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. 2025 May 6;23(2):e70116. doi: 10.1002/msc.70116

The Impact of Chronic Fatigue on Psychopathology in Outpatient Physiotherapy Patients

Zacharias Aslanidis 1,2, Ourania S Kotsiou 2,3,✉
PMCID: PMC12053036  PMID: 40326211

ABSTRACT

Introduction

Chronic fatigue is a debilitating condition marked by physical and mental exhaustion, frequently co‐occurring with psychiatric disorders such as depression and anxiety.

Methods

In a cross‐sectional study, 172 consecutive patients from a busy physiotherapy clinic were assessed using the Fatigue Assessment Scale (FAS) for physical and mental fatigue and the SCL‐90 for various psychological symptoms, with correlation analyses exploring relationships between fatigue severity, psychological distress and demographic factors.

Results

Most participants reported clinically significant fatigue, with 90.69% experiencing physical fatigue and 76.77% experiencing mental fatigue. Paranoid ideation (61.05%) and obsessive‐compulsiveness (59.88%) were common. Strong correlations were found between overall fatigue and psychological distress (r = 0.675, p < 0.001), especially between mental fatigue and depression (r = 0.699, p < 0.001).

Conclusion

Overall, the findings underscore the need for integrated multidisciplinary interventions to address both chronic fatigue and its related psychiatric symptoms.

Keywords: chronic fatigue, multidisciplinary interventions, psychological distress

1. Introduction

Chronic fatigue is a multifaceted condition marked by persistent exhaustion that is not relieved by rest. It affects both physical and mental functioning, often leading to substantial impairment in quality of life. Emerging evidence links chronic fatigue to immune dysregulation, mitochondrial dysfunction and neuroinflammatory mechanisms, all of which may sustain the persistence of symptoms (Fukuda et al. 1994; Sapra and Bhandari 2023; Gerhartz 2024).

Healthcare professionals often differ in their approach to chronic fatigue syndrome (CFS): some medicalise it extensively, while others underestimate its severity, leading to inconsistent care and suboptimal outcomes (Graves et al. 2024). This clinical inconsistency contributes to prolonged disability and diminished functional capacity. The recognition of CFS as a distinct diagnostic entity has stimulated research into its psychiatric comorbidities, particularly anxiety, depression and somatoform disorders. Several studies highlight a symptomatic overlap between CFS and mood or anxiety disorders, which complicates differential diagnosis (Calvo et al. 2015; Jackson and MacLeod 2017; Loades et al. 2020).

However, findings on the psychiatric burden of chronic fatigue remain inconsistent. While some studies report a strong association with emotional disorders, others suggest a weaker link (Prins et al. 2006). This variability underscores the need for further investigation using standardized psychometric assessments. In addition, neurobiological studies suggest that dysfunction of the hypothalamic‐pituitary‐adrenal (HPA) axis may contribute to the psychopathological manifestations of CFS (Cleare 2004; Shinba et al. 2023; Creed 2023).

This study aimed to evaluate the prevalence and psychological impact of chronic fatigue using two validated tools: the Fatigue Assessment Scale (FAS) and the Symptom Checklist‐90 (SCL‐90). By examining the associations between fatigue and psychological distress, we seek to enhance our understanding of the psychological dimensions of chronic fatigue and support the development of more targeted, integrated intervention strategies. Ultimately, our goal is to bridge the gap between somatic and psychiatric perspectives, promoting a more holistic model of care.

2. Methods

2.1. Study Design

A cross‐sectional, quantitative study was conducted to examine the association between chronic fatigue and psychopathology. Data collection took place over a 3‐month period from 1 February 2024 to 30 April 2024. The study adhered to standardized protocols to ensure the reliability and validity of findings. Prior to recruitment, a sample size calculation was performed using G*Power software (version 3.1.9.7) with a power of 0.80, alpha level of 0.05 and a medium effect size (f 2 = 0.15) based on existing literature. The minimum required sample size was determined to be 92 participants. The final sample of 172 exceeded this threshold, thereby increasing the study's statistical power and reliability of findings.

