Validation of the QuickDASH (Disability of the Arm, Shoulder, and Hand) in Patients with Neck Pain

doi:10.21203/rs.3.rs-5332009/v1

Purpose

Many patients with neck pain have upper limb disorders, and prolonged use of computers at work commonly induces neck/shoulder pain. The purpose of this study was to investigate the psychometric properties of the QuickDASH in patients with neck pain.

Methods

A total of 189 patients with neck pain were included in reliability and validity studies. The reliability studies of the QuickDASH included internal consistency and test–retest reliability. The validity studies for the QuickDASH included the convergent and divergent validities, and EFA and CFA were used to examine the structural validity.

Results

The QuickDASH indicated that most participants (83.6%) had upper limb disorders, and it had a slight floor effect (16.4%). For reliability, the internal consistency (Cα = 0.945) and test–retest reliability (ICC = 0.98; SEM = 3.17, and MDC = 8.79) were excellent. For validity, the convergent and divergent validities were satisfactory. The QuickDASH had moderate to high correlations to the Neck Disability Index, VAS of the arm, and the Physical Component Summary of the SF-36 (rho = 0.80, 0.56 and − 0.62, respectively) and was not associated with age or disease duration. EFA revealed that two factors of the QuickDASH (Function-factor and Symptom-factor) explained 80.9% of the variance, and CFA confirmed the two-factor model.

Conclusion

The QuickDASH is a reliable and valid instrument for assessing upper limb disorders in patients with neck pain.

Neck pain

QuickDASH

reliability

validity

EFA

CFA

Neck pain prevalence and disability have increased significantly worldwide, with more than a third of a billion people having neck pain of over 3 months in duration [1]. Patients with neck pain commonly reports upper limb symptoms. About 80% of patients report that upper limb activities aggravate their neck pain, and higher neck pain severity is associated with greater upper limb functional restriction [2, 3]. Prolonged, extensive use of computers in offices can induce musculoskeletal pain, the majority of which (58–62%) is neck/shoulder pain [4, 5]. A systematic review with meta-analysis studied sedentary behavior and found that sitting in the workplace was associated with more neck/shoulder pain (OR = 1.73), as was computer usage time [6]. During the COVID-19 pandemic, millions of people worked from home, and a study of 4,112 homeworkers reported that only 28.1% were free of neck/shoulder pain; most participants reported such pain, which in many cases even interfered with their work [7].

The Neck Disability Index (NDI), developed by Vernon and Mior in 1991, is the most commonly used questionnaire for patients with neck pain [8, 9]. The NDI has 10 items asking about neck pain symptoms and function in daily activities. However, the items do not address upper limb pain and disability. In 2022, Wiitavaara and Florin conducted a systematic review of the content and psychometric properties of questionnaires assessing physical function in people with arm–shoulder–hand disorders [10]. They identified a total of nine questionnaires from 23 studies. The most often used questionnaires with adequate psychometric results were found to be the Disability of the Arm, Shoulder, and Hand (DASH) Outcome Measure, the QuickDASH, and the Shoulder Pain and Disability Index. However, for patients with neck/upper limb disorders, only one research report used the QuickDASH to examine workers with neck/upper limb disorders [11].

The DASH was developed by the Institute for Work and Health and the American Academy of Orthopaedic Surgeons (AAOS) [12]. It includes 30 items assessing physical and psychosocial components. The QuickDASH was developed from the DASH by Beaton et al. through three item-reduction approach methods: concept retention, equidiscriminative item–total correlation, and Rasch analysis [13]. The QuickDASH is a more efficient version, having only 11 items, and it is a reliable and valid measure of physical function and symptoms in the upper limbs. Although studies of the measurement properties of the QuickDASH suggest that the tool is performing well, with strong positive evidence for reliability and moderate to strong validities in structural and hypothesis testing, respectively [14], those studies did not examine patients with neck pain. Assessment of psychometric properties is needed for a good instrument, but to date, research validating the QuickDASH for use in patients with neck pain has been insufficient. Therefore, the purpose of this study was to investigate the psychometric properties of the QuickDASH in patients with neck pain.

