Abstract
Purpose
Effective management of chronic pain in older adults is essential for enhancing physical health, quality of life, and psychological well-being. This study aimed to investigate the knowledge, attitudes, and practices (KAP) of health sciences students regarding chronic pain among older adults.
Materials and Methods
This cross-sectional study was conducted among health sciences students at Fujian Health College from November to December 2023, utilizing a validated questionnaire. A total of 1785 valid questionnaires were enrolled (356 males; mean age: 18.82±0.94 years). A structural equation modeling (SEM) analysis was performed to determine how the KAP dimensions influenced each other.
Results
The mean scores for knowledge, attitudes, and practices were 20.60±3.22 (possible range: 0–32; 64.38% of maximum range), 48.57±8.31 (possible range: 12–60; 80.95% of maximum range), and 28.62±6.67 (possible range: 9–45; 63.60% of maximum range), respectively. The SEM analysis indicated that knowledge directly influenced attitudes (β=0.91, P<0.001) and practices (β=0.14, P=0.002), with an indirect influence on practices (β=0.28, P<0.001). Attitudes directly influenced practices (β=0.30, P<0.001).
Conclusion
The study found that health sciences students exhibited moderate knowledge, a positive attitude, and moderate practices concerning chronic pain in older adults. Targeted educational interventions on this topic are essential in the training curriculum for future healthcare providers.
Keywords: knowledge, attitude, practice, chronic pain, older adults, health sciences students, cross-sectional study
Introduction
Chronic pain, defined as pain for >3 months, is common among adults >65 years old, but the reported prevalence varies widely,1,2 between 30% and 53%.3–5 In the United States, health conditions such as multimorbidity, depressive symptoms, arthritis, and hip fractures are linked to an increased likelihood of experiencing bothersome pain lasting more than one month in older adults.3 Data from the China Health and Aging Tracking Survey (CHARLS) 2018 indicated that 60.0% of adults aged 45 and older experienced physical pain, with the prevalence increasing with age.6 Pain may be categorized based on the underlying biological mechanism. Nociceptive pain is due to chemical, thermal, and/or mechanical damage activating nociceptors and an inflammatory response. Neuropathic pain is caused by damage to or disorders of the central or peripheral nervous system.7 Chronic pain is associated with functional and social limitations, anxiety, depression, sleep impairment, and isolation.1,8
The management of chronic pain in older adults consists of conservative strategies (eg, physical activity, rehabilitation, counseling, and self-management) and, if appropriate, medication-based strategies, and will be based on the type of pain.1 Hence, a proper knowledge of pain among healthcare professionals is crucial to implement effective pain control strategies. Still, it is essential to identify knowledge gaps, misconceptions, and inappropriate practices among healthcare providers to improve chronic pain management. Even though they are not yet practicing, health sciences students will be the future healthcare providers, and determining whether their training curriculum on chronic pain management is appropriate requires studies. Such studies could provide data to improve the teaching and training programs.
The knowledge, attitude, and practice (KAP) methodology is a structured survey method that provides quantitative and qualitative data on the gaps, misunderstandings, and misconceptions toward a specific subject in a specific population. Health sciences students represent a critical force in the future healthcare workforce. Their understanding of chronic pain, especially in older adults, plays a crucial role in delivering high-quality care and ensuring effective pain management. However, health sciences students often lack sufficient knowledge and may have negative attitudes or inadequate skills when dealing with chronic pain in older adults. This deficiency can impair their ability to diagnose and treat pain effectively, leading to inadequate pain relief and negatively affecting the quality of life and mental well-being of older patients. A study conducted among final-semester nursing students in Eritrea revealed insufficient knowledge and poor attitudes toward pain management in general.9 However, there has been limited research exploring the KAP of health sciences students regarding chronic pain in older adults specifically.
Therefore, this study aims to investigate the KAP of health sciences students toward chronic pain in older adults, providing insights to guide educational interventions and improve patient outcomes.
