Home Medicine Pain intensity in anatomical regions in relation to psychological factors in hypermobile Ehlers–Danlos syndrome
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Pain intensity in anatomical regions in relation to psychological factors in hypermobile Ehlers–Danlos syndrome

  • Tage Orenius EMAIL logo , Karin von Smitten-Stubb , Hannu Kautiainen , Liisa Montin , Antonio Bulbena and Karl-August Lindgren
Published/Copyright: June 16, 2025
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Abstract

Objectives

Hypermobile Ehlers–Danlos syndrome (hEDS) is a multisystemic disorder in which pain and psychological symptoms appear to be highly interrelated. We investigate the relationships between pain intensity, pain location, and psychological distress in patients with hEDS.

Methods

The study sample in this cross-sectional study comprised patients with diagnosed hEDS (n = 81) aged 18–67 years, with a mean age of 39.5. Sociodemographic information was collected using a questionnaire. Pain intensity was measured using the numeric rating scale, depressive symptoms with the Beck Depression Inventory, and pain-related anxiety with the Pain Anxiety Symptoms Scale. The interrelations between pain intensity and psychological factors were analysed for each of the following anatomical regions: head, neck, upper extremities, chest, back, abdomen, and lower extremities.

Results

The results show that pain was intense and occurring in multiple anatomical regions. Pain intensity was related to depressive symptoms and pain anxiety, with the strength of the relationship varying across different anatomical regions. Specific findings were that strongest associations of depressive symptoms and pain intensity were in the abdomen and lower extremities. In contrast, pain in the upper extremities did not relate to depressive symptoms or pain anxiety.

Conclusion

This is the first study on patients with hEDS that elucidates the multisite pain symptoms and their interrelation to psychological symptoms. The total burden of pain can be considered a strong contributing element to the results found in our study. These factors should be considered when treating patients with hEDS.

1 Introduction

The hypermobile subtype of Ehlers–Danlos Syndrome (hEDS) is a condition with a genetic background, which is estimated to affect 1 per 10,000–15,000 [1]. The hEDS diagnosis is based on clinical findings based on the international hEDS criteria [2]. Increased joint mobility, stretchable skin, and tissue fragility due to collagen defects, and a broad range of neurological, mucocutaneous, musculoskeletal, and gastrointestinal symptoms present with considerable variation in hEDS [2]. Musculoskeletal pain in two or more limbs for at least 3 months or chronic widespread pain is included in the diagnostic criteria [2]. Pain prevalence in hEDS patients ranges from 43 [3] to 97% [4] with the pain intensity showing a gradual increase over time in 75% of patients [4]. The pain is typically localized in several parts of the body [5,6].

Chronic pain conditions in general implicate complex, multidimensional developmental processes in which various psychosocial factors play a major role [7]. In patients with hEDS pain often impairs daily life and social interactions moderately to severely [8] and relates to lower health-related quality-of-life and greater psychological distress such as anxiety and depression, when compared to healthy individuals [9]. Most commonly diagnosed psychiatric disorders in hEDS are mood disorders and anxiety disorders [10]. It has been proposed that there is a relationship between anxiety, psychological dysfunction, and emotional problems, with indications that 70% of patients with hEDS report lifetime clinical anxiety [11]. It has been shown that 22.4% of patients with hEDS scored high on depression [12]. Further, high depressive symptomatology is significantly higher in highly anxious patients with hEDS [11].

A strong linear relationship between the number of pain sites with a decline in overall health, sleep quality, and psychological health have been shown in chronic conditions [13]. Pain at multiple locations is a risk indicator for developing depressive and anxiety disorders [14]. Patients with hEDS often experience chronic pain that can manifest across various anatomical regions [8]. The features of pain in hEDS are complex and poorly understood by clinicians [4] and the interrelations between anatomical region-specific pain in relation to psychological factors in hEDS have not been studied. Therefore, we investigated pain intensity in specific anatomical regions in relation to depressive symptoms and pain anxiety in patients with hEDS.

