Antonio Sarmento
Sandra Webber2
Diana C. Sanchez-Ramirez- 1Department of Respiratory Therapy, University of Manitoba, Winnipeg, MB, Canada
- 2Department of Physical Therapy, University of Manitoba, Winnipeg, MB, Canada
- 3Rehabilitation Physiotherapy Department, Health Sciences Centre, Winnipeg, MB, Canada
Background: Exertion-intolerant symptoms common in post-COVID-19 syndrome (PCS), often resembling myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), challenge conventional rehabilitation and highlight the need for research into the poorly understood relationship between PCS symptoms and physical activity.
Objectives: We aimed to investigate the longitudinal associations between PCS symptoms and physical activity (same and following day), while accounting for the presence of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) symptoms. Additionally, to compare the characteristics and outcomes of PCS patients with and without ME/CFS symptoms.
Methods: Adults with PCS participated in an in-person evaluation that included assessment of dyspnea (Borg scale), fatigue (Fatigue Severity Scale), ME/CFS symptoms screening (DePaul Symptom Questionnaire), and functional capacity. Participants were also instructed to complete a daily PCS symptoms survey and wear a smartwatch for a week to track daily physical activity (step count).
Results: Eighteen individuals with PCS (78% females, 51 ± 11 years) participated in the study, averaging 4,067 steps per day (95%CI 3,638–4,497) over 117 days of valid data. Individuals with ME/CFS symptoms (n = 11) reported more severe PCS symptoms and had lower functional capacity than those without ME/CFS symptoms. After adjusting for ME/CFS symptoms, greater dizziness was associated with fewer steps on the same [OR 0.94 (95%CI 0.88–0.99), p = 0.026] and following day [OR 0.91 (95%CI 0.84–0.98), p = 0.016]. Lower levels of fatigue [OR 0.69 (95%CI 0.49–0.99), p = 0.043] and chest pain [OR 0.76 (95%CI 0.57–0.99), p = 0.048] were associated with walking ≥5,000 steps on the previous day.
Conclusion: Regardless of the presence of ME/CFS symptoms, dizziness was negatively associated with physical activity on both the same and following day in PCS individuals. Additionally, lower levels of fatigue and chest pain were linked to walking 5,000 steps or more the previous day.
Impact: These results provide insights into the relationships between symptoms and daily physical activity in PCS, which can help tailor interventions and improve the management of this condition. This research also highlights the value of using wearable devices and smartphone apps to collect data for monitoring individuals with PCS over time.
Introduction
The long-term impact of SARS-CoV-2 infection, known as post-COVID-19 syndrome (PCS), is characterized by a range of symptoms that continue for 12 weeks or more after the acute phase of illness (1). This syndrome imposes a substantial burden on affected individuals, making everyday activities more challenging and impairing their functional capacity and quality of life (2–4).
PCS symptoms may be episodic in nature, causing health challenges that fluctuate or relapse over time, leading participants to experience good and bad days in terms of their illness and limitations (5). Literature suggests that a complex interplay of multiple factors may cause PCS and its wide range of symptoms (6–8), which can impact physical activity and lead to physical deconditioning (4, 9, 10). Although the exact mechanisms are still under investigation, persistent inflammation, immune dysregulation, endothelial dysfunction, and tissue damage have been identified as key contributing factors (7, 11, 12) Dysregulation of the cardiovascular and autonomic systems may play a role in the development of PCS symptoms, particularly contributing to shortness of breath, fatigue, chest pain, and dizziness (13, 14). Vestibular dysfunction resulting from COVID-19 may also cause dizziness, balance impairments, and anxiety about potential falls, all of which can limit daily activities (15–17). Additionally, studies have demonstrated that many individuals with PCS exhibit symptoms consistent with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), including severe fatigue, post-exertional malaise, and cognitive dysfunction (18, 19). These ME/CFS-related symptoms, which are often exacerbated by physical or mental exertion, contribute to reduced exercise tolerance and make conventional rehabilitation approaches unsuitable (20).
There is a critical need to study the relationship between PCS symptoms and physical activity, as it remains insufficiently understood. In this context, continuous health monitoring can effectively help achieve this purpose (21). The recent integration of commercial wearable devices and their associated smartphone apps into daily life offers a valuable tool to track and adjust activity levels, helping individuals manage and identify PCS based on their own data. Although wearable fitness trackers (e.g., smartwatches) have been increasingly used to monitor step counts, sedentary behavior, and cardiovascular parameters before and during the COVID-19 pandemic (22–24), literature still lacks longitudinal studies assessing how PCS symptoms affect the daily physical activity of these individuals. Therefore, this study aimed to investigate the longitudinal associations between PCS symptoms and physical activity (same and following day), while accounting for the presence of ME/CFS symptoms. Additionally, it compared the characteristics and outcomes of PCS patients with and without ME/CFS symptoms.
Methods
Design and participants
This prospective short-term longitudinal exploratory study was approved by the research ethics committee of the University of Manitoba [HS25555(B2022:056)] and conducted according to the Declaration of Helsinki. All participants included in this research signed the informed consent form.
A convenience sample was recruited through public advertising and social media. Inclusion criteria were age ≥18 years, persistence of symptoms ≥3 months after confirmed or suspected COVID-19 infection (25), and access to a smart device (phone or tablet) and internet service. Those who reported full recovery of symptoms, limited ability to walk independently, acute lung or heart conditions, hearing or visual impairments, and those who could not complete basic tasks on the smart device (e.g., searching, opening, and closing an app) were excluded.
Assessments and data collection
Individuals were screened for eligibility via telephone. The study, conducted between Nov 2022 and April 2023, involved two components: in-person assessment (RespirabilityLab) and home-based remote monitoring.
In-person assessment
Anthropometric data (height, weight, and body mass index) were initially collected during the in-person assessment, followed by a validated and reliable assessment of dyspnea using the modified Borg scale (0–10 points, where 10 indicating maximal perceived exertion) (26) and fatigue, using the Fatigue Severity Scale (27). The latter is a self-reported instrument that assesses fatigue severity regarding daily activities using a 7-point Likert scale; total scores are determined as the average of responses and range between 1 (no impact) and 7 (greater impact of fatigue symptoms). The visual analog scale of the Fatigue Severity Scale was also used to evaluate overall fatigue (0 indicated “very alert” and 10 “extremely fatigued”) (28). The FSS is a valid, reliable, and responsive instrument for assessing fatigue severity (Cronbach's α > 0.90; ICC 0.80–0.90) (29, 30).
