Changes in physical function,pain and quality of life following app-based exercise intervention: A single-arm interventional cohort study

Abstract

Background

The prevalence of insufficient physical activity among adults has increased globally, driving the demand for remote exercise support. The KOJI AWARENESS (KA) program enables self-assessment and provides corrective exercise routines without professional supervision. In this study, we hypothesized that an 8-week KA telemedicine program would be associated with changes in physical function, pain, fatigue, and EuroQol-5D-5L (EQ-5D-5L), and we tested this hypothesis accordingly.

Methods

This study involved 60 healthy adults aged 20–70 years, from April 2024 to February 2025. This was a single-arm, interventional cohort study without a control group. All participants completed an 8-week individually prescribed exercise program based on their application-based self-screening test scores (KA scores). The pain, KA scores, Brief Fatigue Inventory (BFI), and EQ-5D-5L were assessed before and after exercise.

Results

The KA scores increased at 8 weeks (before vs. after 8 weeks, p < 0.001, r_rb = 0.94), whereas the pain scores decreased significantly (before vs. after 8 weeks, p < 0.05, r_rb = -0.51). The BFI score significantly decreased after 8 weeks, (before vs. after 8 weeks, p < 0.05, r_rb = -0.42), but the EQ-5D-5L score showed no significant change.

Conclusion

Changes in physical function and BFI scores were observed over the 8-week study period; however, these changes did not reach a minimum clinically important difference. Furthermore, no significant differences were observed in EQ-5D-5L scores, suggesting a possible ceiling effect. The results should be interpreted with caution because of the lack of a control group and inherent biases.

Keywords

KOJI AWARENESS self evaluation self care mobile application telemedicine

Introduction

Worldwide, the proportion of adults with insufficient physical activity levels is expected to increase from 23.4% (approximately 900 million people) in 2000 to 31.3% (approximately 1.8 billion people) in 2022.¹ Exercise is widely recognized as the most effective intervention for enhancing muscle strength and general health.^2,3 However, several factors have been reported to hinder the continuation of exercise, including limited access to exercise facilities, financial constraints, and lack of time.^4–7 Addressing these barriers has led to an increasing demand for remote and continuous exercise support as a healthcare service that is accessible to everyone, regardless of location.^1,8,9

Telemedicine healthcare services that utilize internet have gained significant attention during the coronavirus disease pandemic. Mobile applications providing exercise interventions and mindfulness techniques have been developed to improve pain and psychological outcomes. For instance, the Kaia app provides individualized exercises based on self-reported data such as medical history and pain distribution, thereby contributing to improvements in pain and mental health.¹⁰ Similarly, Hinge Health has been reported to achieve significant clinical benefits by integrating remote personal coaching with video-guided exercise sessions.¹¹ While these platforms have demonstrated efficacy in reducing pain and anxiety, most existing interventions, including those for healthy adults, rely on professional supervision or specialized equipment such as yoga mats and resistance bands.^12,13 Furthermore, the personalization of these apps is largely restricted by algorithms based on self-reported surveys. There are limited examples of digital platforms that can replicate objective and dynamic physical function assessments (e.g., measuring the range of motion or muscle strength) typically performed by clinicians in person. Therefore, validating a fully autonomous, equipment-free system that integrates objective assessments with individualized prescriptions remains a significant academic and clinical gap.

