For young women with little exercise habits, establishing exercise habits from a young age is important for preventing lifestyle-related diseases and frailty. This study aimed to examine effective methods for establishing walking as a daily habit and was conducted on 74 female students belonging to a junior college in Fukuoka Prefecture. The intervention was divided into three periods (2 weeks each) from July to December 2023. In the first period, participants wore a pedometer but were unable to check their step count, and in the second period, they were asked to go about their daily lives while being able to check their step count. In the third period, participants were divided into four groups, and a step count ranking and a footrace were displayed. The control group (living a normal life) was compared with a control group (living a normal life) that combined feedback and chat communication. Step counts were measured at the end of each period, and the average number of steps significantly increased from period 1 to period 2 (4,494±1,403 steps/day to 9,581±3,061 steps/day). Furthermore, there was a significant difference between Group 1 (P = 0.02) and Group 3 (P = 0.008) in the additional intervention in period 3. Based on the above, it is believed that an intervention that combines wearing a pedometer, step count rankings and feedback, and SNS is effective in encouraging continued exercise.
Malignant neoplasms (24.3%), cardiovascular disease (14.7%), and cerebrovascular disease (6.6%) are the leading causes of death in Japan [1]. The risk of developing these diseases can be reduced by modifying lifestyle factors, such as maintaining appropriate weight, reducing salt intake, engaging in regular exercise, quitting smoking, and moderating alcohol consumption.
Numerous epidemiological studies have shown that higher levels of physical activity significantly lower the risk of death due to heart and cerebrovascular diseases [2, 3]. A study in the United States reported that engaging in at least 150 minutes of moderate-vigorous exercise per week reduces the incidence and mortality rates of cardiovascular diseases by 20–30% [4].
Conversely, lack of exercise increases the risk of impaired glucose tolerance and hypertension. According to the report “Health Japan 21,” physical inactivity is estimated to contribute to approximately 20,000–50,000 deaths annually [5, 6].
The World Health Organization ranked physical inactivity as the fourth leading risk factor for mortality, and Ikeda identified it as the third leading risk factor for non-communicable disease mortality in Japan (2011) [7].
Physical inactivity is recognized as a significant public health issue in Japan, according to the Ministry of Health, Labour and Welfare. Moreover, the World Health Organization (WHO) ranks it as the fourth leading risk factor for mortality worldwide. Recent data suggest that interventions targeting physical inactivity could reduce the incidence of coronary heart disease by 10% [1].
Furthermore, statistics from 2023 indicate that lifestyle-related diseases account for a significant proportion of the leading causes of death among women [8].
According to surveys conducted from 2010 to 2022, there has been little change in exercise habits among men, whereas there has been a slight increase among women, although their exercise habits remain lower than those of men. The 2022 National Health and Nutrition Survey found that 35.5% of men and 31.5% of women regularly exercised. Particularly, in their 20s, only 18.9% of men and 15.2% of women reported having exercise habits, which is quite low. Additionally, the average number of steps per day showed a decreasing trend, with men averaging 7,445 steps and women averaging 6,417 steps, indicating a particularly low level [5].
Social media interventions are expected to be effective in promoting exercise. For example, message interventions using LINE led to a significant increase in physical activity personalized feedback through the Oura Ring has contributed to an increase of approximately 2,000 steps per day.
Previous studies have suggested that social comparison and peer interaction can enhance exercise motivation. Social networking services (SNS) allow participants to share progress and receive feedback, which may foster both competitiveness and mutual encouragement. Therefore, combining step count feedback with SNS-based communication could be a promising approach to promote exercise adherence among women with low activity levels.
This study aimed to examine whether providing step count feedback and rankings via social media, combined with chat interactions among participants, can promote exercise among young women with low exercise habits.
Study Design and Subjects
Participants were recruited for an intervention study using a poster display campaign that targeted 74 female first- and second-year students attending a junior college in Dazaifu City, Fukuoka Prefecture. The study protocol comprised three phases (Figure 1).