2 Methods

The study participants, all patients with a verified diagnosed hEDS, were recruited through a private clinic and the Finnish Ehlers–Danlos Association. Questionnaires were administered to 111 patients with hEDS: 17 received the questionnaires during a rehabilitation course at a private clinic, and 94 received theirs via mail. A total of 89 questionnaires were returned, yielding a response rate of 80%. Due to insufficient data or an incorrect diagnosis, eight questionnaires were discarded. The participants were provided with written information about the study.

This research project received ethics approval from the Research Ethical Committee at Helsinki University Hospital, Hospital District of Helsinki and Uusimaa (HUS), with reference number 312/13/03/2014.

2.1 Materials and measures

Demographic information, including gender, age, marital status, educational status, and employment status, was collected using a custom-made questionnaire. The study sample comprised 81 patients diagnosed with hEDS, ranging in age from 18 to 67 years, with a mean age of 39.5 years (standard deviation = 10.6). A detailed breakdown of the participants’ demographics is provided in Table 1. Among the 81 participants, 46 (56.8%) received their hEDS diagnosis at the department of clinical genetics of a university hospital in Finland, while 34 (42.2%) received their diagnosis at other medical clinics. Data on one participant were incomplete.

Table 1

Socio-demographics and clinical data on study participants (patients with hEDS)

Demographics n = 81
Female, n (%) 78 (96)
Mean age (SD) 39 (11)
Cohabiting, n (%) 53 (65)
Educational status
Basic education only 13 (16)
Vocational education 31 (38)
Upper secondary school 3 (4)
Upper secondary school and vocational education 20 (25)
Higher education 14 (17)
Employment status
Employed 45 (56)
Studying 10 (12)
Unemployed 10 (12)
Retired 16 (20)

Note. hEDS, hypermobile type Ehler–Danlos Syndrome; n, number of participants; SD, standard deviation.

Pain intensity was measured with a questionnaire that employs the numeric rating scale (NRS), a 0–10 scale on which 0 denotes “no pain” and 10 denotes “the worst pain possible,” which is a standard method used in clinical pain practice [15]. For general purposes, the NRS has good sensitivity and generates useful clinical data; furthermore, it is feasible, provides reliable scores, and is translatable to multi-item patient-reported outcome measures for audit purposes [16]. Pain intensity was measured for the head, neck, upper extremities, chest, back, abdomen, and lower extremities, according to earlier studies on pain [17,18].

Depressive symptoms were measured using the 21-item Beck Depression Inventory (BDI), version 2 (BDI-II) [19]. The BDI is frequently employed in population-based studies as a tool for assessing depression [20], and the Finnish version has shown acceptable psychometrics [20]. Furthermore, it has been demonstrated that the BDI has good construct validity and internal consistency for assessing depressive symptoms in both women and men with chronic pain [21]. The BDI has proven useful for assessing depression among patients with chronic musculoskeletal disorders, with a reported sensitivity of 87.5% in detecting clinical depression in patients with chronic musculoskeletal problems and comorbid depression [22]. According to the reference levels specified in the BDI manual, a score of 0–13 indicates minor depression, 14–19 indicates mild depression, 20–28 indicates moderate depression, and 29–63 indicates severe depression [19].

Pain-related anxiety was measured using the Pain Anxiety Symptoms Scale-20 (PASS-20), which has sub-scales for cognitive anxiety, avoidance behaviours, fear of pain, and physical symptoms of anxiety [23]. The PASS has been shown to have a strong reliability, with minimal validity shrinkage [24].

2.2 Statistical analysis

The study data are presented as mean values (M) with standard deviations (SD) or as counts with percentages. The 95% confidence intervals (CI) are given for the most important outcomes. Correlation coefficients were calculated using Pearson’s method. Differences in the NRS scores for the seven anatomical regions were determined using a multivariate approach that employs a bootstrap-type multivariate Hotelling’s T-squared test (with a paired approach), which is a suitable method of simultaneously comparing the means of all variables of interest in this study while maintaining the chosen magnitude of type I error. Curvilinear relationships between the NRS, BDI, and PASS-20 scores were derived from regression models, including the quadratic terms of the interrelated variables – the models include age and gender as covariates. The Stata 18.0 statistical package (StataCorp LP, College Station, Texas, USA) was used for the data analysis.