KOJI AWARENESS (KA) is a self-corrective exercise program that includes tests to assess physical function and prescribes exercises based on the test results.^14,15 While a previous evaluation of the KA self-screening movement test (KA test) reported an intraclass correlation coefficient of 0.876, the wide 95% confidence interval (CI; 0.434–0.981) suggested some variability in measurement stability.¹⁴ Nevertheless, the KA self-screening movement test score (KA score) showed moderate to high correlation (r = 0.609; p < 0.001) with the Functional Movement Screen (FMS).¹⁶ Previously, improvements in pain after completing up to 2 weeks of KA corrective exercises were demonstrated.¹⁴ Previous studies have employed intervention periods of several weeks to evaluate the changes in physical function. In resistance training research, intervention durations of approximately 8 weeks have been commonly used, with improvements in muscle strength reported.^17,18 Furthermore, systematic reviews have indicated that stretching interventions, which contribute to improvements in flexibility, are typically conducted over several weeks, with many studies employing intervention periods of approximately 3–8 weeks.¹⁹ These findings suggest the need to evaluate the effects of an 8-week intervention to capture the medium-term benefits of sustained exercise. However, the impact of performing both assessments and exercises independently using the KA telemedicine healthcare application over 8 weeks remain unclear.

We hypothesized that the KA application of autonomous assessment and exercise guidance would be associated with changes in physical function, pain, fatigue, and EuroQol-5D-5L (EQ-5D-5L) in the medium term. Given that this was an exploratory pilot study to evaluate the feasibility of this application for larger-scale trials, we investigated the potential utility of implementing corrective exercises for 8 weeks using the KA telemedicine healthcare application on physical function, pain, fatigue, and Eq5D5L. We focused on the persistence and variation of the intervention effects over the medium term.

Methods

Participants

This single-arm interventional cohort study was conducted between April 2024 and February 2025 using the KA telemedicine healthcare application, which participants accessed at their preferred times and locations. Ethical approval for this study was granted by the research ethics committee of the participating institutions (protocol ID: M2023-387). This study adhered to the ethical principles outlined in the Declaration of Helsinki (52nd World Medical Association General Assembly, Edinburgh, Scotland, October 2024) for research involving human participants. Participants were recruited through an information poster for the study and written informed consent for using the KA telemedicine healthcare application was obtained from all participants prior to enrollment. Eligible participants were excluded if they had been instructed by a doctor to restrict their physical activity, had severely impaired physical function, performed corrective exercises fewer than three times at 2-week intervals to ensure repeated engagement with the intervention,^20,21 or did not complete the 8-week program, or lacked self-assessment data (Figure 1).

Figure 1.

Flowchart of participant selection.

Intervention protocol

Each participant self-administered the KA test three times to verify the effect of the KA self-corrective exercise routine: 1) immediately after enrollment in the study, 2) 2 weeks after performing the intervention, and 3) 8 weeks after performing the intervention. For the exercise intervention, each participant was provided with an individualized corrective exercise program via the KA telemedicine healthcare application tailored to the specific shortcomings identified through the screening test. On the day after the first KA test was completed, the participants were assigned an 8-week intervention that they performed at home every second day, six times over 2 weeks, repeated for four sets, and at a rate of three sets of eight repetitions for each session.

KA self-screening movement test and self-corrective exercises

The KA telemedicine healthcare application was created to support both the implementation and documentation of the KA test and the KA self-corrective exercise routine. It is accessible via any type of Internet-connected device including smartphones, tablets, and laptops. It provides instructional videos in which the procedures and scoring methods for both the KA test and self-corrective exercises are demonstrated. The participants could conveniently access these videos. The videos were reviewed as required. The KA test was considered complete when the participants performed the test according to the application guidance and entered the results. Exercise sessions were considered completed upon playback and completion of the instructional video demonstrating the exercise procedure. The KA telemedicine healthcare application was programmed to automatically record the completion time of each KA test and log the number of exercise sessions performed. However, beyond these automated records, there was no mechanism for monitoring adherence or exercise quality in real-time, and the actual variability in the intervention dose was not manually tracked.

Detailed descriptions of the KA test have been reported previously.¹⁶ The participants used a checklist consisting of 11 items to assess the function of each body region scored on a 50-point scale. Higher scores indicated better physical function. The scoring process was automated using the KA Telemedicine Healthcare application. Each participant was assessed three times, and the best scores were recorded. This approach was adopted to capture the participants’ maximal functional capacity by minimizing the influence of fatigue or suboptimal initial effort, which is consistent with the standard protocol of the FMS²² and our previous study.²³ In general, the self-assessment can be completed within 30 min. After completing the KA test, the participants were shown their own scores and feedback was provided by comparing the results with the age-specific average values.