・Phase 1 (2 weeks): All participants taped the cover of their pedometer, preventing them from seeing their step counts, and engaged in their usual daily activities.
・Phase 2 (2 weeks): The tape was removed, allowing the participants to see their step counts while continuing their usual daily activities.
・Based on the step counts from Phase 2, participants were randomly assigned to one of four groups (control and intervention groups Group 1, Group 2, and Group 3). However, to minimize potential bias due to exercise habits, participants were assigned to the groups in a manner that ensured each group had an equal distribution of physical activity levels. Specifically, participants with higher step counts in Phase 2 were evenly distributed across intervention groups Group 1, Group 2, and Group 3, while participants with lower step counts were also assigned to the groups in a way that maintained balance across the groups. This approach ensured that each group had a comparable baseline activity level. Subsequently, each intervention group, excluding the control group, was instructed to walk an additional 3,000 steps per day as part of the exercise intervention.
・Control group: The participants maintained their usual daily activities while wearing a pedometer.
・Intervention Group 1: Weekly feedback was provided on total steps and rankings of the past few days via Microsoft Teams Chat every Wednesday and Sunday.
・Intervention Group 2: Exercise encouragement and interaction through Microsoft Teams Chat.
・Intervention Group 3: Received both ranking feedback and chat-based interactions (Group 2 + Group 3) (Figure 2).
Ranking and Step Count Feedback (Group 1 and Group 3). Exercise-related Interaction via Chat (Group 2 and Group 3). SNS: Social networking services.
Intervention groups Group 1 and Group 3 were required to send a photograph of their step count report either before bed or the following morning daily. A survey of lifestyle and exercise status was conducted at baseline and at the end of Phases 1, 2, and 3 using Microsoft Forms.
In July 2023, 313 female junior college students were recruited through posters, and 74 individuals who provided consent after receiving prior explanations were selected as the participants (Figure 3). The recruitment period was from July 13 to October 12, 2023, with Phase 1 conducted from October 26 to November 8, Phase 2 from November 9 to November 22, and Phase 3 from November 24 to December 7.
At baseline, data on age, exercise habits, stage of behavioral change regarding exercise, sleep duration, breakfast consumption, living arrangements, commuting methods, and weekday sedentary time were collected.
At the end of each phase, the participants were asked about their awareness of step counts, the impact of pedometer use and monitoring, exercise motivation after the intervention, and participation status in each group.
Step counts were measured using a pedometer with an accelerometer (Life corder® Gs) that was worn at the waist. Comparisons were made using the median values during the study period (Figure 4).
Ethical Considerations
Approval for the study was obtained from the Ethics Committee of the University of Occupational and Environmental Health, Japan (R4-076), and written and verbal consent was obtained from all participants.
Statistical Analysis
Fisher’s exact, Kruskal-Wallis, and Wilcoxon tests were used for baseline and between-group comparisons. Within-group changes and intervention effects were analyzed using a two-way repeated measures analysis, and awareness of step count was assessed using Bowker’s test (significance level of 5%). JMP® Pro 18 software was used for data analysis. Data with <100 steps per day were excluded as “forgotten” [5].
Baseline Characteristics
No significant differences were observed among the four groups. Approximately 56.8% of the participants reported being indifferent to their daily step counts and 62.2% stated that they had no exercise habits. The main reasons for not having exercise habits were “being too busy” and “finding it troublesome.” Sedentary time accounted for approximately 65% of the weekday time (Tables 1–1 and Table 1–2).
