Nurses’ competency in pain management is essential for effectively alleviating patients' acute pain, controlling chronic pain, and promoting patient recovery. However, reliable tools for evaluating these competencies across different clinical specialties and healthcare settings are lacking. This study aimed to develop and validate a Pain Management Competency Scale for Nurses (PMCSN) and to assess the pain management competencies of nurses in China through a nationwide survey.
Methods
An item pool and a draft scale were developed through literature reviews, semi-structured interviews, and expert panel discussions. This was followed by refinement of the scale via Delphi expert consultations and a pilot test. To validate the scale, 342 nurses were conveniently sampled from six hospitals in Eastern and Central China. The validation process included item analysis, internal consistency reliability assessment, test–retest reliability (with 40 nurses retaking the questionnaire after a 14-day interval), content validity (evaluated by six experts using a 4-point Likert scale), and structural validity (assessed through exploratory and confirmatory factor analyses). The validated scale was then applied in a survey of 1,500 nurses from 15 hospitals across Eastern, Central, and Western China. Statistical analyses included descriptive statistics, analysis of variance (ANOVA), and t-tests.
Results
The PMCSN comprised six primary dimensions—Pain Assessment and Monitoring, Pharmacological Pain Management, Non-Pharmacological Pain Management, Management of Analgesic Adverse Effects, Patient/Family Education, and Professional Development—and includes 52 tertiary items. The PMCSN scores ranged from 6 to 120, calculated by summing the standardized scores across the six dimensions, with higher scores indicating greater competency in pain management. The scale’s Cronbach’s α was 0.974 (dimension-specific values ranging from 0.863 to 0.935) and a test–retest reliability of 0.871. The content validity index (CVI) of the scale was 0.965. Exploratory factor analysis (EFA) showed that the six-factor model explained 67.50% of the variance. Confirmatory factor analysis (CFA) indicated good model fit, with average variance extracted (AVE) values ranging from 0.659 to 0.811 and composite reliability (CR) between 0.909 and 0.973, confirming good convergent validity. The square roots of the AVE values exceeded the inter-factor correlations, indicating good discriminant validity. In the nationwide survey, the average PMCSN score among 1,500 nurses was 101.27 ± 20.97. Nurses with higher education levels scored higher (F = 14.173, p < 0.01), as did those working in Eastern regions (F = 24.632, p < 0.01) and tertiary hospitals (T = -5.476, p < 0.01).
Conclusions
The PMCSN is a valid and reliable tool for assessing nurses’ pain management competencies. It provides a standardized approach for evaluation and guides targeted interventions to improve competency. Regional and hospital-level disparities highlight the need for enhanced training in underdeveloped areas and collaboration between hospitals to promote balanced healthcare resources.
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Abkürzungen
PMCSN
Pain Management Competency Scale for Nurses
ASPMN
American Society of Pain Management Nurses
KASRP
Knowledge and Attitudes Survey Regarding Pain
NCPMCS
Nurses' Cancer Pain Management Competency Scale
NSAIDs
Nonsteroidal Anti-Inflammatory Drugs
ANOVA
Analysis of Variance
SD
Standard Deviation
AHP
Analytic Hierarchy Process
EFA
Exploratory Factor Analysis
KMO
Kaiser-Meyer-Olkin
CR
Consistency Ratio
PCA
Patient-Controlled Analgesia
Background
Pain, is an unpleasant sensory and emotional experience associated with, or resembling that associated actual or potential tissue damage [1]. Pain is typically classified as acute, lasting less than three months and mainly resulting from injury or surgery, or chronic, persisting beyond three months and sometimes occurring without a clear cause. A global study across 52 countries reported an average prevalence of pain of 27.5%, ranging from 9.9% to 50.3% [2]. The incidence of pain is increasing worldwide [3]. It severely affects sleep, daily activities, and quality of life, often leading to depression and even suicide [4].
Pain management is a fundamental aspect of nursing that requires a multidisciplinary approach, with nurses playing a crucial role [5]. As the understanding of pain concepts and mechanisms evolves, clinical nurses, those providing direct patient care in various healthcare settings, need to continuously update and expand their knowledge to enhance their pain management skills. According to a role delineation study by the American Society of Pain Management Nurses (ASPMN), pain management nursing encompasses eight dimensions: assessment, monitoring, and evaluation of pain; pharmacological pain management; non-pharmacological pain management; therapeutic communication, counseling, and cognitive-behavioral management; patient/family education; activity management; elimination management; and collaboration/institutional activities [6].
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Measuring nursing competency is essential for evaluating the quality of care and ensuring high-quality and safe practices. The World Health Organization defines competency as “a broad composite statement derived from nursing and midwifery practice, which describes a framework of skills reflecting knowledge, attitudes, and psychosocial and psychomotor elements [7].” “Nursing competency” is extensively discussed in the literature through references to international standards and reviews. It is a holistic and integrated concept defined as a performance competency that meets expected standards [8].
Studies have predominantly focused on knowledge and attitudes in pain management nursing competency. The Knowledge and Attitudes Survey Regarding Pain (KASRP) is one of the most extensively used instruments globally [9]. Developed according to established pain management standards, it assesses nurses’ knowledge and attitudes toward pain, including pain assessment, opioid dosing, administration routes, and potential side effects. However, the KASRP questionnaire has limitations, as it primarily evaluates factual knowledge recall and fails to comprehensively assess the multifaceted aspects of pain management competency, such as practical skills and interdisciplinary collaboration [10]. This highlights the need for more holistic tools to assess the full spectrum of competencies required for effective pain management in nursing.
