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. 2023 Jul 12;13(7):e069523. doi: 10.1136/bmjopen-2022-069523

Compliance with ecological momentary assessment programmes in the elderly: a systematic review and meta-analysis

Lin Yao 1,#, Yiqun Yang 1,#, Zhi Wang 2, Xi Pan 2,✉, Lan Xu 1,✉
PMCID: PMC10347474  PMID: 37438069

Abstract

Objective

Ecological momentary assessment (EMA) refers to the repeated sampling of information about an individual’s symptoms and behaviours, enabling the capture of ecologically meaningful real-time information in a timely manner. Compliance with EMA is critical in determining the validity of an assessment. However, there is limited evidence related to how the elderly comply with EMA programmes or the factors that are associated with compliance.

Design

Systematic review and meta-analysis.

Data sources

PubMed, Embase, the Cochrane Library and Web of Science were searched up to 17 July 2022.

Eligibility criteria

We included observational studies on EMA in the elderly reported in English.

Data extraction and synthesis

Two investigators independently performed screening and data extraction. Discrepancies were resolved by discussion or a third investigator. A systematic review was carried out to characterise the basic characteristics of the participants and EMA programmes. Random-effects meta-analysis was conducted to assess overall compliance and to explore factors associated with differences in compliance among the elderly.

Results

A total of 20 studies with 2047 participants were included in the systematic review and meta-analysis. Meta-analysis showed that the combined compliance rate was 86.41% (95% CI: 77.38% to 92.20%; I2=96.4%; p<0.001). Subgroup analysis revealed high levels of heterogeneity in terms of the methods used to assess population classification, assessment method and assessment frequency, although these may not be the sources of heterogeneity. Meta-regression analysis showed that population classification and assessment period might have a significant impact on heterogeneity (p<0.05). Egger’s test indicated significant publication bias (p<0.001).

Conclusions

Compliance with EMA programmes is high in the elderly. It is recommended that scholars design reasonable EMA programmes according to the health status of the elderly in the future.

Keywords: Ecological momentary assessment, Compliance, Elderly, Meta-analysis

STRENGTHS AND LIMITATIONS OF THIS STUDY.

  • We conducted a comprehensive search and analysis of articles on ecological momentary assessment (EMA) in the elderly to facilitate our understanding of EMA programmes and overall compliance.

  • The quality of the evidence from this study might be limited by the fact that there is a lack of design criteria for EMA programmes and that some studies excluded individuals who did not achieve specific compliance rates.

  • We did not include the grey literature, which could have been useful in our analysis.

Introduction

Ecological momentary assessment (EMA) refers to the repeated sampling of an individual’s symptoms, behaviours, effects or perceptions in the natural environment to obtain data closest to the real situation.1 EMA has been widely used in research related to addictive substance use,2 behaviour3 and psychology.4 Initially, EMA data were collected from paper diaries. With the development of mobile technology in recent years, EMA has incorporated real-time data from electronic and wearable devices. This allows the analysis of complex data by dedicated applications or software packages. Because EMA captures real-time data, it can effectively reduce recall bias in the elderly due to memory loss, cognitive impairment, etc, and is more accurate than retrospective questionnaires or scales. Furthermore, EMA is more ecological as it draws its information primarily from the everyday environment of the elderly, rather than from a controlled laboratory setting. Additionally, EMA provides dense longitudinal data that can be analysed mathematically to understand the complex relationships between variables, such as emotions,5 behaviours,5 6 intentions,6 situations,7 etc.

Although EMA offers many advantages in data collection, this approach may be influenced by the compliance of the elderly with EMA. Even if the assessment method is efficient, low compliance can lead to a reduction in the quantity and quality of data. Therefore, compliance with EMA is critical in determining the validity of an assessment. There are several possible reasons for non-compliance in the elderly. First, the elderly will not always respond to EMA prompts, which can result in data loss and biased results. Furthermore, if the elderly feel burdened by EMA, they may provide inaccurate data. The high-frequency and long-term nature of surveys may cause the elderly to not take the EMA questionnaire seriously, thus leading to the perfunctory provision of data or even the refusal to provide data.8 Second, this method may be too costly to collect data and perhaps too burdensome for the elderly, thus resulting in a small sample size, the insufficient generalisation of experimental results and other problems. Finally, EMA may lead to distorted data due to reactivity. Real-time measurements often prompt the elderly to re-examine their behaviour, which may lead to changes in their behaviour, resulting in measurements that do not truly reflect their true behaviour.