Participants

The study population consisted of patients with neck pain with or without arm pain. They were recruited from outpatients and inpatients of the orthopedic and neurosurgery departments and the pain clinic of Kaohsiung Medical University Hospital in Taiwan. Patients were identified by physicians on the basis of symptoms, physical signs, and imaging study results. The diagnoses included degenerative joint disease, herniated intervertebral disc, strain and sprain, and non-specific neck pain. Participants were excluded if the neck pain had been attributed to shoulder disease, inflammatory rheumatic disease, or pain caused by cancer. The study was approved by the hospital’s institutional review board (KMUH-IRB-980589 and KMUH-IRB-E(I)-20210363), and written informed consent was obtained from all the participants.

Procedure

Each participant was asked to complete a questionnaire booklet, which contained the Taiwan version of the QuickDASH, the Taiwanese version of the NDI, the Medical Outcomes Survey Short Form 36 (SF-36), and two types of Visual Analogue Scale (VAS), namely, the VAS-N (assessing neck and shoulder pain) and the VAS-A (assessing arm and hand pain) for determination of the convergent validity. The total sample size of the study was 189. To measure the test–retest reliability, 16 patients from this sample with chronic neck pain of at least 3 months and without recent changes in pain or function were invited to participate in the study. The retest was conducted at intervals of 7–14 days.

Instruments

QuickDASH

The QuickDASH, which contains 11 items, was developed from the DASH through three item-reduction approaches by Beaton et al. and the Upper Extremity Collaborative Group [13]. The 11 items ask about the following: opening a jar (Q1); doing household chores (Q2); carrying a shopping bag (Q3); washing one’s back (Q4); using a knife (Q5); recreational activities with force or impacts (Q6); interference with social activities (Q7); limitations in work or daily activities (Q8); shoulder, arm, or hand pain (Q9); tingling (Q10); and difficulty sleeping (Q11). The two optional modules (work and sports/performing arts) were not used in this study. Each item is scored on a 5-point scale, with 1 representing no limitation and 5 representing maximal limitation. At least 10 of the 11 items must be completed for a score to be calculated. The scores are transformed to a scale of 0 (no disability) to 100 (severe disability).

Neck Disability Index

The NDI contains 10 items developed by Vernon and Mior. The questions were designed to understand how neck pain affects the ability to manage activities in everyday life [8]. The 10 items ask about pain intensity, the level of disability in personal care, lifting, work, headache, concentration, sleeping, driving, reading, and recreation. Each item is scored on a 6-point scale, with 0 representing no limitation and 5 representing maximal limitation. The scores of the 10 items are summed to obtain the NDI score (0–50 points). The Taiwanese version of the NDI is a well-developed and validated questionnaire [15].

Medical Outcomes Survey Short Form 36

The SF-36 measures eight subscales of health-related quality of life: physical functioning (PF), role limitations due to physical health problems (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role limitation due to emotional problems (RE), and mental health (MH) [16]. The subscale scores are transformed to a scale of 0 to 100, and higher scores indicate better quality of life. Two summary measures, the physical component summary (PCS) and the mental component summary (MCS), are calculated from the eight health subscales, and higher scores (0–100) indicate better physical and mental function, respectively. The Taiwanese version of the SF-36 has demonstrated good reliability and validity [17].

Data management and statistical analyses

The α level was set at 0.05. All statistical analyses were performed in IBM SPSS Statistics version 21; CFA was performed in IBM SPSS AMOS version 21 (IBM Corp., Armonk, NY).

Acceptability

To assess the acceptability of the QuickDASH, the missing data, observed score versus possible score range, and floor and ceiling effects were analyzed. Missing data of less than 5% is considered to be acceptable. Floor and ceiling effects greater than 15% are considered to be significant. The acceptable skewness range is from − 1 to 1 [18, 19].

Reliability

Internal consistency

The internal consistency of the 11 items was assessed by Cronbach’s α. The corrected item–total correlations and the Cronbach’s α with each item deleted were assessed. A Cronbach’s α ≥ 0.7 is acceptable [18, 19]. For item–total correlation, the correlations should be moderate to high. For Cronbach’s α with an item deleted, an increase of more than 0.1 indicates that the item is not correlated very well with the scale [20].

Test–retest reliability

Both relative and absolute reliability were used to assess the test–retest reliability. Intraclass correlation coefficients (ICCs) were used to estimate the relative reliability. An ICC value ≥ 0.75 indicates excellent reliability [21]. The standard error of measurement (SEM) and minimal detectable change (MDC) were used to estimate the absolute reliability [22]. Measurement error was evaluated by SEM, which was calculated by using the formula (standard deviation of all test scores) X√ (1-ICC).