Currently, few instruments comprehensively assess nurses’ competencies in managing various types of pain, including acute, chronic, and cancer-related conditions. The Nurses’ Cancer Pain Management Competency Scale (NCPMCS) is an important step forward, focusing specifically on cancer-related pain management [10]. The NCPMCS comprises 21 items across four dimensions: context of pain management, pain assessment and measurement, pain management, and the multidimensional nature of pain. However, while it is grounded in Fishman et al.’s four core pain management competencies, which provide a strong framework for pre-licensure education [11], it may not fully address the complexities of pain management in diverse clinical settings, including the breadth of non-pharmacological approaches, activity management techniques, and the collaborative, institutional strategies advocated by the ASPMN [6]. Accordingly, a new, purpose-built assessment tool is needed to provide detailed guidance and comprehensively evaluate nurses’ competencies in managing both acute and chronic pain.
In recent years, the importance of effective pain management has significantly increased in China [12]. Many hospitals monitor and manage pain, considered the fifth vital sign. The Chinese Nursing Association has played a pivotal role in promoting high standards of postoperative pain assessment and nursing for adult patients by issuing practice guidelines for nurses nationwide [13]. As hospital administrators and researchers increasingly focus on nurses’ competency in pain management, the absence of comprehensive assessment tools for this competency in China and globally has become a notable gap. Therefore, this study aimed to: 1) develop and validate the Pain Management Competency Scale for Nurses (PMCSN), with a focus on both acute and chronic pain management, for use in all clinical departments and verify the scale’s reliability and validity; and 2) investigate the pain management competency levels of nurses across China and identify influencing factors.
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Subjects and methods
Research design
This study was conducted in two phases: the first phase involved developing a scale to assess nurses’ competency in pain management and validating its reliability and validity; in the second phase, the scale was applied in a nationwide survey to evaluate the pain management competency of Chinese nursing professionals (Fig. 1).
Fig. 1
Flowchart of the research design
×
Constructing the item pool and developing the draft scale
This study constructed the item pool by reviewing literature related to clinical nurses’ pain management practices and conducting semi-structured interviews with nurses experienced in pain management.
Literature review
Searches were conducted using keywords, such as “nursing/nursing practice,” “nurses/nurse competency,” “pain management,” “nursing,” “pain/pain management,” and “pain assessment.” These searches spanned English (PubMed, Web of Science, Embase, and EBSCO) and Chinese (CNKI, Wanfang, and VIP) databases from their inception to December 2022. The inclusion criteria included surveys, interventions, guidelines, or practice standards related to pain management nursing. Exclusion criteria included inability to access the full text, literature not in English or Chinese, and conference papers. Content analysis was used to extract the items from the included studies.
A total of 5,769 articles were retrieved, including 2,914 in foreign languages and 2,855 in Chinese. After removing duplicate articles (n = 1,907), articles irrelevant to the research topic (n = 3,794), articles without full-text access (n = 14), and non-Chinese or non-English articles (n = 26), 28 articles were finally included (4 in Chinese and 24 in English).
Semi-structured interviews
Purposive sampling was used to conduct semi-structured interviews with nurses who had over five years of experience in pain management nursing and held intermediate or higher professional titles. The interviews aimed to explore the essential capabilities required for effective pain management, guided by the following questions: What capabilities should a clinical nurse possess to be competent in pain management and why? Among these, which are the most critical and why? The interviews were fully audio-recorded, and key points and non-verbal cues were noted. The recordings were transcribed and cross-checked by two graduate students specializing in pain management nursing. Colaizzi’s seven-step analysis method was employed to organize and analyze the data and extract relevant items. Data collection continued until no new themes emerged [14].
A total of 17 interview participants were included, with an average of 18.7 ± 6.1 years of work experience. Among them, 14 held intermediate professional titles, and 3 held senior titles. Additionally, 9 participants were pain specialist nurses, 3 were surgical nurses, and 5 were internal medicine nurses.
Expert panel discussion
Items were extracted from the 28 included articles and combined with findings from the semi-structured interviews to generate an item pool consisting of 349 items. Subsequently, experts with more than five years of experience in pain management nursing were invited to review, revise, and discuss the dimensions of the extracted items from the literature and interviews. Following expert panel discussions, the item pool was refined to a final set of 67 items, categorized into 21 secondary dimensions and 7 primary dimensions: pain assessment and monitoring, pharmacological pain management, non-pharmacological pain management, management of analgesic-related adverse effects, patient/family education, activity-related pain management, and professional development.
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Developing the scale
Delphi expert consultation
The fifteen experts were invited via email or WeChat to participate in two rounds of Delphi consultations. The inclusion criteria for experts were as follows: 1) specialization in pain management nursing, nursing management, or pain medicine; 2) at least five years of professional experience; 3) a bachelor’s degree or higher; and 4) an intermediate level or higher professional title. The basic information on the experts is presented in Table 1.
Table 1
The general information of the participants involved in this study
Categories
Project
Delphi expert consultationa
Reliability and validity testingb
Survey of Chinese Nursesc
Frequency (N)
Proportion (%)
Frequency (N)
Proportion (%)
Frequency (N)
Proportion (%)
Sex
Male
2
13.3
4
1.2
69
4.6
Female
13
86.7
338
98.8
1431
95.4
Age (years)
< 30
0
0.0
184
53.8
525
35.0
30 ~
5
33.3
116
33.9
717
47.8
40 ~
8
53.3
39
11.4
207
13.8
≥ 50
2
13.3
3
9.0
51
3.4
Educational background
Associate Degree
0
0.0
57
16.7
289
19.3
Bachelor
4
26.7
264
77.2
1191
79.4
Master
9
60.0
21
6.1
20
1.3
Doctor
2
13.3
0
0.0
0
0.0
Profession titles
Junior level
0
0.0
226
66.1
858
57.2
Intermediate level
5
33.3
104
30.4
534
35.6
Senior level
10
66.7
12
3.5
108
7.2
Professional experience(years)
< 10
2
13.3
210
61.4
727
48.5
10 ~ 20
8
53.3
97
28.4
621
41.4
> 20
5
33.3
35
10.2
152
10.1
Work area
Pain medicine
3
20.0
—
—
—
—
Pain management nursing
7
46.7
—
—
—
—
Hospital administration
4
26.7
—
—
—
—
Nursing education
1
6.7
—
—
—
—
“—” indicates the item was not covered in the survey
aGeneral information of experts in the Delphi consultation (n = 15)
bGeneral information of research subjects for scale validation (n = 342)
cGeneral information of subjects in the nurse pain competency survey (n = 1500)
The importance of each item was assessed using a five-point Likert scale ranging from one (not important) to five (especially important). The response rate measured expert enthusiasm, whereas the authority coefficient, which averaged the experts’ judgment capability and familiarity with the indicators, assessed opinion credibility. Kendall’s coefficient of concordance was used to measure consensus among the experts. Items with a mean importance score (M) ≤ 4.00 or a coefficient of variation ≥ 0.25 were considered for deletion [15]. Based on consultations, items were deleted, adjusted, merged, or supplemented.
