A Boost of Health: Effectiveness of a Personalized Communication Intervention to Increase Daily Fruit and Vegetable Intake

NCT07581847 | Completed

• 2 other identifiers: RM-2024-882PE00000003;CUP D93C22000890001
• Study Type: interventional
• Target: 403
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to evaluate the efficacy of a healthy diet promotion intervention focused on increasing fruit and vegetable consumption. The intervention is delivered via mobile application in a sample drawn from the healthy adult population.

Conditions

Interactive Condition (HAPA-I: Group 1); Non-interactive Condition (HAPA-NI: Group 2); Non-communication Condition (No Comm: Group 3)

Keywords

mHealth; Health Action Process Approach; Healthy Diet; Behavioral Change techniques; Behavioral Goal Setting; Self-monitoring; Rewards

Outcome Measures

Primary Outcomes (1)

• Change in Daily Fruit and Vegetable Intake from Baseline

  Participants self-monitored daily fruit and vegetable intake throughout the study period. Each evening, participants received a reminder and recorded the number of fruit and vegetable portions consumed that day via a dedicated app interface. At the end of the 15-day intervention, the mean daily intake was calculated for each participant. This value was then compared with baseline intake (assessed prior to the start of the intervention) to evaluate whether a statistically significant increase in daily fruit and vegetable consumption was observed.

  From Day 1 to Day 15 (end of intervention)

Secondary Outcomes (1)

• Change in Perceived Well-Being (WHO-5 Index)

  Baseline and Day 15 (end of intervention)

Study Arms (3)

Interactive condition (HAPA-I: group 1)

EXPERIMENTAL

Participants received two daily notifications. Each notification included a question about a variable from the HAPA model, and participants responded on a 5-point Likert scale. Those who scored low (1-3) received a motivational message tailored to their response. In contrast, participants who scored high (4-5) received rewarding messages. These notifications gave participants feedback on their standings within the HAPA. Moreover, participants received a daily reminder to log the portions of fruit and vegetables in a dedicated self-monitoring section of the app.

Behavioral: Interactive communication; Behavioral: Self-monitoring

Non-interactive condition (HAPA-NI: group 2)

EXPERIMENTAL

Participants received two daily educational notifications about HAPA variables, but they did not interact with the app. The notifications for both the HAPA-I and HAPA-NI groups were identical in structure, word count, and graphic format. The only difference was the level of content customization: it was generic for the HAPA-NI group and tailored to participants' responses for the HAPA-I group. Moreover, participants received a daily reminder to log the portions of fruit and vegetables in a dedicated self-monitoring section of the app.

Behavioral: Non-interactive Communication; Behavioral: Self-monitoring

Non-communication condition (No-comm: group 3)

EXPERIMENTAL

Participants did not receive HAPA-based notifications during the trial period. They received a daily reminder to log the portions of fruit and vegetables in a dedicated self-monitoring section of the app.

Behavioral: Self-monitoring

Interventions

Interactive communication BEHAVIORAL

Participants received two daily notifications. Each notification included a question about a variable from the HAPA model, and participants responded on a 5-point Likert scale. Those who scored low (1-3) received a motivational message tailored to their response. In contrast, participants who scored high (4-5) received rewarding messages. These notifications gave participants feedback on their standings within the HAPA.

Interactive condition (HAPA-I: group 1)

Non-interactive Communication BEHAVIORAL

Participants received two daily educational notifications about HAPA variables, but they did not interact with the app. The notifications for both the HAPA-I and HAPA-NI groups were identical in structure, word count, and graphic format. The only difference was the level of content customization: it was generic for the HAPA-NI group and tailored to participants' responses for the HAPA-I group.

Non-interactive condition (HAPA-NI: group 2)

Self-monitoring BEHAVIORAL

Participants received a daily reminder to log the portions of fruit and vegetables in a dedicated self-monitoring section of the app.

