Do “central sensitization” questionnaires reflect measures of nociceptive sensitization or psychological constructs? A systematic review and meta-analyses

1. Introduction

Central sensitization (CS) is defined by the International Association for the Study of Pain (IASP) as “increased responsiveness of nociceptive neurons in the central nervous system to either normal or subthreshold afferent input.”25,53,131Central sensitization has been linked with a multitude of chronic pain disorders in humans,62,70,79,105,110,144 with “central sensitivity syndrome (CSS)” being a recently developed diagnosis for several “medically unexplained” pain disorders (eg, fibromyalgia and temporomandibular disorder) for which CS is believed to play an etiological role.143 As of yet, there is no conclusive method of accurately establishing the presence of CS in humans,100 although quantitative sensory testing (QST) is used to assess the dynamic modulation of nociceptive signals, which can suggest the presence of CS.6,137Quantitative sensory testing measures include pain threshold tests, temporal summation (a measure of “wind-up” or enhancement of pain with prolonged nociceptive exposure31), and conditioned pain modulation (said to quantify the efficiency of endogenous inhibition of pain).27

Although QST allows for a comprehensive assessment of pain sensitivity profiles, it often involves select training, expensive laboratory equipment, and additional patient burden, which limits its use in clinical settings.104 Self-report questionnaires would make a pragmatic alternative assessment of CS in clinics, allowing for quick and convenient assessment at little cost. To serve this purpose, however, these questionnaires would need to demonstrate acceptable associations with known measures of CS to show sufficient construct validity.

A self-report questionnaire that is widely used in the assessment of central sensitization is the Central sensitization Inventory (CSI). The CSI was designed as a self-report screening measure to help identify patients who might have a CSS, such as fibromyalgia, neck injury, temporomandibular joint disorder, or migraine or tension headaches.89 It has been shown to be a reliable and valid psychometric instrument for identifying individuals vulnerable to pain.74

The Pain Sensitivity Questionnaire (PSQ), however, may more directly measure the sensory facilitation involved in CS.107 The PSQ is a valid and reliable measured designed to investigate self-reported pain sensitivity as a supplement or alternative to experimental pain testing.80,108 It focuses more on respondents imagining situations that involve nociceptive input and predicting how they would react. The questions are posed to measure sensitization to sensory input, but the degree to which it reflects a top–down component influenced by the personality type or disposition remains open. More specifically, whether it reflects these psychological profiles to the same degree as the CSI is a germane question for understanding how closely related and psychometrically distinct these measures are.

It would appear that the term “central sensitization” has undergone construct drift from its canonical (preclinical) use describing enhanced responsivity of central nociceptive neurons64,139,140 to a broader usage including psychological profiles. This construct drift may reflect a noble desire to legitimize poorly explained pain by providing a putative central mechanism, but the degree to which this broader construct reflects mechanisms outlined in animal models of central sensitization is unclear. As such, we are interested in exploring the degree to which the CSI and PSQ reflects CS as an “increased responsiveness of nociceptive neurons.” The meta-analyses of available studies examined whether self-report measures (the PSQ or CSI) aligned more closely with QST measures or experimental measures of nociceptive sensitivity or psychological questionnaires such as anxiety, depression, stress, etc. In doing so, we aim to assess and compare the 2 questionnaires for the degree to which they assess nociceptive sensitization or emotional sensitization.

2. Methods

The review protocol has been previously published1 and registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=208731) prepared in accordance with recommendations specified in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.95

2.1. Sources of evidence

We searched MEDLINE, PsycINFO, and Web of Science from their inception until June 2021. Two separate searches were conducted including both the CSI and PSQ. One search reviewed these questionnaires for sensory correlates (eg, quantitative sensory testing). The second search reviewed their correlations with psychological questionnaires (eg, anxiety, depression, pain catastrophising, etc). Any duplicates within both searches were removed.

2.2. Search terms 2.2.1. Search 1 terms

(“Quantitative Sensory Testing” or “wind-up” or “temporal summation” or “conditioned pain modulation” or “pain threshold” or “pain ratings” or “hyperalgesia” or “allodynia” or “offset analgesia” or “widespread pain” or “evoked pain” or “experimental pain” or “pain tolerance”) AND (“central sensitization inventory” or “central sensitization inventory” or “pain sensitivity questionnaire”).

2.2.2. Search 2 terms

(“depression” or “anxiety” or “stress” or “catastrophizing” or “rumination” or “neuroticism” or “personality” or “abuse” or “trauma”) AND (“central sensitization inventory” or “central sensitization inventory” or “pain sensitivity questionnaire”).