Materials and Methods
Study Design and Participants
This cross-sectional study was conducted between November 2023 and December 2023 at Fujian Health College and enrolled health sciences students. The inclusion criterion was being a full-time student at Fujian Health College. The exclusion criterion was a refusal to participate in this study. This study was approved by the Ethics Committee of Fujian Health College (#RT2023-04), and all participants provided written informed consent.
Questionnaire Introduction
The questionnaire was developed and modified based on available guidelines10–12 and suggestions from three pain domain experts to ensure content validity. A pilot study was conducted with a small sample (33 participants). The participants were requested to identify any difficult-to-understand questions to determine face value. The reliability of the questionnaire was assessed, resulting in an overall Cronbach’s α of 0.900 (or 0.542 for knowledge, 0.959 for attitude, and 0.829 for practice).
The final questionnaire (the items are presented in Tables S1–S5) was in Chinese and encompassed information collection across four dimensions: basic information (13 questions), knowledge dimension (16 items), attitude dimension (12 items), and practice dimension (nine items). In the knowledge dimension, a correct answer (ie, true when the statement was true or false when the statement was false) was awarded 2 points. An incorrect answer (ie, true when the statement was false and vice versa) scores 0 points. An “unsure” answer was warranted 1 point because the participant acknowledged that he/she did not know the answer. In the attitude and practice dimensions, the scores were assigned on a scale from positive to negative, ranging from high (5 points) to low (1 point). The final total scores were within a specified range (minimum-maximum). Items that could not be scored were treated as categorical variables. For each dimension, a cumulative score exceeding 70% is regarded as indicative of adequate knowledge, a positive attitude, and proactive practice. In KAP surveys, we often categorize respondents as having “good”, “adequate”, or “poor” KAP based on their total scores. The cutoff point used to distinguish these categories is not universally standardized and can range from 60% to 80% or higher, depending on the study and context.13,14 The 70% cutoff is frequently used in KAP studies to define a “good” level of knowledge, attitude, or practice. This threshold is often chosen because it is seen as a reasonable indicator that a respondent possesses a substantial majority of the required knowledge or practices, but not necessarily perfect mastery.15,16 Many KAP studies refer to a “modified Bloom’s cutoff”, where scores >80% are considered “good”, 60%-79% as “moderate”, and <60% as “poor”. Some studies simplify this by using 70% as a single cutoff to clearly distinguish between “good” and “poor” KAP, especially when only two categories are needed.13,17 Using a 70% cutoff allows for easier comparison with other studies that have adopted the same threshold, supporting consistency in reporting and interpretation across research.15,16,18 The 70% threshold is often seen as a practical balance—high enough to reflect meaningful knowledge or practice, but not so high as to be unattainable for most respondents.13
The survey was administered online through the electronic questionnaire platform Sojump (https://www.wjx.cn/). The survey link was distributed to the study participants through WeChat and QQ groups, using snowball sampling. Class representatives were added to the QQ communication directory based on the school’s class committee list, and the questionnaire was forwarded to class groups for distribution. The questionnaire was distributed to the overall study department group (which included academic representatives from various classes within the school), and academic representatives further forwarded it to class groups. To maintain data quality and ensure comprehensive responses, a one-submission-per-IP address restriction was enforced, and all questionnaire items were mandatory. The participants were assured of anonymity during the survey process. The fact that answers to all questions are mandatory is made clear in the instructions that the participants must read before completing the questionnaire. The instructions also reassure the participants that no intimate questions are being asked, and that all data are handled anonymously. The research team, comprising three doctors trained as research assistants responsible for questionnaire promotion and distribution, meticulously reviewed all submissions for completeness, internal consistency, and logical coherence. Investigators were trained to grasp the problem’s meaning and the investigation process, enhancing data accuracy and consistency. Questionnaires containing logical errors, incomplete answers, or uniform responses across all items were categorized as invalid.
