Changes in cognitive function among older adults aged 60–79 without dementia following use of the mHealth app “Vitality Wellness Program”: a prospective single-group intervention trial
Brief Report

Changes in cognitive function among older adults aged 60–79 without dementia following use of the mHealth app “Vitality Wellness Program”: a prospective single-group intervention trial

Yuto Nakayama1 ORCID logo, Yuma Sonoda1 ORCID logo, Kouhei Masumoto2 ORCID logo, Kazuhiro Harada2 ORCID logo, Atsuhiko Uchida2 ORCID logo, Narihiko Kondo2, Tomonori Harada3, Toshio Sawada3, Hisatomo Kowa1, Toshihiro Akisue1 ORCID logo

1Graduate School of Medicine, Kobe University, Kobe, Japan; 2Graduate School of Human Development and Environment, Kobe University, Kobe, Japan; 3Sumitomo Life Insurance Company, Osaka, Japan

Contributions: (I) Conception and design: Y Sonoda, K Masumoto, K Harada, A Uchida, N Kondo, H Kowa, T Akisue; (II) Administrative support: N Kondo, T Sawada, H Kowa, T Akisue; (III) Provision of study materials or patients: T Harada, T Sawada; (IV) Collection and assembly of data: Y Nakayama, Y Sonoda, T Harada, T Sawada, T Akisue; (V) Data analysis and interpretation: Y Nakayama, Y Sonoda, H Kowa, T Akisue; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Yuma Sonoda, degree; Toshihiro Akisue, degree. Graduate School of Medicine, Kobe University, 7-10-2, Tomogaoka, Suma, Kobe 654-0142, Hyogo, Japan. Email: yuma@dragon.kobe-u.ac.jp; akisue@med.kobe-u.ac.jp.

Abstract: Increasing physical activity is important for reducing the risk of developing dementia. The Vitality Wellness Program (Vitality), an mHealth app designed to increase physical activity through rewards, has been shown to increase users’ average step counts; however, its impact on health-related outcomes remains unclear. This study investigated the effects of a 12-week Vitality program on cognitive function among older adults. A total of 467 older adults aged 60–79, who lived or worked in Kobe City, Hyogo Prefecture, and owned a smartphone were recruited for this study. Participants underwent cognitive function testing prior to the intervention, followed by a 12-week intervention period during which they had unrestricted access to Vitality, and then underwent post-intervention cognitive function testing. Cognitive function, the primary outcome, was assessed using the Cogstate Brief Battery, with concentration and memory scores calculated; the number of rewards (up to 12) earned was also recorded as a secondary measure. The analysis included 314 older adults (mean age 67.6±4.9 years; 126 men) who completed pre- and post-intervention assessments. Following app use, significant improvements were observed in both concentration and memory scores (both P<0.001). However, no significant association was found between the number of rewards earned (7.3±4.2) and changes in cognitive function (Δconcentration score: P=0.32; Δmemory score: P=0.20). In conclusion, participation in Vitality contributed to improvements in cognitive function among older adults; however, these improvements could not be explained by rewards earned through the app.

Keywords: mHealth app; Cogstate Brief Battery; cognitive function; reward; Vitality Wellness Program

Received: 14 April 2026; Accepted: 23 June 2026; Published online: 29 June 2026.

doi: 10.21037/mhealth-2026-0018

Introduction

Physical inactivity is a risk factor for dementia, whereas physical activity reduces this risk (1-4). Specifically, increasing the average daily step count non-linearly lowers dementia risk (5). While improving physical function is key to maintaining and enhancing cognitive function, 31.3% of the global population remains physically inactive (6). Because physical inactivity also increases all-cause mortality, cardiovascular events, and the risk of cancer (7-9), effective strategies promoting behavioral changes to encourage physical activity are needed.

Reward-based behavioral change techniques are prominent strategies for promoting physical activities (10-12). Behavioral economics suggests that monetary rewards for achieving physical activity goals can offset the immediate cost of exertion (13), making incentive-based interventions effective. Consequently, over 300 mHealth apps utilize rewards to encourage behavior change (14). These apps primarily employ five techniques: feedback provision, self-monitoring, goal setting, social support, and rewards (15). However, the specific impact of reward-based behavioral change techniques on behavioral change and health outcomes remains insufficiently understood.