The KA self-corrective exercises have been previously described.¹⁴ The exercise program was designed to correspond to each of the 11 components of the KA test. Participants were assigned exercises for items in the KA test for which their scores declined. For example, appropriate exercises are prescribed when limited neck flexibility is identified. Before beginning the intervention, the procedures for performing the exercises were fully explained to all participants under the supervision of the KA telemedicine healthcare application. Exercise implementation was displayed using a biweekly calendar, in which completed days were highlighted to allow participants to visually track their adherence.

Assessment tools

Information on the participants’ age, sex, height, weight, and body mass index was collected through self-reports via the application. In addition, the participants reported outcome measures, including pain, Brief Fatigue Inventory (BFI),²⁴ and EuroQol-5D-5L (EQ-5D-5L) scores,²⁵ before beginning the prescribed exercise interventions and at 2 and 8 weeks after beginning the intervention. The visual analog scale was used to assess the pain level of the participants, with total scores ranging from 0 to 100 points, with 0 representing no pain and 100 representing the most severe pain. The participants could also select multiple sites of pain, and the values representing the most severe pain were used for the analysis. The BFI was used to assess the fatigue status of participants. This tool has nine questions, scored 0–10 points each, with a possible total score of 90 points; higher scores indicate greater fatigue. The EQ-5D-5L was used to assess health-related quality of life. The validated Japanese version of the EQ-5D-5L²⁶ was self-administered and utility scores were calculated using the Japanese value set.

Statistical analysis

Participant characteristics, including age, sex, BMI, and the number of exercise sessions performed every 2 weeks, were summarized using descriptive statistics. The KA test was designated as the primary outcome, whereas pain, BFI, and EQ-5D-5L were defined as secondary outcomes. The normality of the distribution of each variable was confirmed using a histogram and the Shapiro–Wilk test. Values for each variable are expressed as mean ± 95% CI. The Friedman test was used to examine the differences across the three time points for the scores recorded for pain, BFI, EQ-5D-5L, and KA. When the Friedman test indicated statistical significance, post hoc analyses were conducted using pairwise Wilcoxon signed-rank tests with Bonferroni correction for multiple comparisons. To assess the magnitude of the intervention effect, rank-biserial correlation (r_rb) was calculated as the effect size for each pairwise comparison. In addition, Spearman’s rank correlation coefficients (ρ) were calculated to examine the association between the change in each outcome from before exercise to 8 weeks and baseline characteristics (age, sex, BMI, and before exercise scores). In addition, intention-to-treat (ITT) analysis was conducted for sensitivity analysis. For the ITT analysis, a linear mixed model (LMM) was used to account for missing data, including all participants who provided baseline data. Similar to the primary analysis, post-hoc pairwise comparisons were performed with Bonferroni correction, and effect sizes were calculated as Cohen’s d using the model’s residual standard deviation. Statistical significance was set at p < 0.05. Data were analyzed using R version 4.4.2 with RStudio (Posit Team, 2025). RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA, USA. https://posit.co/.

Results

In total, 82 of the initial 150 participants completed the 2nd-week screening. Between 2 and 8 weeks, 22 participants were excluded because of missing final self-check data. Consequently, 60 participants (24 men and 34 women, aged 20–70 years) completed the 8-week program and were included in the analysis (Figure 1). No adverse events were reported during the 8-week intervention. The participants’ age, sex, height, weight, body mass index, and the number of exercises performed are presented in Table 1.

Table 1.

Characteristics of the study participants.