2.2. Study Population

2.2.1. Setting

The study was conducted in a private physiotherapy clinic in Serres, Greece. Recruitment, exposure, follow‐up and data collection occurred during the 3‐month period mentioned above, starting from 1 February 2024 and ending on 30 April 2024. This setting was chosen to provide a diverse sample of individuals seeking physiotherapy care who may also experience chronic fatigue.

2.2.2. Eligibility Criteria

Participants were recruited from individuals seeking physiotherapy treatment at the clinic, due to musculoskeletal pain, and post‐operative rehabilitation, specifically targeting those who reported experiencing persistent fatigue. Participants were selected based on their willingness to take part in the study, and recruitment occurred during regular physiotherapy appointments at the clinic. After providing information about the study, all participants gave informed consent before data collection.

Efforts were also made to reduce selection bias by recruiting participants from a diverse population attending a private physiotherapy clinic. This helped ensure that the sample was representative of individuals experiencing chronic fatigue within the clinic setting. Exclusion criteria included individuals with chronic neurological diseases. Follow‐up was not necessary for this study since it is a cross‐sectional design, with data collection occurring at a single point in time.

While blinding was not possible due to the nature of the study, the consistency of the measurement tools, the careful consideration of confounders including demographic factors such as age, gender, education level and employment status, and the exclusion of specific health conditions all worked to minimise bias and enhance the validity of the study’s findings.

2.3. Quantitative Variables

The primary outcomes and predictors in this study included psychological distress, which was measured using the SCL‐90, and physical and mental fatigue, which were measured using the FAS. Chronic fatigue served as the exposure variable. Potential confounders considered in the analysis included demographic factors such as age, gender, education level, and employment status. FAS was employed to measure the severity of physical and mental fatigue, while the SCL‐90 was used to evaluate various psychological symptoms.

2.3.1. Fatigue Assessment Scale (FAS)

FAS is a validated self‐report questionnaire designed to assess both physical and mental fatigue in individuals. It consists of 10 items, each rated on a five‐point Likert scale (1 = never to 5 = always), with a total score ranging from 10 to 50, where higher scores indicate greater fatigue severity. The scale captures two dimensions of fatigue: physical fatigue, which includes symptoms such as muscle weakness and lack of energy, and mental fatigue, which reflects cognitive exhaustion and difficulty concentrating. Based on the total score, fatigue levels were classified as no fatigue (10–21), moderate fatigue (22–34) and severe fatigue (≥ 35). FAS is widely used in clinical and research settings due to its ease of administration and reliability.

2.3.2. Symptom Checklist‐90 (SCL‐90)

SCL‐90 is a validated self‐report questionnaire designed to assess a wide range of psychological symptoms and overall mental distress. It consists of 90 items, each rated on a five‐point Likert scale (0 = not at all to 4 = extremely), measuring the severity of symptoms experienced over the past week. The SCL‐90 evaluates nine primary symptom dimensions, including somatisation, obsessive‐compulsive tendencies, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation and psychoticism, providing a comprehensive profile of an individual’s psychological well‐being. According to clinical cutoffs, SCL‐90 scores greater than 160 or subscale scores above 2 are considered pathological. Additionally, it includes three global indices—the global severity index (GSI), the positive symptom total (PST) and the positive symptom distress index (PSDI)—which reflect overall psychological distress and symptom burden. SCL‐90 is widely used in clinical and research settings for screening, diagnosis and treatment evaluation.

2.4. Ethical Considerations

Ethical approval was obtained from the Ethics Committee (approval number: 48841/25/10/2019). Informed consent was secured from all participants before data collection. Participants were assured of confidentiality, and data handling complied with ethical research guidelines.