Using the average scores from the second round of evaluations, a judgment matrix was constructed for the evaluation criteria. The Analytic Hierarchy Process (AHP) was used to establish a hierarchical structure model and determine item weights [16].
Pilot test
After expert consultation, a pilot test of the scale was conducted in a hospital. One-on-one surveys using paper questionnaires were administered to 20 nurses, and responses were collected immediately upon completion. Based on participants’ feedback on the clarity and comprehensibility of the items, modifications were made, resulting in a preliminary scale.
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Psychometric testing of the scale
Survey participants
China is divided into three economic regions—Eastern, Central, and Western—which are categorized by their economic development and geographical location. The eastern region is the most economically developed, whereas the western region is the least [17, 18]. We employed convenience sampling to select nurses from six hospitals in the eastern and central regions for the survey. Based on the applicable standards for validity and reliability testing, the sample size is generally required to be in a 5:1 ratio to the number of questionnaire items [19]. Considering an expected 10%–20% rate of invalid questionnaires, with 57 items in this study, the estimated sample size ranges from 315 to 350 participants. A total of 360 questionnaires were distributed, and 342 valid responses were received, yielding a 95% effective response rate. The average age of the nurses was 37.06 ± 9.21 years, with an average work experience of 17 ± 9.67 years. The general demographic information of the participants is shown in Table 1.
Survey tool
Based on the preliminary scale, we designed a draft questionnaire that included: (1) instructions for completing the questionnaire; (2) a general information survey; and (3) the Pain Management Competency Scale for Nurses (PMCSN). Each item was rated using a 5-point Likert scale (five = completely agree, one = completely disagree).
Item analysis
The total scores of the respondents were ranked from highest to lowest, and an independent samples t-test was used to calculate the differences between the top 27% (high-scoring group) and the bottom 27% (low-scoring group) for each item. Items with significant differences (p < 0.01) were retained. Additionally, Pearson’s product-moment correlation coefficient assessed the relationship between each item and the total score, with items retained if their correlation coefficient was r > 0.4 and significant at p < 0.01 [20].
Validity analysis
The validity of the scale was assessed through construct validity and content validity. Construct validity was evaluated using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). First, Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin (KMO) measure were used to determine the suitability of the data for EFA, requiring a significant Bartlett’s test result (p < 0.05) and a KMO value greater than 0.7. EFA utilized principal component analysis with a restricted factor extraction method, limiting the extraction to six factors based on the six dimensions determined through expert consultation. Items with factor loadings below 0.4 or not aligned with the main components were removed, ensuring that all common factors accounted for more than 40% of the total variance. CFA was used to validate the factor structure obtained from prior expert consultations and EFA. Model fit was evaluated using indices such as the root mean square error of approximation (RMSEA), the parsimonious goodness-of-fit index (PGFI), the parsimonious normed fit index (PNFI), the parsimonious comparative fit index (PCFI), and others. To assess convergent validity, the average variance extracted (AVE) and composite reliability (CR) values were calculated. The AVE value exceeding 0.50 indicates good convergent validity; values above 0.40 are also acceptable. The CR value greater than 0.70 suggests that the scale has sufficient internal consistency. Discriminant validity was evaluated by comparing the square roots of the AVE values with the correlation coefficients between factors. Specifically, the square root of a factor’s AVE should be greater than its correlation coefficients with other factors, indicating that the factor can be effectively distinguished from others.
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To assess the content validity of the questionnaire, we randomly selected six experts who had previously participated in Delphi consultations. These experts rated the relevance of the questionnaire items using a four-point scale (1 = not relevant, 2 = somewhat relevant, 3 = quite relevant, 4 = highly relevant). Content validity is typically evaluated at two levels: the item-level content validity index (I-CVI) and the scale-level content validity index (S-CVI). When the number of experts is ≥ 6, an I-CVI > 0.78 and an S-CVI > 0.90 indicate that the questionnaire has good content validity [21].
Reliability analysis
To evaluate the internal consistency reliability of the scale, Cronbach’s α coefficient was calculated. Additionally, 40 participants who had previously completed the survey were invited to fill out the questionnaire again two weeks later to assess the stability of the scale over time. To establish good internal consistency reliability and test–retest reliability, both the Cronbach’s α coefficient and the test–retest reliability coefficient should be 0.70 or higher.
Survey of Chinese nurses’ competency in pain management
Survey population
China’s healthcare system is divided into three tiers: primary care facilities, secondary hospitals, and tertiary hospitals. This classification is based on the capabilities of the institutions involved in medical care, education, and research [22]. Tertiary hospitals, which are often located in major cities, represent the highest level of healthcare and provide advanced medical treatments and research opportunities. Secondary hospitals and medium-sized institutions offer comprehensive healthcare services. Primary care facilities deliver basic health services to local communities using limited resources and technology.