3 Results

The number of anatomical regions in which participants reported pain ranged from 6 of 7 (3.7%) to 7 of 7 (96.3%). The total mean pain intensity reported in the study sample was 4.80 (SD = 1.65), while the most intense level of pain reported was 7.4 (SD = 1.87) on the NRS. The anatomical region for which the most intense pain was reported was the back (M = 5.99, SD = 2.24), followed by the lower extremities (M = 5.83, SD = 2.28), neck (M = 5.68, SD = 2.29) and upper extremities (M = 5.25, SD = 2.11). The mildest reported pain intensity was in the chest (M = 3.07, SD = 2.38) followed by the abdominal pain (M = 3.08, SD = 2.40) and head pain (M = 4.34, SD = 2.52). The pain intensity in specific anatomical regions is plotted in Figure 1. The NRS scores reported for different body regions differed significantly (p < 0.001).

Figure 1 
               NRS scores (0–10), including confidence intervals (95% CI), of hEDS patients for seven anatomical regions.
Figure 1

NRS scores (0–10), including confidence intervals (95% CI), of hEDS patients for seven anatomical regions.

The study participants had a mean BDI score of 18.07 (SD = 11.26), with scores ranging between 0 and 57. Based on the diagnostic reference values for the BDI-II [17], 32 (39.5%) patients had minor depression (0–13), 18 (22.2%) had mild depression (14–19), 18 (22.2%) had moderate depression (20–28), and 13 (16.0%) were severely depressed (29–63). A positive correlation was found between the BDI scores and the NRS scores (r[76] = 0.366, p = 0.001).

The PASS-20 total scores – ranging between 3 and 89 – had a mean of 46.10 (SD = 18.29). There was a significant positive linear correlation between the PASS-20 and NRS total scores (r[76] = 0.347, p = <0.002; Table 2). Correlations between NRS, BDI, and Pass-20 are presented in Table 2 and Figure 2.

Table 2

Correlations (age and gender controlled) between pain intensity (NRS scores) in various anatomical regions and depressive symptoms and pain anxiety in patients with hEDS. The table presents the correlation coefficients for these variables for various body regions

Measure Head Neck Upper extremities Chest Back Abdomen Lower extremities Total
Body regions
BDI 0.20 0.27* 0.22 0.27* 0.21 0.29** 0.33** 0.36**
PASS-20 0.24* 0.25* 0.17 0.25* 0.28* 0.22* 0.27* 0.34**

Note. *p < 0.05 and **p < 0.01. NRS, Numeric Rating Scale; BDI, Beck Depression Inventory; PASS-20, Pain Anxiety Symptom Scale.

Figure 2 
               Pain intensity (NRS) in relation to depressive symptoms (BDI) and pain anxiety (PASS-20). The age- and gender-adjusted quadratic equation and grey bands show the 95% CI.
Figure 2

Pain intensity (NRS) in relation to depressive symptoms (BDI) and pain anxiety (PASS-20). The age- and gender-adjusted quadratic equation and grey bands show the 95% CI.

Analyses showed that mean total pain intensity related to depressive symptoms (r[76] = 0.359, p = 0.001) and pain anxiety (r[76] = 0.339, p = 0.002).

Analyses of relations between pain intensity in the specific body regions and psychological symptoms show that depressive symptoms are related to neck pain (r[76] = 0.274, p = 0.015), chest pain (r[76] = 0.274, p = 0.015), abdominal pain (r[76] = 0.292, p = 0.009), and pain in the lower extremities (r[76] = 0.331, p = 0.003).