Therefore, we examined the Vitality Wellness Program (Vitality), an mHealth app that leverages behavioral economics’ loss aversion principle to encourage physical activity through rewards (12). A previous retrospective cohort study in Japan demonstrated that this program increased daily step count by approximately 2,000 steps over 3 years (16). However, because previous work focused solely on step count, Vitality’s broader impact on health-related outcomes remains unclear.

This study aimed to evaluate the effects of Vitality on cognitive function among community-dwelling older adults aged ≥60 years. As an initial phase of the prospective study, we conducted a single-group pre-post comparison analysis of all participants using the trial version of the program to investigate the effects of three months of “Vitality” use on cognitive function and the subsequent conversion rate to the paid version.

Methods

Study design

This prospective study examines various outcomes over 2 years; the study design reported here is a single-group intervention study presenting preliminary results on cognitive function over 12 weeks.

Participants

Participants had to meet three criteria: they were 60–79 years old, lived or worked in Kobe, Japan, and owned a smartphone. We excluded people who had dementia, mild cognitive impairment, health problems that affect walking, or had already participated in Vitality. A previous study for older adults with cognitive decline reported that the effect size of a 12-week mHealth intervention was 0.70 (17). Using G*Power 3.1.9.7, the necessary sample size was 29 participants (with alpha =0.05 and power =0.95). However, we expected a smaller effect size because our participants use the app by themselves. Also, no past studies tested how reward-based mHealth apps affect cognitive function. Therefore, this single-group pilot study aimed to check the effect size and the dropout rate. We set the target sample size at 1,000 participants to prevent a loss of statistical power from dropouts. As a result, we recruited 467 participants through public sessions. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Graduate School of Health Sciences, Kobe University (Approval No. 1277-2). Informed consent was obtained from all individual participants. This study was registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR ID: 000057861).

Baseline measurement

Participants were divided into groups of 30 or fewer and arrived at the testing site. All participants received a thorough explanation regarding registration for Vitality, how to use it, and how to receive rewards. Next, participants completed a questionnaire on basic characteristics (age, sex, educational background, and pre-existing conditions), as well as the Japanese version of the Cognitive Function Instrument (CFI-J) to assess subjective cognitive function (18,19) and the Exercise Behavioral Skills Questionnaire (EBS) to evaluate exercise-related behavioral skills (20). Association between EBS and behavioral change stages has been demonstrated (20). They then took the cognitive function test using the Cogstate Brief Battery (CBB) Japanese version (21-24) on their own smartphones. The CBB used in this study was developed by Eisai (Tokyo, Japan) based on the original CBB created by Cogstate Corporation, utilizing NouKNOW® (Eisai Co., Ltd.). Participants received leaflets containing QR codes and scanned them using their own smartphones or tablets to access the online test platform. During the test phase, explanatory assistance regarding the test procedure was provided only when participants requested support; however, no assistance was provided for the actual test.

Vitality Wellness Program Intervention protocol

During the intervention period, participants used the app on their own smartphones for 12 weeks. Vitality offers several versions with different reward structures; herein, the Vitality trial version was used, allowing users to earn rewards solely through exercise. The program sets weekly exercise goals. Participants earned daily points by achieving a minimum step count, such as 8,000 steps per day for those aged ≤64, or 6,000 steps per day for those aged ≥65 (criteria at the time of analysis). Upon reaching the weekly point target, participants could obtain reward tickets for drinks or light meals at specific stores. Step counts were measured using the built-in pedometer of the smartphone or wearable devices such as smartwatches. App usage was left to participants’ discretion during the 12-week app usage period.

Follow-up measurement

After the intervention period, participants returned to the same testing site, where they underwent another round of cognitive function testing using the CBB and completed the CFI-J and EBS questionnaires. Follow-up assessments were primarily conducted in a face-to-face group setting. However, 23% of the participants who underwent follow-up assessment were unable to attend in person; they were assessed individually via remote means. During the follow-up assessment, participants were asked whether they wished to continue subscribing to the paid version of Vitality. Those who expressed interest were assisted with the subscription process.

