Keywords

Physical Activity; Tailored communication; Behavior Change; Self Efficacy; Health Action Process Approach; Persuasive Communication; Walking

Outcome Measures

Primary Outcomes (2)

• Change from Baseline in Physical Activity

  Physical activity is assessed with the International Physical Activity Questionnaire (IPAQ; Mannocci et al., 2010). The scale comprises seven items on Physical Activity providing information about time spent walking, moderate and vigorous intensity, and sedentary activity. The elements are structured to provide separate scores for walking, moderate and vigorous intensity activity, and a combined total score to describe the overall activity level. Data collected with IPAQ are reported as a continuous measure and reported as MET-median minutes.

  Baseline and 30 days

• Change from Baseline in Walk behavior

  Walk behavior is self-monitored daily. Each evening, participants receive a message and enter the number of steps taken in a specific app section based on the data reported on the smartwatch or the smartphone's native app. The mean number of steps at the intervention's beginning and the end is then calculated. These two measures are compared to verify whether a statistically significant increase in daily steps is observed over time.

  Baseline and 30 days

Other Outcomes (15)

• Adherence to a healthy lifestyle: diet

  Baseline

• Adherence to a healthy lifestyle: alcohol consumption

  Baseline

• Adherence to a healthy lifestyle: smoking

  Baseline

Study Arms (3)

Tailored messages (TM)

EXPERIMENTAL

Participants assigned to this arm receive a daily tailored message on the benefits of taking at least 7000 steps daily. Tailoring concerns change-related expectations, risk perception, planning, retention capacity, resilience, and coping skills and is based on the responses provided by participants at baseline evaluation. In addition, they receive a daily request to declare the number of steps taken (walking self-monitoring).In particular, every evening, the mobile application sends a message to the participants requesting to enter the number of steps taken during the day in a dedicated app section.

Behavioral: Walk behavior change: Tailored messages (TM)

Non tailored messages (NTM)

EXPERIMENTAL

Participants assigned to this arm receive a daily non-tailored message on the emotional benefits of taking at least 7000 steps daily. In addition, they receive a daily request to declare the number of steps taken (walking self-monitoring). In particular, every evening, the mobile application sends a message to the participants requesting to enter the number of steps taken during the day in a dedicated app section.

Behavioral: Walk behavior change: Non tailored messages (NTM)

No messages (NM)

NO INTERVENTION

Participants assigned to this arm receive a daily request to declare the number of steps taken (walking self-monitoring). In particular, every evening, the mobile application sends a message to the participants requesting to enter the number of steps taken during the day in a dedicated app section.

Interventions

Walk behavior change: Tailored messages (TM) BEHAVIORAL

Every afternoon at the same time, the mobile application sends a message to the participants of the TM arm. The message is tailored based on the answers provided to the pre-intervention questionnaire. An example message is: "you think you are not able to walk regularly when your morale is low: do not give up because physical activity is also good for the mood!" The intervention is provided for 30 days.

Tailored messages (TM)

Walk behavior change: Non tailored messages (NTM) BEHAVIORAL

Every afternoon at the same time, the mobile application sends a message to the participants of the NTM arm. The message concerns the emotional well-being resulting from the performance of the physical activity and is not tailored. An example message is: "walking regularly in the fresh air improves your mood." The intervention is provided for 30 days.

Non tailored messages (NTM)

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Participants from the general population, in good health and sedentary
• A level of education sufficient to understand the procedures of the study and to use a smartphone
• Having a smartphone

You may not qualify if:

• The participant always (or almost always) takes at least 7,000 steps a day
• The participant achieves an IPAQ score equal to or greater than 3000 MET-min / week
• The participant has symptoms or pathologies that could represent a contraindication to the physical activity proposed by the study. In particular
• Cardiovascular diseases for which physical activity is allowed only under medical supervision
• Chest pain during daily activities
• Drug treatment for cardiovascular diseases
• Severe arterial hypertension not pharmacologically controlled
• Episodes of loss of consciousness within the past 12 months
• Osteoarticular disorders that could be aggravated by a change in the level of physical activity
• Fractures of the lower limbs, vertebrae, or pelvis in the past six months
• Walking difficulty
• Respiratory insufficiency

Sponsors & Collaborators

• University of Milano Bicocca: lead
• Federico II University: collaborator
• University of Bergamo: collaborator

Study Sites (1)

University of Milano-Bicocca

Milan, MI, 20126, Italy

RECRUITING

Related Publications (14)

• Davis A, Sweigart R, Ellis R. A systematic review of tailored mHealth interventions for physical activity promotion among adults. Transl Behav Med. 2020 Oct 12;10(5):1221-1232. doi: 10.1093/tbm/ibz190.

  PMID: 33044542 BACKGROUND

• Martin-Martin J, Roldan-Jimenez C, De-Torres I, Muro-Culebras A, Escriche-Escuder A, Gonzalez-Sanchez M, Ruiz-Munoz M, Mayoral-Cleries F, Biro A, Tang W, Nikolova B, Salvatore A, Cuesta-Vargas AI. Behavior Change Techniques and the Effects Associated With Digital Behavior Change Interventions in Sedentary Behavior in the Clinical Population: A Systematic Review. Front Digit Health. 2021 Jul 8;3:620383. doi: 10.3389/fdgth.2021.620383. eCollection 2021.