2.3. Inclusion criteria

Only human studies were eligible for inclusion. They must have been written in English and an original peer-reviewed experiment (ie, not a dissertation, case study, or review article). Finally, studies must have included at least one of the CSI or PSQ instruments. The CSI or PSQ must have been correlated against at least one psychological or sensory measure of interest.

2.4. Types of studies

The review included studies that correlate the PSQ or CSI with sensory or psychological measures. In studies that involved an intervention, measures were only considered if they were assessed at baseline.

2.5. Data collection, extraction, and management

Two independent reviewers assessed studies for eligibility (G.R.A. and W.G.). Initially, titles and abstracts were screened using excel, and full-text screening was performed on citations felt to be potentially eligible. Both authors were required to agree for inclusion. We excluded studies that did not satisfy our inclusion criteria. Discrepancies between the reviewers were resolved by discussion and consensus, with a third reviewer being consulted in cases of disagreement. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart of this process is provided (Fig. 1).

F1Figure 1.:

Flowchart to show the process of inclusion eligibility for meta-analyses. CSI, Central Sensitization Inventory; PSQ, Pain Sensitivity Questionnaire.

2.6. Outcome Measures

Our primary outcomes were correlations between the CSI total score and the PSQ total score with sensory measures associated with CS. These include QST measures: temporal summation, pain thresholds and tolerance, and any measure related to nociceptive hypersensitivity or widespread pain. We were also interested in exploring the extent to which self-report questionnaires may be predictive of descending aspects of modulation (impaired inhibition), therefore, including conditioned pain modulation as a measure of interest.

The second outcome measure was correlations between the CSI and the PSQ and psychological factors. These included questionnaires that assess depression, anxiety, stress, pain catastrophizing, abuse, trauma, mindfulness, neuroticism, or personality and any other measure related to emotional hypersensitivity.

2.7. Data extraction and management

One reviewer (G.R.A.) extracted relevant data from each study (correlation coefficient r and number of participants n). If these values were not given within the paper, authors were contacted to provide the relevant correlation coefficient. A second reviewer checked the extracted data (D.W.-A.). Data extracted from each citation included information about the study design and the correlation coefficients age, sex, and number/type of participants.

2.8. Data items 2.8.1. Psychological measures

Psychological correlates with PSQ or CSI that were provided for at least 3 studies were included in meta-analyses; these were depression, anxiety, pain catastrophising, stress, sleep, and kinesiophobia. The questionnaires used to assess depression were the Depression Anxiety Stress Scale (DASS-21),67 the 4-dimensional Symptom Questionnaire (4DSQ),125 the Hospital Anxiety and Depression Scale (HADS-D),146 the Symptom Checklist 90 Depression Subscale (SCL90-D),14 Beck Depression Inventory (BDI),114 the Depression Scale (DEPS),97 the Centre for Epidemiologic Studies Depression Scale (CES-D), the Geriatric Depression Scale (GDS-15),101 and the Hamilton Depression Rating Scale (HAM-D).71 The questionnaires used to assess anxiety were DASS21,67 4DSQ,125 HADS-A,146 the Symptom Checklist 90 anxiety subscale (SCL90-A),14 the State and Trait Anxiety Inventory (STAI),81 the Brief Symptom Inventory (BSI),34 the Beck Anxiety Inventory (BAI), and the Hamilton Anxiety Rating Scale (HAM-A).71 The questionnaire used to assess pain catastrophising was the Pain Catastrophising Scale (PCS).94 The questionnaires used to assess stress were the DASS-21,67 the Perceived Stress Scale (PSS),68 4DSQ125and the Brief Measure of Emotional Preoperative Stress (B-MEPS).138 The questionnaires used to assess sleep were the Medical Outcomes Study Sleep Scale (MOS),3 the Basic Scale of Insomnia Complaints and Quality of Sleep (BaSIQs),2 and the Insomnia Severity Index (ISI).87 The questionnaire used to assess kinesiophobia was the Tampa Scale of Kinesiophobia (TSK).126

Other questionnaires that reported correlations with CSI or PSQ in fewer than 3 studies were included for narrative review but not for meta-analyses; these were the Brief Resilience Scale (BRS),120 the Patient Health Questionnaire (PHQ-15),59 the Adolescent or Adult Sensory Profile (AASP),15 the Sensory Responsiveness Questionnaire (SRQ),10 the Difficulties in Emotion Regulation Scale (DERS),13 the Positive and Negative Affect Schedule (PANAS),24 the Pain Anxiety Sensitivity Scale (PASS),75 the Childhood Trauma Questionnaire (CTQ),11 and the Child Abuse and Trauma questionnaire (CATS).111