Participants were also screened for ME/CFS symptoms using the DePaul Symptom Questionnaire short-form (DSQ-SF) (31) by rating the frequency and severity of 14 symptoms on a 5-point Likert scale. The DSQ short-form demonstrates strong psychometric properties, it can accurately classify individuals with Long COVID and ME/CFS with high degrees of sensitivity and specificity (32). To fulfill the Canadian ME/CFS criteria (33), which is the most complete case definition, the participant should score at least a 2/5 frequency and 2/5 severity threshold on the DSQ-SF domains related to fatigue, post-exertional malaise, unrefreshing sleep, and neurocognitive impairment, and should list one symptom from at least two of the following domains: pain (either muscle pain or bloating), autonomic (either irritable bowel problems or feeling unsteady on your feet, like you might fall), neuroendocrine (either sensation of cold limbs or feeling hot or cold for no reason), and immune (either flu-like symptoms or some smells, foods, medications, or chemicals make you feel sick). The total score for each DSQ-SF domain was also averaged and multiplied by 25 to create a 100-point composite score; values close to 100 represent more burden of symptoms (31, 34).
Two field tests were applied to assess functional capacity. Firstly, participants performed the 1-minute sit-to-stand test (1MSTST) using a chair without armrests. The 1MSTS demonstrates good reliability, validity, and responsiveness for evaluating functional exercise capacity in clinical populations, with strong test-retest agreement and moderate correlations to other recognized functional assessments (35, 36). They were asked to fold their arms across their chest and stand up and sit down as quickly as possible for one minute. The best performance out of the three attempts was included in the analyses. Absolute and percentage of predicted values of the trial with the greatest number of repetitions were included for analysis (37). Secondly, the six-minute walk test (6MWT) was conducted by asking participants to walk as far as possible without running in a 30-meter corridor during six minutes (38). The distance covered was recorded in meters and presented as absolute and percentage of predicted values (37, 38). The 6MWT demonstrates moderate to excellent psychometric properties including validity, reliability, and responsiveness to change which make it clinically useful and applicable for assessing functional capacity in a variety of populations (39). Lastly, lung function (forced vital capacity, forced expiratory volume in the first second and peak expiratory flow) was assessed using a SpiroBank Smart spirometer (MIR, Rome, Italy) according to ATS/ERS recommendations (40). Data were compared to reference values for the Canadian population (41).
Remote monitoring
A Garmin Venu Sq® smartwatch (Garmin, Kansas, USA), provided during the in-person assessment, was paired via Bluethooth with the participant's smartphone and connected to the Garmin Connect and Labfront Companion (Labfront, Boston, USA) applications. The feasibility of this wearable device to acquire data throughout the day was validated in a previous study with individuals with PCS (42). After instructions about daily data synchronization, participants were asked to wear the smartwatch on the non-dominant wrist for seven days during waking hours while continuing with their regular activities. Participants completed an electronic questionnaire (using the Labfront Companion application) daily, reporting the severity (0 “none” to 10 “very severe”) of some of the most prevalent PCS symptoms: shortness of breath at rest and during activities, chest pain, dizziness, and fatigue (43). Participants were able to remove the watch overnight for charging and were instructed to avoid using the smartwatch during showering or swimming.
For data to be considered valid, participants should have worn the smartwatch for at least eight consecutive waking hours. The following variables were calculated: total wear time (in hours) during the day and during waking hours (i.e., between 6am and 10pm), daily step count, and HR (average, minimum, and maximum). Daily step count was used to determine physical activity levels (44) and was presented using two variables: steps acquired the same day and steps acquired the following day.
Statistical analysis
Demographic data, lung function, and DSQ-SF scores were compared between individuals with and without ME/CFS symptoms using the Mann–Whitney test. Valid data on wear time, daily step count, heart rate (HR), and symptoms, clustered at the participant level, were compared between individuals with and without ME/CFS symptoms. Generalized Estimating Equations (GEEs) were applied to examine the associations between PCS symptoms and daily step count (same and following day), using three models with data clustered at the participant level and adjusted for sex and age: Model 1 assessed associations for each symptom individually, Model 2 considered all symptoms simultaneously, and Model 3 built on Model 2 by further adjusting for the presence of ME/CFS symptoms. Furthermore, GEEs were applied to examine the associations between walking ≥5,000 steps/day (44) (yes/no) and symptom severity the next day. Three models were developed, each building upon the previous one: Model 1 adjusted for same day symptom, Model 2 adjusted for sex and age, and Model 3 further adjusted for the presence of ME/CFS symptoms (Model 3).
Data were analyzed using SPSS software (IBM Corp., NY, USA) and presented as means ± standard deviations, estimated marginal means (95% confidence intervals), and odds ratio (OR). Significance was set at p < 0.05.
Results
Eighteen individuals with PCS (78% females, 51.16 ± 11.03 years, and 29.83 kg/m2) were included in the study (Table 1). Six participants worked in office-based roles (graphic designer, supervisor, actuary, library technician, sales, accountant), 4 were healthcare providers (2 nurses, 1 paramedic, 1 massage therapist), 3 were teachers, 2 were retired, 1 was an engineer, 1 worked in aerospace manufacturing, and occupational information was missing for one participant. Twelve participants reported having one or more pre-existing comorbidities, the most common being asthma, hypothyroidism, diabetes, migraine, obstructive sleep apnea, hypertension arterial, and orthostatic hypotension. Fifteen individuals wore the smartwatch for 7 days, while the other three individuals wore it for 6, 4, and 2 days, totaling 117 days of valid data. Overall, participants wore the watch for a mean time of 18.83 hours per day and walked a mean of 4,067 steps daily (95%CI 3,638–4,497). The most severe symptoms reported were shortness of breath during activity and fatigue (Table 2). Dizziness was reported by 78% (n = 14) of the participants.