The MDC is used as the threshold to indicate whether the change score of an individual subject is real and not within the measurement error for an individual at the 0.95 confidence level. The formula for MDC is 1.96 X SEM X√2. A good outcome measure should have low SEM and MDC values that are sensitive to change resulting from clinical intervention.

Construct validity

Convergent and divergent validity

The convergent validity of the QuickDASH was assessed with the correlations between the QuickDASH and the NDI, the VASs (VAS-N and VAS-A), and the SF-36 (PCS/MCS and 8 subscales). Spearman rank correlation was used to examine the correlations. We hypothesized that the QuickDASH and the NDI would have strong correlation, and that the correlation of the QuickDASH would be higher with the VAS-A than with the VAS-N. We also hypothesized that the QuickDASH would have a higher correlation with the PCS than with the MCS, and that its correlation would be higher with the PF, RP, BP, and GH than with the VT, SF, RE and MH subscales. The divergent validity of the QuickDASH was assessed with the correlations between the QuickDASH and age and disease duration. We hypothesized that the QuickDASH would have low or no correlation with age and disease duration.

Exploratory factor analysis (EFA)

EFA was used to investigate the dimensionality of the scale to identify the underlying factor structure of the items. Half the patients (n = 94) were randomly selected from the whole sample of patients for EFA. The Kaiser–Meyer–Olkin measure of sampling adequacy and Bartlett’s test of sphericity were used to assess the data fit for factor analysis. High values of the Kaiser–Meyer–Olkin (greater than 0.5) and small values of Bartlett’s test of sphericity (significance level less than 0.05) generally indicate that a factor analysis is useful with the data [23]. We hypothesized that the items could be extracted into one, two or more factors. All eleven items of the QuickDASH were used for the EFA. The principal axis factoring method was used for factor analysis extraction, and the direct oblimin method of oblique rotation was used for factor analysis rotation.

Confirmatory factor analysis (CFA)

CFA is used to test the fit of an a priori hypothesized structure of a scale [24]. The patients (n = 95) included in the CFA were those not used for the EFA. We tested the hypothesized model after the results of the EFA for the QuickDASH were obtained. In the parameter estimates, a factor loading of each section of higher than 0.5 was used to confirm satisfactory fit. Several fit indices were used to assess the goodness of fit of the models. [24–26] The indices included the χ2 divided degree of freedom (χ2/df), Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), and Normed Fit Index (NFI).

Participant Characteristics

The demographic data of the participants are listed in Table 1. Regarding the gender distribution, women outnumbered men; the male–female ratio was about 1:1.55 for all 189 participants. The most common occupation of the patients was office worker (about 44%). The mean QuickDASH scores were 24.9 ± 22.7 (range 0–90.9) for all patients, indicating that most participants had mild to moderate disability. The mean ages of the participants in the test–retest and validity studies were similar (52.6 vs. 57.9 years). The mean disease durations of the participants in the test–retest and validity studies were similar (46.4 vs. 42.7 months).

Table 1 Demographic characteristics of the participants

Characteristic group	Test–Retest (n = 16)	Validity (n = 189)

Age*	52.6 ± 18.3 (21–75)	57.9 ± 11.1 (21–83)
Gender (male/female)	6/10	74/115
Disease duration (months)*	46.4 ± 69.5 (5–270)	42.7 ± 78.0 (0.1–660)
Stage
Acute (< 6 weeks)	0%	8.7%
Sub-acute (6 weeks to 3 months)	0%	7.7%
Chronic (≥ 3 months)	100%	83.6%

Education (%) Elementary school High school University	31.3% 25.0% 43.7%	24.3% 50.8% 24.9%
Marital status (%) Single/widowed Married	31.3% 68.7%	23.8 % 76.2 %
Occupation (%) Office worker Laborer Homemaker Unemployed Retired	50.0% 6.3% 12.5% 12.5% 18.7%	43.9% 6.9 % 22.2 % 8.5 % 18.5%

Acceptability

The acceptability of the QuickDASH was assessed in the total sample participating in the study. Most participants (83.6%) were found to have upper limb symptoms, and the QuickDASH had a slight floor effect (16.4%) in patients with neck pain. The score range of the patients was 0–90.9; therefore, no ceiling effect (0%) was found. The QuickDASH was easy to administer and only took a short time to finish. No missing data were found (the participants answered at least 10/11 questions). Most participants answered all the questions, and only 6 (3.2%) provided no answer for one question (limitations in work or daily activities in three persons, difficulty sleeping in two persons, and recreational activities with force or impacts in one person). Regarding the score distribution, the QuickDASH scores did not have adequate normal distribution, with a high skewness value (1.2 ± 0.2).