In this study, nurses from secondary and tertiary hospitals across three economic regions were surveyed from September 2023 to February 2024 using stratified whole-cluster sampling. The inclusion criteria were as follows: 1) possession of a nursing qualification certificate, and 2) involvement in pain management in daily nursing work. The exclusion criteria included interns, trainees, non-stationary staff (including those on learning assignments or leave), and auxiliary or office nurses. Because primary care facilities provide basic medical services and many do not have inpatients, nurses from these institutions were not included. Adopted the research-validated PMCSN, which was supplemented by a collection of sociodemographic data (age, sex, education, years of working experience, and professional titles). Finally, we surveyed 1,500 nurses, with their general demographic information presented in Table 1. Among them, 41.2% (n = 618) worked in the eastern economic region, and 62.7% (n = 940) worked in tertiary hospitals.
Survey methods and statistical processing
At each hospital site, an investigator established initial contact with the participants and collected data via Wenjuanxing, an online survey tool with functions equivalent to those of Amazon Mechanical Turk. Statistical analyses were performed using IBM SPSS (Version 26.0, IBM Corp., Released 2019, Armonk, NY), with frequency, proportion, and Mean ± SD for descriptive statistics. Analysis of variance and t-tests were used to compare the pain care competency scores of clinical nurses with different demographic characteristics.
Results
Results of expert consultation
In the first round of consultation, 15 questionnaires were distributed, and all 15 were returned, yielding an effective response rate of 100%. In the second round, 15 questionnaires were again distributed, and all 15 were returned, maintaining an effective response rate of 100%, indicating a high level of expert engagement. Furthermore, the rate of expert opinion submission in the first round was 80%, while in the second round, it was 40%. Kendall’s coordination coefficients for the primary, secondary, and tertiary dimensions were 0.218, 0.226, and 0.248 in the first round and 0.282, 0.231, and 0.260 in the second round, respectively. All Kendall test results were statistically significant (p < 0.01), indicating a high degree of consistency among the experts’ opinions. Furthermore, the increase in Kendall’s coordination coefficients in the second round compared to the first suggests that the experts’ opinions became progressively more aligned throughout the consultation process.
In the first round, the mean importance scores of the items ranged from 3.33 to 4.93, with a coefficient of variation between 0.050 and 0.316. In the second round, the mean importance scores ranged from 3.47 to 4.93, with a coefficient of variation between 0.050 and 0.300. After two rounds of expert consultations, one primary indicator (activity-related pain management) was excluded. Four secondary indicators were removed; one was added, and three were modified. Thirteen tertiary items were removed, three were added, and 14 were modified. After two rounds of Delphi consultation, the scale comprised six primary indicators, 18 secondary indicators, and 57 tertiary items.
Weight determination and Pilot test
AHP was used to calculate the raw weights of the primary, secondary, and tertiary indicators. The consistency ratio of the primary indicators was 0.019. For the secondary indicators and items, the consistency ratio values ranged from 0 to 0.0515. All consistency ratio values were less than 0.1, indicating reasonable and consistent weight settings among the primary indicators, secondary indicators, and items. Subsequently, based on the pilot test results, six unclear semantic expressions were revised, resulting in a preliminary scale.
Table 2
The reliability and content validity of the Pain Management Competency Scale for Nurses
Cronbach’s α
(n = 342)
Test–retest reliability (n = 40)
I-CVI (n = 6)
S-CVI (n = 6)
Dimension A
0.929
0.869
0.830 ~ 1.000
0.965
Dimension B
0.863
0.814
Dimension C
0.882
0.779
Dimension D
0.867
0.811
Dimension E
0.935
0.706
Dimension F
0.879
0.739
Total
0.974
0.871
I-CVI Content validity index of the item, S-CVI Content validity index of the scale
Results of the psychometric testing of the scale
Results of item analysis
All items passed the extreme value test (p < 0.01), indicating good discrimination. The correlation analysis showed that the correlation coefficients for all items ranged from 0.371 to 0.918. The coefficients for items A-1–4 and B-2–1 were less than 0.4. After a group discussion, these two items were removed, resulting in the retention of 55 items.
Internal consistency reliability and test–retest reliability
The overall Cronbach’s α coefficient for the scale was 0.974, with individual dimensions ranging from 0.863 to 0.935, indicating good internal consistency. The overall test–retest reliability was 0.871, with dimension-specific values ranging from 0.706 to 0.869, demonstrating strong stability. The specific results are shown in Table 2.
Content validity
Six experts from the Delphi consultation group were randomly selected to evaluate the scale’s content validity. The item-level content validity index ranged from 0.83 to 1.00, whereas the scale-level content validity index was 0.965, confirming good content validity. The specific results are shown in Table 2.
Construct validity
The results of the EFA indicated that the KMO value was 0.954, and Bartlett’s test of sphericity was significant (X2 = 17,322.862, p < 0.01), confirming that the data were suitable for factor analysis. The first round of EFA revealed eigenvalues of 23.648, 5.337, 3.256, 2.073, 1.822, and 1.470, with a cumulative variance contribution of 65.98%. Items A-1–3 and B-3–1 were removed due to factor loadings below 0.4. In the second round of EFA, the six factors had eigenvalues of 52.230, 4.989, 3.103, 2.182, 1.808, and 1.291, with a cumulative variance contribution of 80.99%. Although item A-1–1 had a factor loading below 0.4, it was retained due to its clinical relevance. Item F-2–3, which was incorrectly loaded onto a different component, was removed before the third round of EFA. The final EFA revealed eigenvalues of 22.649, 5.227, 3.106, 1.856, 1.647, and 1.288, with a cumulative variance contribution of 67.50%. All remaining items were appropriately loaded onto their corresponding factors. The factor loadings for all items across the three rounds of EFA are provided in the Appendix.