| Total (N=74) | Control (N=18) | Intervention 1 (N=19) | Intervention 2 (N=19) | Intervention 3 (N=18) | P-value | |
|---|---|---|---|---|---|---|
| n (%); mean ± SD | n (%); mean ± SD | n (%); mean ± SD | n (%); mean ± SD | n (%); mean ± SD | ||
| Age (years) | 19.0±1.0 | 18.7±0.5 | 18.9±0.8 | 19.1±0.8 | 19.3±1.5 | 0.37 |
| Awareness of step count | 0.49 | |||||
| No | 42 (56.8%) | 11 (60.0%) | 9 (50.0%) | 12 (70.0%) | 9 (50.0%) | |
| Yes | 32 (43.2%) | 7 (40.0%) | 10 (80.0%) | 6 (30.0%) | 9 (50.0%) | |
| Exercise habit | 0.32 | |||||
| No | 46 (62.2%) | 7 (38.9%) | 10 (52.6%) | 7 (36.8%) | 4 (22.2%) | |
| Yes | 28 (37.8%) | 11 (61.1%) | 9 (47.4%) | 12 (63.2%) | 14 (77.8%) | |
| Reasons for not exercising (multiple answers) | ||||||
| Too busy | 19 (41.3%) | 2 (18.2%) | 2 (22.2%) | 3 (25.0%) | 8 (57.1%) | |
| Too much trouble | 15 (32.6%) | 3 (27.2%) | 4 (44.4%) | 5 (41.7%) | 3 (21.4%) | |
| Do not like exercise | 12 (26.1%) | 2 (18.1%) | 2 (22.2%) | 6 (50.0%) | 2 (14.3%) | |
| No exercise facilities | 12 (26.1%) | 0 (0.0%) | 3 (33.3%) | 5 (41.2%) | 2 (14.8%) | |
| Too hot / Too cold | 6 (1.3%) | 0 (0.0%) | 1 (11.1%) | 4 (33.3%) | 1 (7.1%) | |
| Dislike sweating | 4 (8.7%) | 0 (0.0%) | 1 (11.1%) | 3 (25.0%) | 0 (0.0%) | |
| Do not feel the need | 3 (6.5%) | 6 (54.5%) | 1 (11.1%) | 0 (0.0%) | 2 (14.3%) | |
| Others | 2 (4.3%) | 1 (9.1%) | 0 (0.0%) | 1 (8.3%) | 0 (0.0%) | |
| Exercise purposes (multiple answers) | ||||||
| Hobby / Enjoyment | 11 (39.3%) | 5 (71.4%) | 3 (30.0%) | 2 (28.6%) | 1 (25.0%) | |
|
Health / Maintaining physical fitness |
10 (35.7%) | 3 (42.9%) | 5 (50.0%) | 1 (14.3%) | 1 (25.0%) | |
| Long-standing habit | 8 (28.6%) | 1 (14.3%) | 3 (30.0%) | 3 (42.9%) | 1 (25.0%) | |
| Weight loss | 8 (28.6%) | 2 (28.6%) | 2 (20.0%) | 2 (28.6%) | 2 (50.0%) | |
| Body shape /Appearance | 5 (17.9%) | 2 (28.6%) | 3 (30.0%) | 0 (0.0%) | 0 (0.0%) | |
| Muscle strengthening | 4 (14.3%) | 1 (14.3%) | 1 (10.0%) | 1 (14.3%) | 1 (25.0%) | |
| Socializing with friends | 3 (10.7%) | 1 (14.3%) | 1 (10.0%) | 1 (14.3%) | 0 (0.0%) | |
| Preparing for competitions | 1 (3.6%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (25.0%) | |
| Injury rehabilitation | 1 (3.6%) | 1 (14.3%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |
| Others | 6 (21.4%) | 0 (0.0%) | 1 (40.0%) | 1 (14.3%) | 1 (25.0%) | |
| Exercise behavior stages | 0.68 | |||||
| No interest | 14 (18.9%) | 1 (5.6%) | 3 (15.8%) | 8 (42.1%) | 2 (11.1%) | |
| Plan to start (not in 6 months) | 8 (10.8%) | 2 (11.1%) | 2 (10.5%) | 2 (10.5%) | 2 (11.1%) | |
| Plan to start (within 6 months) | 4 (5.4%) | 2 (11.1%) | 1 (5.3%) | 0 (0.0%) | 1 (5.6%) | |
| Occasionally | 31 (41.9%) | 7 (38.9%) | 8 (42.1%) | 6 (31.6%) | 10 (55.6%) | |