Reliability

Internal consistency

Table 2 lists the results on internal consistency for the Cronbach’s α, item–total score correlation, and Cronbach’s α if the item was deleted from the scale. The Cronbach’s α was 0.945, indicating excellent internal consistency. The item–total score correlations were high, ranging from 0.67 (difficulty sleeping) to 0.84 (limitations in work/daily activities). The Cronbach’s α with an item deleted did not increase for each question, indicating that all questions were relevant to the neck pain population.

Table 2

Item–total score correlations of each item of the QuickDASH
Item	Item–total score correlation (r)	Cronbach’s α if item deleted
Q1. Opening a jar	0.73	0.940
Q2. Doing household chores	0.83	0.936
Q3. Carrying a shopping bag	0.78	0.939
Q4. Washing one’s back	0.73	0.940
Q5. Using a knife	0.78	0.940
Q6. Recreational activities with force/ impacts	0.77	0.939
Q7. Interference with social activities	0.81	0.937
Q8. Limitations in work or daily activities	0.84	0.936
Q9. Shoulder, arm, or hand pain	0.74	0.940
Q10. Tingling	0.71	0.942
Q11. Difficulty sleeping	0.67	0.943
Cronbach’s α = 0.945

Test–retest reliability

Table 3 presents the test–retest reliability results, including both the relative reliability (ICC) and absolute reliability (SEM and MDC). The ICC value was 0.98, indicating excellent test–retest reliability. The SEM was 3.17, indicating only 3.17% of the total range of scores (0–100% disability). The MDC value was 8.79.

Table 3

Relative and absolute test–retest reliabilities
Instrument	First test	Retest	Bland and Altman analysis		Relative reliability	Absolute reliability
Instrument	Mean (SD)		(SD)	LOA	ICC (95%CI)	SEM	MDC
QuickDASH (0–100)	18.1 (21.5)	19.9 (21.3)	1.4 (4.5)	-7.42–10.22	0.98 (0.94–0.99)	3.17	8.79
SD, standard deviation; : mean difference of the test and retest scores; LOA, limit of agreement = d ± 1.96 SD; SEM, standard error of measurement = √(total variance)(1-ICC); MDC, minimal detectable change = 1.96 x √2 x SEM

Convergent and divergent validity

Table 4 lists the correlation coefficients of the scores of the QuickDASH and the variables used to examine the convergent and divergent validity. For convergent validity, the QuickDASH scores were highly correlated with the NDI scores (|rho| = 0.80) and the BP and SF subscale scores (|rho| = 0.68 and 0.67, respectively). The QuickDASH scores were more highly correlated with the VAS-A scores (|rho| = 0.56) than with the VAS-N scores (|rho| = 0.49). The QuickDASH scores were more highly correlated with the PCS, PF, and RP scores (|rho| = 0.62, 0.54, 0.50, respectively) than with the MCS, RE, GH, VT, and MH scores (|rho| = 0.47, 0.49, 0.41, 0.49, 0.37, respectively). Briefly, the results showed moderate to high correlation, indicating satisfactory convergent validity. For divergent validity, the QuickDASH scores were not correlated with age or disease duration (|rho| = 0.06 and 0.096, p > 0.05), indicating satisfactory divergent validity.

Table 4

Spearman’s rho correlation coefficients of the QuickDASH
QuickDASH	NDI	VAS-N	VAS-A
	0.80	0.49	0.56
	PCS	MCS	PF	RP	BP
	-0.62	-0.47	-0.54	-0.50	-0.68
	GH	VT	SF	RE	MH
	-0.41	-0.49	-0.67	-0.49	-0.37
	Age	Disease duration
	0.06	0.096
NDI, Neck Disability Index; VAS-N, Visual Analogue Scale for neck and shoulder; VAS-A, VAS for arm and hand pain; PCS, physical component summary; MCS, mental component summary; PF, physical functioning; RP, role limitations due to physical health problems; BP, bodily pain; GH, general health; VT, vitality; SF, social functioning; RE, role limitation due to emotional problems; MH, mental health

