Abstract
Background
Fatigue is one of the main symptoms in anxiety or mood disorders (AMDs). Despite this, different qualitative subjective fatigue dimensions (e.g., physical fatigue, mental fatigue, etc.) have not been researched in relation to depression and especially anxiety symptom severity. The current study examined the associations between depression and anxiety symptom severity and fatigue characteristics in individuals with AMDs.
Methods
A total of 233 individuals with AMDs who were attending a psychiatric daycare unit (78.5% women, mean age 39.0 years) participated in this cross-sectional study. Participants completed the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Multidimensional Fatigue Inventory-20 (MFI-20) self-report questionnaires.
Results
Multivariable regression analysis found that PHQ-9 depression symptom severity was associated with general fatigue (b = 0.366, p < 0.001), physical fatigue (b = 0.503, p < 0.001), reduced activity (b = 0.603, p < 0.001), reduced motivation (b = 0.511, p < 0.001), and mental fatigue (b = 0.459, p < 0.001), according to the MFI-20. GAD-7 anxiety symptom severity was associated with MFI-20 general fatigue (b = 0.185, p = 0.032). Analyses were controlled for age, sex, education, body mass index, smoking, and current medication use. Analyses in comorbid AMDs showed that fatigue was consistently linked to depression severity but not to anxiety severity.
Conclusions
In individuals with AMDs, depression symptom severity was linked to all subjective fatigue characteristics and that is particularly prevalent in individuals with comorbid AMDs. Anxiety symptom severity showed weaker, more specific associations with subjective fatigue characteristics. These results show the importance of assessing and addressing specific fatigue characteristics in the clinical management of AMDs.
Clinical trial number
Not applicable.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12888-026-08356-8.
Keywords: Fatigue, Anxiety, Depression, Symptom burden, Mood disorders
Background
Fatigue is commonly described as a subjective feeling of reduced energy, exhaustion, and diminished capacity for physical or mental work [24]. It is closely linked to various psychiatric disorders, especially prevalent in anxiety and mood disorders (AMDs) [39, 58].
According to the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; (American Psychiatric Association [2]), fatigue is an important symptom and diagnostic criterion for major depressive disorder (MDD) and can occur throughout the illness’ course. For instance, fatigue may precede the onset of MDD and manifest as a premorbid symptom of MDD [27], act as a risk factor for its development in the general population [13], and persist even after hospitalization [17] or remission, with up to 83% of individuals in remission or partial remission of MDD still reporting significant experiences of fatigue [11]. Residual fatigue is associated with worse treatment outcomes, such as inability to reach remission with treatment, and impaired psychosocial functioning [19].
Although anxiety disorders are generally not as closely associated with fatigue compared to mood disorders, the DSM-5 includes “easy fatigability” as a potential symptom of generalized anxiety disorder (GAD; (American Psychiatric Association [2]). However, results from studies that examined the topic are mixed. Jiang et al., [31] found that trait and state anxiety had strong positive correlations with fatigue in individuals with psychiatric disorders, while [28] found no clear correlation between fatigue, loss of energy, and anxiety symptoms in women with probable GAD, suggesting the relationship may be more complex.
Despite the frequent mention of fatigue in both clinical criteria and empirical studies, the specific nature of the relationship between fatigue and AMDs remains insufficiently understood. Most of the existing research treated fatigue as a unidimensional construct and often studied it with a single item question from broader depression inventories [40, 62]. This approach fails to capture the multidimensional nature of fatigue, which may include physical, mental, and motivational components [5]. For example, mental fatigue has been linked to reduced activity and productivity [18] and concentration difficulties, such as an inability to sustain attention and focus [42] – aspects of fatigue not adequately assessed with a single question. Interestingly, Zimmerman et al. [62] reported that while fatigue did not differentiate between levels of depression severity in severely depressed individuals compared to individuals who were moderately depressed, symptoms like indecisiveness and concentration difficulties did, suggesting that different fatigue components may have distinct clinical implications. For example, mental fatigue, reduced activity and motivation has been associated with the presence of obsessive-compulsive personality disorder in individuals with AMDs [22, 55], mental fatigue has been associated with worse sleep quality in individuals with AMDs [54].