2.8.2. Nociceptive sensory measures

Sensory correlates suitable for meta-analyses included pressure pain threshold (PPT), heat pain threshold (HPT), conditioned pain modulation (CPM), temporal summation (TS), and widespread pain. Methods that were not performed regularly enough for meta-analyses (ie, fewer than 3 studies reported correlations for these measures) included suprathreshold (pain rating associated with the fifth heat pulse out of a series of 5 heat pulses [46°C]),23 offset analgesia,119 pain tolerance33,55,60,99,128,129,138 (electrical and pressure or thermal), area or number of pain sites,70,86 cold pain threshold,38 electrical pain threshold,103 and tonic heat.107 Correlations for the CSI or PSQ with these measures can be found in Supplementary Tables 1a-d (available at https://links.lww.com/PAIN/B753).

The methodologies for the nociceptive measures included in the meta-analyses were considered standardised and generally consistent, although they did show slight variations in some cases, as outlined below:

2.8.3. Pressure pain threshold

In most cases for PPT, a digital or handheld mechanic pressure algometer was used to apply pressure through a 1 cm2 probe. The main variation in PPT was in the rate of pressure applied being between 0.1 kg/second and 1 kg/second. The body site for which the PPT was applied varied across studies, although it was consistently applied to muscles. Participants were asked to report the moment that the increasing pressure became painful or unpleasant.

2.8.4. Heat pain threshold

For heat pain threshold, a thermode was applied to various body sites depending on the study, consistently applied to muscles. In all studies, the thermode started at a baseline temperature (commonly 32°C) and was increased at a varied rate between 0.5°C/second and 2°C/second across studies. Participants were asked to report the moment that the increasing heat became painful or unpleasant.

2.8.5. Conditioned pain modulation

For CPM, the conditioning stimulus was most regularly a cold-water bath applied to the opposite hand of the test stimulus. One study used a thermode to elicit cold pain,37 and another used a hot water bath.103 Most commonly, the test stimulus was a predetermined pressure applied to a body part on the opposite side of the conditioning stimulus using a pressure algometer. One study used a combination of pressure and heat pain,60 and another used electrical stimuli applied to the right sural nerve.103 One study used PPT as the test stimulus and ischemic compression using a sphygmomanometer was used as the conditioning stimulus.98 The average pain ratings for the test stimulus given during the conditioning stimulus condition (both test and conditioning stimulus simultaneously administered) were subtracted from the average pain ratings of the test-stimulus only condition to give a CPM score.

2.8.6. Temporal Summation

Temporal summation was often calculated by applying a predetermined pressure intensity using a pressure algometer to a body site (body sites varied across studies) for several repetitions (commonly 10 consecutive stimulations) at a rate of 1/second. The first pain rating in the series was subtracted from the final pain rating to give a TS score. One study used this same paradigm, as well as a similar paradigm using electrical stimulation.60 Another study applied a 60 g von Frey filament to the forearm and knee for 4 stimulations; the stimulus was then applied for 30 stimulations at a rate of 1/second. The initial pain rating was subtracted from the second to give a TS score.37

2.8.7. Widespread Pain

Widespread pain measures consisted of the Widespread Pain Index (WPI)32 and the Michigan Body Map (MBM),16 which are both questionnaires used to assess the number of painful body sites and area of pain across the body.

2.8.8. Phasic heat

Phasic heat stimulation was administered at 47°C or 48°C for 5 seconds. The average of 4 ratings collected at the set temperature of 47/48°C was used as a phasic pain rating. If the phasic heat rating was performed at 2 temperatures, the average of these 2 scores was taken as the phasic heat score.

2.8.9. Tonic cold

A thermode surface oscillated around 3°C (0.5 Hz, amplitude: ±1°C) for 60 seconds. The average of the ratings over the 4-time points and 4 measurements (twice on each hand) was used as the tonic cold pain rating.

2.8.10. Pinprick stimulation

Pain-intensity ratings of pinprick stimuli were obtained from the volar forearm using a weighted pinprick stimulator (force: 512 mN).