Exploratory factor analysis

EFA was used to explore the possible factor structures of the 11 items. The value of the Kaiser–Meyer–Olkin Measure of Sampling Adequacy was 0.925, and the Bartlett's test of sphericity result was significant (p < 0.001), indicating that factor analysis was useful with those data. Two factors had eigenvalues over 1, and two steep slopes of the scree plot confirmed the existence of 2 factors. The factor loadings from the pattern matrix with direct oblimin rotation also demonstrated the two-factor model for the 11 items of the QuickDASH. The two factors were correlated, with correlation of 0.689. Factor 1 had 8 items (Q1 to Q8) representing disability of the upper limb, named the Function-factor, and factor 2 had 3 items (Q9 to Q11) representing symptom information, named the Symptom-factor. The two-factor structure explained 80.9% of the variance. The factor loadings of the 8 items (Q1 to Q8) in factor 1 ranged from 0.43 to 1.00, and the factor loadings of the 3 items in factor 2 (Q9 to Q11) ranged from 0.90 to 0.91.

Confirmatory factor analysis (CFA)

The CFA results demonstrated that the factor loadings of the sections for the Function-factor and Symptom-factor were all satisfactory (0.83 to 0.93 for the Function-factor and 0.80–0.97 for the Symptom-factor). Several model fit indices were used for model comparison. The two-factor model had low values of χ2/df (2.985) and RMSEA (0.145) and high values of CFI, TLI, and NFI (0.873, 0.805 and 0.826, respectively).

The study examined various psychometric properties of the QuickDASH in patients with neck pain. The results showed the QuickDASH to have satisfactory acceptability, reliability and validity in patients with neck pain.

Acceptability

For patients with neck pain, the questions of the QuickDASH were easy to answer without missing values. The disadvantage of the QuickDASH was its slight floor effect (16.4%). A possible reason may be that the study included participants with neck pain whether or not they had pain in an upper limb. We found that the QuickDASH detected upper limb problems in most of our participants (83.6%), and the maximum score was 90.9. For all patients, the mean score of the NDI was 12.3 ± 10.0. When we checked the scores of the NDI against the scores of the QuickDASH of 0 (n = 31), the score range of the NDI was 0 to 14.45. The mean score of the QuickDASH was 24.9 ± 22.7. For the two patients with NDI scores of 0, the scores of the QuickDASH were also 0; however, for patients with NDI scores between 2 to 3 (five patients), the range of the scores of the QuickDASH was large (from 0–47.7). Therefore, the QuickDASH should not be used in place of the NDI. We suggest that both the QuickDASH and NDI be used concurrently to assess neck and upper limb disorders in patients with neck pain.

Reliability

The internal consistency of the QuickDASH in our study was high (Cronbach’s alpha = 0.945), equal in quality to those in reports on patients with upper limb problems (0.92–0.94) [27–30]. The item–total score correlations were high (0.67–0.84). When single items were deleted, none of the deletions increased the Cronbach’s alpha by more than 0.1, indicating high homogeneity of all the items.

The test–retest reliability in this study was excellent. For relative reliability, the ICC was 0.98; that value was even better than those reported for patients with upper limb problems (0.92–0.94). For absolute reliability, the SEM and the MDC at the 95% confidence level were 3.17 and 8.79, respectively. An SEM value exceeding 3.17 points in group comparisons indicates an actual difference in function. An MDC value at the 95% confidence level of over 8.79 for an individual indicates that a change is real and not within the range of error of the measure. The MDC in the current study was better than those in previous reports (12.3–20.4) on patients with upper limb problems [27, 31, 32]. The SEM and MDC of the NDI (score range 0–50) were 3.15 and 8.74, respectively, in a study by Lue [15]. The values of the SEM and MDC of the QuickDASH were also better than those of the NDI.