| Less than 6 months | 6 (8.1%) | 2 (11.1%) | 2 (10.5%) | 1 (5.3%) | 1 (5.6%) | |
| More than 6 months | 11 (14.9%) | 4 (22.2%) | 3 (15.8%) | 2 (10.5%) | 2 (11.1%) | |
| Step count tracking | 0.90 | |||||
| Track steps | 38 (51.4%) | 9 (50.0%) | 10 (52.6%) | 11 (57.9%) | 8 (44.4%) | |
| Do not track steps | 36 (48.6%) | 9 (50.0%) | 9 (47.4%) | 8 (42.1%) | 10 (55.6%) | |
| Weekly average steps of trackers | ||||||
| <4,000 steps | 2 (5.6%) | 2 (22.2%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |
| 4,001–5,000 steps | 3 (7.9%) | 1 (11.1%) | 2 (20.0%) | 0 (0.0%) | 0 (0.0%) | |
| 5,001–6,000 steps | 6 (15.8%) | 1 (11.1%) | 2 (20.0%) | 0 (0.0%) | 3 (37.5%) | |
| 6,001–7,000 steps | 3 (7.9%) | 0 (0.0%) | 0 (0.0%) | 2 (18.2%) | 1 (12.5%) | |
| 7,001–8,000 steps | 11 (28.9%) | 3 (33.3%) | 3 (30.0%) | 5 (45.5%) | 0 (50.0%) | |
| 8,001–9,000 steps | 3 (7.9%) | 0 (0.0%) | 1 (10.0%) | 2 (18.2%) | 0 (0.0%) | |
| 9,001–10,000 steps | 1 (2.6%) | 1 (11.1%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |
| >10,000 steps | 3 (23.7%) | 1 (11.1%) | 2 (20.0%) | 2 (18.2%) | 4 (0.0%) | |
Continuous variables are presented as mean ± standard deviation, and categorical variables are presented as numbers (%).
| Total (N=74) | Control (N=18) | Intervention 1 (N=19) | Intervention 2 (N=19) | Intervention 3 (N=18) | P-value | |
|---|---|---|---|---|---|---|
| n (%); mean ± SD | n (%); mean ± SD | n (%); mean ± SD | n (%); mean ± SD | n (%); mean ± SD | ||
| Average sleep per day | 0.53 | |||||
| <5 hours | 11 (14.9%) | 4 (22.2%) | 3 (15.8%) | 3 (15.8%) | 1 (6%) | |
| 5–6 hours | 31 (41.9%) | 7 (38.9%) | 6 (31.6%) | 10 (52.6%) | 8 (44%) | |
| 6–7 hours | 25 (33.8%) | 4 (22.2%) | 7 (36.8%) | 6 (31.6%) | 8 (44%) | |
| >7 hours | 7 (9.5%) | 3 (16.7%) | 3 (15.8%) | 0 (0.0%) | 1 (6%) | |
| Breakfast | 0.59 | |||||
| Eat | 61 (82.5%) | 16 (90.0%) | 14 (80.0%) | 15 (80.0%) | 16 (90.0%) | |
| Do not eat | 13 (17.6%) | 2 (20.0%) | 5 (26.3%) | 4 (21.1%) | 2 (20.0%) | |
| Living arrangement | 0.37 | |||||
| Dormitory | 36 (48.6%) | 8 (44.4%) | 11 (57.9%) | 8 (42.1%) | 9 (50.0%) | |
| Parents’ house | 34 (45.9%) | 7 (38.9%) | 7 (36.8%) | 11 (57.9%) | 9 (50.0%) | |
| Living alone | 4 (5.4%) | 3 (16.7%) | 1 (5.3%) | 0 (0.0%) | 0 (0.0%) | |
| Travel time | ||||||
| Walking/Cycling time (min) | 19.9±16.6 | 14.9±9.1 | 22.6±20.4 | 20.7±18.8 | 21.0±15.4 | 0.52 |
| Sitting time (car/train/bus/station) (min) | 18.6±31.9 | 14.7±29.6 | 18.4±42.8 | 30.8±32.7 | 9.7±15.8 | 0.23 |
| Standing time (train/bus/station) (min) | 3.7±8.8 | 1.7±3.8 | 2.6±6.5 | 6.8±14.1 | 3.7±7.2 | 0.31 |
| Sitting, Standing, Walking (%) | ||||||
| Sitting (%) | 68.4±11.6 | 69.4±10.0 | 70.0±9.9 | 68.9±8.1 | 65.2±16.9 | 0.73 |