Outcomes

The primary outcome was the change in participants’ cognitive function over a 12-week period. We adopted the concentration and memory scores generated by NouKNOW as indicators of cognitive function. Secondary outcomes included changes in CFI-J and EBS scores, program retention rates, the number of rewards during the 12-week period (maximum: 12), the reliability of CBB scores, the minimum detectable change in this intervention, conversion rate to the paid version, and reports of adverse events during the intervention period.

Statistical analysis

All data were tested for normality using the Shapiro-Wilk test. To compare the scores before and after the intervention, we used paired statistical tests. We used the Wilcoxon signed-rank test if the data did not have a normal distribution. We also calculated the rank-biserial correlation (rrb) for the effect size. Additionally, we performed a simple regression analysis to check the effect of rewards. In this analysis, the explanatory variable was the number of rewards (maximum of 12 times in 12 weeks), and the dependent variable was the change in cognitive function. To check the reliability of measurements before (TEST1) and after (TEST2) the intervention, we calculated the intraclass correlation coefficient (ICC) (25). We used ICC (2, 1) to show the reliability of a single measurement. Finally, we calculated the minimum detectable change at the 95% confidence level (MDC95). All statistical analyses were performed using R software version 4.5.0. For all statistical analyses, the significance threshold was set at P<0.05 using a two-sided test to avoid analytical bias.

Results

Participant characteristics are shown in Table 1. Of the 467 participants, 314 who completed both the initial and second cognitive function assessments were included in the analysis. The retention rate for this study was 67% (314/467). Seven participants told us that they wanted to withdraw from the study. Three of them gave reasons, but none were caused by the app intervention. The reasons were: not used to carrying a smartphone, unexpected illness, and slow recovery after surgery. Additionally, 137 participants (29%) joined the paid version of Vitality after the intervention period ended.

Table 1

Participant characteristics (n=314)

Characteristics Value
Age, mean (standard deviation), years 67.6 (4.9)
Sex (n)
   Male 126
   Female 188
Years of education (%)
   12 years or less 28
   Over 13 years 69
   Unknown 3
Medical conditions (%)
   Hypertension 26
   Diabetes 10

Table 2 shows the results for each cognitive function, EBS, ICC, and MDC95. The Shapiro-Wilk test indicated that all variables, including concentration, memory, CFI-J, and EBS, did not follow a normal distribution (P<0.05). We observed significant improvements in concentration score, memory score, CFI-J, and EBS after the intervention. The measurement reliability for the concentration score was moderate, whereas that for the memory score was low.

Table 2

The results for each cognitive function and the Exercise Behavioral Skills Questionnaire

Variable TEST1 TEST2 P rrb ICC (2, 1) MDC95
Concentration score 21.5 (4.8) 23.2 (4.6) <0.001 0.559 0.7 7.2
Memory score 25.9 (4.9) 27.0 (4.9) <0.001 0.246 0.42 10.3
The Japanese version of the Cognitive Function Instrument 2.3 (1.9) 2.2 (2.0) 0.028 −0.163 – –
The Exercise Behavioral Skills Questionnaire 13.5 (6.0) 15.0 (5.6) <0.001 0.38 – –

Test results are expressed as mean (standard deviation). ICC, intraclass correlation coefficients; MDC95, minimum detectable change at the 95% confidence level.

The results of the regression analysis examining the relationship between cognitive function changes and the number of rewards received are shown in Table 3. During the intervention period, participants received 7.3±4.2 rewards. We found no significant association between cognitive function changes and the number of rewards achieved.

Table 3

The results of the regression analysis examining the relationship between cognitive function changes and the number of rewards received

Variable F R2 b P
ΔConcentration score 1 0.003 −0.04 0.32
ΔMemory score 1.7 0.005 −0.09 0.2

This study investigated changes in CBB scores among participants aged 60 and older who used Vitality. The current results indicate that while CBB scores improved with the use of the mHealth app “Vitality Wellness Program,” changes in cognitive function were not associated with the rewards earned through mHealth use over the short term (12 weeks).