Interactive condition (HAPA-I: group 1); Non-communication condition (No-comm: group 3); Non-interactive condition (HAPA-NI: group 2)

Eligibility Criteria

• Age: 18 Years - 55 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• Individuals from the general population in good health
• Adequate level of education to understand study procedures and to use a smartphone
• Ownership and regular use of a smartphone

You may not qualify if:

• Medical conditions that contraindicate an increased consumption of fruit and vegetables
• Habitual consumption of five (or more) portions of fruit and vegetables per day at baseline

Sponsors & Collaborators

• Marco D'Addario: lead

Study Sites (1)

Adorni Roberta

Milan, Milano, 20126, Italy

Location

Related Publications (8)

• Schwarzer, R. (2008). Modeling health behavior change: How to predict and modify the adoption and maintenance of health behaviors. Applied Psychology: An International Review, 57(1), 1-29. https://doi.org/10.1111/j.1464-0597.2007.00325.x

  BACKGROUND

• Mujcic R, J Oswald A. Evolution of Well-Being and Happiness After Increases in Consumption of Fruit and Vegetables. Am J Public Health. 2016 Aug;106(8):1504-10. doi: 10.2105/AJPH.2016.303260.

  PMID: 27400354 BACKGROUND

• Kamphuis CB, van Lenthe FJ, Giskes K, Brug J, Mackenbach JP. Perceived environmental determinants of physical activity and fruit and vegetable consumption among high and low socioeconomic groups in the Netherlands. Health Place. 2007 Jun;13(2):493-503. doi: 10.1016/j.healthplace.2006.05.008. Epub 2006 Jul 11.

  PMID: 16815073 BACKGROUND

• Fjeldsoe B, Neuhaus M, Winkler E, Eakin E. Systematic review of maintenance of behavior change following physical activity and dietary interventions. Health Psychol. 2011 Jan;30(1):99-109. doi: 10.1037/a0021974.

  PMID: 21299298 BACKGROUND

• D'Addario M, Cappelletti ER, Sarini M, Greco A, Steca P. The TTCYB Study Protocol: A Tailored Print Message Intervention to Improve Cardiovascular Patients' Lifestyles. Int J Environ Res Public Health. 2020 Apr 23;17(8):2919. doi: 10.3390/ijerph17082919.

  PMID: 32340219 BACKGROUND

• Blanchflower, D. G., Oswald, A. J., & Stewart-Brown, S. (2013). Is psychological well-being linked to the consumption of fruit and vegetables? Social Indicators Research, 114(3), 785-801. https://doi.org/10.1007/s11205-012-0173-y

  BACKGROUND

• Aune D, Giovannucci E, Boffetta P, Fadnes LT, Keum N, Norat T, Greenwood DC, Riboli E, Vatten LJ, Tonstad S. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose-response meta-analysis of prospective studies. Int J Epidemiol. 2017 Jun 1;46(3):1029-1056. doi: 10.1093/ije/dyw319.

  PMID: 28338764 BACKGROUND

• Adorni R, Zanatta F, Cappelletti ER, Greco A, Steca P, D'Addario M. Effectiveness of a tailored communication intervention to improve physical activity in hypertensive patients: a twelve-month randomized controlled trial. BMC Cardiovasc Disord. 2024 Mar 5;24(1):143. doi: 10.1186/s12872-024-03786-2.

  PMID: 38443805 BACKGROUND

MeSH Terms

Interventions

Blood Glucose Self-Monitoring

Intervention Hierarchy (Ancestors)

Blood Chemical Analysis; Clinical Chemistry Tests; Clinical Laboratory Techniques; Diagnostic Techniques and Procedures; Diagnosis; Diagnostic Techniques, Endocrine; Monitoring, Physiologic; Self-Testing; Self Care; Therapeutics; Investigative Techniques

Study Officials

• Marco D'Addario, PhD

  University of Milano Bicocca

  PRINCIPAL INVESTIGATOR

• Maria Elide Vanutelli, PhD

  University of Milano Bicocca

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, INVESTIGATOR
• 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 the study begins and do not know which group they are assigned to. These features of the study minimize observer bias.
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: May 5, 2026
• First Posted: May 12, 2026
• Study Start: December 3, 2024
• Primary Completion: January 16, 2026
• Study Completion: January 16, 2026
• Last Updated: May 20, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will not share

Locations

IT (1)