After conducting EFA, CFA was performed to validate the scale’s structure. The model fit indices were as follows: RMSEA = 0.092, PGFI = 0.563, PNFI = 0.782, PCFI = 0.792, and SRMR = 0.062. In the convergent validity analysis, the AVE values for the six factors ranged from 0.659 to 0.811, all exceeding the threshold of 0.5. The CR values ranged from 0.909 to 0.973, all above 0.7, indicating good convergent validity. For discriminant validity, the square roots of the AVE values ranged between 0.69 and 0.80, surpassing the correlation coefficients between corresponding factors, confirming the scale’s strong discriminant validity. The specific results are shown in Table 3.
Table 3
Convergent validity and discriminant validity of the Pain Management Competency Scale for Nurses
Factors
Correlation between factors
AVE
Sqrt (AVE)
CR
1
2
3
4
5
6
1
1
0.659
0.812
0.973
2
0.780
1
0.676
0.822
0.909
3
0.784
0.793
1
0.775
0.880
0.945
4
0.726
0.819
0.808
1
0.784
0.885
0.948
5
0.774
0.818
0.879
0.847
1
0.781
0.884
0.966
6
0.538
0.497
0.636
0.476
0.629
1
0.811
0.900
0.945
AVE Average variance extracted, CR Composite reliability
In summary, after item analysis and scale validation, five tertiary items (A-1–3, A-1–4, B-2–1, B-3–1, and F-2–3) across the four secondary dimensions were removed. Their initially assigned weights were redistributed among the remaining items within the same secondary dimension to ensure consistency in the total dimension weight and maintain the integrity of the weighting process (see values marked with # in Table 4). The final PMCSN comprises six primary dimensions, 18 secondary dimensions, and 52 tertiary items, each rated on a five-point Likert scale ranging from five (completely agree) to one (completely disagree). Scoring was conducted in three steps: 1) Item Scoring: Each item’s weighted score was calculated by multiplying its AHP weight coefficient by its Likert scale score. 2) Dimension Scoring: The weighted scores of all items within each of the six primary dimensions were summed and converted into standardized scores ranging from one to 20, with higher scores indicating stronger competency. 3) Overall Scoring: The total PMCSN score was obtained by adding the standardized scores across the six dimensions, resulting in a range of six to 120 points.
Table 4
Composition and Weight Values of the Pain Management Competency Scale for Nurses
Item
Weight value
A
Pain assessment and monitoring (Dimension One)
0.2701
A-1
Pain screening
0.0880
A-1–1
Screen for presence of pain upon patient admission
0.0348/0.0500b
A-1–2
Screen for pain during routine daily vital signs assessment
0.0204/0.0368b
A-1-3a
Screen for pain when there is a change in patient's condition
0.0124
A-1-4a
Screen for pain when patient returns to ward post-surgery
0.0204
A-2
Proper use of pain assessment tools
0.0572
A-2–1
For patients capable of communicating (including verbal and non-verbal), use self-report pain assessment tools
0.0282
A-2–2
For patients lacking communication abilities, use behavioral pain assessment tools
0.0178
A-2–3
Consistently use the same type of self-report pain assessment tool throughout the patient’s whole hospital stay
0.0112
A-3
Comprehensive pain assessment
0.0386
A-3–1
Assess the location of pain
0.0065
A-3–2
Assess the intensity of pain
0.0065
A-3–3
Assess the timing characteristics of pain
0.0027
A-3–4
Assess the nature of pain
0.0065
A-3–5
Assess any symptoms accompanying pain
0.0043
A-3–6
Assess factors that exacerbate or alleviate pain
0.0037
A-3–7
Assess patient’s history of previous pain treatments
0.0018
A-3–8
Assess the impact of pain on the patient’s daily life and work
0.0039
A-3–9
Assess psychological and emotional effects of pain on the patient
0.0027
A-4
Continuous pain assessment and documentation
0.0291
A-4–1
Continuously assess changes in the patient’s pain location, intensity, nature, duration, presence of breakthrough pain, and factors that alleviate or exacerbate the pain
0.0091
A-4–2
Document the pain assessment tool used for each evaluation
0.0057
A-4–3
Document the results of each pain assessment
0.0144
A-5
Assessment of active pain
0.0572
A-5–1
Evaluate pain during patient activity using both subjective and objective pain assessment methods
0.0191
A-5–2
Assess effectiveness of postoperative analgesia by evaluating both resting and active pain experienced by patients
0.0381
B
Pharmacological pain management (Dimension Two)
0.2701
B-1
Implementation, evaluation, and documentation of pharmacological interventions
0.0840
B-1–1
Administer analgesia correctly as per physician’s orders
0.0414
B-1–2
Evaluate the effectiveness of analgesia promptly based on reassessment times for different routes of administration
0.0164
B-1–3
Document the results of analgesia following pharmacological intervention
0.0261
B-2
Management of analgesic medications
0.1333
B-2-1a
Manage morphine and other controlled substances according to hospital regulations, ensuring designated personnel, locked cabinets, specific prescriptions, dedicated ledgers, and exclusive registration
0.0533
B-2–2
Residual liquids and tablets of opioids, such as morphine, are checked by two individuals and then disposed of in a sink (tablets are crushed) and documented
0.0533/0.0799b
B-2–3
Used opioid patches and injectables are collected, batch numbers and quantities verified, and the details recorded
0.0267/0.0534b
B-3
Management of Patient-Controlled Analgesia (PCA)
0.0529
B-3-1a
During the use of PCA pumps, assess patient pain according to hospital guidelines at scheduled times
0.0086
B-3–2
Regularly check the functionality of the PCA pump, medication infusion volume, button presses, and tubing status during its use
0.0086/0.0129b
B-3–3