Not only do we need to understand compliance with EMA in the elderly, we also need to explore the factors that influence compliance in this population. Based on current research, we need to develop an appropriate EMA programme for the elderly. In a previous study, Stone et al recommend an 80% compliance rate if EMA is to meet our research study.9 Previous systematic evaluations of EMA compliance have focused on children and adolescents, adults and disease-specific populations.2 3 10 11 For example, the compliance rate was previously reported to be 54.6%–96.21% in children and adolescents, and 38%–98% in adults.3 10 Due to the advantages of EMA and its application in other populations, the use of EMA among the elderly has attracted a great deal of academic attention and many studies have been conducted in different regions to investigate the compliance with EMA in the elderly.12–14 However, the reported compliance with EMA in the elderly varied widely from 36% to 98.33%.14–22 Therefore, it is necessary to conduct studies to investigate the factors responsible for differences in compliance in the elderly with respect to EMA, as this will provide reference guidelines for the effective implementation of EMA in the future.

Differences in compliance may arise from different design aspects of EMA programmes, including assessment method, frequency and the periodicity of assessment. The rapid development of mobile technology has provided highly appropriate conditions for EMA. Data collection using electronic diaries, multimedia devices and wearable devices is far more effective than traditional methods. However, this approach is heavily influenced by the ability of the elderly to use smart devices. In addition, it has been demonstrated that longer prompt intervals reduce compliance, and that compliance decreases as study progresses over time. Therefore, improving the compliance of the elderly with EMA programmes is one of the most important aspects of its implementation. Some studies now suggest that the provision of certain incentives can improve compliance.23 24 Despite the importance of the design factors associated with EMA programmes, few studies have directly investigated the effect of these variables on compliance.

While there have been some reviews focused on the application of EMA in the elderly, these studies had certain limitations. For example, both Cain et al25 and Kim et al4 reviewed studies of the elderly undergoing EMA, but only described individual studies of EMA compliance and did not quantitatively analyse the overall compliance and analyse factors influencing compliance. Although studies have explored how EMA design options may affect compliance, there is a significant lack of uniform design criteria and no specific EMA design options for the elderly. Therefore, in order to provide accurate data on EMA compliance in the elderly, this systematic evaluation and meta-analysis quantitatively investigated the compliance of the elderly with EMA programme and explored the influencing factors to inform the design of EMA programme for the elderly.

Methods

The systematic review and meta-analysis is reported in accordance with the Preferred Reporting Item for Systematic Reviews and Meta-Analysis 2020.

Information sources and search strategy

We performed electronic literature searches of four databases (PubMed, Embase, the Cochrane Library, Web of Science) from inception to 17 July 2022. Relevant references from previously published meta-analysis or systematic reviews were also searched manually. The keyword search formula was as follows: (ecological momentary assessment OR mobile ecological momentary assessment OR ecological momentary intervention OR health momentary assessment OR momentary OR experience sampling methods OR event sampling methods OR daily diary methods OR electronic diary OR ambulatory assessment OR structured diary method OR real-time data capture studies) AND (aged OR elderly OR older OR older adults OR ageing OR aging). See online supplemental appendix A of the supplemental materials for specific search strategies.

Supplementary data

bmjopen-2022-069523supp003.pdf (193.6KB, pdf)

Eligibility criteria

Inclusion criteria were as follows: (1) study type was observational and included cross-sectional studies and cohort studies; (2) age ≥60 years old; (3) study content used EMA; (4) outcome indicators included compliance of the elderly with EMA and (5) publication in the English language. Exclusion criteria were as follows: (1) duplicate publication of study data; (2) study design type was not in accordance with EMA programmes; (3) conferences, reviews, protocols or meta-analyses; (4) literature for which the full text was not available and (5) non-English literature.