2.8.11. Assessment of risk of bias in included studies

For each study included in the review, a modified version of the quality appraisal process proposed by Hayden et al.40 was conducted by 2 independent authors (G.R.A. and W.G./R.H.) to evaluate potential sources of bias across 5 domains: participation bias, publication bias, attrition, methodological quality, and statistical analysis. We assessed the following for each study: (1) Were potential sources of participation bias considered and addressed? (2) Was there any missing data regarding the variables of interest? (3) Was the methodology of the variable of interest of a standardized quality? (4) Was the desirable statistical analyses performed? (5) Was the sample size adequate? Each category was assigned a low, unclear, or high risk of bias and presented with a “risk of bias” summary. Disagreements between reviewers were resolved by discussion and consensus. A third reviewer (W.G./R.H.) was consulted where assessments could not be agreed on.

2.8.12. Analysis of participation bias

Specific sources of participation bias (bias assessment category (1)) were identified, i.e., age and sex characteristics of the population sample, as well as population samples that excluded participants based on mental health, physical health, or medication being taken.

2.9. Synthesis of results 2.9.1. Data eligibility

Sample sizes (n) and correlation scores (r) on primary outcomes were extracted from papers or by responses collected from emailing corresponding authors and presented to show individual study characteristics. Only data that provided sample size and a correlation value were included. Only Spearman rank and Pearson correlation (r-values) were considered eligible so that meta-analyses could be conducted.

2.9.2. Data preparation

Central Sensitization Inventory correlations were extracted for each construct separately: depression, anxiety, stress, pain catastrophising, kinesiophobia, and sleep. Meta-analyses were conducted if at least 3 studies reported findings for a related construct. Each meta-analysis was made up of a combination of instruments for that construct, eg, correlates with CSI and anxiety will include CSI against STAI Trait and State, the Anxiety component of the Depression Anxiety stress scale (DASS-21), the anxiety component of the Hospital Anxiety and Depression Scale (HADS), etc.

Meta-analyses for quantitative sensory measures were conducted for each measure separately: Pressure pain threshold, heat pain threshold, conditioned pain modulation, and temporal summation were separately meta-analysed against CSI. If studies reported 2 correlations for one construct (eg, multiple body sites taken for pain threshold or trait, and state anxiety scores were reported for anxiety), scores were averaged together.

2.9.3. Data visualization

Data for individual studies were reported in Supplementary Tables 1a-d (available at https://links.lww.com/PAIN/B753) to show individual study characteristics. This table was presented in 4 sections: CSI with psychological constructs (Supplementary Table 1a, available at https://links.lww.com/PAIN/B753), CSI with nociceptive measures (Supplementary Table 1b, available at https://links.lww.com/PAIN/B753), PSQ with psychological constructs (Supplementary Table 1c, available at https://links.lww.com/PAIN/B753), and PSQ with nociceptive measures (Supplementary Table 1d, available at https://links.lww.com/PAIN/B753). Meta-analyses findings were presented in the table format with a summary of the effect size on the right of the table. For visualisation purposes, forest plots were provided for some of the main findings (forest plots for all other meta-analyses can also be found in Supplementary Figures 1a-n, available at https://links.lww.com/PAIN/B753). Any other findings with insufficient data for a meta-analysis were reviewed narratively where appropriate.

2.9.4. Primary analysis

Meta-analyses consisted of sample sizes (n) and correlation scores (r) on primary outcomes extracted from papers or by response from emailing corresponding authors and will be presented in a table. These values were then input into a meta-analysis to give a weighted mean correlation using the Hunter–Schmidt method.113 Statistical software StatsDirect version 3.3.5 was used to calculate weighted mean correlations, to test for heterogeneity and to perform subgroup analysis.122 Weighted mean correlations were calculated to measure the overall strength of a correlation between the PSQ or CSI and each construct. A subgroup analysis was performed where applicable to assess and compare the relative strength of our correlations of interest for patients with chronic pain vs healthy controls.

2.9.5. Tests for heterogeneity

The χ2 test was used to measure statistical heterogeneity across studies. Significant heterogeneity (P < 0.05) is an indicator of clinical and methodological heterogeneity. The I2 statistic was calculated to report heterogeneity as a percentage.29,43 A value of 0% implies no observed heterogeneity, 1% to 40% indicates low heterogeneity, 30% to 60% suggests moderate heterogeneity, 50% to 90% signifies substantial heterogeneity, and 75% to 100% is considered heterogeneous.43 Moderator analyses were conducted when heterogeneity scores were above 50% to examine whether certain factors contributed towards heterogenous findings (eg, age or sex).43

3. Results

After excluding duplicates, the initial literature search identified 175 articles (Fig. 1). Forty-nine of these articles were eligible after full screening. A further 74 corresponding authors were emailed for specific correlations (either the PSQ or CSI with our variables of interest) as data were collected but not reported within their publication. Twenty authors responded and provided the correlates of interest. Therefore, a total of 69 studies were eligible for quality appraisal or bias assessment (see Fig. 1 for further details).