Table 1. Characteristics of study participants.
Table 2. Smartwatch wear time, physical activity (daily step count), heart rate, and PCS symptoms of study participants.
Individuals with ME/CFS symptoms (n = 11) performed worse on the 6MWT (p < 0.001) and 1MSTST (p = 0.033) than those without ME/CFS symptoms. They also reported significantly more shortness of breath during activity (p = 0.006), chest pain (p = 0.008), dizziness (p = 0.004), and fatigue (p = 0.001) (Table 2).
Increased severity of all symptoms was independently associated with a lower step count on the same day (all p < 0.05). However, when including all symptoms in the same model, only dizziness remained significantly associated even after adjusting for ME/CFS symptoms [OR 0.94 (95%CI 0.88–0.99), p = 0.026]. Greater dizziness was also significantly associated with lower step count on the following day in individuals with PCS, independent of ME/CFS symptoms [OR 0.91 (95%CI 0.84–0.98), p = 0.016] (Table 3). Moreover, lower levels of fatigue [OR 0.69 (95% CI 0.49–0.99), p = 0.043] and chest pain on the following day [OR 0.76 (95%CI 0.57–0.99), p = 0.048] were associated with walking ≥5,000 steps/day independent of the magnitude of these symptoms on the previous day, age, sex, and presence of ME/CFS symptoms (Table 4).
Table 3. Associations between PCS symptoms and physical activity (daily step count) in the same and following days adjusted for sex, age and presence of ME/CFS symptoms.
Table 4. Associations between physical activity (daily step count) and PCS symptoms in the following day adjusted for age, sex, same day symptom severity, and presence of ME/CFS symptoms.
Discussion
To the best of our knowledge, this is the first study that has investigated the longitudinal associations between PCS symptoms and physical activity in individuals with PCS using wearable devices, accounting for the presence of ME/CFS symptoms. Our results indicated that PCS individuals with ME/CFS symptoms presented greater SOB during activity, chest pain, dizziness, and fatigue, along with lower functional capacity compared to those without ME/CFS symptoms. Although the exact causes remain unclear, post-infectious fatigue has been linked to several factors, including chronic immune activation, autoimmunity, and mitochondrial dysfunction. However, the presence of ME/CFS symptoms did not affect the study findings, which revealed that dizziness was negatively associated with daily step count on the same and following day. Additionally, walking ≥5,000 steps was linked to lower levels of fatigue and chest pain the following day.
Research has found that dizziness is highly prevalent in PCS (45, 46). Evidence suggests that individuals experiencing dizziness often make significant adjustments to their daily routines, encounter physical performance limitations, and may reduce or avoid physical activities due to fear-avoidance behavious (47, 48). However, the association of dizziness with physical function and physical activity have been minimally explored in PCS, with studies relying mainly on questionnaires or self-reports (45, 49). A recent multicenter study (49) demonstrated that dizziness in individuals with PCS was linked to higher degrees of dependency, limitations in functionality and challenges in activities of daily living (e.g., self-care, home management, recreation, and travel). Perceived disability due to dizziness and fear of falling was also reported in young adults with PCS (50). In this study, we found a correlation between increased dizziness and reduced step count on the same and following day. This finding aligns with results from research on adolescent athletes post-concussion, who were monitored using smartwatches. In that study (51), self-reported dizziness at the initial assessment was associated with lower daily step count (mean reduction of 1,035 steps per day) in the following two weeks, suggesting that dizziness may contribute to sustained low levels of physical activity.
The influence of physical activity on the emergency of PCS symptoms has been addressed in recent studies (9, 52, 53). A large retrospective cohort (52) reported that being physically active during the pandemic was associated with a lower prevalence of symptoms of PCS. Similarly, other retrospective cohorts observed that sedentary behavior was associated with a 25% higher risk of developing at least one symptom of PCS (53), while high physical activity over the year prior to a COVID-19 infection was a protective factor against experiencing fatigue and chest pain (54). Despite the importance of these results, physical activity was self-reported and subjected to memory bias, which could overestimate vigorous activity and underestimate sedentary time (55). Furthermore, it remains unclear whether the real-time reciprocal relationships between physical activity and symptoms persist in individuals with established PCS, largely because inactivity in a day-to-day basis might contribute to and/or result from PCS (10, 56). PCS symptoms (43) can impact functional capacity and physical activity levels (18, 57), potentially explaining the decreased performance in the 6MWT and 1MSTST and the lower activity levels identified in our study (18, 58, 59) Additionally, reduced physical activity may lead to physical deconditioning (4, 9, 10), reduced aerobic capacity and muscle strength (60), further diminishing functional capacity in this population (52, 61). Conversely, physical activity may exacerbate symptoms such as severe fatigue, post-exertional malaise, and cognitive dysfunction in PCS individuals with ME/CFS symptoms (18, 19). This may result in reduced exercise tolerance, making conventional rehabilitation approaches unsuitable (20).
In this context, the associations between walking at least 5,000 steps/day and lower levels of fatigue and chest pain on the following day (regardless of ME/CFS symptoms), may provide valuable insights into the potential cycle of symptom exacerbation and physical deconditioning in individuals with PCS. Lippi et al. (10) suggested that individuals with PCS are more likely to reduce their physical activity levels after recovering from an acute infection; thus, increasing the risk of generating a continuous loop of symptom worsening. Individuals with PCS spend a shorter time walking up to six months after an acute infection (62), whereas those who are more physically active present with less fatigue, better performance on the 6MWT, higher number of repetitions in the 1MSTST, and higher handgrip muscle strength (63). Higher time in sedentary behavior and prolonged sitting without intermittent activity, as observed in COVID-19 survivors (64), may also potentially contribute to cardiovascular issues that could manifest as chest pain (65). Although different from sedentary behavior, inactivity may cause physical deconditioning, lowering the pain threshold and potentially increasing the likelihood of experiencing symptoms, such as non-cardiac chest pain (66).