Data extraction and quality assessment

Two researchers independently screened the literature against inclusion and exclusion criteria, extracted information and cross-checked the data. Differences in opinion were judged by discussion or by the participation of other researchers (see online supplemental appendix B of supplemental materials for the list of excluded articles). The extracted study data included author, publication date, country, population classification, age, sample size, assessment content, assessment method, assessment period, assessment frequency, incentives and EMA compliance rate.

To assess the quality of each study, we applied the 11 evaluation criteria recommended by the Agency for Healthcare Research and Quality (AHRQ) for cross-sectional studies and the Newcastle–Ottawa Scale (NOS) for cohort studies.26 27 Each of the 11 evaluation criteria recommended by the AHRQ was answered with ‘yes’ (1 point), ‘no’ (0 points) or ‘unclear’ (0 points). The total score was 11 points, with 0–3 indicating low quality, 4–7 indicating moderate quality and 8–11 indicating high quality. The NOS consists of eight items in three dimensions, including subject selection (four items), comparability between groups (one item) and the risk of bias (three items). The scale was 9 points, with 0–4 representing low quality, 5–6 representing medium quality and ≥7 representing high quality.

Data analysis

Statistical analysis was performed using Stata V.15.0 software. Effect sizes (ESs) were obtained by log-transforming the proportion of completed assessments. Compliance rate after conversion was normally distributed. The formula was as follows SE=loge(p/(1−p)), ES=√([(1/np])+[(1/n{1−p}])).2 10 Statistical heterogeneity was judged by p value and I2; if I2<50% or p≥0.05 indicated acceptable heterogeneity among the study results, a fixed-effects model was used for analysis, and conversely, a random-effects model was used for analysis. Subgroup analysis and meta-regression were performed to analyse the source of heterogeneity when heterogeneity was significant. Sensitivity analysis was performed by excluding the included literature one by one to evaluate the stability of the meta-analysis results. Publication bias was evaluated by funnel plots and Egger’s test, and differences were considered statistically significant at p<0.05.

Patient and public involvement

None.

Results

Study selection

A total of 5465 relevant studies were obtained in the initial review; of these, 895 duplicates were excluded and 4570 irrelevant studies were excluded according to the titles and abstracts. The remaining 20 studies were finally included after reading the full text. The detailed study search process is shown in figure 1.

Figure 1.

Figure 1

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Flow chart of literature selection. EMA, ecological momentary assessment.

Study characteristics

In this systematic review, these studies were conducted between 2011 and 2022 across eight countries: nine in America (45%), three in Germany (15%), two in Australia (10%), two in China (10%), one in the UK (5%), one in France (5%), one in Belgium (5%) and one in Switzerland (5%). By population classification, 15 included the general elderly (75%), and 5 included sick people (25%). All 20 studies had a quality evaluation score ≥4. Further details are shown in table 1 and online supplemental table 1.

Table 1.

Characteristics of the included studies

Author Published time Area Study design Population classification Age Sample size Compliance rate (%) Quality score
Compernolle et al15 2021 USA Cross-sectional General population 65–97 342 36 7
Mardini et al24 2021 USA Cross-sectional Knee osteoarthritis ≥65 19 82 5
Hevel et al5 2021 USA Cross-sectional General population 60–98 103 92 6
Zhaoyang et al30 2022 USA Cross-sectional General population 70–91 317 82.75 5
Badal et al18 2022 USA Cross-sectional General population 68–93 22 83.9 6
Chu et al12 2020 China Cross-sectional General population ≥60 82 88.57 4
Liu and Lou23 2019 China Cross-sectional General population 60–69 37 89.2 5
Windsor et al17 2021 Australia Cross-sectional General population ≥84 73 88.6 4
Chui et al13 2014 Australia Cross-sectional General population 84–102 74 96.1 4
Martin et al19 2021 Switzerland Cross-sectional General population 60–91 136 94.41 4
Maes et al6 2022 Belgium Cross-sectional General population 65–86 64 77.7 6
Drewelies et al14 2020 Germany Cross-sectional General population 67–93 87 98.33 5
Kornadt et al16 2021 Germany Cross-sectional General population 66–90 167 92.9 5
Potts et al21 2020 UK Cross-sectional Dementia 61–94 28 73.2 6
Röcke et al20 2011 Germany Cross-sectional General population 72–92 53 89.93 5
Murphy and Kratz32 2014 USA Cross-sectional Knee osteoarthritis 65–90 162 98 5
Ramsey et al31 2016 USA Cross-sectional Emotional and cognitive difficulties ≥65 103 46 4
Matz-Costa et al28 2019 USA Cross-sectional General population 63–80 30 89.7 5
Noftle and Gust (a)29 2019 USA Cross-sectional General population 66–81 25 87.66 5
Noftle and Gust (b)29 2019 USA Cross-sectional General population 65–80 65 90 5
Rullier et al (a)22 2014 France Cohort Cognitive impairment 70 12 62.5 5
Rullier et al (b)22 2014 France Cohort General population 70 46 77.5 5
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Supplementary data