3.1. Risk of bias

All 69 studies included in the review went through an assessment of quality and risk of bias. The results are presented in Figure 2. An additional breakdown of participation bias is presented in Figure 3.

(1) Participation bias—Many studies showed participation bias. This reflects some common exclusion criteria that occur in studies that measure pain sensitivity, eg, patients with neuropathic pain are often excluded as well as individuals with any mental health disorders or people taking any medication as this may affect their responsivity to stimuli. We ran a separate assessment to showcase the common characteristics which were excluded from study populations. The “other” column was primarily made up of participants being excluded due to cognitive deficits (Fig. 3). (2) Missing data—A few studies reported missing data. This was in part due to incomplete questionnaires or participation dropout. Data not being reported for all the participants (eg, reporting for pain patients but not healthy controls) were reflected in their bias assessment. (3) Standardized method—Most studies conducted a standardized method. The questionnaires were standardized for CSI, PSQ, and psychological correlates, and if sensory measures were taken, the method was of standardised quality. We could check this by assessing whether studies used protocols from previously published work or how homogenous protocols were across studies. Two studies were excluded due to a lack of methodological standardization.76,133 (4) Desirable statistics—Most studies provided Pearson correlations for our variables of interest, but a few provided Spearman rank correlations. If the study had undergone the relevant methodology but did not provide Pearson or Spearman correlations, we contacted the authors to provide data for one of these correlations. Synthesised results could then be analysed comparatively and included in meta-analyses. One study gave partial correlations and was, therefore, excluded.80 (5) Sample size—63 of 69 studies had an adequate sample size—a power calculation based on r = 0.3 indicated that the sample size should have been 43 or over. Anything lower than n = 43 was flagged. However, all studies were included for weighted meta-analyses. Low sample sizes simply reflected less influence in a weighted meta-analysis. However, these small sample sizes may be relevant when reviewing less frequent correlations that were not suitable for meta-analysis, ie, narrative review. F2Figure 2.:

Bias assessment (quality assessment).

F3Figure 3.:

Bias assessment (participation bias).

Overall, the quality assessment for studies selected for this study showed that the studies were of good quality with a low risk of bias. Three studies were excluded due to a nonstandardised method being used or data not being given in the required format for correlational meta-analyses.76,80,133

There were some concerns over participation bias (Fig. 3) due to certain types of patients with chronic pain being excluded in several studies (n = 46) based on their medical condition, eg, neuropathy. Patients on pain medication were excluded in several studies (n = 19), patients with mental health or psychiatric disorders were excluded in studies (n = 24), and individuals with cognitive deficits were excluded in a number of studies (n = 12). These exclusion criteria may appear biased, but it is typical across studies that examine pain populations as medical conditions, medication, cognitive deficits, and mental health can all interfere with the pain processing or interpretation of pain.51,65,130 Similarly, owing to the typical nature of chronic pain populations, some study populations were predominantly female, and the mean age was high (over 60).

Only one study was identified as high risk in any of the assessed domains on participation bias. The reasons for this were that in one study of a Chinese population, women taking contraception were excluded.99 However, this study was still included for further analysis as the potentially affected representation of females was balanced against having an international sample.

3.2. Excluded studies

Two studies were excluded due to a lack of methodological standardization,76,133 and one study gave partial correlations and was, therefore, excluded.80

3.3. Summary

All studies included in this review were assessed for methodology and were considered standardized by at least 2 reviewers. Although it should be noted, in general, there was a certain level of heterogeneity in methodology across studies involving nociceptive sensory measures, particularly with CPM.

3.4. Primary outcomes

The surviving 66 studies included a total of 13,284 participants. 7470 participants took the Central sensitization Inventory across 37 different studies and 5531 took the Pain Sensitivity Questionnaire across 30 different studies (one study included both questionnaires).23 Thirty-one studies containing a total of 6885 participants provided correlations for the CSI with at least one psychological primary outcome. Sixteen studies consisting of 1857 participants provided correlations for the CSI with at least one sensory primary outcome. Twenty-five studies consisting of a total of 4482 participants provided correlations for the PSQ with at least one psychological primary outcome. Sixteen studies consisting of a total of 3375 participants provided correlations for the PSQ with at least one primary sensory measure. All extracted correlations can be seen in Supplementary Tables 1a-d (available at https://links.lww.com/PAIN/B753).