2.5. Statistical Analysis

Descriptive statistics were used to summarise participant characteristics in detail. Specifically, means and standard deviations were calculated for continuous variables such as age, fatigue scores from the FAS and both total and subscale scores from the SCL‐90. Frequencies and percentages were computed for categorical variables, including gender, education level and employment status. To explore the relationships between fatigue scores and various psychopathology subscales, Pearson's correlation coefficients were calculated, with significance determined at p < 0.05. In addition, multiple regression models were used to assess the predictive value of fatigue scores on overall psychological distress, adjusting for potential confounders such as age, gender and education. Standardized beta coefficients were reported to highlight the relative importance of each predictor, and both R 2 and adjusted R 2 values were included to evaluate the explanatory power of the models. Subgroup comparisons based on factors such as age and education level were conducted using Cohen's d to quantify standardized differences between groups, with effect sizes classified as small (0.2), medium (0.5) and large (0.8). When analyses such as ANOVA were conducted, partial eta‐squared values were reported to provide additional insight into the magnitude of group differences, going beyond statistical significance.

To ensure robustness in the analysis, sensitivity analyses were conducted to examine the impact of different handling methods for the data. This included checking the stability of regression models under various assumptions and exploring potential biases due to unmeasured variables. Since there were no missing data in this cohort, no specific imputation or handling methods for missing values were required.

3. Results

The study included 172 participants. Although the study included all participants who sought physiotherapy treatment and met the eligibility criteria, 10 patients were excluded due to known chronic neurological diseases or refusal to participate after receiving information about the study. The flow diagram of the study is presented in Figure 1.

FIGURE 1.

FIGURE 1

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Study flow diagram.

The majority of the participants were female (62.2%), while 37.8% were male. This distribution indicates a higher representation of women in the study, which may reflect the general attendance patterns at the physiotherapy clinic. The participants were categorised into five age groups. The largest proportion (30.23%) were aged 60 and above. The second‐largest group (22.67%) consisted of individuals aged 41–50 years. Participants aged 51–60 years accounted for 19.18% of the sample. The youngest group (18–30 years) made up 17.4% of the sample. The 31–40 age group had the lowest representation, at 10.46%. Participants’ education levels varied, with a significant proportion having higher education. 33.14% were university graduates, while an equal percentage (33.14%) had completed secondary education. 20.34% held postgraduate degrees (Master's or PhD). 8.14% had completed post‐secondary vocational education, and 5.23% had only primary education. Regarding work experience, the majority (45.93%) had more than 21 years of employment experience. 25% had worked for 11–20 years, while 11.04% had 6–10 years of experience. 18.02% had less than 5 years of work experience, including some who were retired or unemployed.

3.1. Fatigue Assessment Scale (FAS)

The total score for FAS was 22,901 (SD = 3.689). The mean score for each parameter of fatigue (FAS) was 2.72 (SD = 0.630), suggesting significant chronic fatigue symptoms among participants. The FAS scores ranged from 1.800 to 4.800, indicating that some individuals experienced mild fatigue, while others reported severe exhaustion.

The mean score for physical fatigue was 2.837 (SD = 0.693), with a range from 1.800 to 5.000. The mean score for mental fatigue was 2.602 (SD = 0.673) with values ranging from 1.400 to 4.600. These findings indicate that physical fatigue levels were slightly higher than mental fatigue levels, although both exceeded the threshold for clinical concern. The higher mean score for physical fatigue compared with mental fatigue indicates that bodily exhaustion is a dominant complaint.

3.2. Symptom Checklist‐90 (SCL‐90)

The mean total score across all participants was 220.581 (SD = 72.188), indicating a wide range of symptom severity. The median score was 205.5, and the most frequently occurring score was 162. The minimum score recorded was 113, while the highest was 447, suggesting substantial variability in symptom expression.

A significant majority (79.06%) of participants had a total score exceeding 160, which is the threshold for clinical significance in psychological distress. This finding suggests that a large proportion of individuals in the study exhibit clinically relevant symptoms, requiring further psychological assessment and intervention.

Given that the mean SCL‐90 score in this study was 2.12, a significant proportion of participants exhibited clinically relevant psychopathological symptoms. Similarly, the high FAS mean score (2.72) suggests that chronic fatigue was a major concern in this group, potentially contributing to or exacerbating psychological distress.

The lowest SCL‐90 score recorded was 0.989, while the highest was 4.489, showing a wide range of psychological distress levels. Figure 2 presents the percentage of participants whose mean scores exceeded the clinical threshold of 2 across various psychological and fatigue‐related domains.

FIGURE 2.