bmjopen-2022-069523supp002.pdf (88.5KB, pdf)

Pooled compliance rate for EMA programmes in the elderly

Of the 20 included studies, the compliance rate of EMA programmes among the elderly ranged from 36% to 98.33%. Tests revealed significant heterogeneity among studies (I2=96.4%, p<0.001); therefore, the random-effects model was used to combine the transformed rates; the outcome was 1.85 (95% CI: 1.23 to 2.47) (figure 2). The actual compliance rate was 86.41% (95% CI: 77.38% to 92.20%) in the elderly.

Figure 2.

Figure 2

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Forest plot of eligible studies. Weights are from random-effects model. ES, effect size.

Subgroup analysis

Subgroup analysis showed that the compliance for articles published before 2017, 2017–2019 and after 2019 was 85.32% (95% CI: 61.30% to 95.56%), 89.38% (95% CI: 83.48% to 93.28%) and 86.18% (95% CI: 71.30% to 93.99%), respectively. In the subgroup analysis of areas, America had a compliance rate of 83.34% (95% CI: 67.48% to 92.34%); this compared with 88.80% (95% CI: 81.76% to 93.28%) in Asia and 86.18% (95% CI: 76.49% to 92.27%) in Europe. Compared with large sample sizes (n>100), compliance was higher in small sample sizes (86.18%; 95% CI: 81.46% to 89.93%). Compliance was also higher for assessment periods that were ≤7 days (89.57%; 95% CI: 83.62% to 93.52%) than for assessment periods that were >7 days. Compliance was higher when compensatory measures were provided (90.97%; 95% CI: 85.94% to 94.37%) than when such measures were not provided. However, none of these subgroup differences were statistically significant. Nevertheless, compliance with EMA was significantly lower in the elderly with cognitive and emotional impairment (53.99%; 95% CI: 38.94% to 53.25%), compared with those with cognitive impairment only (69.42%; 95% CI: 54.98% to 81.00%), knee osteoarthritis (93.76%; 95% CI: 59.39% to 99.36%) and the general elderly (88.29%; 95% CI: 77.73% to 94.21%) (p<0.001). Among assessment methods, choosing paper diaries (92.62%; 95% CI: 80.38% to 97.44%) had a significantly higher compliance than for electronic diaries and telephone interviews (p=0.039). Among the daily assessment frequencies, compared with randomised assessments (73.11%; 95% CI: 55.48% to 85.69%), the highest compliance was observed for assessments ≥6 times/day (88.80%; 95% CI: 81.34% to 93.46%), followed by 4–5 times/day (86.53%; 95% CI: 64.57% to 95.77%) and 2–3 times/day (82.64%; 95% CI: 53.99% to 95.07%) (p<0.001) (for details, see online supplemental table 2).

Meta-regression analysis

Meta-regression was performed for the time of publication, region, population classification, sample size, assessment method, assessment period, the frequency of assessment and whether compensatory measures were given. Analysis showed that the presence of emotional and cognitive impairment (β=−0.5781, p=0.035) and an assessment period of >7 days (β=−0.64091, p=0.050) made the elderly less compliant with EMA. In contrast, there were no significant differences with regard to the analysis of assessment frequency (β=0.1306, p=0.651). As a result, population classification and assessment period accounted for the overall heterogeneity (online supplemental table 3).