	Male	Female	Total
	n = 24	n = 34	n = 60
Age, years	48.9	49.6	49.3
Age, years	(45.2-52.6)	(47.2-51.2)	(47.3-51.3)
Height, cm	175.0	160.0	166.0
Height, cm	(173.0-175.0)	(157.0-162.0)	(164.0-168.0)
Weight, kg	74.7	56.6	64.1
Weight, kg	(71.1-78.2)	(54.0-59.3)	(61.0-67.1)
Body Mass Index	24.39	22.25	23.8
Body Mass Index	(23.34-24.45)	(21.24-23.25)	(22.33-23.84)
Number of exercise
0 - 2 weeks	6.6	6.8	6.7
0 - 2 weeks	(6.3-7.0)	(6.6-7.0)	(6.5-6.9)
2 - 4 weeks	5.9	5.7	5.8
2 - 4 weeks	(5.7-6.1)	(5.4-5.9)	(5.6-5.9)
4 - 6 weeks	5.7	5.8	5.8
4 - 6 weeks	(5.5-6.0)	(5.7-6.0)	(5.6-5.9)
6 - 8 weeks	5.62	5.9	5.8
6 - 8 weeks	(5.3-5.9)	(5.7-6.0)	(5.6-5.9)

Data are presented as mean (95 % CI).

Continuous variables (age, height, weight, body mass index, and number of exercises per 2-week period) were presented as means and 95% CI, and categorical variables (sex) were presented as counts.

KA score

Mean scores for the KA test showed statistically significant changes across all three time points (before exercise, after 2 weeks, and after 8 weeks) during the intervention period: before exercise, 38.1 points (95% CI: 36.3–40.0); after 2 weeks, 41.1 points (95% CI: 39.3–42.8); after 8 weeks, 44.4 points (95% CI: 43.2–45.6); before exercise vs. after 2 weeks, p < 0.001, r_rb = 0.63; before exercise vs. after 8 weeks, p < 0.001, r_rb = 0.94; and after 2 vs. after 8 weeks, p < 0.001, r_rb = 0.75 (Figure 2). While an overall upward trend was observed in these self-reported scores, individual responses varied; most participants showed an increase from baseline to after two weeks (n = 43, 71.7%), followed by further changes after 8 weeks (n = 50, 83.3%). However, inter-individual variability was evident, with some participants exhibiting alternating patterns of increase and decrease, or an overall deterioration in scores from baseline to 8 weeks (n = 5, 8.3%) (Figure S1, Table. S1). Furthermore, the change from baseline to 8 weeks was strongly associated with before exercise KA score and before exercise BFI score; before exercise KA score, ρ = –0.724, p < 0.001, before exercise BFI score, ρ = –0.330, p = 0.010 (Table 2).

Figure 2.

KOJI AWARENESS self-screening movement test scores Changes in KA scores before and after the 8-week self-corrective exercise intervention. The mean values are presented as 95% confidence intervals. **p < 0.001.

Table 2.

Correlations between change scores (0–8 weeks) and characteristics before exercise.

	Spearman’s ρ	p-value
Δ KA score (0–8 weeks)
Age	0.120	0.359
Sex	0.187	0.152
Body Mass Index	0.014	0.914
Before exercise KA score	-0.724	< 0.001
Before exercise Pain score	-0.190	0.146
Before exercise BFI score	-0.330	0.010
Before exercise EQ-5D-5L score	0.204	0.117
Δ Pain score (0–8 weeks)
Age	-0.004	0.977
Sex	0.225	0.084
Body Mass Index	-0.125	0.341
Before exercise KA score	0.050	0.705
Before exercise Pain score	-0.503	< 0.001
Before exercise BFI score	-0.054	0.680
Before exercise EQ-5D-5L score	0.039	0.765
Δ BFI score (0–8 weeks)
Age	0.019	0.885
Sex	0.008	0.949
Body Mass Index	-0.344	0.007
Before exercise KA score	0.028	0.832
Before exercise Pain score	-0.041	0.753
Before exercise BFI score	-0.396	0.002
Before exercise EQ-5D-5L score	0.227	0.082
Δ EQ-5D-5L score (0–8 weeks)
Age	-0.118	0.371
Sex	-0.134	0.306
Body Mass Index	0.115	0.382
Before exercise KA score	0.048	0.716
Before exercise Pain score	0.017	0.897
Before exercise BFI score	0.133	0.312
Before exercise EQ-5D-5L score	-0.626	< 0.001