Moreover, while some studies reported that fatigue elevates the risk of more severe depression and anxiety symptoms [30, 40, 44], others question the usefulness of fatigue as a marker of severity [20, 62]. These inconsistencies emphasize that prior studies have not examined how distinct fatigue dimensions relate to depression and anxiety symptoms, using a multidimensional fatigue instrument in a clinical population.
Multidimensional Fatigue Inventory-20 (MFI-20) [23, 50] is a well-established self-report questionnaire that consists of five different fatigue dimensions: general fatigue, physical fatigue, reduced activity, reduced motivation, and mental fatigue. The questionnaire has been found to be valid and reliable for assessing fatigue in individuals with MDD with residual symptoms [10]. The MFI-20 has also been widely used in broader clinical populations beyond psychiatry, such as individuals with chronic medical conditions (e.g., cancer, multiple sclerosis, coronary artery disease) [4, 23, 29], burnout [25], as well as in general population samples [59]. The application of a widely used multidimensional inventory may help us facilitate broader understanding of fatigue characteristics across medical and mental health specialties.
Depression and anxiety disorders are highly comorbid [48] and this overlap challenges both clinical diagnosis and treatment planning, as symptom-based assessments may fail to identify the distinct contributions of subjective fatigue characteristics to depression or anxiety symptoms. For example, in a study by Gao and Calabrese [21], anxiety severity was not associated with the severity of fatigue in individuals with MDD and bipolar disorder. Understanding how specific fatigue characteristics relate to depression and anxiety symptoms in comorbid AMDs might help to further explore factors uniquely associated with AMDs diagnostic criteria and improve therapeutic strategies. Therefore, the aim of the current exploratory study was to explore the associations between depressive and anxiety symptoms, respectively, with subjective fatigue characteristics, for the first time assessed with the MFI-20 in a sample of individuals with AMDs. In order to reach this goal, we have used a cross-sectional study design. Although causal relationships cannot be inferred from cross-sectional data, we aimed to clarify whether specific fatigue characteristics differentially associate with depressive or anxiety symptoms in individuals with AMDs, potentially offering more targeted insights for assessment and treatment.
Methods
Study procedure and participants
A cross-sectional study was conducted among individuals admitted to the Stress-Related Disorders daycare unit of Palanga Hospital (Neuroscience Institute, Lithuanian University of Health Sciences) with an AMD diagnosis (for details, see Results and Table 1). The study was conducted between April 2018 and September 2022. A convenience sample of clinic patients was recruited through in-person study introductions delivered during weekly patient meetings. Individuals included in the study had to be 18 years or older and had to have any of the following AMDs: major depressive disorder, dysthymia, bipolar disorder, generalized anxiety disorder, panic disorder, agoraphobia and social anxiety disorder. Individuals were excluded from the study if they had severe somatic illness (e.g., thyroid-related disorder, cancer), current psychotic symptoms, cognitive impairment, high suicidal risk, and were unable to speak fluent Lithuanian. Out of 291 initially interested individuals, 58 (19.9%) individuals were excluded from the study based on the following exclusion criteria: (a) did not have AMDs and were attending the clinic for different diagnosis, e.g. obsessive-compulsive disorder (n = 33; 11.3%); (b) had significant cognitive impairment as documented in clinical history that could impair the ability to accurately self-reflect on symptom severity (n = 2; 0.7%); (c) had severe somatic illnesses, e.g. cancer (n = 10; 3.4%); and (d) did not provide consent after the initial inclusion interview (n = 13; 4.5%). The final sample consisted of 233 individuals, with the response rate of 80.1%.
Table 1.