FIGURE 2

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Percentage of participants whose mean fatigue assessment scale (FAS) scores exceeded the clinical threshold of 2.

The highest prevalence of scores greater than 2 was observed in Physical Fatigue (90.69%), indicating that most participants experienced significant physical exhaustion. Similarly, Mental Fatigue (76.77%) was also highly prevalent, suggesting that a large proportion of individuals reported high levels of psychological fatigue. Among the psychological symptoms, Paranoid Ideation (61.05%) and Obsessive‐Compulsiveness (59.88%) were among the most frequently reported, highlighting their significance in the sample.

Conversely, the lowest prevalence of scores greater than 2 was recorded for Phobic Anxiety (22.67%), indicating that fewer participants experienced significant phobic symptoms. Additionally, Psychoticism (33.14%) and Anxiety (34.30%) were present at lower rates compared with other psychopathological dimensions.

These results suggest that fatigue, both physical and mental, was the most prevalent concern among participants, while paranoid ideation and obsessive‐compulsiveness emerged as the most common psychological symptoms in this population.

The study identified several significant correlations between chronic fatigue, psychopathology and demographic factors.

A strong positive correlation was found between total chronic fatigue and overall psychopathological distress (r = 0.675, p < 0.001), indicating that higher fatigue levels were associated with greater mental health symptoms. Similarly, mental fatigue showed a strong correlation with total psychopathology scores (r = 0.655, p < 0.001), reinforcing the connection between cognitive exhaustion and psychological distress.

Among specific mental health symptoms, depression was highly correlated with mental fatigue (r = 0.699, p < 0.001), suggesting that individuals experiencing chronic mental exhaustion were more likely to develop depressive symptoms. Likewise, obsessive‐compulsiveness was strongly associated with mental fatigue (r = 0.688, p < 0.001), indicating that chronic fatigue may contribute to rigid repetitive thoughts and behaviours. Furthermore, somatisation was positively correlated with physical fatigue (r = 0.532, p < 0.001), meaning that individuals with higher levels of physical exhaustion were more likely to report physical symptoms such as pain and bodily discomfort.

Regarding demographic factors, lower education levels were significantly correlated with both higher fatigue scores (r = −0.356, p < 0.001) and greater psychological distress (r = −0.332, p < 0.001), suggesting that individuals with less education may have fewer coping resources or experience greater physical and emotional stress. Additionally, paranoid ideation was negatively correlated with educational level (r = −0.181, p = 0.017), meaning that individuals with lower education levels exhibited higher levels of suspicious thinking and mistrust.

Age also played a key role, as older individuals reported higher levels of both chronic fatigue (r = 0.356, p < 0.001) and psychological distress (r = 0.343, p < 0.001). These findings suggest that age‐related physical decline, increased stress and social factors may contribute to worsening fatigue and mental health symptoms over time. Overall, the results highlight a strong interplay between fatigue and mental health disorders, emphasising the need for integrated treatment approaches that address both physical and psychological well‐being, particularly in vulnerable populations such as older adults and individuals with lower educational attainment.

Table 1 shows the results of the multiple regression analysis where fatigue scores (Fatigue Assessment Scale), age, gender and education level were used to predict overall psychological distress (Symptom Checklist‐90, SCL‐90). The fatigue score emerged as the strongest predictor, with a standardized beta coefficient of 0.65 and a p‐value of less than 0.001, suggesting that higher fatigue levels were robustly associated with increased psychological distress. Age also significantly contributed to the model (β = 0.20, p = 0.010), indicating that older participants tended to report higher distress. In contrast, gender did not reach statistical significance (β = −0.10, p = 0.150), implying that there were no strong differences in distress between males and females in this sample. Education level was also a significant predictor as well (β = −0.15, p = 0.040), suggesting that individuals with higher educational attainment may experience lower psychological distress. Overall, the model explained 48% of the variance in psychological distress, with an adjusted R 2 of 45%.

TABLE 1.

Multiple regression analysis summary to predict overall psychological distress (SCL = 90).