  PMID: 34713097 BACKGROUND

• Newsome A, Gilliard T, Phillips A, Dedrick R. Understanding the perceptions of sedentary college students' engagement in physical activity: application of the theory of planned behavior. J Am Coll Health. 2023 Dec;71(9):2813-2822. doi: 10.1080/07448481.2021.1998069. Epub 2021 Nov 17.

  PMID: 34788584 BACKGROUND

• Romeo A, Edney S, Plotnikoff R, Curtis R, Ryan J, Sanders I, Crozier A, Maher C. Can Smartphone Apps Increase Physical Activity? Systematic Review and Meta-Analysis. J Med Internet Res. 2019 Mar 19;21(3):e12053. doi: 10.2196/12053.

  PMID: 30888321 BACKGROUND

• Rowley TW, Lenz EK, Swartz AM, Miller NE, Maeda H, Strath SJ. Efficacy of an Individually Tailored, Internet-Mediated Physical Activity Intervention in Older Adults: A Randomized Controlled Trial. J Appl Gerontol. 2019 Jul;38(7):1011-1022. doi: 10.1177/0733464817735396. Epub 2017 Oct 25.

  PMID: 29165018 BACKGROUND

• Steca P, Pancani L, Cesana F, Fattirolli F, Giannattasio C, Greco A, D'Addario M, Monzani D, Cappelletti ER, Magrin ME, Miglioretti M, Sarini M, Scrignaro M, Vecchio L, Franzelli C. Changes in physical activity among coronary and hypertensive patients: A longitudinal study using the Health Action Process Approach. Psychol Health. 2017 Mar;32(3):361-380. doi: 10.1080/08870446.2016.1273353. Epub 2017 Jan 4.

  PMID: 28049344 BACKGROUND

• Tudor-Locke C, Bassett DR Jr. How many steps/day are enough? Preliminary pedometer indices for public health. Sports Med. 2004;34(1):1-8. doi: 10.2165/00007256-200434010-00001.

  PMID: 14715035 BACKGROUND

• Zhang CQ, Zhang R, Schwarzer R, Hagger MS. A meta-analysis of the health action process approach. Health Psychol. 2019 Jul;38(7):623-637. doi: 10.1037/hea0000728. Epub 2019 Apr 11.

  PMID: 30973747 BACKGROUND

• Carfora V, Caso D, Palumbo F, Conner M. Promoting water intake. The persuasiveness of a messaging intervention based on anticipated negative affective reactions and self-monitoring. Appetite. 2018 Nov 1;130:236-246. doi: 10.1016/j.appet.2018.08.017. Epub 2018 Aug 16.

  PMID: 30121311 BACKGROUND

• Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self-reported measure of medication adherence. Med Care. 1986 Jan;24(1):67-74. doi: 10.1097/00005650-198601000-00007.

  PMID: 3945130 BACKGROUND

• Ajzen I. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 1991; 50(2): 179-211.

  BACKGROUND

• Mannocci A, Di Thiene D, Del Cimmuto A, Masala D, Boccia A, De Vito E, La Torre G. International Physical Activity Questionnaire: validation and assessment in an Italian sample. Italian Journal of Public Health. 2012; 7(4)

  BACKGROUND

• Schwarzer R. Modeling health behavior change: How to predict and modify the adoption and maintenance of health behaviors. Applied Psychology. 2008; 57(1): 1-29

  BACKGROUND

• Adorni R, Zanatta F, Serino S, Vanutelli ME, Caso D, D'Addario M, Steca P. Efficacy of a theory-based and tailored mHealth intervention promoting walking behavior: a preliminary randomized controlled trial. Sci Rep. 2025 Jul 18;15(1):26033. doi: 10.1038/s41598-025-09634-3.

  PMID: 40676042 DERIVED

MeSH Terms

Conditions

Sedentary Behavior; Motor Activity

Condition Hierarchy (Ancestors)

Behavior

Study Officials

• Marco D'Addario, PhD

  University of Milano Bicocca

  PRINCIPAL INVESTIGATOR

• Patrizia Steca, PhD

  University of Milano Bicocca

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Marco D'Addario, PhD

CONTACT

0039 02 6448 3824; marco.daddario@unimib.it

Roberta Adorni, PhD

CONTACT

roberta.adorni1@unimib.it

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Masking Details: The baseline assessment, the intervention, and the post-intervention assessment are provided automatically via the mobile app. In addition, participants are randomly assigned to a specific experimental group before starting the study and do not know which experimental group they are assigned. These features of the study minimize observer bias.
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: October 25, 2022
• First Posted: November 17, 2022
• Study Start: October 3, 2022
• Primary Completion: September 30, 2024
• Study Completion: June 1, 2025
• Last Updated: December 9, 2024

Record last verified: 2024-12

Data Sharing

• IPD Sharing: Will not share

Locations

IT (1)