Sociodemographic and psychological characteristics of the study participants
| Total (N = 233) |
|
|---|---|
| Age, mean (95% CI) | 39.0 (37.4–40.5) |
| Sex, n (%) | |
| Men | 50 (21.5) |
| Women | 183 (78.5) |
| Education, n (%) | |
| Tertiary education | 67 (28.8) |
| College/university degree | 166 (71.2) |
| Anxiety and mood disorders | |
| Mood | 53 (22.7) |
| Anxiety | 60 (25.8) |
| Anxiety and mood | 120 (51.0) |
| Diagnosis (ICD-10 code), n (%) | |
| Major depressive disorder (F32.0-F32.3) | 161 (69.1) |
| Dysthymia (F34.1) | 31 (13.3) |
| Bipolar disorder (F31) | 23 (9.9) |
| Depressive episode (F31.3-F31.4) | 16 (69.6) |
| Manic episode (F31.0-F31.1) | 7 (30.4) |
| Generalized anxiety disorder (F41.1) | 91 (39.1) |
| Panic disorder (F41.0) | 84 (36.1) |
| Agoraphobia (F40.0) | 64 (27.5) |
| Social anxiety disorder (F40.1) | 54 (23.2) |
| Current medication use, n (%) | |
| Antidepressants | 166 (71.2) |
| Benzodiazepines | 86 (36.9) |
| Mood stabilizers | 10 (4.3) |
| Antipsychotics | 57 (24.5) |
| History of smoking, n (%) | 60 (25.8) |
| Fatigue as measured with the MFI-20, mean (95% CI) | |
| General fatigue | 15.0 (14.5–15.5) |
| Physical fatigue | 13.5 (12.9–14.1) |
| Reduced activity | 14.1 (13.6–14.6) |
| Reduced motivation | 13.2 (12.7–13.6) |
| Mental fatigue | 13.9 (13.9–15.0) |
| PHQ-9 | |
| PHQ-9, total score; mean (95% CI) | 12.5 (11.7–13.3) |
| PHQ-9 total score ≥ 11, n (%)* | 140 (60.1) |
| GAD-7 | |
| GAD-7, total score; mean (95% CI) | 8.2 (7.7–8.7) |
| GAD-7 total score ≥ 7, n (%)* | 167 (71.7) |
Note. CI – confidence interval; ICD-10 – International Classification of Diseases, 10th Revision; MFI-20 – Multidimensional Fatigue Inventory-20; PHQ-9 – Patient Health Questionnaire-9; GAD-7 – Generalized Anxiety Disorder-7
*Cut-off score based on Stanyte et al., [52]
Standard treatments were provided to all participants in accordance with their clinical needs. Same methodology has been described previously in another study [54].
The study procedure was approved by the Kaunas Regional Biomedical Research Ethics Committee (reference no. B-2-38), and the study was consistent with the principles of the Declaration of Helsinki. Before being included in the study, each participant signed an informed consent form.
Measures
During the first 5 days of admission, sociodemographic and clinical characteristics were evaluated. Diagnoses of AMD were evaluated by a trained clinical psychologist using Mini-International Neuropsychiatric Interview (M.I.N.I.) 7.0.2. Sheehan et al., [49]. Other characteristics included were age, sex, education level, body mass index (BMI), current smoking status, medication use, depression, anxiety symptoms, and subjective fatigue characteristics.
The following questionnaires were used: The Patient Health Questionnaire-9 (PHQ-9; [35, 43, 52] was used to assess depression severity. In the present study, McDonald’s omega for the measure was 0.88. The Generalized Anxiety Disorder-7 (GAD-7; [43, 51, 52] was used to assess anxiety severity. McDonald’s omega for the measure was 0.84. The MFI-20 [23, 50] was used to evaluate subjective fatigue characteristics, such as general fatigue, physical fatigue, reduced activity, reduced motivation, and mental fatigue. In the current study, McDonald’s omega for the measure was 0.93. In all the scales used, higher scores indicated higher symptom or subjective fatigue severity. Detailed descriptions of questionnaires used can be found in another study [54].
Statistical analyses
Our statistical analyses were completed with SPSS Version 27.0 for Windows (SPSS Inc., Chicago, IL, USA). Descriptive statistics (means and frequencies) were calculated for all demographic and psychological variables included in the study. Correlations between study variables (depression, anxiety symptom severity, and fatigue characteristics) were assessed using the Pearson correlation coefficient. Multivariable regression analyses were used to examine associations between depression and anxiety symptom severity and fatigue characteristics. Multidimensional regression analysis models included both depression and anxiety symptoms, allowing us to control for the possible effects of anxiety and depression symptoms in the model as well as adjusting for age, sex, education, BMI, smoking, and current medication use. Smoking and BMI were included in the models since smoking [15, 16] and higher BMI [14, 45] have been linked with greater fatigue.