Continuous variables are analyzed using Spearman’s rank correlation coefficients (ρ), and categorical variables (sex) are analyzed in the same manner. The results are presented as correlation coefficients and p-values. Δ: change from before exercise to 8 weeks.

Pain score

Mean scores for pain showed statistically significant decreases at the 2-week and 8-week time points compared with baseline: before exercise, 31.2 points (95% CI: 24.9–37.4); after 2 weeks of exercise, 24.4 points (95% CI: 18.7–30.2); after 8 weeks, 21.5 points (95% CI: 15.0–27.9); before exercise vs. after 2 weeks, p < 0.05, r_rb = –0.42; before exercise vs. after 8 weeks, p < 0.05, r_rb = –0.51; and after 2 vs. after 8 weeks, p = 0.61, r_rb = –0.22 (Figure 3). While these data indicated an overall change in pain, individual responses varied. Some participants exhibited a decrease in scores (n = 35, 58.3%), whereas others showed no change (n = 12, 20.0%) or even an increase in pain levels (deterioration) (n = 13, 21.7%) over the 8-week period (Figure S2, Table S1). Furthermore, the magnitude of change in pain scores from before exercise to 8 weeks was associated with before exercise pain levels; ρ = –0.503, p < 0.001 (Table 2).

Figure 3.

Visual analog scale scores for pain Changes in pain scores before and after the 8-week self-corrective exercise intervention. The mean values are presented as 95% confidence intervals. *p < 0.05.

BFI score

Mean BFI scores showed a statistically significant decrease at the 8-week time point compared with before exercise during the study period: before exercise, 1.89 points (95% CI: 1.50–2.29); after 2 weeks, 1.75 points (95% CI: 1.34–2.16); after 8 weeks, 1.47 points (95% CI: 1.04–1.89); before exercise vs. after 2 weeks, p = 0.17, r_rb = –0.30; before exercise vs. after 8 weeks, p < 0.05, r_rb = –0.42; after 2 weeks vs. after 8 weeks, p = 0.17, r_rb = –0.30 (Figure 4). Most participants showed a decrease in the BFI scores from baseline to 2 weeks (n = 31, 51.7%). followed by gradual continuation or maintenance of this change for up to eight weeks. However, the individual response patterns varied significantly. Others showed a continuous increase in fatigue level (deterioration) throughout the study period (n = 16, 26.7%). Additionally, some participants showed no substantial change in their scores (n = 8; 13.3%). While the majority of participants exhibited decreases in BFI scores (n = 36, 60.0%), these results highlight the presence of notable inter-individual variability in the scores observed over time (Figure S3, Table S1). Furthermore, weak negative correlations were observed between the change in BMI and before exercise BFI score, BMI, ρ = –0.344, p = 0.007, before exercise BFI scores, ρ= –0.396, p = 0.002 (Table 2).

Figure 4.

Brief Fatigue Inventory scores Changes in Brief Fatigue Inventory (BFI) scores before and after an 8-week self-corrective exercise intervention. The mean values are presented as 95% confidence intervals. *p < 0.05.