The bidirectional relationships between the intensity of symptoms and physical activity observed in this study also has important implications for PCS management. Although more in-depth research is needed to elucidate the cycle of symptom exacerbation and physical deconditioning in PCS, comprehensive rehabilitation strategies (15, 16) addressing dizziness during rehabilitation might mitigate the fear avoidance behavior (67) and increase daily step count in the same and following days. Studies have demonstrated that vestibular rehabilitation can improve dizziness, balance, and mobility (68), while lower dizziness severity is correlated with higher physical activity levels (69). Consequently, increasing mobility to a minimum of a low active physical activity level (5,000 steps) could influence the reduction of chest pain and fatigue symptoms in the following day, assisting with recovery. Being physically active provides several health benefits, including protection against inflammation (70) and autoimmunity disorders (71), which are potentially linked to the development of PCS. Studies have shown a protective effect of a physically active lifestyle on COVID-19-related outcomes (72). Similarly, a meta-analysis of 23 studies (1,579 individuals) suggested that physical exercise-based rehabilitation programs were potential effective therapeutic strategies against PCS, as they resulted in significant improvements in dyspnea, fatigue, exercise capacity, and quality of life (73). As PCS patients may experience difficulty return to the pre-infection levels of physical activity (62), it may be advisable to cautiously encourage a gradual increase in the level of physical activity (at least from sedentary to low active) on a case-by-case basis, ensuring progression is safe and tailored to the severity of symptoms (74, 75). This approach can be integrated into routine clinical practice to help alleviate the burden of PCS symptoms. However, patient-tailored multidisciplinary support, along with greater attention from health care providers for early detection and proper management of PCS symptoms, are also essential to improve outcomes in this population (76).
Limitations and strengths
While this study provides valuable insights, the findings should be interpreted with caution, as certain limitations may restrict their generalizability. First, we acknowledge that including participants with both confirmed and suspected COVID-19 symptoms may introduce heterogeneity into the sample. This approach was used to capture a broader range of experiences during the evolving pandemic, recognizing that diagnostic confirmation was not always accessible. According to the WHO (Global Surveillance for COVID-19: Interim guidance, 20 March 2020), a confirmed case is one with laboratory confirmation of COVID-19 infection regardless of symptoms, while a suspected (presumptive) case meets clinical and/or epidemiological criteria without laboratory confirmation. Both definitions have been accepted in the literature to ensure timely data collection and broader case identification (77). Second, pre-existing comorbidities and/or medication use may have influenced the reported symptoms. A summary of the main reported comorbidities was provided; however, information on medication use was not available. Although controlling for these factors was not feasible due to the small sample size, we acknowledge their relevance for interpreting the findings. Third, the relatively small sample, composed mainly of females and individuals with a low level of physical activity, may impact the generalizability of the findings. However, literature indicates that these characteristics are common in individuals with PCS, suggesting that the sample may properly represent the population (10). Also, generalized estimating equations were employed to control the type I error and to maintain accuracy in the estimated marginal means. Fourth, the use of convenience sampling via social media may have introduced selection bias, limiting the representativeness of the sample. However, many studies have successfully utilized social media to identify participants and collect data, demonstrating its practical value in reaching diverse populations (77, 78). Fifth, information about lifestyle, which may have influenced the physical activity level of participants, was not gathered; however, we believe this does not affect the findings since step count was used to objectively measure activity levels in all participants and examine their relationship with symptom severity. Sixth, post-exertional malaise was not assessed in detail (79) and the self-reported information obtained in this study only allowed identification of ME/CFS symptoms, as ME/CFS diagnosis requires a full clinical assessment (80). Also, may have led to over- or under-reporting of symptoms, but in the absence of a valid tool, this questionnaire has been commonly used in other studies exploring this condition in PCS (73). Last, some participants experienced technical difficulties during the synchronization of Garmin data with the third-party app, resulting in data loss. The development or identification of a new application with similar data transfer capabilities may help overcome this challenge.
Nevertheless, this is the first study that longitudinally assessed daily step counts using wearable devices in PCS individuals with and without ME/CFS symptoms. In the context of PCS research, smartwatches and smartphone apps have emerged as invaluable personalized tools for remotely assessing, monitoring, and understanding the complex array of symptoms experienced by affected individuals (21, 81). Furthermore, the ability to track daily step counts helps quantify physical activity, adding to the comprehensive view of functional status and monitoring of recovery progress (75). As shown in our study, integrating these data points in the same and following days may help patients, clinicians and researchers understand the temporal relationships between PCS symptoms and daily physical activity; thus, enhancing the ability to tailor interventions and improve management strategies for those with PCS (76, 82, 83). Future research should explore the underlying mechanisms linking PCS, ME/CFS symptoms, and tachycardia, as well as investigate potential therapeutic strategies to address them. Additionally, future studies should aim for larger and more balanced sample sizes to increase statistical power, enhance the generalizability of findings, enable more detailed subgroup analyses, and adjustment for potentially relevant factors.
Summary of recommendations
PCS management should include rehabilitation strategies addressing dizziness and supporting an individualized increase in physical activity to at least a low active level (≥5,000 steps/day), ensuring progression is safe and tailored to the severity of symptoms. Wearable devices and their companion apps can be used to monitor step counts and symptom fluctuations, enabling personalized care. Clinician guidance and patient education on the benefits and precautions of physical activity in PCS are essential to effectively support recovery and improve outcomes.
Conclusion
Regardless of the presence of ME/CFS symptoms, dizziness was negatively associated with physical activity on both the same and following day in PCS individuals. Additionally, lower levels of fatigue and chest pain were linked to walking 5,000 steps or more on the previous day. These findings offer important insights into the complex interplay between symptoms and daily physical activity in PCS, which can inform the development of targeted interventions and enhance the management of the condition. This research also highlights the value of using wearable devices and smartphone apps to collect data for monitoring individuals with PCS over time.
Data availability statement
The datasets used in this article are not publicly available due to participant confidentiality agreements. However, they may be obtained from the corresponding author upon reasonable request and with the necessary ethical approvals. Requests to access the datasets should be directed toZGlhbmEuc2FuY2hlei1yYW1pcmV6QHVtYW5pdG9iYS5jYQ==.