Results
A total of 233 individuals were included in this study (78.5% female). Participants had a mean age of 39 years (95% confidence interval [CI] = 37.4–40.5). Moreover, 51% of participants had a comorbid diagnosis of both depression and anxiety disorders. The most common current diagnosis was MDD (69.1%), followed by GAD (39.1%) and panic disorder (36.1%). Table 1 presents a detailed description of the participants.
We also compared subjective fatigue characteristics between separate diagnostic groups (Supplemental Table S1). We found that in comorbid AMDs group, all subjective fatigue characteristics were higher (all p < 0.001).
We then analysed correlations between depression and anxiety symptom severity and subjective fatigue characteristics. Depression symptom severity displayed moderate positive correlations with all the subjective fatigue characteristics: physical fatigue (r = 0.529, p < 0.001), reduced activity (r = 0.525, p < 0.001), general fatigue (r = 0.511, p < 0.001), reduced motivation (r = 0.484, p < 0.001), and mental fatigue (r = 0.476, p < 0.001). Anxiety symptom severity was also positively correlated with all the subjective fatigue characteristics: a moderate positive correlation with general fatigue (r = 0.453, p < 0.001) and positive weak associations with physical fatigue (r = 0.376, p < 0.001), mental fatigue (r = 0.365, p < 0.001), reduced activity (r = 0.334, p < 0.001), and reduced motivation (r = 0.330, p < 0.001) were observed.
Next, we evaluated if the associations between depression and anxiety symptom severity and subjective fatigue characteristics were independent of the evaluated sociodemographic characteristics, BMI, smoking, and current medication use (Table 2). Multivariable regression analysis showed that depression symptom severity as measured by the PHQ-9 was associated with higher fatigue characteristics of general fatigue (β = 0.366, p < 0.001), physical fatigue (β = 0.503, p < 0.001), reduced activity (β = 0.603, p < 0.001), reduced motivation (β = 0.511, p < 0.001), and mental fatigue (β = 0.459, p < 0.001) after adjusting for age, sex, education, BMI, smoking, and current medication use. GAD-7 anxiety symptom severity was associated with higher general fatigue (β = 0.185, p = 0.032), again after adjusting for age, sex, education, BMI, smoking, and current medication use.
Table 2.
Multivariable regression analyses of associations between depression and anxiety symptom severity and subjective fatigue characteristics (N = 233)
| R2 | PHQ-9 | GAD-7 | |||||
|---|---|---|---|---|---|---|---|
| B (95% CI) | β | p | B (95% CI) | β | p | ||
| General fatigue | 0.266 | 0.238 (0.127; 0.349) | 0.366 | < 0.001 | 0.206 (0.018; 0.393) | 0.185 | 0.032 |
| Physical fatigue | 0.308 | 0.365 (0.245; 0.486) | 0.503 | < 0.001 | 0.044 (–0.160; 0.248) | 0.035 | 0.672 |
| Reduced activity | 0.261 | 0.406 (0.291; 0.521) | 0.603 | < 0.001 | –0.098 (-0.293; 0.097) | –0.085 | 0.323 |
| Reduced motivation | 0.232 | 0.302 (0.199; 0.405) | 0.511 | < 0.001 | –0.026 (–0.200; 0.149) | –0.025 | 0.773 |
| Mental fatigue | 0.218 | 0.315 (0.194; 0.436) | 0.459 | < 0.001 | 0.064 (–0.140; 0.268) | 0.055 | 0.538 |
Note. PHQ-9 – Patient Health Questionnaire-9; GAD-7 – Generalized Anxiety Disorder-7. Values adjusted for age, sex, education, body mass index, smoking, and current medication use. Variance inflation factors (VIF) ranged from 2.32 to 2.35, indicating no problematic multicollinearity. p < 0.05, bold
Finally, we evaluated the associations between depression and anxiety symptom severity and subjective fatigue characteristics in different diagnosis groups (Table 3). Multivariable regression analyses for mood disorders (n = 53) showed significant associations between PHQ-9 scores and reduced activity (β = 0.502, p = 0.047) and between GAD-7 scores and general fatigue (β = 0.502, p = 0.023). Multivariate regression analyses for anxiety disorders (n = 60) showed significant associations between PHQ-9 scores and physical fatigue (β = 0.560, p = 0.003), reduced activity (β = 0.645, p < 0.001), and mental fatigue (β = 0.640, p < 0.001); no significant associations between GAD-7 symptoms and subjective fatigue characteristics were observed. Finally, multivariate regression analyses for comorbid AMDs (n = 120) showed significant associations between PHQ-9 scores and all subjective fatigue characteristics, including general fatigue (β = 0.382, p = 0.002), physical fatigue (β = 0.473, p < 0.001), reduced activity (β = 0.579, p < 0.001), reduced motivation (β = 0.486, p < 0.001), and mental fatigue (β = 0.438, p < 0.001). No significant associations with GAD-7 scores and subjective fatigue characteristics in this group were observed.