Sensitivity analysis

Sensitivity analysis of the 20 included studies revealed a log-transformed EMA programme compliance rate of 1.85 (95% CI: 1.23~2.47) after the exclusion of any one article; this was consistent with our other results, thus indicating that the results arising from meta-analysis were stable (figure 3).

Figure 3.

Figure 3

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Sensitivity analysis estimating heterogeneity.

Publication bias

Funnel plot analysis showed that the distribution of study sites was not symmetrical (online supplemental figure 1). Egger’s test (p<0.001) further suggested that there was significant publication bias (online supplemental figure 2).

Supplementary data

bmjopen-2022-069523supp001.pdf (104.3KB, pdf)

Discussion

Principal findings

This systematic review and meta-analysis of observational studies aimed to investigate EMA programmes and compliance rate in the elderly. This systematic review included 20 studies with a total sample size of 2047 cases. Our meta-analysis showed that the combined compliance rate of EMA programmes in the elderly was 86.41% (95% CI: 77.38% to 92.20%). The pooled compliance rate identified here is higher than the 80% level recommended previously by Stone et al.9 Thus, EMA is acceptable in the elderly.

The use of EMA in the elderly

EMA has been used in a wide range of applications for children, adolescents and adults. The number of published studies describing the use of EMA in the elderly has begun to increase over the last 3 years, thus indicating that researchers are beginning to focus on the use of ecological methods to monitor health status in the elderly. We found that articles that were published between 2017 and 2019 showed a higher EMA compliance rate when compared with articles published before 2017 and after 2019. This may be due to the widespread use of smart devices that allow for automatic recognition and monitoring, thus making it possible to reduce inputs from the elderly, reduce burden and improve their compliance.28 Moreover, as the body of EMA research increases, researchers have designed more rational targeted EMA regimens based on the characteristics of past EMA designs and combined with the characteristics of the current population, thereby improving compliance in the elderly.29 However, over the last 3 years, scholars have started to use EMA more frequently to conduct research on complex behaviours and mental states, including social interaction, loneliness, context, intention, self-efficacy, security, responsibility, etc.30 This complexity of assessment content has led to increased burden in the elderly, thus reducing compliance. Participant burden is known to directly affect compliance with EMA programmes. Therefore, in order to use ecological methods to effectively assess the health status of the elderly, we encourage future researchers to focus on the rational design of EMA programmes and reduce burden on the participants. Subgroup analysis showed that compliance with EMA protocols was higher among the elderly in Asia than in the USA and Europe. This might be because EMA was first proposed by American academics and was gradually applied in Europe and Asia over time.9 More studies on EMA have been conducted in America; early EMA protocols were associated with a large number of studies with low compliance rates, thus resulting in lower overall compliance rates.15 31 Early studies in the USA provide key lessons for conducting EMA studies in Asia.12 13 However, only a few studies on Asian regions were included in our analysis; this may have led to bias.12 23 Future EMA studies in more regions are recommended.

The EMAs identified in this review reflect those reported in previous systematic reviews and involve mood, situation, sleep, cognition, symptom, dietary factors and physical activity. Therefore, the application of EMA in the elderly mostly concerns health-related behaviours and psychological conditions. We also included EMAs related to sick elderly including those with knee osteoarthritis, dementia and cognitive and emotional difficulties; these data were generally consistent with those reported previously.21 22 24 31 32 Subgroup analysis further showed that the compliance rate of sick elderly with the EMA programmes was different from the general elderly. The elderly may be more affected by disease, thus resulting in a decline in cognition, memory, thinking, activity and other functions. Consequently, their compliance may not be as good as the general elderly due to forgetfulness or operational errors. Therefore, when conducting EMA for the sick elderly, compliance should be improved by providing detailed training on the EMA programmes prior to assessment and setting reasonable reminders during the assessment.