Pain anxiety related to head pain (r[76] = 0.244, p = 0.031), neck pain (r[76] = 0.252, p = 0.026), chest pain (r[76] = 0.248, p = 0.028), back pain (r[76] = 0.282, p = 0.012), and pain in the lower extremities (r[76] = 0.273, p = 0.016).

Only pain in the upper extremities did not relate to depressive symptoms (r[76] = 0.219, p = 0.054) or pain anxiety (r[76] = 0.172, p = 0.132).

4 Discussion

The findings in our cross-sectional study highlight the relationship between pain intensity in specific anatomical regions and levels of depressive symptoms and pain anxiety and in patients with hEDS. The results show that the pain was widespread across anatomical regions. Second, the mean total pain intensity scores were related significantly to both depressive symptoms and pain anxiety. Specific findings were that strongest associations of depressive symptoms and pain intensity were in the abdomen and lower extremities. In contrast, pain in the upper extremities did not relate to depressive symptoms or pain anxiety.

The relations between abdominal pain intensity and depressive symptoms resemble findings documented in studies on patients with irritable bowel syndrome [25]. Additionally, it has been demonstrated that psychological distress can contribute to the onset of abdominal pain in hEDS [26]. In this regard, our findings suggest that there is a complex interplay between abdominal pain symptoms and psychological factors in hEDS.

Pain intensity in the lower extremities is related to depressive symptoms, which resembles results reported in studies on patients with rheumatoid arthritis [27]. Pain intensity in the lower extremities impacts the ability to move and perform daily life activities, and the loss of valued activities could explain the relations to depressive symptoms [28].

In most body regions, pain intensity is related to pain anxiety. This resembles findings in a meta-analysis on chronic musculoskeletal pain conditions by Martinez-Calderon et al. [29], which revealed that greater pain intensity associated significantly with higher level of pain-related anxiety. Further, in a study by Alter et al. [30], it was shown – using an exceptionally large unclassified sample of pain patients – that the extent of pain distribution impacts various clinical outcomes. Regarding our results, it seems that these associations also apply to hEDS.

Notably, the symptom burden is high in hEDS, which may increase anxiety-proneness [31]. It has been proposed that higher levels of anxiety contribute to the experience of pain [32]. Furthermore, pain catastrophising (i.e., anxiety) and fear of pain have been shown to impact the pain experience and its convergence with mental health [33]. These bidirectional relationships between experienced pain and anxiety may explain why total pain has the strongest correlation with pain anxiety in our study.

Pain in the upper extremities did not relate to psychological factors in this sample of hEDS patients, which differs from findings of Beleckas et al. [34], according to which patients with upper extremity conditions frequently experience anxiety and depression. This clinically interesting finding warrants further study.

The results show that the pain was intensive and widespread across body sites, which may be a significant contributing factor to depressive symptoms and pain anxiety in hEDS, given that hEDS represents a multifaceted syndrome with an extensive disease burden [35]. To the best of our knowledge, this study is the first to examine pain in specific anatomical regions in relation to psychological distress in the hEDS patient population.

4.1 Limitations in the study

Self-assessment tools are susceptible to information bias, which might affect the validity of results in health research [36]. Patients with hEDS may over- or underreport their symptoms. Pain sites and pain intensity also vary and may make the reporting of pain confusing.

Although each participant was diagnosed with a chronic pain condition, inclusion of data on the pain duration could have provided additional information about the temporal changes in interrelations between various factors. Unfortunately, this information was not collected in the early stage of the study.

4.2 Strengths of the study

Given that hEDS is a relatively rare condition, the data on the 80 patients used in this study can be considered a representative sample. Even the response rate of 80% can be considered a strength. Furthermore, validated measurement methods were employed in the study, and the study findings are clinically relevant, considering the multiple pain sites and related psychological distress in hEDS.