Predictor Standardized beta 95% CI for beta p‐value
Fatigue assessment scale 0.65 [0.52, 0.77] < 0.001
Age, years 0.20 [0.05, 0.35] 0.010
Gender −0.10 [–0.24, 0.04] 0.150
Education level −0.15 [–0.29, −0.01] 0.040
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Note: Overall model: R 2 = 0.48, adjusted R 2 = 0.45.

Table 2 provides effect size estimates for subgroup comparisons and ANOVA analyses. For subgroup comparisons, the analysis comparing older participants (≥ 60 years) to younger ones (< 60 years) yielded a Cohen's d of 0.55, which is considered a medium effect size and was statistically significant (p = 0.020) with a partial eta‐squared of 0.08. Similarly, when comparing groups based on education (low vs. high), a Cohen's d of 0.60 was observed (medium effect, p = 0.010) along with a partial eta‐squared of 0.10. Additionally, the ANOVA for fatigue scores resulted in a highly significant p‐value (< 0.001) with a partial eta‐squared of 0.12, while the ANOVA for psychological distress produced a p‐value of < 0.001 and a partial eta‐squared of 0.15. The ANOVA results, which provided partial eta‐squared values of 0.12 for fatigue scores and 0.15 for psychological distress, indicate that approximately 12%–15% of the variance in these outcomes can be attributed to group differences, underscoring that both age and education level are important factors that moderately influence the levels of fatigue and psychological distress, highlighting their practical significance in the context of chronic fatigue research.

TABLE 2.

Subgroup comparisons and ANOVA effect sizes.

Comparison Effect size (Cohen's d) 95% CI for d p‐value Partial eta‐squared (η 2)
Age (≥ 60 vs. < 60 years) 0.55 (medium) [0.09, 1.01] 0.020 0.08
Education (primary vs. higher) 0.60 (medium) [0.15, 1.05] 0.010 0.10
ANOVA (fatigue scores) < 0.001 0.12
ANOVA (psychological distress) < 0.001 0.15
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4. Discussion

The findings of this study highlight the substantial burden of chronic fatigue and psychological distress among participants recruited from a physiotherapy clinic. The results indicate that fatigue, both physical and mental, is a predominant concern, with the majority of individuals reporting symptoms exceeding clinically relevant thresholds. Moreover, the strong correlation between fatigue and psychological distress underscores the complex interplay between physical exhaustion and mental health disorders, suggesting the need for integrated interventions.

The high prevalence of physical fatigue (90.69%) and mental fatigue (76.77%) in our study population highlights exhaustion as a predominant concern. These findings underscore the importance of equipping physiotherapists with the skills to effectively screen for fatigue‐related psychological distress during routine clinical evaluations. Moreover, our findings align with previous research indicating that chronic fatigue is not only a physiological phenomenon but also closely linked to emotional and cognitive strain (Michielsen et al. 2003; Harvey et al. 2008; Möller et al. 2023). The mean FAS score (2.72, SD = 0.630) further supports the conclusion that fatigue symptoms were persistent and clinically significant.

A substantial portion of individuals experiencing chronic fatigue exhibit significant psychological distress (Ruis et al. 2014; König et al. 2024), a finding that is echoed in our observation that 79.06% of participants scored above the clinical threshold on the SCL‐90. Similarly, the high prevalence of paranoid ideation (61.05%) and obsessive‐compulsiveness (59.88%) in our study parallels the results of Pasquini et al., who documented that individuals with chronic fatigue frequently experience heightened vigilance, intrusive thoughts and compulsive behaviours (Pasquini et al. 2015). These similarities underscore the consistency of our results with the existing literature, suggesting that both severe psychological distress and specific psychopathological symptoms are common features in populations suffering from chronic fatigue.

Manning et al. reported that phobic anxiety tends to be less prominent in this population, which is reflected in our study by a relatively low prevalence of 22.67% (Manning et al. 2022). This suggests that specific fears or avoidance behaviours may not be as central to the clinical picture of chronic fatigue. Conversely, other studies observed moderate levels of psychoticism and anxiety in similar populations (Ciccone et al. 2003), findings that are echoed in our results with psychoticism and anxiety reported at 33.14% and 34.30%, respectively. These moderate levels indicate that, while not the most dominant symptoms, a broad spectrum of psychological distress is present, underscoring the multifaceted nature of the psychopathology associated with chronic fatigue.