Table 3.
Multivariable regression analyses of associations between depression and anxiety symptom severity and subjective fatigue characteristics in different diagnosis groups
| R2 | PHQ-9 | GAD-7 | |||||
|---|---|---|---|---|---|---|---|
| B (95% CI) | β | p | B (95% CI) | β | p | ||
| Mood disorders ( n = 53) | |||||||
| General fatigue | 0.257 | 0.142 (-0.117; 0.402) | 0.240 | 0.274 | 0.493 (0.073; 0.913) | 0.502 | 0.023 |
| Physical fatigue | 0.269 | 0.326 (-0.054; 0.525) | 0.353 | 0.107 | 0.349 (–0.118; 0.816) | 0.317 | 0.138 |
| Reduced activity | 0.052 | 0.318 (0.005; 0.631) | 0.502 | 0.047 | 0.012 (-0.494; 0.517) | 0.011 | 0.963 |
| Reduced motivation | 0.256 | 0.234 (–0.001; 0.465) | 0.436 | 0.051 | 0.081 (–0.298; 0.460) | 0.091 | 0.669 |
| Mental fatigue | 0.215 | 0.123 (–0.189; 0.435) | 0.177 | 0.429 | 0.396 (–0.108; 0.900) | 0.344 | 0.120 |
| Anxiety disorders ( n = 60) | |||||||
| General fatigue | 0.255 | 0.305 (-0.011; 0.622) | 0.359 | 0.058 | 0.220 (–0.211; 0.651) | 0.193 | 0.310 |
| Physical fatigue | 0.317 | 0.497 (0.180; 0.813) | 0.560 | 0.003 | 0.007 (–0.424; 0.438) | 0.006 | 0.976 |
| Reduced activity | 0.307 | 0.529 (0.234; 0.823) | 0.645 | < 0.001 | –0.066 (-0.467; 0.336) | –0.059 | 0.744 |
| Reduced motivation | 0.110 | 0.196 (–0.087; 0.480) | 0.282 | 0.170 | 0.174 (–0.212; 0.560) | 0.186 | 0.369 |
| Mental fatigue | 0.337 | 0.536 (0.242; 0.830) | 0.640 | < 0.001 | 0.002 (–0.399; 0.403) | 0.008 | 0.994 |
| Comorbid anxiety and mood disorders ( n = 120) | |||||||
| General fatigue | 0.182 | 0.260 (0.100; 0.420) | 0.382 | 0.002 | 0.027 (–0.255; 0.310) | 0.023 | 0.847 |
| Physical fatigue | 0.221 | 0.368 (0.190; 0.546) | 0.473 | < 0.001 | –0.168 (–0.493; 0.146) | -0.124 | 0.291 |
| Reduced activity | 0.235 | 0.412 (0.251; 0.574) | 0.579 | < 0.001 | –0.171 (-0.456; 0.115) | –0.137 | 0.238 |
| Reduced motivation | 0.137 | 0.316 (0.159; 0.473) | 0.486 | < 0.001 | –0.083 (–0.359; 0.194) | –0.073 | 0.556 |
| Mental fatigue | 0.108 | 0.304 (0.134; 0.474) | 0.438 | < 0.001 | –0.073 (–0.374; 0.227) | –0.060 | 0.631 |
Note. PHQ-9 – Patient Health Questionnaire-9; GAD-7 – Generalized Anxiety Disorder-7. Values adjusted for age, sex, education, body mass index, smoking, and current medication use. Variance inflation factors (VIF) ranged from 2.04 to 3.20, indicating no problematic multicollinearity. p < 0.05, bold
Since PHQ-9 includes an item directly assessing fatigue (item 4 “feeling tired or having little energy”), there may be a possible overlap with the constructs measured by the MFI-20. To investigate this, we calculated correlations (Supplemental Table S2) and ran a multivariate regression analyses (Supplemental Table S3 and Supplemental Table S4) excluding the item 4 from the PHQ-9. After removing the PHQ-9 item 4, all correlations and multivariable regression associations remained significant, except the association between PHQ-9 and reduced activity in mood disorders (β = 0.402, p = 0.105; Supplemental Table S4).