Ethics statement
The studies involving humans were approved by the research ethics committee of the University of Manitoba [HS25555(B2022:056)]. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
AS: Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. SW: Formal analysis, Investigation, Methodology, Writing – review & editing. SS: Formal analysis, Investigation, Methodology, Writing – review & editing. BT: Formal analysis, Investigation, Methodology, Writing – review & editing. DS-R: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing.
Funding
The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by the Manitoba Lung Association and the Physiotherapy Foundation of Canada. The funders had no direct involvement in the study design, data collection or analysis.
Acknowledgments
The authors would like to thank Rachel Adodo for her valuable contributions to participant recruitment and data collection.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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The author(s) declare that no Generative AI was used in the creation of this manuscript.
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References
1. Parotto M, Gyöngyösi M, Howe K, Myatra SN, Ranzani O, Shankar-Hari M, et al. Post-acute sequelae of COVID-19: understanding and addressing the burden of multisystem manifestations. Lancet Respir Med. (2023) 11:739–54. doi: 10.1016/S2213-2600(23)00239-4
2. Arjun MC, Singh AK, Pal D, Das K, G A, Venkateshan M, et al. Characteristics and predictors of long COVID among diagnosed cases of COVID-19. PLoS One. (2022) 17:e0278825. doi: 10.1371/journal.pone.0278825
3. Tan S, Pryor AJG, Melville GW, Fischer O, Hewitt L, Davis KJ. The lingering symptoms of post-COVID-19 condition (long-COVID): a prospective cohort study. Intern Med J. (2024) 54:224–33. doi: 10.1111/imj.16251
4. Vélez-Santamaría R, Fernández-Solana J, Méndez-López F, Domínguez-García M, González-Bernal JJ, Magallón-Botaya R, et al. Functionality, physical activity, fatigue and quality of life in patients with acute COVID-19 and long COVID infection. Sci Rep. (2023) 13:19907. doi: 10.1038/s41598-023-47218-1
5. O’Brien KK, Brown DA, McDuff K, St Clair-Sullivan N, Solomon P, Chan Carusone S, et al. Conceptualising the episodic nature of disability among adults living with long COVID: a qualitative study. BMJ Glob Health. (2023) 8(3):e011276. doi: 10.1136/bmjgh-2022-011276
6. Batiha GE, Al-Kuraishy HM, Al-Gareeb AI, Welson NN. Pathophysiology of post-COVID syndromes: a new perspective. Virol J. (2022) 19:158. doi: 10.1186/s12985-022-01891-2
7. Diar Bakerly N, Smith N, Darbyshire JL, Kwon J, Bullock E, Baley S, et al. Pathophysiological mechanisms in long COVID: a mixed method systematic review. Int J Environ Res Public Health. (2024) 21(4):473. doi: 10.3390/ijerph21040473
8. Najafi MB, Javanmard SH. Post-COVID-19 syndrome mechanisms, prevention and management. Int J Prev Med. (2023) 14:59. doi: 10.4103/ijpvm.ijpvm_508_21
9. Gil S, Bruno B, de Araújo AL, de Oliveira Júnior GN, Damiano RF, Pinna F, et al. Post-acute sequelae of SARS-CoV-2 associates with physical inactivity in a cohort of COVID-19 survivors. Sci Rep. (2023) 13:215. doi: 10.1038/s41598-022-26888-3
10. Lippi G, Mattiuzzi C, Sanchis-Gomar F. Physical activity, long-COVID, and inactivity: a detrimental endless loop. J Phys Act Health. (2024) 21:420–2. doi: 10.1123/jpah.2024-0057
11. Son K, Jamil R, Chowdhury A, Mukherjee M, Venegas C, Miyasaki K, et al. Circulating anti-nuclear autoantibodies in COVID-19 survivors predict long COVID symptoms. Eur Respir J. (2023) 61(1):2200970. doi: 10.1183/13993003.00970-2022
12. Xie L, Chen L, Li X, Zhou J, Tian H, Zhao J, et al. Analysis of lung microbiome in COVID-19 patients during time of hospitalization. Pathogens. (2023) 12(7):944. doi: 10.3390/pathogens12070944
13. Ståhlberg M, Reistam U, Fedorowski A, Villacorta H, Horiuchi Y, Bax J, et al. Post-COVID-19 tachycardia syndrome: a distinct phenotype of post-acute COVID-19 syndrome. Am J Med. (2021) 134:1451–6. doi: 10.1016/j.amjmed.2021.07.004
14. Raman B, Bluemke DA, Lüscher TF, Neubauer S. Long COVID: post-acute sequelae of COVID-19 with a cardiovascular focus. Eur Heart J. (2022) 43:1157–72. doi: 10.1093/eurheartj/ehac031
15. Pazdro-Zastawny K, Dorobisz K, Misiak P, Kruk-Krzemień A, Zatoński T. Vestibular disorders in patients after COVID-19 infection. Front Neurol. (2022) 13:956515. doi: 10.3389/fneur.2022.956515
16. Ekstrand E, Brogårdh C, Axen I, Fänge AM, Stigmar K, Hansson EE. Perceived consequences of post-COVID-19 and factors associated with low life satisfaction. Int J Environ Res Public Health. (2022) 19(22):15309. doi: 10.3390/ijerph192215309
17. Davis HE, McCorkell L, Vogel JM, Topol EJ. Long COVID: major findings, mechanisms and recommendations. Nat Rev Microbiol. (2023) 21:133–46. doi: 10.1038/s41579-022-00846-2
18. Beyer S, Haufe S, Dirks M, Scharbau M, Lampe V, Dopfer-Jablonka A, et al. Post-COVID-19 syndrome: physical capacity, fatigue and quality of life. PLoS One. (2023) 18:e0292928. doi: 10.1371/journal.pone.0292928
19. Edward JA, Peruri A, Rudofker E, Shamapant N, Parker H, Cotter R, et al. Characteristics and treatment of exercise intolerance in patients with long COVID. J Cardiopulm Rehabil Prev. (2023) 43:400–6. doi: 10.1097/hcr.0000000000000821
20. Ferreira EVM, Oliveira RKF. Mechanisms of exercise intolerance after COVID-19: new perspectives beyond physical deconditioning. J Bras Pneumol. (2021) 47:e20210406. doi: 10.36416/1806-3756/e20210406
21. Khondakar KR, Kaushik A. Role of wearable sensing technology to manage long COVID. Biosensors (Basel). (2022) 13(1):62. doi: 10.3390/bios13010062
22. Bayoumy K, Gaber M, Elshafeey A, Mhaimeed O, Dineen EH, Marvel FA, et al. Smart wearable devices in cardiovascular care: where we are and how to move forward. Nat Rev Cardiol. (2021) 18:581–99. doi: 10.1038/s41569-021-00522-7
23. Masoumian Hosseini M, Masoumian Hosseini ST, Qayumi K, Hosseinzadeh S, Sajadi Tabar SS. Smartwatches in healthcare medicine: assistance and monitoring; a scoping review. BMC Med Inform Decis Mak. (2023) 23:248. doi: 10.1186/s12911-023-02350-w
24. Panicker RM, Chandrasekaran B. Wearables on vogue": a scoping review on wearables on physical activity and sedentary behavior during COVID-19 pandemic. Sport Sci Health. (2022) 18:641–57. doi: 10.1007/s11332-021-00885-x
25. World Health Organization. Post COVID-19 Condition (Long COVID). Geneva: WHO (2022). Available online at: https://www.who.int/europe/news-room/fact-sheets/item/post-covid-19-condition (Accessed October 17, 2024).