5 Conclusion

We conclude that hEDS is a multidimensional syndrome that involves – in addition to pain occurring in multiple anatomical regions – psychological co-factors. A deeper understanding of behavioural factors and recognising the critical significance of pain intensity and pain location can equip healthcare professionals to develop suitable therapeutical interventions for patients with hEDS. Consequently, a multidisciplinary biopsychosocial treatment programme for patients with hEDS seems indicated. To the best of our knowledge, this study is the first to examine pain in specific anatomical regions in relation to psychological distress in the hEDS patient population.


# These authors contributed equally to the study.


Acknowledgments

We thank the Finnish Ehlers–Danlos Association for their help in recruiting participants. Furthermore, we warmly thank Marja Louhi, LicPs, for the great work she did in collecting the study data and creating the data file.

  1. Research ethics: The research project received ethics approval (312/13/03/2014) from the Research Ethical Committee of Helsinki University Hospital (HUS), and research permission was obtained from the Orton Research Institute. All procedures in this study were performed in accordance with the ethical standards of the HUS Research Ethical Committee and with the 1964 Declaration of Helsinki and its later amendments.

  2. Informed consent: Written informed consent was obtained from all participants in this study.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and have approved its submission.

  4. Competing interests: The authors state no conflicts of interest.

  5. Research funding: Funding for this study was obtained through Orton Evo grants from the Ministry of Social Affairs and Health, Finland (Project number: 9310/462).

  6. Data availability: The data sets generated during and/or analysed during this study are available from the corresponding author on reasonable request.

  7. AI/Machine learning tools: Not applicable.

References

[1] Beighton PH, Bird H, Beighton P, Grahame R. Assessment of hypermobility. In: Beighton PH, editor. Hypermobility of joints. 5th ed London: Springer; 2012. p. 11–26. 10.1007/978-1-84882-085-2.Search in Google Scholar

[2] Malfait F, Francomano C, Byers P, Belmont J, Berglund B, Black J, et al. The 2017 international classification of the Ehlers–Danlos syndromes. Am J Med Genet C. 2017;175(1):8–26. 10.1002/ajmg.c.31552.Search in Google Scholar PubMed

[3] Kalisch L, Hamonet C, Bourdon C, Montalescot L, de Cazotte C, Baeza-Velasco C. Predictors of pain and mobility disability in the hypermobile Ehlers-Danlos syndrome. Disabil Rehabil. 2020;42(25):3679–86. 10.1080/09638288.2019.1608595.Search in Google Scholar PubMed

[4] Bénistan K, Martinez V. Pain in hypermobile Ehlers‐Danlos syndrome: new insights using new criteria. Am J Med Genet A. 2019;179(7):1226–34. 10.1002/ajmg.a.61175.Search in Google Scholar PubMed

[5] Chopra P, Tinkle B, Hamonet C, Brock I, Gompel A, Bulbena A, et al. Pain management in the Ehlers–Danlos syndromes. Am J Med Genet C. 2017;175(1):212–9. 10.1002/ajmg.c.31554.Search in Google Scholar PubMed

[6] Syx D, De Wandele I, Rombaut L, Malfait F. Hypermobility, the Ehlers-Danlos syndromes and chronic pain. Clin Exp Rheumatol. 2017;35(5):116–22. 10.1002/ajmg.c.31552.Search in Google Scholar

[7] Vlaeyen JW, Linton SJ. Fear-avoidance and its consequences in chronic musculoskeletal pain: a state of the art. Pain. 2000;85(3):317–32. 10.1016/S0304-3959(99)00242-0.Search in Google Scholar PubMed

[8] Voermans NC, Knoop H, Bleijenberg G, van Engelen BG. Pain in Ehlers-Danlos syndrome is common, severe, and associated with functional impairment. J Pain Symptom Manage. 2010;40(3):370–8. 10.1016/j.jpainsymman.2009.12.026.Search in Google Scholar PubMed

[9] Orenius T, Kautiainen H, Louhi M, Montin L, Bulbena A, Lindgren K-A. Health-related quality of life and psychological distress in patients with hypermobility type ehlers-danlos syndrome. SAGE Open. 2022;12(2):21582440221091237. 10.1177/21582440221091237.Search in Google Scholar