Discussion
Main findings
Our current study examined the relationship between depression and anxiety symptom severity and subjective fatigue characteristics, as measured by the MFI-20 questionnaire for the first time in individuals with AMDs. Moreover, our study examined these associations in different disorder groups. Our study findings highlight the association between depression symptom severity and all the subjective fatigue characteristics (general fatigue, physical fatigue, reduced activity, reduced motivation, and mental fatigue) as measured by the MFI-20. Furthermore, they show the potential link between anxiety symptom severity and general fatigue even after controlling for age, sex, education, BMI, smoking, and current medication use. In comorbid AMDs, subjective fatigue characteristics are associated specifically with depression symptom severity, not with anxiety symptom severity.
Fatigue and depression symptom severity
Fatigue is one of the diagnostic criteria for MDD [2], and our study results confirm the relationship between subjective fatigue and depression symptom severity. Other studies have also shown that fatigue severity can correlate with depression severity [46, 57]. Zimmerman et al., [62] found that fatigue, defined as loss of energy, was not associated with higher levels of depression severity. However, in the same study, concentration and indecisiveness, which are similar to the construct of mental fatigue, were related to depression severity [62], showing that some aspects of subjective fatigue are still related to depressive symptoms. It is important to understand that even though fatigue is often seen as a dependent feature of AMDs, it can also be an independent symptom that can exist even without the experience of depression or anxiety [27]. However, the causal relationship between variables is still under-researched. Future research is needed to investigate the causality of the relationship, as both fatigue and depression are seen to increase the risk of one another [13].
Because there is an overlap between the questionnaires measuring depressive symptoms (PHQ-9) and fatigue (MFI-20), we wanted to investigate whether fatigue is an independent correlate or just a defining component of depressive symptomatology. The results indicate that the exclusion of the PHQ-9 question resulted in minimal and non-significant decreases in the associations, suggesting that fatigue can be seen as an independent correlate in the relationship. Similar results were seen in a study by Bunevicius et al., [7] examining the relationship between depression and fatigue in individuals with coronary artery disease. They propose that the cumulative score of depression itself, rather than a single specific item related to fatigue, determine the association between depression and subjective fatigue in individuals with coronary artery disease. Therefore, fatigue-related items should not be removed. Similarly, our study results suggest that subjective fatigue characteristics could serve as potential markers for the severity of depressive symptoms in individuals with AMD.
Fatigue and anxiety symptom severity
We additionally found associations between anxiety symptom severity and subjective fatigue characteristics. Other studies have found elevated levels of fatigue in individuals with panic disorder [33] and in women with GAD [36]. However, anxiety symptom severity has not previously been associated with an increase in subjective fatigue. It is important to note that the associations with anxiety symptom severity were weak and should be interpreted with caution.