Identify and resolve common issues with PCA pumps such as alarms, tubing blockages, or exhaustion of medication
Implementation of non-pharmacological interventions
0.0369
C-1–1
Develop individualized non-pharmacological pain intervention plans based on the patient’s condition, effective non-pharmacological treatment history, or preferences
0.0115
C-1–2
With physician approval, implement non-pharmacological interventions based on the patient’s pain condition
0.0182
C-1–3
Provide comfort care for patients with pain, such as arranging suitable bed positions
0.0072
C-2
Evaluation and documentation of non-pharmacological interventions
0.0185
C-2–1
Evaluate the effectiveness of non-pharmacological interventions
0.0123
C-2–2
Document outcomes of the pain assessments following non-pharmacological interventions
0.0062
D
Management of analgesic side effects (Dimension Four)
0.1865
D-1
Monitoring adverse drug reactions
0.1243
D-1–1
Monitor for adverse reactions such as respiratory depression, excessive sedation, constipation, nausea, vomiting, and urinary retention during opioid use; promptly report any abnormalities to physicians
0.0414
D-1–2
Monitor for gastrointestinal side effects, liver and kidney function abnormalities, platelet dysfunction, and allergic reactions during the use of Nonsteroidal Anti-Inflammatory Drugs (NSAIDs); promptly report any abnormalities to physicians
0.0829
D-2
Addressing adverse drug reactions
0.0622
D-2–1
Identify the causes of analgesia adverse reactions and other potential contributing factors
0.0249
D-2–2
Evaluate the effectiveness of managing analgesia adverse reactions
0.0124
D-2–3
Document adverse reactions, management strategies, and outcomes
0.0249
E
Patient/family education (Dimension Five)
0.0822
E-1
Education on pharmacological and non-pharmacological pain interventions
0.0271
E-1–1
Instruct patients and families on proper medication use and precautions
0.0204
E-1–2
Teach patients and families the methods and precautions for non-pharmacological interventions
0.0068
E-2
Education on active pain management
0.0271
E-2–1
Instruct patients and families on ways to reduce pain during activity
0.0087
E-2–2
For patients using PCA therapy, advise them to press the dosing button 5 min before activities
0.0152
E-2–3
Teach patients to self-assess pain during functional activities, such as deep breathing and effective coughing
0.0033
E-3
Education on pain management principles
0.0164
E-3–1
Inform patients that they do not need to endure pain and encourage them to express their true feelings about pain
0.0016
E-3–2
Educate patients on how to accurately express their pain using tools
0.0040
E-3–3
Instruct patients when they should report pain to healthcare professionals
0.0068
E-3–4
Correct patients’ and their families’ misconceptions, and alleviate their concerns
0.0040
E-4
Discharge education for pain self-management
0.0115
E-4–1
Ensure patients understand correct usages and routes for their discharge pain medications
0.0037
E-4–2
Collaborate with patients to set post-discharge pain control goals, self-management plans, and follow-up schedules
0.0014
E-4–3
Educate patients to seek medical attention promptly if they encounter any abnormalities during home medication use, such as new pain, pain unrelieved by medication, or unmanageable side effects
0.0064
F
Professional development (Dimension Six)
0.1356
F-1
Research and innovation skills
0.0904
F-1–1
Possess basic ability to conduct pain management research, including literature searches, data retrieval, and paper writing
0.0603
F-1–2
Have a certain capacity to proactively explore and implement new methods and technologies in pain management and integrate these innovations into practice
0.0301
F-2
Pain management quality control ability
0.0452
F-2–1
Participate in pain management quality improvement initiatives, identifying deficiencies in pain management and suggesting improvements
0.0226/0.0283b
F-2–2
Collect and analyze patient outcomes in pain management to target improvements in quality more effectively
0.0113/0.0169b
F-2-3a
Evaluate the suitability of prescribed analgesic treatment based on individual patient conditions and provide prompt feedback if unsuitable
0.0113
aThe item was deleted by item analysis and scale validation
bindicates the new weighting targets. Five tertiary items across four secondary dimensions were removed during item analysis and scale validation, with their corresponding weights redistributed among the remaining items in those dimensions
Survey results of Chinese nurses’ competency in pain management
We surveyed 1,500 nurses across China, with 41.2% (n = 618) working in the eastern economic region and 62.7% (n = 940) working in tertiary hospitals. The PMCSN scores were 101.27 ± 20.97. The six primary dimension scores, ranked from highest to lowest, were as follows: Pharmacological Pain Management (17.84 ± 3.59), Management of Analgesic Side Effects (17.76 ± 3.76), Non-Pharmacological Pain Management (17.14 ± 4.05), Patient/Family Education (17.13 ± 3.96), Pain Assessment and Monitoring (17.01 ± 3.63), and Professional Development (14.39 ± 5.66).
Our findings indicated that educational background, region, and hospital level significantly influenced nurses’ pain management competencies (p < 0.05). Specifically, nurses with higher educational levels scored higher on the PMCSN (F = 14.173, p < 0.01). Nurses in eastern region hospitals scored (104.71 ± 18.82) higher than those in central (101.34 ± 20.71) and western region hospitals (94.93 ± 23.51) (F = 24.632, p < 0.01). Additionally, nurses in tertiary hospitals scored (103.54 ± 19.51) higher than those in secondary hospitals (97.47 ± 22.73) (T = -5.476, p < 0.01). The specific scores and comparisons are presented in Fig. 2 and Table 5.