EQ-5D-5L score

No statistically significant changes were observed in the mean EQ-5D-5L score between before exercise and the 8-week follow-up: before exercise, 0.94 (95% CI: 0.93–0.96): after 2 weeks, 0.96 (95% CI: 0.94–0.97); after 8 weeks of exercise, 0.95 (95% CI, 0.94–0.97); before exercise vs. after 2 weeks, p = 0.22, r_rb = 0.37; before exercise vs. after 8 weeks, p = 0.39, r_rb = 0.33; after 2 vs. after 8 weeks, p = 1.00, r_rb = –0.07 (Figure 5). Some inter-individual variability was observed in the EQ-5D-5L scores from baseline to 8 weeks; however, most participants showed no overall change at the final assessment (n = 32, 53.3%) (Figure S4, Table S1). A negative correlation was found between EQ-5D-5L changes and its before exercise EQ-5D-5L score, ρ = –0.626, p < 0.001, (Table 2).

Figure 5.

EuroQol-5D-5L scores Changes in EuroQol-5D-5L (EQ-5D-5L) scores before and after the 8-week self-corrective exercise intervention. The mean values are presented as 95% confidence intervals. n.s., not significant.

Result of sensitivity analysis

The results of the sensitivity analysis using ITT analysis were similar to those of the per-protocol analysis (Table S2). The observed changes were consistent across the study population in the ITT analysis using the LMM.

Discussion

In this study, we aimed to investigate the potential utility of implementing corrective exercises for eight weeks using the KA telemedicine healthcare application on physical function, pain, fatigue, and EQ-5D-5L. The results showed that participants, after following the 8-week KA self-corrective exercise program guided by the KA telemedicine healthcare application and without professional supervision, demonstrated no changes in EQ-5D-5L, while exhibiting statistically significant changes in the KA score, pain, and BFI score. The novelty of this study lies in its role as a critical preliminary step toward future Randomized Controlled Trial (RCT). As no adverse events were reported during the 8-week period, the safety and feasibility of an autonomous intervention integrating assessment and exercise implementation were suggested for healthy adults. Furthermore, the observed differences in the sensitivity of the outcome measures over time provide essential guidance for refining the primary endpoints and optimizing the intervention duration. These findings establish a methodological foundation for the rigorous evaluation of digital exercise interventions in broader clinical settings.

In the current study, statistically significant changes in KA scores, which represent physical function, were observed during the 8-week study period. Similarly, subgroup analyses from a systematic review and meta-analysis of untrained populations detected no significant changes in Functional Movement Screen scores at 6 weeks, whereas significant improvements emerged at 8 and 12 weeks,²⁷ which is consistent with the functional changes observed in the present study at 8 weeks. Furthermore, regarding the heterogeneity of individual responses, a negative correlation was observed between baseline functional status and the magnitude of change (ρ = –0.724, p < 0.001). This indicates that the observed statistical changes were primarily driven by participants with lower initial KA scores, whereas those with higher baseline scores exhibited minimal changes. However, it should be noted that the Minimal Clinically Important Difference (MCID) for the KA score has not yet been established. Consequently, although the changes observed in the present study were statistically significant, it remains unclear whether these differences represent clinically meaningful changes in physical function.

Statistically significant changes in pain were observed during the 8-week study period. Our previous report involving healthy adults also identified a statistically significant decrease following a similar 2-week intervention.¹⁴ In the present study, the mean pain score decreased from 31.2 at baseline to 21.5 at 8 weeks, representing a reduction of approximately 31 %. Furthermore, a significant negative correlation was found between the baseline pain score and the magnitude of change (ρ = –0.503, p < 0.001), indicating that participants with higher initial pain experienced more substantial reductions in their scores. While previous literature suggests that a 30–40% reduction may constitute a clinically meaningful improvement,²⁸ and the effect size in this study reached r_rb = –0.51, these results should be interpreted with caution. Given the single-arm design of this study, it is impossible to definitively conclude whether the observed changes represent clinically meaningful changes in pain.