| Standing (%) | 12.8±6.6 | 15.0±8.4 | 13.0±8.0 | 12.1±4.5 | 10.6±4.2 | 0.21 |
| Walking (%) | 17.9±6.2 | 15.6±5.4 | 17.2±5.9 | 19.0±5.4 | 19.7±7.8 | 0.22 |
| Sitting Time(%) (Walking Hours) | 0.36 | |||||
| Daily Sitting (%) | 65.1±10.7 | 66.1±10.5 | 63.7±11.9 | 67.9±12.1 | 62.5±7.7 |
Continuous variables are presented as mean ± standard deviation, and categorical variables are presented as numbers (%).
Change in Step Count
・Unable to See Step Counts vs. Able to See Step Counts
In Phase 1 (Step count not available), the average step count was 4,494 steps, whereas in Phase 2 (Step count available), it increased to 9,207 steps, showing a significant increase of approximately 4,713 steps after the pedometer display became visible (P < 0.001) (Figure 5).
The average step count in Phase 1 (Step count not available) was 4,494 steps, whereas in Phase 2 (Step count available), it increased to 9,207 steps, showing a significant increase of approximately 4,713 steps after the pedometer display became visible (P<0.001).
・Comparison of Intervention Effects
In intervention groups Group 1 (from 10,224 to 11,203 steps) (P=0.12), Group 2 (from 9,426 to 9,871 steps) (P=0.28), and Group 3 (from 9,441 to 10,338 steps) (P=0.13), the increase from Phase 2 did not reach statistical significance (P=0.12–0.28). However, the control group showed a significant increase from 9,207 to 10,185 steps (P=0.02) (Figure 6).
In intervention groups Group 1 (10,224 → 11,203 steps, P=0.12), Group 2 (9,426 → 9,871 steps, P=0.28), and Group 3 (9,441 → 10,338 steps, P=0.13), the increase from Phase 2 was not statistically significant (P=0.12–0.28). In contrast, the control group showed a significant increase from 9,207 to 10,185 steps (P=0.02).
・Comparison of the mean differences between the control and intervention groups.
Comparing the mean values between the control and intervention groups revealed significant or marginally significant differences. The mean differences were 1,062 steps in Group 1 (P = 0.02), 1,191 steps in Group 3 (P = 0.008), and -823 steps in Group 2 (P = 0.07) (Table 2).
| Group | N | Median [IQR] | Mean ± SD | P-value | Effect size r | |
|---|---|---|---|---|---|---|
| Control | 18 | 8,165 | [6,088–10,848] | 8,807±731 | ― | ― |
| Group 1 | 19 | 10,318 | [9,743–12,498] | 11,203±2,733 | 0.02 | 0.38 |
| Group 2 | 19 | 10,154 | [8,267–11,003] | 9,915±2,542 | 0.07 | 0.29 |
| Group 3 | 18 | 9,908 | [8,493–12,662] | 10,385±2,515 | 0.008 | 0.44 |
| Combined Group | 56 | 10,220 | [8,881–12,146] | 10,504±2,609 | 0.0096 | 0.30 |
Comparison of the difference in the average number of steps between the control group and post-intervention groups (Groups 1, 2, and 3). IQR: Interquartile Range, SD: Standard deviation.