Fig. 2
Pain Management Competency Scale for Nurses scores of nurses across three economic regions and at secondary and tertiary hospitals in China
Table 5
Demographic data and Pain Management Competency Scale for Nurses scores of Chinese nurses (n = 1500)
Categories
Project
N
D1
D2
D3
D4
D5
D6
Totals
Sex
Male
69
16.44 ± 3.76
17.35 ± 3.08
17.02 ± 3.38
17.27 ± 3.45
16.44 ± 4.34
14.88 ± 4.42
99.39 ± 18.82
Female
1431
17.04 ± 3.62
17.87 ± 3.62
17.14 ± 4.09
17.79 ± 3.77
17.16 ± 3.94
14.37 ± 5.71
101.36 ± 21.07
T
1.349
1.170
0.247
1.110
1.478
-0.736
0.761
P
0.178
0.242
0.805
0.267
0.14
0.462
0.447
Age (years)
< 30
525
16.81 ± 3.53
17.68 ± 3.44
16.93 ± 3.95
17.58 ± 3.69
16.96 ± 3.81
14.43 ± 5.68
100.38 ± 20.47
30 ~
717
17.18 ± 3.68
17.99 ± 3.51
17.24 ± 4.03
17.87 ± 3.67
17.23 ± 3.96
14.35 ± 5.68
101.85 ± 20.77
40 ~
207
16.96 ± 3.56
17.75 ± 4.01
17.19 ± 4.36
17.72 ± 4.12
17.03 ± 4.31
14.44 ± 5.54
101.09 ± 22.34
50 ~
51
17.05 ± 4.26
17.88 ± 4.51
17.55 ± 4.23
18.36 ± 4.13
17.75 ± 4.04
14.37 ± 5.74
102.96 ± 23.22
F
1.051
0.823
0.807
1.019
0.948
0.025
0.614
P
0.369
0.481
0.49
0.383
0.417
0.995
0.606
Profession titles
Junior level
858
16.86 ± 3.79
17.73 ± 3.71
17.03 ± 4.07
17.62 ± 3.91
17.07 ± 4.00
14.53 ± 5.65
100.83 ± 21.41
Intermediate level
534
17.28 ± 3.31
18.04 ± 3.34
17.35 ± 3.92
17.97 ± 3.49
17.25 ± 3.86
14.20 ± 5.69
102.11 ± 19.86
Senior level
108
16.89 ± 3.80
17.80 ± 3.87
16.95 ± 4.53
17.92 ± 3.83
16.97 ± 4.13
14.09 ± 5.55
100.63 ± 22.76
F
2.197
1.281
1.167
1.529
0.424
0.611
0.671
P
0.111
0.278
0.312
0.217
0.654
0.543
0.511
Educational background
Associate degree
289
15.86 ± 4.11
17.26 ± 3.78
15.95 ± 4.75
17.10 ± 4.14
16.09 ± 4.37
13.40 ± 6.53
95.66 ± 24.14
Bachelor
1191
17.27 ± 3.47
17.97 ± 3.56
17.41 ± 3.83
17.90 ± 3.67
17.36 ± 3.84
14.58 ± 5.43
102.49 ± 20.01
Master
20
18.15 ± 2.01
19.05 ± 2.04
17.72 ± 3.03
19.06 ± 1.80
18.29 ± 2.16
17.29 ± 2.68
109.56 ± 11.50
F
19.167
5.736
15.65
6.536
12.823
7.789
14.173
P
< 0.001*
0.003*
0.000*
0.001*
< 0.001*
< 0.001*
< 0.001*
Regions
Eastern
618
17.82 ± 3.17
18.41 ± 3.19
17.81 ± 3.64
18.29 ± 3.44
17.72 ± 3.68
14.66 ± 5.55
104.71 ± 18.82
Central
541
16.92 ± 3.65
17.76 ± 3.71
17.14 ± 3.91
17.59 ± 3.91
17.17 ± 3.88
14.76 ± 5.35
101.34 ± 20.71
Western
341
15.70 ± 3.98
16.95 ± 3.90
15.91 ± 4.66
17.07 ± 3.94
15.99 ± 4.32
13.31 ± 6.19
94.93 ± 23.51
F
39.395
18.993
24.958
12.512
21.599
8.121
24.632
P
< 0.001*
< 0.001*
0.000*
< 0.001*
0.001*
< 0.001*
< 0.001*
Categories
Project
N
D1
D2
D3
D4
D5
D6
Totals
Hospital level
Secondary
560
16.17 ± 3.91
17.52 ± 3.66
16.41 ± 4.48
17.26 ± 3.98
16.39 ± 4.26
13.72 ± 6.28
97.47 ± 22.73
Tertiary
940
17.51 ± 3.36
18.04 ± 3.54
17.57 ± 3.71
18.06 ± 3.59
17.56 ± 3.71
14.79 ± 5.22
103.54 ± 19.51
T
-7.033
-2.738
-5.447
-4.009
-5.547
-3.576
-5.476
P
< 0.001*
0.006***
< 0.001*
< 0.001*
0.000*
< 0.001*
< 0.001*
Total
1500
17.01 ± 3.63
17.84 ± 3.59
17.14 ± 4.05
17.76 ± 3.76
17.13 ± 3.96
14.39 ± 5.66
101.27 ± 20.97
D1–Pain assessment and monitoring
D2–Pharmacological pain management
D3–Non-pharmacological pain management
D4–Management of analgesic-related adverse effects
D5–Patient/Family education
D6–Professional development
* represent 1% significance levels, respectively
×
Discussion
Pain is considered the fifth vital sign, and nurses, who work with patients 24 h a day, play an integral role in evaluating and managing pain. Therefore, efficient pain management is critical for nurses [23]. This study developed and validated the PMCSN through a scientific scale development process that primarily included item construction and consultations with Delphi experts. The results of the reliability and validity analyses indicated that the scale had good measurement performance and could accurately assess the pain management competency of clinical nurses across various departments in China.