It needs to be emphasized that chronic pain education was not a formalized, standalone component of all students’ curricula; however, relevant knowledge was incorporated into specific programs and courses, particularly those focused on geriatric care. Nursing students received training in geriatric nursing that included modules on managing chronic pain in older adults, while the Geriatric Management and Health Care program covered foundational aspects of age-related pain conditions. Additionally, anatomy and physiology courses (eg, joint anatomy, neuroanatomy) occasionally addressed chronic pain topics—such as osteoarthritis or neuropathic pain—within broader discussions of age-related musculoskeletal and neurological conditions. Nevertheless, systematic, in-depth instruction on chronic pain pathophysiology or multimodal management was not universally mandated across all disciplines.
Statistical Analysis
Statistical analyses were performed using R 4.3.0, and SEM analyses were performed using SPSS 14.0. Continuous data meeting the normal distribution (according to the Kolmogorov–Smirnov test) were presented as means ± standard deviations (SD) and maximum and minimum values and tested using Student’s t-test (two levels) or ANOVA (more than two levels). Continuous data not meeting the normal distribution were presented as medians (interquartile ranges) and maximum and minimum values and tested using the Mann–Whitney U-test (two levels) or the Kruskal–Wallis H-test (more than two levels). Categorical data were presented as n (%) and analyzed using the chi-squared test. The correlations between the pairs of dimensions were tested using Pearson Correlation Analysis. Pearson correlation coefficient ranges from −1 to +1, with negative values indicating a negative correlation, positive values indicating a positive correlation, and 0 indicating no correlation. In multivariable analysis, 70% of the total score was used as the cutoff value, as recommended by the guidelines for the design of KAP studies.13,19,20 Variables with p<0.05 in the univariable analyses were included in the multivariable logistic regression analysis. Multicollinearity was assessed using the variance inflation factor (VIF) analysis; no multicollinearity was found in this study. A structural equation modeling (SEM) analysis was used to test the relationships among KAP dimensions. The SEM analysis was based on the assumption that knowledge influences attitude, knowledge influences practice, and attitude influences practice. The SEM assumptions were validated: multivariate normality, linearity, no systematic missing data, sufficient sample size, independence of observations, correct model specification, no multicollinearity, unidimensionality of constructs, independence of error terms, interval-level data, and validity and reliability. The model fit indices included root mean square error of approximation (RMSEA), standardized root mean squared residual (SRMR), Tucker-Lewis index (TLI), and comparative fit index (CFI). Two-sided P-values <0.05 were considered statistically significant.
Results
Characteristics of the Participants
A total of 1981 individuals participated, with 1785 valid questionnaires (90.11%) and an effective response rate of 90.11%. Their mean age was 18.82±0.94 years. There were 356 males (19.94%); 64.31% were living in urban areas, 88.46% were following a 3-year course, 59.50% were freshmen, 41.68% were studying nursing, 50.03% had living expenses of 1000–1500, 87.51% had older adults in their family, 58.66% had no family members with chronic pain, and 48.18% never had education on chronic pain (Table 1). Table S1 presents the causes of chronic pain among the family members of the participants who reported family members with chronic pain. The most common (>10%) causes were lumbar disc herniation (42.68%), cervical spondylosis (30.35%), rheumatoid arthritis (22.76%), osteoporosis (22.09%), gout (21.82%), frozen shoulder (20.73%), osteoarthritis (18.56%), and diabetic peripheral neuropathy (11.52%).
Table 1.