26. Borg G. Borg’s Perceived Exertion and Pain Scales. Champaign, IL, US: Human Kinetics (1998). p. viii, 104.
27. Whitehead L. The measurement of fatigue in chronic illness: a systematic review of unidimensional and multidimensional fatigue measures. J Pain Symptom Manage. (2009) 37:107–28. doi: 10.1016/j.jpainsymman.2007.08.019
28. Naik H, Shao S, Tran KC, Wong AW, Russell JA, Khor E, et al. Evaluating fatigue in patients recovering from COVID-19: validation of the fatigue severity scale and single item screening questions. Health Qual Life Outcomes. (2022) 20:170. doi: 10.1186/s12955-022-02082-x
29. Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. (1989) 46:1121–3. doi: 10.1001/archneur.1989.00520460115022
30. Lerdal A, Wahl A, Rustøen T, Hanestad BR, Moum T. Fatigue in the general population: a translation and test of the psychometric properties of the Norwegian version of the fatigue severity scale. Scand J Public Health. (2005) 33:123–30. doi: 10.1080/14034940410028406
31. Sunnquist M, Lazarus S, Jason LA. The development of a short form of the DePaul symptom questionnaire. Rehabil Psychol. (2019) 64:453–62. doi: 10.1037/rep0000285
32. McGarrigle WJ, Furst J, Jason LA. Psychometric evaluation of the DePaul symptom questionnaire-short form (DSQ-SF) among adults with long COVID, ME/CFS, and healthy controls: a machine learning approach. J Health Psychol. (2024) 29:1241–52. doi: 10.1177/13591053231223882
33. Carruthers BM, Jain AK, De Meirleir KL, Peterson DL, Klimas NG, Lerner AM, et al. Myalgic encephalomyelitis/chronic fatigue syndrome. Journal of Chronic Fatigue Syndrome. (2003) 11:7–115. doi: 10.1300/J092v11n01_02
34. Jason LA, Brown A, Evans M, Sunnquist M, Newton JL. Contrasting chronic fatigue syndrome versus myalgic encephalomyelitis/chronic fatigue syndrome. Fatigue. (2013) 1:168–83. doi: 10.1080/21641846.2013.774556
35. Mellaerts P, Demeyer H, Blondeel A, Vanhoutte T, Breuls S, Wuyts M, et al. The one-minute sit-to-stand test: a practical tool for assessing functional exercise capacity in patients with COPD in routine clinical practice. Chron Respir Dis. (2024) 21:14799731241291530. doi: 10.1177/14799731241291530
36. Bohannon RW, Crouch R. 1-Minute Sit-to-Stand test: systemaic review of procedures, performance, and clinimetric properties. J Cardiopulm Rehabil Prev. (2019) 39:2–8. doi: 10.1097/hcr.0000000000000336
37. Strassmann A, Steurer-Stey C, Lana KD, Zoller M, Turk AJ, Suter P, et al. Population-based reference values for the 1-min sit-to-stand test. Int J Public Health. (2013) 58:949–53. doi: 10.1007/s00038-013-0504-z
38. Enright PL, Sherrill DL. Reference equations for the six-minute walk in healthy adults. Am J Respir Crit Care Med. (1998) 158:1384–7. doi: 10.1164/ajrccm.158.5.9710086
39. Skjerbæk AG, Hvid LG, Boesen F, Taul-Madsen L, Stenager E, Dalgas U. Psychometric measurement properties and reference values of the six-spot step test, the six-minute walk test, the 25-foot walk test, and the 12-item multiple sclerosis walking scale in people with multiple sclerosis. Mult Scler Relat Disord. (2025) 94:106242. doi: 10.1016/j.msard.2024.106242
40. Bhakta NR, McGowan A, Ramsey KA, Borg B, Kivastik J, Knight SL, et al. European Respiratory Society/American thoracic society technical statement: standardisation of the measurement of lung volumes, 2023 update. Eur Respir J. (2023) 62(5):2251519. doi: 10.1183/13993003.51519-2022
41. Coates AL, Wong SL, Tremblay C, Hankinson JL. Reference equations for spirometry in the Canadian population. Ann Am Thorac Soc. (2016) 13:833–41. doi: 10.1513/AnnalsATS.201508-569OC
42. Sarmento A, Adodo R, Hodges G, Webber SC, Sanchez-Ramirez DC. Virtual pulmonary rehabilitation approaches in patients with post COVID syndrome: a pilot study. BMC Pulm Med. (2024) 24:139. doi: 10.1186/s12890-024-02965-3
43. Ma Y, Deng J, Liu Q, Du M, Liu M, Liu J. Long-term consequences of COVID-19 at 6 months and above: a systematic review and meta-analysis. Int J Environ Res Public Health. (2022) 19(11):6865. doi: 10.3390/ijerph19116865
44. Tudor-Locke C, Hatano Y, Pangrazi RP, Kang M. Revisiting “how many steps are enough?”. Med Sci Sports Exerc. (2008) 40:S537–543. doi: 10.1249/MSS.0b013e31817c7133
45. Degen CV, Mikuteit M, Niewolik J, Schröder D, Vahldiek K, Mücke U, et al. Self-reported tinnitus and vertigo or dizziness in a cohort of adult long COVID patients. Front Neurol. (2022) 13:884002. doi: 10.3389/fneur.2022.884002
46. Fahriani M, Ilmawan M, Fajar JK, Maliga HA, Frediansyah A, Masyeni S, et al. Persistence of long COVID symptoms in COVID-19 survivors worldwide and its potential pathogenesis - A systematic review and meta-analysis. Narra J. (2021) 1:e36. doi: 10.52225/narraj.v1i2.36