Association between EMA programme design and compliance

A small sample size (no more than 100 individuals) is considered appropriate when conducting an EMA survey to avoid the huge burden imposed by data analysis. The systematic evaluation also showed higher compliance rates in a small sample size (n≤100). EMA programmes generally include assessment methods, duration, frequency and the use of incentives. Several of the studies in this review involved wearable devices such as accelerometers, Global Positioning System, ECG and voice/video recording. These devices were an addition to the EMA subjective reporting platforms, such as paper diaries and electronic diaries. However, we found that the use of smart devices did not result in an increased compliance in the elderly. In contrast, our meta-analysis showed that the use of electronic devices for EMA reduced compliance with EMA in the elderly. One reason for this is that the elderly have limited access to smart devices. Therefore, it is important to provide the elderly with appropriate EMA training in advance and familiarise them with EMA equipment. In addition, the duration and frequency of assessment can have an impact on EMA compliance. Our subgroup analysis showed that the compliance rate of 89.57% for an assessment period ≤7 days was higher than the other groups. It is possible that long-term self-reporting leads to reduced compliance in the elderly. However, compliance with EMA was highest among the elderly who were assessed ≥6 times/day, which is inconsistent with the findings of Burke et al.8 This may be due to the fact that the total period of the EMA study was 1 year and because high-frequency assessments can increase participant burden and reduce compliance rates. Therefore, in the process of designing EMA studies, it is important to integrate various factors such as assessment method, assessment period and assessment frequency. Furthermore, timely adjustments should be made through participant feedback to rationalise study design to improve participant compliance. This study also noted that the compliance rate of the elderly who were given financial compensation or other measures was 90.97%; this was higher than those who were not given compensation (81.76%). Thus, the provision of incentives may increase the compliance of the elderly with EMA programmes.

Strengths and limitations

This meta-analysis has several advantages. First, our comprehensive review of studies relating to EMA in the elderly led to a better understanding of compliance. Furthermore, we provide key details related to the design of EMA, which will provide a basis for designing future EMA programmes and conducting EMA studies for the elderly. Second, this study quantitatively assessed compliance with EMA programmes in the elderly and analyse factors that might affect compliance. Finally, we performed subgroup analysis and meta-regression to investigate sources of heterogeneity. We also performed sensitivity analysis and publication bias analysis to account for the stability of our results. This study also has limitations that need to be considered. First, there is a lack of uniform standards regarding the design of EMA studies when summarising previous studies. Furthermore, some studies excluded subjects with excessively low compliance during data analysis, which may have led to an overestimation of the combined compliance rate in this study. Therefore, it is recommended developing a standard EMA programme. Another point to consider is that we did not include the grey literature in this study; this may have caused publication bias. The results of our analysis need to be further validated. We recommended that future relevant studies incorporate grey literature and design reasonable EMA-related programmes.

Conclusions

Compliance with EMA was high in the elderly (86.41%); therefore, EMA is acceptable in the elderly. In addition, compliance with EMA among the elderly varied significantly depending on disease status and the design of the EMA programme. It is recommended that future studies be conducted to design different EMA programmes according to the disease characteristics of the elderly.

Supplementary Material

Reviewer comments
bmjopen-2022-069523.reviewer_comments.pdf (196.6KB, pdf)
Author's manuscript
bmjopen-2022-069523.draft_revisions.pdf (4.7MB, pdf)

Footnotes

LY and YY contributed equally.

Contributors: LY and YY searched and checked the databases according to the inclusion and exclusion criteria, extracted the data and assessed their quality. LY analysed the data and wrote the draft of the paper. YY, ZW, LX and XP gave advice on meta-analysis methodology and revised the paper. All authors contributed to reviewing or revising the paper. LX and XP are the guarantors of this work and had full access to all the data in the study and take responsibility for its integrity and the accuracy of the data analysis. All authors read and approved the final manuscript.

Funding: This work was supported by the National Science Foundation of China (no. 72104168); Suzhou 32nd Batch of Science and Technology Development Plan (Medical and Health Technology Innovation) (2021) (no. SKY2021036, SKJY2021066); and Suzhou Nursing Association Gusu Nursing Talent ‘Youth’ Program (2021) (no. SHQM202102).

Competing interests: None declared.

Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review: Not commissioned; externally peer reviewed.

Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

Ethics statements

Patient consent for publication

Not required.

Ethics approval

This study was based on published data so did not require ethics approval.

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Supplementary Materials

Supplementary data

bmjopen-2022-069523supp003.pdf (193.6KB, pdf)

Supplementary data

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Supplementary data

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Reviewer comments
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Author's manuscript
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Data Availability Statement

All data relevant to the study are included in the article or uploaded as supplementary information.

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