The significant positive correlation between total fatigue and total psychopathology (r = 0.675, p < 0.001) confirms that higher fatigue levels are associated with increased psychological distress. This relationship is particularly evident in the correlation between mental fatigue and overall psychological distress (r = 0.655, p < 0.001), reinforcing the connection between cognitive exhaustion and emotional dysregulation (Harris et al. 2016).

Among specific psychopathological symptoms, depression showed the strongest association with mental fatigue (r = 0.699, p < 0.001). This finding is consistent with prior studies indicating that chronic fatigue contributes to feelings of hopelessness, low motivation and emotional exhaustion (Anderson et al. 2014; Larkin and Martin 2017; Chaves‐Filho et al. 2019). Similarly, obsessive‐compulsiveness was strongly correlated with mental fatigue (r = 0.688, p < 0.001), suggesting that fatigued individuals may develop rigid thought patterns or compulsive behaviours as a coping mechanism (Gecaite‐Stonciene et al. 2020; Steward and Chib 2024).

Physical fatigue was also significantly correlated with somatisation (r = 0.532, p < 0.001), meaning that individuals with higher levels of bodily exhaustion were more likely to experience somatic complaints, such as pain and physical discomfort (Hashimoto et al. 2022). This supports the notion that fatigue‐related distress manifests both physically and psychologically.

Age played a significant role, with older individuals reporting higher levels of both chronic fatigue (r = 0.356, p < 0.001) and psychological distress (r = 0.343, p < 0.001) (Tetsuka 2021). These findings suggest that age‐related physical decline, increased life stressors, and social isolation may contribute to worsening fatigue and mental health symptoms over time. Given that older adults often face comorbidities, functional limitations and reduced access to mental health resources, targeted interventions focussing on fatigue management and psychological well‐being in ageing populations are necessary (Torossian and Jacelon 2021; Hu et al. 2025).

The study also found that lower education levels were significantly associated with both higher fatigue scores (r = −0.356, p < 0.001) and greater psychological distress (r = −0.332, p < 0.001) (Engberg et al. 2017). This suggests that individuals with less education may have fewer coping strategies, greater occupational stress or lower health literacy, contributing to increased vulnerability to fatigue and mental health issues (Engberg et al. 2017).

Moreover, paranoid ideation was negatively correlated with educational level (r = −0.181, p = 0.017), indicating that individuals with lower education levels reported higher levels of suspicious thinking and mistrust (Williams and Schreier 2005; Ibanez‐Casas et al. 2021). This aligns with existing literature suggesting that socioeconomic disparities contribute to heightened stress and perceived threats, exacerbating psychological distress (Evans‐Lacko et al. 2018).

Our regression analysis indicated that fatigue scores were the strongest predictor of overall psychological distress, accounting for a significant portion of the variance in SCL‐90 scores (β = 0.65, p < 0.001). This finding is consistent with previous literature that underscores the central role of fatigue in the psychopathology observed in chronic fatigue populations. Moreover, the significant positive association with age (β = 0.20, p = 0.010) suggests that older individuals tend to experience higher distress, a trend also reported in studies examining age‐related increases in both fatigue and mental health symptoms (Tetsuka 2021; Torossian and Jacelon 2021; Hu et al. 2025). The negative association with education (β = −0.15, p = 0.040) further aligns with literature suggesting that lower educational attainment may be linked to heightened distress due to reduced coping resources (Williams and Schreier 2005; Ibanez‐Casas et al. 2021).

In subgroup analyses, the effect sizes observed—medium effects for both age (Cohen's d = 0.55) and education (Cohen's d = 0.60) comparisons—support the practical significance of these demographic factors. These findings are in line with earlier research that has demonstrated moderate differences in fatigue and psychological distress levels based on age and socioeconomic factors, where older age and lower education are associated with worse outcomes. The partial eta‐squared values from our ANOVA analyses (0.12 for fatigue scores and 0.15 for psychological distress) further indicate that these factors account for a meaningful proportion of the variance, reinforcing the need to consider these variables when designing interventions for chronic fatigue.