[10] Kennedy M, Loomba K, Ghani H, Riley B. The psychological burden associated with Ehlers-Danlos syndromes: a systematic review. J Osteopath Med. 2022;122(8):381–92. 10.1515/jom-2021-0267.Search in Google Scholar PubMed

[11] Bulbena A, Baeza‐Velasco C, Bulbena‐Cabré A, Pailhez G, Critchley H, Chopra P, et al. Psychiatric and psychological aspects in the Ehlers–Danlos syndromes. Am J Med Genet C. 2017;175(1):237–45. 10.1002/ajmg.c.31544.Search in Google Scholar PubMed

[12] Berglund B, Pettersson C, Pigg M, Kristiansson P. Self-reported quality of life, anxiety and depression in individuals with Ehlers-Danlos syndrome (EDS): a questionnaire study. BMC Musculoskelet Disord. 2015;16:1–5. 10.1186/s12891-015-0549-7.Search in Google Scholar PubMed PubMed Central

[13] Kamaleri Y, Natvig B, Ihlebaek CM, Benth JS, Bruusgaard D. Change in the number of musculoskeletal pain sites: a 14-year prospective study. Pain. 2009;141(1–2):25–30. 10.1016/j.pain.2008.09.013.Search in Google Scholar PubMed

[14] Gerrits MM, Van Oppen P, Van Marwijk HW, Penninx BW, van der Horst HE. Pain and the onset of depressive and anxiety disorders. Pain. 2014;155(1):53–9. 10.1016/j.pain.2013.09.005.Search in Google Scholar PubMed

[15] Hjermstad MJ, Fayers PM, Haugen DF, Caraceni A, Hanks GW, Loge JH, et al. Studies comparing numerical rating scales, verbal rating scales, and visual analogue scales for assessment of pain intensity in adults: a systematic literature review. J Pain Symptom Manage. 2011;41(6):1073–93. 10.1016/j.jpainsymman.2010.08.016.Search in Google Scholar PubMed

[16] Modarresi S, Lukacs MJ, Ghodrati M, Salim S, MacDermid JC, Walton DM. A systematic review and synthesis of psychometric properties of the numeric pain rating scale and the visual analog scale for use in people with neck pain. Clin J Pain. 2022;38(2):132–48. 10.1097/AJP.0000000000000999.Search in Google Scholar PubMed

[17] Koho P, Orenius T, Kautiainen H, Haanpää M, Pohjolainen T, Hurri H. Association of fear of movement and leisure-time physical activity among patients with chronic pain. J Rehabil Med. 2011;43(9):794–9. 10.2340/16501977-0850.Search in Google Scholar PubMed

[18] Orenius T, Koskela T, Koho P, Pohjolainen T, Kautiainen H, Haanpää M, et al. Anxiety and depression are independent predictors of quality of life of patients with chronic musculoskeletal pain. J Health Psychol. 2013;18(2):167–75. 10.1177/1359105311434605.Search in Google Scholar PubMed

[19] Beck A, Steer R, Brown G. BDI-II Käsikirja [Manual of the BDI-II, Finnish Version]. Helsinki: Psykologien Kustannus; 2004. 10.1037/t00742-000.Search in Google Scholar

[20] Nuevo R, Lehtinen V, Reyna-Liberato PM, Ayuso-Mateos JL. Usefulness of the beck depression Inventory as a screening method for depression among the general population of Finland. Scand J Public Health. 2009;37(1):28–34. 10.1177/1403494808097169.Search in Google Scholar PubMed

[21] Harris CA, Joyce LD. Psychometric properties of the beck depression inventory-(BDI-II) in individuals with chronic pain. Pain. 2008;137(3):609–22. 10.1016/j.pain.2007.10.022.Search in Google Scholar PubMed

