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

NCT ID: NCT05620888

Last Updated: 2024-12-09

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

255 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-10-03

Study Completion Date

2025-06-30

Brief Summary

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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.

Detailed Description

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A sample of sedentary adults will be invited to participate in a 30 days intervention delivered via a mobile app to achieve the goal of 7,000 daily steps.

Before and after the intervention, some crucial variables will be evaluated for the formation of the intention to change behavior and for the transition from intention to action (attitudes, subjective norms, self-efficacy, expectations related to change, risk perception, social support, planning) to compare two models of behavioral change.

During the intervention, messages will be sent daily, and the number of steps taken daily will be monitored. The aim is to compare the effectiveness of two types of communication in promoting a positive behavioral change: non-personalized communication centered on well-being (non-tailored communication) vs. personalized communication based on the psychological characteristics evaluated before the intervention (tailored communication). The physical activity carried out over 30 days by the participants who will receive the messages (tailored and non-tailored) will be compared with the physical activity carried out by participants who will not receive any messages (control group).

Conditions

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Physical Inactivity

Keywords

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

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

PREVENTION

Blinding Strategy

SINGLE

Participants
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.

Study Groups

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Tailored messages (TM)

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.

Group Type EXPERIMENTAL

Walk behavior change: Tailored messages (TM)

Intervention Type 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.

Non tailored messages (NTM)

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.

Group Type EXPERIMENTAL

Walk behavior change: Non tailored messages (NTM)

Intervention Type 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.

No messages (NM)

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.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Walk behavior change: Tailored messages (TM)

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.

Intervention Type BEHAVIORAL

Walk behavior change: Non tailored messages (NTM)

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.

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

* 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

Exclusion Criteria

* 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
Minimum Eligible Age

18 Years

Maximum Eligible Age

70 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Federico II University

OTHER

Sponsor Role collaborator

University of Bergamo

OTHER

Sponsor Role collaborator

University of Milano Bicocca

OTHER

Sponsor Role lead

Responsible Party

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Marco D'Addario

Associate Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Marco D'Addario, PhD

Role: PRINCIPAL_INVESTIGATOR

University of Milano Bicocca

Patrizia Steca, PhD

Role: PRINCIPAL_INVESTIGATOR

University of Milano Bicocca

Locations

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University of Milano-Bicocca

Milan, MI, Italy

Site Status RECRUITING

Countries

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Italy

Central Contacts

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Marco D'Addario, PhD

Role: CONTACT

Phone: 0039 02 6448 3824

Email: [email protected]

Roberta Adorni, PhD

Role: CONTACT

Email: [email protected]

Facility Contacts

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Marco D'Addario, PhD

Role: primary

Roberta Adorni, PhD

Role: backup

References

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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.

Reference Type BACKGROUND
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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.

Reference Type BACKGROUND
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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.

Reference Type BACKGROUND
PMID: 34788584 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 30888321 (View on PubMed)

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.

Reference Type BACKGROUND
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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.

Reference Type BACKGROUND
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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.

Reference Type BACKGROUND
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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.

Reference Type BACKGROUND
PMID: 30973747 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 30121311 (View on PubMed)

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.

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Reference Type 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)

Reference Type BACKGROUND

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Reference Type 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.

Reference Type DERIVED
PMID: 40676042 (View on PubMed)

Other Identifiers

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RM-2021-482

Identifier Type: -

Identifier Source: org_study_id