Supplementary Tables 1a-d (available at https://links.lww.com/PAIN/B753) show the extracted data for each of these studies (Supplementary Table 1a, available at https://links.lww.com/PAIN/B753 shows all extracted correlations for CSI with psychological primary outcomes, Supplementary Table 1b, available at https://links.lww.com/PAIN/B753 for CSI with sensory primary outcomes, Supplementary Table 1c, available at https://links.lww.com/PAIN/B753 for PSQ with psychological primary outcomes, and Supplementary Table 1d, available at https://links.lww.com/PAIN/B753 for PSQ with sensory primary outcomes). All tables provide data for age, sex, and subject population for each study if it was provided. Note that if multiple correlations of the same or very similar constructs were provided for a study, which only occurs when trait anxiety and state anxiety are reported within the STAI, the values were averaged together as these 2 measures have high intercorrelation.102 Similarly, if measures for multiple body sites were recorded for PPT, HPT, CPM etc., the multiple correlations per study were averaged together to give a mean correlation score for that construct, given that intraclass correlations for pain measures across different body sites have been found to be high (Cronbach alpha values >0.80).63,72 This meant that one correlation score for each construct was provided for each population which could be used for meta-analysis.

3.5. Meta analyses

The results of the meta-analyses are reported in Table 1. Studies reporting data for subset samples instead of a total (eg, patients and healthy controls) were entered into the meta-analyses as separate correlations as they reflected separate populations. In a separate subanalysis, they were divided appropriately to compare findings for pain patients with healthy participants (Table 2). Data for some of the main findings are presented as forest plots in Figures 4A–H. Forest plots for all other meta-analyses can be found in Supplementary Figures 1a-n (available at https://links.lww.com/PAIN/B753).

Table 1 - Meta-analyses for Central Sensitization Inventory and Pain Sensitivity Questionnaire with psychological and sensory measures. Outcome measures Studies No. of populations Total number of participants Weighted mean correlation (95% CI) Heterogeneity Strength of correlation All participants—CSI  Depression 4,19,23,41,48,50,73,83–85,90–92,117,118 15 4248 0.58 (0.54 to 0.62) χ2 = 52.66, df = 14 (P < 0.001); I2 = 61.3% Strong  Anxiety 4,19–21,23,41,50,73,83,84,90–92,96,117,118 16 3295 0.60 (0.56 to 0.63) χ2 = 58.35, df = 15 (P < 0.001); I2 = 72% Strong  Pain catastrophizing 4,12,18,28,37,48,54,56,58,84,92,96,116–118,134,136 17 3812 0.48 (0.43 to 0.54) χ2 = 82.56, df = 16 (P < 0.001); I2 = 82.6% Moderate–strong  Stress 4,23,41,132,138 5 1889 0.62 (0.56 to 0.69) χ2 = 27.79, df = 4 (P < 0.001); I2 = 80.2% Strong  Sleep 4,54,90,91 4 2649 0.40 (0.29 to 0.51) χ2 = 44.57, df = 3 (P < 0.001); I2 = 92.8% Moderate  Kinesiophobia 4,85,118,132,134 5 1865 0.46 (0.40 to 0.53) χ2 = 16.08, df = 4 (P = 0.003); I2 = 80% Moderate–strong  Pressure pain threshold 23,28,35,37,41,58,82,86,96,98,138 14 1272 −0.22 (−0.28 to −0.17) χ2 = 17.37, df = 13 (P = 0.183); I2 = 24.2% Weak  Heat pain threshold 23,96 3 132 −0.01 (−0.12 to 0.09) χ2 = 1.16, df = 2 (P = 0.558); I2 = 0% No effect  Conditioned pain modulation 37,58,86,98,138 6 679 0.10 (0.01 to 0.19) χ2 = 9.09, df = 5 (P = 0.106); I2 = 45.5% Weak  Temporal summation 37,41,82,86,96 7 600 0.09 (0.01 to 0.16) χ2 = 6.07, df = 6 (P = 0.415); I2 = 0% None–weak (negligible)  Widespread pain 37,82,96,136 6 455 0.39 (0.23 to 0.50) χ2 = 10.53, df = 5 (P = 0.061); I2 = 54.9% Moderate

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