[22] Olaya-Contreras P, Persson T, Styf J. Comparison between the beck depression inventory and psychiatric evaluation of distress in patients on long-term sick leave due to chronic musculoskeletal pain. J Multidiscip Healthcare. 2010;161–7. 10.2147/JMDH.S12550.Search in Google Scholar PubMed PubMed Central

[23] Roelofs J, McCracken L, Peters ML, Crombez G, van Breukelen G, Vlaeyen JW. Psychometric evaluation of the Pain Anxiety Symptoms Scale (PASS) in chronic pain patients. J Behav Med. 2004;27:167–83. 10.1023/b:jobm.0000019850.51400.a6.Search in Google Scholar PubMed

[24] McCracken LM, Dhingra L. A short version of the Pain Anxiety Symptoms Scale (PASS-20): preliminary development and validity. Pain Res Manag. 2002;7:45–50. 10.1155/2002/517163.Search in Google Scholar PubMed

[25] Lu J, Chen Y, Shi L, Xiaoqing L, Guijun F, Li J, Yang A, et al. Cognition of abdominal pain and abdominal discomfort in Chinese patients with irritable bowel syndrome with diarrhea. Biopsychosoc Med. 2023;17:31. 10.1186/s13030-023-00286-1.Search in Google Scholar PubMed PubMed Central

[26] Silvernale C, Garcia-Fischer I, Staller K. Relationship Between psychological trauma and irritable bowel syndrome and functional dyspepsia in a joint hypermobility syndrome/ehlers–danlos syndrome patient population. Dig Dis Sci. 2024;69:870–5. 10.1007/s10620-023-08201-y.Search in Google Scholar PubMed

[27] Covic T, Adamson B, Spencer D, Howe G. A biopsychosocial model of pain and depression in rheumatoid arthritis: a 12-month longitudinal study. Rheumatology. 2003;42(11):1287–94. 10.1093/rheumatology/keg369.Search in Google Scholar PubMed

[28] Katz PP, Yelin EH. Activity loss and the onset of depressive symptoms: do some activities matter more than others? Arthritis Rheum. 2001;44(5):1194–202. 10.1002/1529-0131(200105)44:5<1194:AID-ANR203>3.0.CO;2-6.Search in Google Scholar

[29] Martinez-Calderon J, Flores-Cortes M, Morales-Asencio JM, Luque-Suarez A. Pain-related fear, pain intensity and function in individuals with chronic musculoskeletal pain: a systematic review and meta-analysis. J Pain. 2009;20(12):1394–415. 10.1016/j.jpain.2019.04.009.Search in Google Scholar

[30] Alter BJ, Anderson NP, Gillman AG, Yin Q, Jeong JH, Wasan AD. Hierarchical clustering by patient-reported pain distribution alone identifies distinct chronic pain subgroups differing by pain intensity, quality, and clinical outcomes. PLoS One. 2021;16(8):e0254862. 10.1371/journal.pone.0254862.Search in Google Scholar

[31] De Wandele I, Calders P, Peersman W, Rimbaut S, De Backer T, Malfait F, et al. Autonomic symptom burden in the hypermobility type of Ehlers–Danlos syndrome: A comparative study with two other EDS types, fibromyalgia, and healthy controls. In Semin Arthritis Rheum. 2014;44(3):353–61. 10.1016/j.semarthrit.2014.05.013.Search in Google Scholar PubMed

[32] King CD, Mano KEJ, Barnett KA, Pfeifer M, Ting TV, Kashikar-Zuck S. Pressure pain threshold and anxiety in adolescent females with and without juvenile fibromyalgia: a pilot study. Clin J Pain. 2017;33(7):620. 10.1097/AJP.0000000000000444.Search in Google Scholar PubMed PubMed Central

[33] Van Meulenbroek T, Huijnen IP, Simons LE, Conijn AE, Engelbert RH, Verbunt JA. Exploring the underlying mechanism of pain-related disability in hypermobile adolescents with chronic musculoskeletal pain. Scand J Pain. 2021;21(1):22–31. 10.1515/sjpain-2020-0023.Search in Google Scholar PubMed