Statistically significant changes in the BFI scores were observed during the 8-week study period. The BFI score is an indicator widely used to evaluate the effects of chemotherapy and exercise interventions in patients with malignant tumors, with the level of fatigue categorized as mild, moderate, or severe.^29,30 For example, in patients with head and neck cancer undergoing radiotherapy, a 6-week exercise program designed by physical therapists that included strength training and stretching significantly reduced BFI scores.³⁰ However, it should be noted that these previous studies primarily focused on clinical populations; therefore, their findings cannot be directly extrapolated to the healthy participants in the present study. The association between BFI changes and baseline characteristics showed only weak negative correlations with baseline BMI (ρ = –0.344, p = 0.007) and baseline BFI scores (ρ = –0.396, p = 0.002). These low coefficients suggest that the influence of baseline status on fatigue reduction was marginal. However, while the MCID for the BFI has been reported to be 1.33,³¹ the changes observed between time points in the present study were approximately 0.43. This suggests that the observed changes may not represent clinically meaningful differences. Furthermore, the effect size for the change between baseline and 8 weeks was r_rb = –0.42, indicating a medium effect size. Given the weak associations and failure to meet the MCID criteria, the observed changes in the BFI in this pilot study may reflect minor individual fluctuations rather than a robust clinical response observed over the study period.

In the current study, while changes were observed in the KA score, pain, and BFI, no statistically significant change was detected in the EQ-5D-5L score. This may be due to the high baseline scores of our participants (mean = 0.94), suggesting a potential ceiling effect.^32,33 Subtle improvements may be difficult to detect in populations with a relatively good baseline health status, subtle improvements may be difficult to detect.³³ The association between EQ-5D-5L changes and baseline status showed a negative correlation (ρ = –0.626, p < 0.001). This suggests a “regression to the mean” effect, where the direction and magnitude of the change were highly dependent on the initial score. Furthermore, it is important to consider that the EQ-5D-5L is a multidimensional instrument that encompasses domains beyond physical symptoms, such as anxiety, depression, and self-care. While the KA self-corrective exercise focused on musculoskeletal function, it may not have been sufficient to influence the broader psychosocial components captured by the EQ-5D-5L within an 8-week period. Therefore, the lack of significant change in this measure reflects the limited scope of our intervention on global health-related quality of life rather than a lack of change in the specific physical domains targeted. Consequently, our findings should be interpreted as being limited to physical health changes rather than general health improvements or disease prevention.

The clinical relevance of this study lies in the observation of significant changes in physical function and fatigue-related outcomes during the intervention period. In the exploratory pilot study, the primary focus was on evaluating the feasibility of the application. Although the magnitude of change may not have fully reached the MCID, the observed statistical significance provides a preliminary clinical signal of the potential utility of the intervention. These findings serve as essential foundational data for future large-scale studies, including RCTs.

This study has several limitations. First, no control group of participants who did not undertake the intervention was included; therefore, attributing the observed effects solely to the intervention itself was difficult. Without a control group, it is possible that the observed changes represent natural progression over the 8-week period, regression to the mean, or measurement of familiarity (learning effects) from repeated self-assessments. Second, several potential biases are inherent to the study design. Selection bias may have been introduced because of the use of informational posters for recruitment, and all outcomes relied on self-reported and self-administered measurements via the same application used for the intervention. Because no blinding or independent verification was performed, there were risks of measurement bias, expectation effects, and common method bias. In addition, adopting the “best value” from multiple assessments may have increased the risk of regression toward the mean and selective outcome reporting. Furthermore, because adherence, exercise quality, and the actual volume of the intervention performed were not monitored, the reproducibility of the intervention protocol remains insufficient. Attrition bias may also have occurred because of the exclusion of participants who did not complete the program or had missing data. Third, the rate of continuation during the 8-week intervention period was 40%. A previous study reported that only 37.3% of athletes adhered to home-based ankle sprain prevention training using mobile application.³⁴ Similarly, the markedly low continuation rate in the present study indicates that adherence remains a key challenge in the implementation of this intervention. Fourth, detailed assessments of physical function, such as range of motion of the joints and muscle strength, were not conducted. Consequently, the specific changes in physical function and the underlying mechanisms associated with the observed changes have not been fully elucidated. Finally, this study is not prospectively registered in a public clinical trial database. While all outcomes were analyzed as pre-specified in the internal protocol, the lack of prospective registration may have limited the perceived transparency of reporting. Given these constraints, the present study should be regarded as an exploratory investigation intended to generate hypotheses for future rigorously designed trials rather than providing definitive evidence of clinical efficacy.