Validity

The QuickDASH had good validity in patients with neck pain, as determined by various psychometric testing methods. The hypothesis testing showed that the similar constructs were as expected, having moderate to high correlation, and the different constructs were as expected, with very low correlation. The correlation coefficient of the QuickDASH and the NDI (rho = 0.80) was high, similar to those in studies by Mehta (person’s r = 0.82) and Khalifen (rho = 0.74 to 0.82) [14, 33]. The correlation was higher with arm pain (VAS-A rho = 0.56) than with neck and shoulder pain (VAS-N rho = 0.49). The correlation coefficients for PCS and the PF, RP, and BP subscales were high (absolute rho = 0.62, 0.51, 0.50, and 0.68, respectively). The QuickDASH was also highly correlated with the SF subscale (absolute rho = 0.67). A possible reason might be cross-loading in the SF subscale (factor loading in physical factor = 0.34; in mental factor = 0.39), which was previously found in a study of 7,093 patients [34]. The clinical implication of the high correlation between the QuickDASH and SF subscale is that people with high QuickDASH scores might have poor social function.

For structural validity, we performed EFA and CFA on different samples chosen by random selection. The EFA identified two factors: the Function-factor (8 items, from Q1 to Q8) and the Symptom-factor (3 items, from Q9 to Q11). The two factors were correlated and together explained 80.9% of the variance. CFA was used to examine the two-factor model identified by the EFA. The factor loadings of the items for the factors to which they belonged were large, and the several model fits were satisfactory, verifying the two-factor model (Function-factor and Symptom-factor). The two factors were correlated. The current study was the first to examine the structural validity of the QuickDASH; furthermore, both EFA and CFA were used.

Study limitations

The limitations of our study must be noted. First, this was a single-center study with a heterogeneous patient cohort. Second, the sample size of our study was small. The sample size for the EFA was 94 and that for the CFA was 95. A minimum sample size of 100 subjects is suggested for CFA [35]. Finally, the study lacked an anchor-based responsiveness study. The responsiveness can be measured by anchor-based methods and distribution-based methods [36, 37]. The MDC value which we provided was determined with a distribution-based method. An anchor-based method needs an external anchor in a longitudinal study design, as different methodology might easily result in different results. The distribution-based MDC method is based on measurement error, the values are more stable, and it can support estimation of the values from anchor-based methods.

Clinical Implications

Over 80% of the patients with neck pain also had arm/shoulder/hand disorders, according to the QuickDASH. The QuickDASH has excellent reliability. The small measurement error (SEM = 3.17) and MDC_95% (8.79) make this measure suitable for clinical application to check whether improvement after intervention is real in both group and individual comparisons. The QuickDASH has satisfactory validity. The QuickDASH correlated well with the NDI, pain VASs, and health-related quality of life subscale of the SF-36. The QuickDASH has two factors: the Function-factor and the Symptom-factor. We suggest that the NDI and the QuickDASH be used concurrently for patients with neck pain.

The QuickDASH is a reliable and valid assessment instrument for assessing function and pain in patients with neck/arm disorders. In the current study, the internal consistency and test–retest reliability were both shown to be excellent. In terms of absolute reliability, the SEM and MDC at the 95% confidence level were 3.17 and 8.79. The convergent and divergent validity were also good. The examination of the construct validity showed the QuickDASH to have two factors: the Function-factor and the Symptom-factor.

Author Contributions

YJL and YML contributed to the study conception and design. YJL headed the project and acquired the funding. Material preparation and data collection were performed by KIC, CLL, CHC and YML. The psychometric evaluation, data analysis and interpretation were performed by YJL. The first draft of the manuscript was written by YJL, and all authors commented on subsequent versions of the manuscript. All authors have read and approved the final manuscript.

Funding

The study was supported by a grant from the Kaohsiung Medical University (KMU-M112017) and National Science and Technology Council (NSTC 113-2314-B-037-080).

Data Availability

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

Competing interest

Yi-Jing Lue, Kuang-I Cheng, Chih-Lung Lin, Chung-Hwan Chen, and Yen-Mou Lu have no relevant financial or non-financial interests to disclose.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Kaohsiung Medical University Hospital (KMUH-IRB-980589 and KMUH-IRB-E(I)-20210363)

Consent to participate

Informed consent was obtained from all individual participants included in the study.

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No competing interests reported.

Validation of the QuickDASH (Disability of the Arm, Shoulder, and Hand) in Patients with Neck Pain

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Introduction

Methods

Procedure

Instruments

QuickDASH

Neck Disability Index

Medical Outcomes Survey Short Form 36

Data management and statistical analyses

Acceptability

Reliability

Construct validity

Results

Discussion

Acceptability

Reliability

Validity

Study limitations

Clinical Implications

Conclusion

Declarations

References

Additional Declarations

Status:

Version 1