[34] Beleckas CM, Wright M, Prather H, Chamberlain A, Guattery J, Calfee RP. Relative prevalence of anxiety and depression in patients with upper extremity conditions. J Hand Surg Am. 2018;43(6):571. 10.1016/j.jhsa.2017.12.006.Search in Google Scholar PubMed PubMed Central

[35] Castori M, Morlino S, Celletti C, Ghibellini G, Bruschini M, Grammatico P, et al. Re‐writing the natural history of pain and related symptoms in the joint hypermobility syndrome/Ehlers–Danlos syndrome, hypermobility type. Am J Med Genet A. 2013;161(12):2989–3004. 10.1002/ajmg.a.36315.Search in Google Scholar PubMed

[36] Althubaiti A. Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthcare. 2016;4:211–7. 10.2147/JMDH.S104807.Search in Google Scholar PubMed PubMed Central

Received: 2024-06-24
Revised: 2025-03-24
Accepted: 2025-04-06
Published Online: 2025-06-16

© 2025 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  26. Properties of pain catastrophizing scale amongst patients with carpal tunnel syndrome – Item response theory analysis
  27. Adding information on multisite and widespread pain to the STarT back screening tool when identifying low back pain patients at risk of worse prognosis
  28. The neuromodulation registry survey: A web-based survey to identify and describe characteristics of European medical patient registries for neuromodulation therapies in chronic pain treatment
  29. A biopsychosocial content analysis of Dutch rehabilitation and anaesthesiology websites for patients with non-specific neck, back, and chronic pain
  30. Topical Reviews
  31. An action plan: The Swedish healthcare pathway for adults with chronic pain
  32. Team-based rehabilitation in primary care for patients with musculoskeletal disorders: Experiences, effect, and process evaluation. A PhD synopsis
  33. Persistent severe pain following groin hernia repair: Somatosensory profiles, pain trajectories, and clinical outcomes – Synopsis of a PhD thesis
  34. Systematic Reviews
  35. Effectiveness of non-invasive vagus nerve stimulation vs heart rate variability biofeedback interventions for chronic pain conditions: A systematic review
  36. A scoping review of the effectiveness of underwater treadmill exercise in clinical trials of chronic pain
  37. Neural networks involved in painful diabetic neuropathy: A systematic review
  38. Original Experimental
  39. Knowledge, attitudes, and practices of transcutaneous electrical nerve stimulation in perioperative care: A Swedish web-based survey
  40. Impact of respiration on abdominal pain thresholds in healthy subjects – A pilot study
  41. Measuring pain intensity in categories through a novel electronic device during experimental cold-induced pain
  42. Robustness of the cold pressor test: Study across geographic locations on pain perception and tolerance
  43. Experimental partial-night sleep restriction increases pain sensitivity, but does not alter inflammatory plasma biomarkers
  44. Is it personality or genes? – A secondary analysis on a randomized controlled trial investigating responsiveness to placebo analgesia
  45. Investigation of endocannabinoids in plasma and their correlation with physical fitness and resting state functional connectivity of the periaqueductal grey in women with fibromyalgia: An exploratory secondary study
  46. Educational Case Reports
  47. Stellate ganglion block in disparate treatment-resistant mental health disorders: A case series
  48. Regaining the intention to live after relief of intractable phantom limb pain: A case study
  49. Trigeminal neuralgia caused by dolichoectatic vertebral artery: Reports of two cases
  50. Short Communications
  51. Neuroinflammation in chronic pain: Myth or reality?
  52. The use of registry data to assess clinical hunches: An example from the Swedish quality registry for pain rehabilitation
  53. Letter to the Editor
  54. Letter to the Editor For: “Stellate ganglion block in disparate treatment-resistant mental health disorders: A case series”
  55. Corrigendum
  56. Corrigendum to “Patient characteristics in relation to opioid exposure in a chronic non-cancer pain population”
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