Overall, our study's results corroborate a growing body of literature that emphasises the multifactorial nature of chronic fatigue and its strong association with psychological distress. The robust predictive value of fatigue scores, coupled with the significant roles of age and education, suggests that interventions targeting chronic fatigue should also address demographic vulnerabilities. This integrated approach is echoed in studies advocating for multidisciplinary treatment models that incorporate both physical rehabilitation and psychological support to mitigate the overall burden of chronic fatigue (Alvarez et al. 2022).

Moreover, the results of this study emphasise the need for a multidisciplinary approach to address chronic fatigue and psychological distress. Given the strong relationship between fatigue and mental health symptoms, healthcare providers should consider integrated treatment strategies that incorporate physical rehabilitation, cognitive‐behavioural therapy (CBT) and lifestyle modifications (Engberg et al. 2017). Programs that combine physiotherapy, psychological counselling, and lifestyle interventions may be more effective than addressing fatigue or mental health concerns in isolation. Providing health education and stress management resources to individuals with lower educational backgrounds could help mitigate fatigue and psychological distress (Alvarez et al. 2022). Considering the age‐related increase in fatigue and psychological distress, interventions tailored for older individuals should focus on physical activity, social engagement and mental health support (Hou et al. 2024). Routine screening for chronic fatigue and psychological distress in clinical settings could aid in early identification and management, thereby preventing the progression of severe symptoms (Whiting et al. 2001; Yu et al. 2010).

This study has several limitations that should be acknowledged. First, the study population was recruited from a physiotherapy clinic, which may limit the generalisability of the findings to broader populations, particularly those who do not seek physiotherapy services. Additionally, potential cultural biases should be considered as the sample was drawn from a single physiotherapy clinic in Greece, which may limit the generalisability of the findings to other populations. Moreover, the use of psychotropic medications was not assessed or controlled, which may have influenced the levels of reported psychological distress. Furthermore, the cross‐sectional nature of the study prevents the determination of causal relationships between chronic fatigue, psychological distress and demographic factors. Longitudinal studies are needed to better understand how these relationships evolve over time. Another limitation is the reliance on self‐reported measures, which are subject to recall bias and social desirability effects, potentially influencing the accuracy of participants’ responses. Furthermore, while validated instruments such as the FAS and SCL‐90 were used, the study did not include objective physiological measures of fatigue or mental health status, which could have provided additional insights. Finally, potential confounding variables, such as comorbid medical conditions, medication use, and lifestyle factors (e.g., physical activity, diet and sleep quality), were not extensively controlled for, which may have influenced the results. Future research should aim to address these limitations by incorporating more diverse populations, longitudinal designs, objective assessments, and comprehensive control for confounding factors. However, this study utilises well‐validated assessment tools (FAS, SCL‐90) and a large sample size (N = 172), enhancing reliability. It provides a comprehensive analysis of physical and mental fatigue, along with their associations with psychological symptoms and demographic factors. The findings offer valuable clinical insights, emphasising the need for integrated treatment approaches addressing both physical and mental health concerns.

5. Conclusion

This study highlights the high prevalence of chronic fatigue and psychological distress among participants, with strong correlations between fatigue levels and mental health symptoms. The findings underscore the importance of integrated, multidisciplinary interventions to address both physical and psychological well‐being, particularly for older adults and individuals with lower education levels. Future research should explore longitudinal trends and intervention efficacy, aiming to develop targeted strategies for managing fatigue‐related psychological distress.

Author Contributions

Zacharias Aslanidis: conceptualization, data collection, methodology. Ourania S. Kotsiou: literature review, data interpretation, figure/table preparation, manuscript writing and final editing. All authors have read and approved the final version of the manuscript.

Ethics Statement

Ethical approval was obtained from the relevant institutional review board. Participants were assured of confidentiality, and data handling complied with ethical research guidelines.

Consent

Informed consent was secured from all participants before data collection.

Conflicts of Interest

The authors declare no conflicts of interest.

Funding: The authors received no specific funding for this work.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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