47. Kamo T, Ogihara H, Tanaka R, Kato T, Tsunoda R, Fushiki H, et al. Relationship between physical activity and dizziness handicap inventory in patients with dizziness -A multivariate analysis. Auris Nasus Larynx. (2022) 49:46–52. doi: 10.1016/j.anl.2021.04.004
48. Koo JW, Chang MY, Woo SY, Kim S, Cho YS. Prevalence of vestibular dysfunction and associated factors in South Korea. BMJ Open. (2015) 5:e008224. doi: 10.1136/bmjopen-2015-008224
49. Rodríguez-Pérez MP, Sánchez-Herrera-Baeza P, Rodríguez-Ledo P, Serrada-Tejeda S, García-Bravo C, Pérez-de-Heredia-Torres M. Headaches and dizziness as disabling, persistent symptoms in patients with long COVID–A national multicentre study. J Clin Med. (2022) 11:5904. doi: 10.3390/jcm11195904
50. Obeidat FS, Alghwiri AA, Whitney SL. Predictors of dizziness and hearing disorders in people with long COVID. Medicina (B Aires). (2023) 59:1901. doi: 10.3390/medicina59111901
51. Smulligan KL, Wingerson MJ, Seehusen CN, Wilson JC, Howell DR. Postconcussion dizziness severity predicts daily step count during recovery among adolescent athletes. Med Sci Sports Exerc. (2022) 54:905–11. doi: 10.1249/mss.0000000000002877
52. Rocha JQS, Caputo EL, Vieira YP, Afonso MDS, Duro SMS, de Oliveira Saes M. Physical activity status prevents symptoms of long COVID: sulcovid-19 survey. BMC Sports Sci Med Rehabil. (2023) 15:170. doi: 10.1186/s13102-023-00782-5
53. Zheng C, Huang WY, Sun FH, Wong MC, Siu PM, Chen XK, et al. Association of sedentary lifestyle with risk of acute and post-acute COVID-19 sequelae: a retrospective cohort study. Am J Med. (2025) 138(2):298–307.e4. doi: 10.1016/j.amjmed.2023.12.002
54. Malisoux L, Backes A, Fischer A, Aguayo G, Ollert M, Fagherazzi G. Associations between physical activity prior to infection and COVID-19 disease severity and symptoms: results from the prospective predi-COVID cohort study. BMJ Open. (2022) 12:e057863. doi: 10.1136/bmjopen-2021-057863
55. Dyrstad SM, Hansen BH, Holme IM, Anderssen SA. Comparison of self-reported versus accelerometer-measured physical activity. Med Sci Sports Exerc. (2014) 46:99–106. doi: 10.1249/MSS.0b013e3182a0595f
56. Subramanian A, Nirantharakumar K, Hughes S, Myles P, Williams T, Gokhale KM, et al. Symptoms and risk factors for long COVID in non-hospitalized adults. Nat Med. (2022) 28:1706–14. doi: 10.1038/s41591-022-01909-w
57. Omar A, Ferreira AS, Hegazy FA, Alaparthi GK. Cardiorespiratory response to six-minute step test in post COVID-19 patients-A cross sectional study. Healthcare (Basel). (2023) 11(10):1386. doi: 10.3390/healthcare11101386
58. Núñez-Cortés R, Flor-Rufino C, Martínez-Arnau FM, Arnal-Gómez A, Espinoza-Bravo C, Hernández-Guillén D, et al. Feasibility of the 30 s sit-to-stand test in the telehealth setting and its relationship to persistent symptoms in non-hospitalized patients with long COVID. Diagnostics. (2023) 13:24. doi: 10.3390/diagnostics13010024
59. Paradowska-Nowakowska E, Łoboda D, Gołba KS, Sarecka-Hujar B. Long COVID-19 syndrome severity according to sex, time from the onset of the disease, and exercise capacity—the results of a cross-sectional study. Life. (2023) 13:508. doi: 10.3390/life13020508
60. Tryfonos A, Pourhamidi K, Jörnåker G, Engvall M, Eriksson L, Elhallos S, et al. Functional limitations and exercise intolerance in patients with post-COVID condition: a randomized crossover clinical trial. JAMA Netw Open. (2024) 7:e244386. doi: 10.1001/jamanetworkopen.2024.4386
61. Feter N, Caputo EL, Delpino FM, Leite JS, da Silva LS, de Almeida Paz I, et al. Physical activity and long COVID: findings from the prospective study about mental and physical health in adults cohort. Public Health. (2023) 220:148–54. doi: 10.1016/j.puhe.2023.05.011
62. Delbressine JM, Machado FVC, Goërtz YMJ, Van Herck M, Meys R, Houben-Wilke S, et al. The impact of post-COVID-19 syndrome on self-reported physical activity. Int J Environ Res Public Health. (2021) 18(11):6017. doi: 10.3390/ijerph18116017
63. Galluzzo V, Zazzara MB, Ciciarello F, Tosato M, Martone AM, Pais C, et al. Inadequate physical activity is associated with worse physical function in a sample of COVID-19 survivors with post-acute symptoms. J Clin Med. (2023) 12:2517. doi: 10.3390/jcm12072517
64. Van Bakel BMA, Van Den Heuvel FMA, Vos JL, Rotbi H, Bakker EA, Nijveldt R, et al. COVID-19 survivors are physically inactive with high levels of sedentary time, regardless of patient characteristics, disease severity or cardiac dysfunction. Eur J Prev Cardiol. (2022) 29:zwac056.313. doi: 10.1093/eurjpc/zwac056.313