Survey on Lifestyle and Exercise Status
1) Awareness of Step Counts
Even when wearing the pedometer, awareness increased and further improved when step counts became visible (from 66.2% in Phase 1 to 83.8% in Phase 2, P=0.03). Among the intervention groups, Group 2 showed a tendency toward an increase (P=0.07).
2) Exercise Motivation
A total of 82.4% of the participants reported that using a pedometer increased their exercise motivation and 70.3% reported an improvement when their step count was visible.
After the intervention, 89.5%, 84.2%, and 100% of the participants in groups Group 1, Group 2, and Group 3, respectively, and 88.9% in the control group reported increased exercise motivation. Notably, Group 3 showed the highest response of “I was able to engage actively” (P<0.01) (Figure 7).
Changes in participants’ perception of their daily step count before and after each stage. Perception significantly increased after using a pedometer (P<0.01) and after step count visualization (P=0.03).
Effect of Step Count Monitoring
The number of steps taken by the 74 participants nearly doubled from 4,494 steps (when the pedometer was not visible) to 9,207 steps (when the pedometer was visible, P<0.001), exceeding the average reported in the National Health and Nutrition Examination Survey [5]. These results suggest that visualizing step counts may increase motivation to engage in physical activity more than simply using a pedometer. Furthermore, being able to see step counts increased awareness and motivation to exercise. This is consistent with previous research showing that activity monitoring using pedometers has a positive impact on exercise motivation and activity levels [9]. For example, Lee et al (2012) reported that using a pedometer led to increased physical activity among participants, and that conscious monitoring of step counts had a strong impact on motivation [2].
Furthermore, a comparison of the mean differences between the control and intervention groups revealed a significant difference in the group that received feedback and chat interaction. This suggests that feedback via social media also contributed to increased physical activity in a study conducted by Tong et al (2018) [10], and is consistent with our findings that raising awareness through the use of pedometers is effective in promoting exercise [9].
Effects of the Additional Interventions
All participants reported improved exercise motivation and increased levels of proactiveness. This finding is consistent with previous research suggesting that interventions utilizing social media and competition can enhance motivation [11]. The increase observed in the control group may be due to a sense of competition among participants. In this regard, Futami et al (2017) demonstrated that competition and social comparison play an important role in enhancing motivation, potentially explaining the improvement observed in the control group [9]. Furthermore, it is not only the use of pedometers that increases motivation; the influence of competition and feedback via social media also influences motivation. Notably, Group 3 had the highest response rate of “being able to actively participate” (P<0.01), suggesting that interactions via social media may have contributed to increased motivation. This result is consistent with previous research demonstrating the effectiveness of social media interventions for health promotion [12]. Furthermore, while the use of pedometers alone may not lead to a significant increase in physical activity, other studies have pointed out that combining them with chat interactions may lead participants to more proactive behavior [10].
Limitations of this Study
This study has several limitations. First, the participants were limited to female junior college students, which limits the generalizability of the findings to other populations. Second, the intervention period was only two weeks, which may have been insufficient to achieve the full effects of the program. Third, information exchange among classmates may have influenced the results across the groups. In addition, chat-based interactions were limited to communication between participants and the facilitator, and sufficient participant-to-participant support and engagement may not have been established.
Although not analyzed in this study, future research could examine step count increases rather than absolute values, and compare all intervention groups combined with the control group to further clarify the intervention effect.
Wearing a pedometer may have influenced exercise motivation, leading to an increase in step count. Furthermore, additional interventions such as ranking feedback via social media and chat led to a significant increase in step count. Therefore, combining a pedometer with an exercise intervention via social media may be an effective method for encouraging participants to exercise regularly.
We deeply appreciate all the participants who cooperated with and participated in this study.
There are no conflicts of interest to disclose for this study.
The datasets generated and/or analyzed during the current study are not publicly available due to privacy and ethical restrictions but are available from the corresponding author on reasonable request.