In pain management competency research, scholars initially focused more on the competencies of pre-licensure health professionals and developed corresponding assessment tools. For example, the “InterProfessional Core Competencies for Pain Management” framework aims to promote understanding and collaboration in pain management among students from various health professions [11]. Similarly, the “Clinical Pain Knowledge Test” assesses the pain management knowledge and skills of medical students before they enter clinical practice [24, 25]. Although these tools are primarily intended for medical and nursing students, they provide valuable insights for defining the competency requirements of practicing nurses. In addition, researchers have often focused more on nurses’ knowledge of pain, rather than their overall competency in managing it. Some tools, such as the Self-Perceived Pain Assessment Knowledge and Confidence Scale, used to assess nurses’ pain management practices primarily emphasize their knowledge and attitudes toward pain management [26, 27]. While knowledge is a critical component of competency, these tools do not comprehensively evaluate nurses’ broader pain management abilities. The NCPMCS, drawing on Fishman et al.’s core framework for pre-licensure education and specifically focused on cancer-related pain, may have limitations in addressing the broader complexities of pain management across diverse clinical settings [10, 28].
The development of pain specialties in China is still in its early stages, and pain management nursing remains underdeveloped, with the specific responsibilities of clinical nurses in pain management not yet clearly defined. The ASPMN identified 91 key pain management activities involving nurses, most of which are covered by the six dimensions of the PMCSN: 1) Pain assessment and monitoring: This dimension focuses on pain screening, using assessment tools, conducting comprehensive evaluations, activity-related pain assessment, and continuous monitoring. 2) Pharmacological pain management: This dimension emphasizes administering prescribed analgesics, evaluating their effectiveness, and handling opioids, with three items (B-2–1, B-2–2, B-2–3) specific to the Chinese context related to the storage and management of morphine, a specially regulated drug under the Drug Administration Law of the People’s Republic of China [29]. 3) Management of analgesic side effects: This dimension involves monitoring and managing the adverse effects of analgesics. 4) Professional development: This dimension encompasses research, innovation, and quality improvement capabilities. 5) Patient/family education: This dimension focuses on guiding patients or family members in pain self-management. 6) Non-pharmacological pain management: This dimension focuses on implementing and evaluating non-pharmacological pain relief measures. Therefore, the PMCSN, aligned with the key pain management activities outlined by the ASPMN, serves as a valuable tool for conducting comprehensive evaluations of pain management competencies, enabling the identification of subtle gaps in nurses’ skills across various clinical departments. By addressing these gaps, it facilitates targeted training and supports the standardization of pain management practices.
This study is the first nationwide survey in China to assess nurses’ pain management competencies. Nurses in hospitals in the eastern economic region outperformed those in the central and western regions (p < 0.01), and nurses in tertiary hospitals scored higher on the PMCSN than those in secondary hospitals (p < 0.01). These differences are likely due to better medical resource allocation, more comprehensive nurse training programs, and more effective pain management policies in the eastern economic region. Tertiary hospitals, being larger institutions, typically have more resources and specialized personnel. These findings are consistent with those of Chen et al. [30]. Among the nurses surveyed, those with higher educational qualifications scored higher on the PMCSN (p < 0.05), reflecting their more specialized education, greater knowledge base, and proficiency in handling complex issues.
In the six primary dimensions of the PMCSN, nurses scored highest in the “Management of Analgesic Side Effects” dimension, underscoring the critical importance of side effect management for patient safety. However, owing to China's low nurse-to-bed ratio and high workload, ensuring safety often comes at the expense of patient comfort, comprehensive pain assessment, intervention, and health education [31]. Conversely, scores were lowest in “Professional Development,” which can be attributed to the demanding nature of bedside nursing, restricting the time available for exploring innovative pain management techniques and participating in quality control, typically overseen by nursing supervisors.
China currently implements the “medical assistance” policy, where tertiary hospitals support lower-level healthcare facilities, and eastern hospitals provide targeted assistance to western hospitals [32, 33]. This strategy aims to improve medical service levels and capabilities in underdeveloped regions, thereby reducing regional resource disparities. These results highlight the need for cross-regional and cross-hospital targeted support and training programs to enhance the pain management competencies of nurses nationwide. Additionally, efforts should include improving the nurse-to-bed ratio to allow for more comprehensive pain management and patient care; prioritizing training programs on pain assessment, intervention, and patient education, particularly for less experienced nurses; and encouraging nurses’ involvement in quality control and professional development through mentorship programs.
Limitation
This study had several limitations. First, the development of the PMCSN relied primarily on data collected from Chinese samples. Therefore, its applicability on a global scale requires further validation and cultural adaptation. Second, there is a possibility of self-reporting bias in the survey. Nurses may be influenced by subjective and cultural factors, such as the desire to present favorable results, which could affect the accuracy of the data. Lastly, the study did not explore subjective factors, such as self-efficacy and personal pain experiences, which may influence nurses’ pain management competencies.
Conclusions
This study developed and validated the PMCSN, demonstrating that it is a reliable and scientific tool. The PMCSN can be used to clarify the responsibilities of clinical nurses, identify deficiencies in their pain management practices, and provide a basis for targeted pain management training. Additionally, applying this scale to survey nurses in secondary and tertiary hospitals across China revealed significant disparities between economic regions and hospital levels. To address these imbalances, it is essential to increase resource support and training programs for underdeveloped and lower-tier hospitals. Future research should apply this scale in other countries to validate and adapt it for global use.
Acknowledgements
We sincerely thank every nurse who participated in this study and the experts who provided valuable insights during the consultation on this scale.
Clinical trial number
Not applicable.
Declarations
Ethics approval and consent to participate
This study protocol was approved by the Ethics Committee of the Nursing College of Hangzhou Normal University (2022055). The study was conducted after obtaining written informed consent from the participants. It was also carried out in accordance with the relevant guidelines and regulations of the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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