Fatigue and comorbid AMDs
Moreover, an analysis in different disorder groups showed specific relationships between subjective fatigue characteristics and depression and anxiety symptom severity. Most notably, in individuals with comorbid AMDs, subjective fatigue characteristics were associated with depression symptom severity and not with anxiety symptom severity. In a study by Gao and Calabrese [21] anxiety severity was not associated with fatigue after controlling for possible confounders in individuals with MDD and bipolar disorder. Our study expands on these results and suggests that while anxiety severity is associated with fatigue, the severity of depressive symptoms, especially in comorbid cases, has a more consistent and independent association with fatigue severity. Similar patterns can be seen in studies examining the relationship between anxiety and fatigue in different populations. Even though anxiety is reported as an important, yet usually weak correlate to fatigue, depression is still seen as a more important variable in individuals with multiple sclerosis or cancer [1, 6]. Other studies have explained the connection between trait anxiety and the experience of fatigue through personality characteristics, such as low self-directedness and high harm avoidance [31]. However, it is important to note that other studies usually treat anxiety either as a state or trait [31], while the current study focused on individuals with AMDs and measured anxiety symptom severity with the GAD-7 questionnaire, which measures symptoms of anxiety in a period of 2 weeks.
Clinical implications
Symptom severity has clinical importance, as it influences treatment decisions and management options and affects functional impairment as well as emotional well-being [26, 37]. Our results suggest that subjective fatigue characteristics in AMDs should not be treated as a nonspecific unidimensional symptom, but should be routinely assessed with multidimensional tools such as the MFI-20. In practice, clinicians should place particular emphasis on screening for different fatigue characteristics in individuals with higher depression severity. In contrast, since anxiety severity showed limited associations with fatigue, clinicians may avoid over-attributing fatigue complaints to anxiety alone and instead evaluate for co-occurring depression. For individuals with comorbid AMDs, prioritizing interventions that reduce depressive symptoms may yield the greatest improvements in fatigue. Overall, incorporating structured fatigue assessment into routine evaluation and tailoring interventions to specific fatigue characteristics could improve functional outcomes and treatment precision in individuals with AMDs.
It is important to note that part of our study took place during the coronavirus (SARS-CoV-2; COVID-19) pandemic, therefore it is important to note the potential impact that the pandemic had on the current study. During the COVID-19 pandemic, the rates of depression and anxiety increased [61]. However, a systematic review and meta-analysis of longitudinal cohort studies examining changes in mental health during the pandemic showed that symptoms tend to decrease to pre-pandemic levels [47]. They also found no evidence of worsening mental health symptoms in participants with pre-existing mental health conditions [47]. Nevertheless, COVID-19 symptoms can persist long after the infection. Post-COVID-19 syndrome includes such symptoms as depression [38], anxiety [9], and fatigue [3, 32]. During the COVID-19 pandemic, day care unit work capacity was limited and data was not collected during that time. After the restrictions were lifted, data collection was resumed. Only a small part of the participants was included during that period. However, future research should keep in mind the effects of COVID-19, especially as a form of post-COVID-19 syndrome, and control for the possible effects on fatigue and AMD symptoms.
Strengths and limitations
To the best of our knowledge, this is the first study to investigate the associations between depressive and anxiety symptoms and subjective fatigue characteristics as measured with the MFI-20 in individuals with AMDs.
However, the results of this study need to be interpreted in the light of some limitations. First, our chosen cross-sectional study design prevented us from making any inferences about causality. Second, we used a convenience sample of individuals from a single day care unit, which makes it harder to generalize results to a broader population of individuals with AMDs. Third, our study sample was predominantly female, which may have had an effect on the external validity. Since women tend to have a higher prevalence of AMDs [56] and report higher levels of fatigue [41, 60] compared to men, this could have also influenced the observed prevalence of both AMDs and fatigue characteristics. Finally, our recruitment process only excluded individuals with severe somatic illnesses and included those with mild or moderate medical comorbidities. Various somatic diseases can enhance the experience of fatigue [41], therefore future studies should include medical comorbidities as a potential confounder in the analysis. Similarly, the possible effects of COVID-19 and post-COVID-19 syndrome were not included in our study.