Discussion

Systematic reviews and meta-analyses have demonstrated that various types of exercise interventions improve cognitive function in adults aged ≥50 years (26), and even short-term interventions of up to 12 weeks, similar to this study, enhance overall cognitive function in older adults (27). These prior studies provide a basis for considering that Vitality examined here, which induces exercise and promotes physical activity, may influence cognitive function. However, the changes in cognitive function measured here were not associated with the rewards gained from exercise. One possible interpretation for these results is that participation in Vitality may have induced behavioral changes among participants, resulting in increased physical activity levels that, nonetheless, remained insufficient to enhance cognitive function.

Previous studies have suggested that intrapersonal behavior change strategies involving specific goal-setting do not increase physical activity in older adults (28). Vitality also employs a reward-based intrapersonal behavior change strategy, and the current results showed improvements in EBS related to behavior change that were inconsistent with prior research. The discrepancy between previous reports and the present study may be explained by the effect of rewards (incentives) on behavioral change. Previous studies have reported that rewards influence various behavioral changes (29-32). This study also suggested that rewards may have influenced the behavioral skills of participants, leading to behavioral changes such as increased physical activity. However, this study was merely a single-center, uncontrolled study, and the changes in cognitive function observed may simply have been due to the practice effects of the CBB. Studies examining practice effects of the CBB have demonstrated significant practice effects between the first and second assessments (33), and particularly in older adults, rapid practice effects have been observed between the first and second sessions even in large sample sizes (34). Given that changes in cognitive function in this study were not associated with reward acquisition, we cannot completely rule out the possibility that the changes in cognitive function observed in this study were due to the effects of CBB training rather than the intervention of Vitality.

Finally, although no adverse events were reported during the implementation of the intervention, indicating its safety, the measurement protocol requires further consideration. The completion rate for the two measurements reported in this study (67%) was not particularly high compared to similar pilot studies (17,35), suggesting that the methods used to measure outcomes warrant further review. Although CBB was primarily administered in person in this pilot study, it has been demonstrated that CBB performs similarly regardless of the setting (34); therefore, the follow-up assessment will be conducted entirely online, and we will also examine the impact of the assessment format on dropout rates.

This study had several limitations. First, this study did not have a control group. Therefore, we cannot know if the improvements in cognitive function came from the intervention itself, practice effects, natural changes over time, or regression to the mean. Our findings do not prove a cause-and-effect relationship, so we must interpret them carefully as preliminary results. Second, we did not measure physical activity levels before the study. Thus, we could not see how much the program changed participants’ physical activity. This study showed that cognitive scores improved after a real-world mobile health program. However, in the future, we need randomized controlled trials with objective measures of physical activity to check the program’s real effects and mechanisms.

In conclusion, participation in Vitality contributed to improvements in CBB scores among participants aged 60 and older; however, these cognitive improvements cannot be explained solely by a clear short-term association with rewards earned through the app.

Acknowledgments

We are grateful to the staff at Sumitomo Life Insurance Company for their assistance with data collection. We also thank all the participants who took part in this study.

Footnote

Peer Review File: Available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-2026-0018/prf

Funding: This study was supported by a joint research grant from Sumitomo Life Insurance Company.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-2026-0018/coif). All authors report that this study was supported by a joint research grant from Sumitomo Life Insurance Company. T.H. and T.S. are full-time employees of Sumitomo Life Insurance Company. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Graduate School of Health Sciences, Kobe University (Approval No. 1277-2). Informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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doi: 10.21037/mhealth-2026-0018
Cite this article as: Nakayama Y, Sonoda Y, Masumoto K, Harada K, Uchida A, Kondo N, Harada T, Sawada T, Kowa H, Akisue T. Changes in cognitive function among older adults aged 60–79 without dementia following use of the mHealth app “Vitality Wellness Program”: a prospective single-group intervention trial. mHealth 2026;12:26.

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