Future research should build on these findings by conducting RCT with healthy adults to rigorously evaluate the efficacy of the intervention used in this study against a control group. Further investigations are required to determine whether such programs can elicit changes in more objective physical outcomes, such as joint range of motion, muscle strength, and postural balance. Subsequent pilot studies are required to explore the applicability of this autonomous digital approach to individuals with specific medical conditions.

Conclusion

In this 8-week pilot study, statistically significant changes in physical function and BFI scores were observed between the baseline and 8-week period among healthy adults. Although the results are encouraging, the lack of a control group and the presence of various inherent biases necessitate a cautious interpretation of these findings. While these preliminary findings suggest the potential utility of digital intervention, further RCTs are necessary to rigorously evaluate its efficacy and confirm the causal relationship between the intervention and the observed improvements.

Supplemental material

Supplemental material - Changes in physical function, pain and quality of life following app-based exercise intervention: A single-arm interventional cohort study

Supplemental material for Changes in physical function, pain and quality of life following app-based exercise intervention: A single-arm interventional cohort study by Hiroki Katagiri, Naoki Shimada, Sho Mitomo, Takehiro Ohmi, Yukio Miyagoshi, Koji Kaneoka, Hiroshi Akuzawa, Gen Kobashi, Ryusuke Saito and Koji Murofushi in Digital Health.

Supplemental material

Supplemental material - Changes in physical function, pain and quality of life following app-based exercise intervention: A single-arm interventional cohort study

Footnotes

Acknowledgements

We would like to thank Editage () for the English language editing and proofreading support.

ORCID iDs

Naoki Shimada

Koji Murofushi

Ethical considerations

Ethical approval for this study was granted by the research ethics committee of the participating institutions (protocol ID: M2023-387). This study adhered to the ethical principles outlined in the Declaration of Helsinki (52nd World Medical Association General Assembly, Edinburgh, Scotland, October 2024) for research involving human participants.

Consent to participate

Participants were recruited through an information poster for the study and written informed consent for using the KOJI AWARENESS telemedicine healthcare application was obtained from all participants prior to enrollment.

Author contributions

All authors contributed to conceptualization and validation, and participated in writing, reviewing, and editing. Hiroki Katagiri and Naoki Shimada conducted the formal analysis and visualization, performed data curation, and wrote the original draft. Koji Murofushi and Ryusuke Saito received funding. Hiroki Katagiri, Sho Mitomo, Takehiro Omi, Yukio Miyagoshi, Koji Kaneoka, Hiroshi Akuzawa, and Koji Murofushi contributed to the study, methodology, and resources. Yukio Miyagoshi developed the software. Koji Murofushi was responsible for project administration and supervision. All the authors have read and approved the final submitted manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the Japan Agency for Medical Research and Development (Grant Number 23le0110027) and JSPS KAKENHI (Grant-in-Aid for Early-Career Scientists, Grant Number 23K15694).

Declaration of conflicting interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Mr. Miyagoshi is the Representative Director of AXIS Co., Ltd., Tokyo, Japan and developed the application used in this study. The authors declare no potential conflicts of interest.

Data Availability Statement

The data that support the findings of this study are available from the Institute of Science, Tokyo, but restrictions apply to the availability of these data, which were used under license for the current study and are not publicly available. The data are available from the authors upon reasonable request and with permission from the Institute of Science, Tokyo, Japan.*

Supplemental material

Supplemental material for this article is available online.

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