65. Lavie CJ, Ozemek C, Carbone S, Katzmarzyk PT, Blair SN. Sedentary behavior, exercise, and cardiovascular health. Circ Res. (2019) 124:799–815. doi: 10.1161/CIRCRESAHA.118.312669
66. Castonguay J, Turcotte S, Fleet RP, Archambault PM, Dionne CE, Denis I, et al. Physical activity and disability in patients with noncardiac chest pain: a longitudinal cohort study. Biopsychosoc Med. (2020) 14:12. doi: 10.1186/s13030-020-00185-9
67. Van Laer L, Dunlap PM, Vereeck L, Hendriks E, Sluydts M, Whitney SL. Fear avoidance beliefs, anxiety, and depression in healthy individuals and persons with vestibular disorders across cultures. Front Neurol. (2023) 14:1296411. doi: 10.3389/fneur.2023.1296411
68. Han BI, Song HS, Kim JS. Vestibular rehabilitation therapy: review of indications, mechanisms, and key exercises. J Clin Neurol. (2011) 7:184–96. doi: 10.3988/jcn.2011.7.4.184
69. Shiozaki T, Ito T, Wada Y, Yamanaka T, Kitahara T. Effects of vestibular rehabilitation on physical activity and subjective dizziness in patients with chronic peripheral vestibular disorders: a six-month randomized trial. Front Neurol. (2021) 12:656157. doi: 10.3389/fneur.2021.656157
70. Gleeson M, Bishop NC, Stensel DJ, Lindley MR, Mastana SS, Nimmo MA. The anti-inflammatory effects of exercise: mechanisms and implications for the prevention and treatment of disease. Nat Rev Immunol. (2011) 11:607–15. doi: 10.1038/nri3041
71. Sharif K, Watad A, Bragazzi NL, Lichtbroun M, Amital H, Shoenfeld Y. Physical activity and autoimmune diseases: get moving and manage the disease. Autoimmun Rev. (2018) 17:53–72. doi: 10.1016/j.autrev.2017.11.010
72. Ezzatvar Y, Ramírez-Vélez R, Izquierdo M, Garcia-Hermoso A. Physical activity and risk of infection, severity and mortality of COVID-19: a systematic review and non-linear dose–response meta-analysis of data from 1 853 610 adults. Br J Sports Med. (2022) 56:1188. doi: 10.1136/bjsports-2022-105733
73. Zheng C, Chen XK, Sit CH, Liang X, Li MH, Ma AC, et al. Effect of physical exercise–based rehabilitation on long COVID: a systematic review and meta-analysis. Med Sci Sports Exerc. (2024) 56(1):143–54. doi: 10.1249/MSS.0000000000003280
74. Ladlow P, Barker-Davies R, Hill O, Conway D, O’Sullivan O. Use of symptom-guided physical activity and exercise rehabilitation for COVID-19 and other postviral conditions. BMJ Mil Health. (2024) 170(6):510–5. doi: 10.1136/military-2023-002399
75. Hughes DC, Orchard JW, Partridge EM, La Gerche A, Broderick C. Return to exercise post-COVID-19 infection: a pragmatic approach in mid-2022. J Sci Med Sport. (2022) 25:544–7. doi: 10.1016/j.jsams.2022.06.001
76. Humphreys H, Kilby L, Kudiersky N, Copeland R. Long COVID and the role of physical activity: a qualitative study. BMJ Open. (2021) 11(3):e047632. doi: 10.1136/bmjopen-2020-047632
77. Davis HE, Assaf GS, McCorkell L, Wei H, Low RJ, Re’em Y, et al. Characterizing long COVID in an international cohort: 7 months of symptoms and their impact. eClinicalMedicine. (2021) 38:101019. doi: 10.1016/j.eclinm.2021.101019
78. Garrett C, Qiao S, Tam CC, Li X. Low-cost recruitment approach: utilizing Facebook groups to recruit COVID-19 long-haulers. Res Sq. [Preprint] (2024):rs.3.rs-4078924. doi: 10.21203/rs.3.rs-4078924/v1
79. Jason LA, Dorri JA. ME/CFS and post-exertional malaise among patients with long COVID. Neurol Int. (2022) 15:1–11. doi: 10.3390/neurolint15010001
80. Grach SL, Seltzer J, Chon TY, Ganesh R. Diagnosis and management of myalgic encephalomyelitis/chronic fatigue syndrome. Mayo Clin Proc. (2023) 98(10):1544–51. doi: 10.1016/j.mayocp.2023.07.032
81. Channa A, Popescu N, Skibinska J, Burget R. The rise of wearable devices during the COVID-19 pandemic: a systematic review. Sensors (Basel). (2021) 21(17):5787. doi: 10.3390/s21175787
82. Burki T. Wearable technology and COVID-19. Lancet Respir Med. (2022) 10:934–5. doi: 10.1016/s2213-2600(22)00351-4
Keywords: post COVID “long-haulers”, post COVID syndrome, post COVID symptoms, physical activity, wearables
Citation: Sarmento A, Webber S, Sargent S, Tittlemier B and Sanchez-Ramirez DC (2025) Relationship between post-COVID-19 symptoms and daily physical activity. Front. Rehabil. Sci. 6:1646093. doi: 10.3389/fresc.2025.1646093
Received: 12 June 2025; Accepted: 18 August 2025;
Published: 15 September 2025.
Edited by:
Laura Tabacof, Icahn School of Medicine at Mount Sinai, United StatesReviewed by:
Rui Viana, Fernando Pessoa Foundation, PortugalErmilo Canton-Martinez, Universidad Autónoma de Baja California, Mexico
Copyright: © 2025 Sarmento, Webber, Sargent, Tittlemier and Sanchez-Ramirez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Diana C. Sanchez-Ramirez, ZGlhbmEuc2FuY2hlei1yYW1pcmV6QHVtYW5pdG9iYS5jYQ==