For future studies, we recommend considering other variables not included in the present study and researching their potential impact on the relationship between subjective fatigue characteristics and depression and anxiety symptom severity. For example, obsessive-compulsive personality disorder, which is prominent in psychiatric populations [12], has been connected to the prevalence of mental fatigue in individuals with AMDs [22], while specific obsessive-compulsive personality traits (e.g., rigidity and preoccupation with details) have been associated with various subjective fatigue characteristics in individuals with AMDs [53]. Other factors, such as cognitive functioning [8] and social support [34], have been linked to subjective fatigue characteristics in individuals with coronary artery disease, which might also apply to individuals with AMDs.
Conclusions
In conclusion, our results confirm that in individuals with AMDs, depression symptom severity is associated with a higher level of all subjective fatigue characteristics as measured with the MFI-20, independent of the sociodemographic variables and anxiety symptoms. These associations are particularly prevalent in individuals with comorbid AMDs. Simultaneously, our study found that anxiety symptom severity may be associated with some aspects of subjective fatigue, namely general fatigue. However, the correlations between anxiety and fatigue should be interpreted with caution. Certain aspects of subjective fatigue could have clinical significance as potential markers of the severity of depressive and anxiety symptoms in individuals with AMDs. Future research is needed to confirm such a hypothesis, especially concentrating on the anxiety symptoms and their potential relationship with subjective fatigue.
Electronic Supplementary Material
Below is the link to the electronic supplementary material.
Acknowledgements
We appreciate the members of the European College of Neuropsychopharmacology (ECNP) Obsessive Compulsive and Related Disorders Research Network (OCRN) and Anxiety Disorders Network (ADRN) (members: NF, KD, JB), whose comments have shaped this manuscript in its development. The ECNP, OCRN, and ADRN are components of the ECNP-Network Initiative (ECNP-NI) and receive financial support from the ECNP to support its academic activities.
Abbreviations
- AMD
Anxiety and mood disorders
- BMI
Body mass index
- GAD
Generalized anxiety disorder
- GAD-7
Generalized Anxiety Disorder-7
- MDD
Major depressive disorder
- MFI-20
Multidimensional Fatigue Inventory-20
- PHQ-9
Patient Health Questionnaire-9
Authors contributions
AS, VS, JB contributed to the study conception and design. AP performed statistical analysis. AS, AP, JB interpreted the data. The first draft of the manuscript was written by AS and all authors (NF, KD, JGS, JM, VS, JB) commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
The funding source was not involved in the conduct of the research and preparation of this article.
Data availability
The datasets used and analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The study procedure was approved by the Kaunas Regional Biomedical Research Ethics Committee (reference no. B-2-38), and the study was conducted in accordance with the Declaration of Helsinki. Before being included in the study, each participant signed an informed consent form.
Consent for publication
Not applicable.
Competing interests
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Naomi A. Fineberg reports in the past 5 years personal fees from Taylor and Francis, Oxford University Press, Global Mental Health Academy, and Elsevier; she reports personal fees and non-financial support from Sun, non-financial support from RCPsych, CINP, WPA, the International Forum of Mood and Anxiety Disorders, ECNP, and the Indian Association of Biological Psychiatry and grants from Wellcome, UKRI, Orchard, and NIHR, and grants and non-financial support from EU COST Action, and payment for consultancy from the UK MHRA, all outside of the submitted work. Katharina Domschke is a member of the Lundbeck Neurotorium Editorial Board and has been a member of the Steering Committee Neuroscience, Janssen Pharmaceuticals, Inc., since 2022. Julija Gecaite-Stonciene works as a consultant at FACITtrans. Jurate Macijauskiene reports collaboration with Ipsen. Vesta Steibliene reports personal fees from Lundbeck, Sanofi-Aventis, Servier, Janssen, and grants from the Lithuanian Research Council. In the past 2 years, JB has been serving as a consultant at IQVIA and has received research funding grants from the Research Council of Lithuania and speaking fees from the Council of Europe International Cooperation Group on Drugs and Addiction (Pompidou Group). The other authors had no conflicts of interest to declare.
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Data Availability Statement
The datasets used and analysed during the current study are available from the corresponding author on reasonable request.