Demographic Characteristics and KAP Score
| Variables | n (%) | Knowledge | Attitude | Practice | |||
|---|---|---|---|---|---|---|---|
| Score | pk | Score | pa | Score | pp | ||
| Total | 1785 (100) | 20.60±3.22 | 48.57±8.31 | 28.62±6.67 | |||
| Gender | 0.003 | 0.591 | 0.145 | ||||
| Male | 356 (19.94) | 20.03±3.30 | 48.45±10.61 | 29.40±7.59 | |||
| Female | 1429 (80.06) | 20.74±3.18 | 48.60±7.64 | 28.43±6.41 | |||
| Age | 18.82±0.94 | ||||||
| Residence | 0.910 | 0.251 | 0.053 | ||||
| Rural | 1148 (64.31) | 20.59±3.23 | 48.44±7.96 | 28.44±6.45 | |||
| Urban | 637 (35.69) | 20.62±3.20 | 48.82±8.91 | 28.96±7.04 | |||
| Professional nature | 0.016 | 0.233 | 0.956 | ||||
| 3-year diploma | 1579 (88.46) | 20.63±3.21 | 48.48±8.18 | 28.61±6.57 | |||
| 5-year diploma | 133 (7.45) | 19.98±3.03 | 48.86±10.15 | 28.78±7.66 | |||
| Other | 73 (4.09) | 21.01±3.53 | 50.08±7.37 | 28.70±6.96 | |||
| Grade | 0.285 | <0.001 | 0.298 | ||||
| Freshman | 1062 (59.50) | 20.58±3.10 | 49.12±8.06 | 28.44±6.77 | |||
| Sophomore | 637 (35.69) | 20.68±3.39 | 47.29±8.44 | 28.78±6.32 | |||
| Junior and above | 86 (4.82) | 20.22±3.37 | 51.30±9.09 | 29.63±7.79 | |||
| College | 0.002 | <0.001 | 0.103 | ||||
| Nursing college | 744 (41.68) | 20.83±3.29 | 48.61±7.75 | 28.83±6.44 | |||
| Pharmacy college | 261 (14.62) | 20.64±3.07 | 48.64±8.68 | 28.12±6.84 | |||
| Medical technology department | 7 (0.39) | 22.86±2.27 | 58.14±4.49 | 32.29±7.23 | |||
| Medical department | 358 (20.06) | 20.59±3.06 | 49.26±8.67 | 28.84±6.64 | |||
| Health management department | 415 (23.25) | 20.13±3.27 | 47.72±8.65 | 28.31±6.96 | |||
| Major | 0.004 | 0.011 | 0.014 | ||||
| Nursing | 524 (29.36) | 20.97±3.22 | 48.97±7.60 | 28.41±6.44 | |||
| Geriatric health and management | 93 (5.21) | 20.42±3.68 | 46.28±7.79 | 30.41±5.61 | |||
| Other | 1168 (65.43) | 20.45±3.17 | 48.58±8.63 | 28.57±6.83 | |||
| Living expenses (CNY) | 0.812 | 0.110 | 0.656 | ||||
| <1000 | 328 (18.38) | 20.50±3.25 | 48.31±8.85 | 28.79±6.64 | |||
| 1000-1500 | 893 (50.03) | 20.66±3.17 | 48.42±7.82 | 28.43±6.39 | |||
| 1500-2000 | 470 (26.33) | 20.53±3.25 | 48.74±8.64 | 28.80±6.89 | |||
| >2000 | 94 (5.27) | 20.73±3.37 | 50.15±9.19 | 28.98±8.08 | |||
| Presence of older adults in the family | 0.485 | 0.416 | 0.124 | ||||
| Yes | 1562 (87.51) | 20.60±3.22 | 48.64±8.27 | 28.72±6.64 | |||
| No | 223 (12.49) | 20.61±3.19 | 48.08±8.58 | 27.97±6.86 | |||
| Family members with chronic pain | 0.389 | 0.203 | 0.097 | ||||
| Yes | 738 (41.34) | 20.70±3.09 | 48.86±8.25 | 28.93±6.63 | |||
| No | 1047 (58.66) | 20.53±3.31 | 48.37±8.35 | 28.40±6.69 | |||
| Duration of chronic pain education | <0.001 | <0.001 | <0.001 | ||||
| Never received | 860 (48.18) | 19.99±3.29 | 47.75±8.54 | 26.72±6.75 | |||
| <1 year | 726 (40.67) | 21.10±3.05 | 48.98±7.92 | 29.87±5.91 | |||
| 1-2 years | 121 (6.78) | 21.41±3.25 | 50.18±7.97 | 31.60±5.97 | |||
| >2 years | 78 (4.37) | 21.42±2.79 | 51.32±8.74 | 33.41±6.75 | |||
Notes: Continuous variables are presented as means±standard deviations. Categorical variables are presented as n (%). CNY: Chinese yuan. pk: Comparison of knowledge scores between different demographic characteristics; pa: Comparison of attitude scores between different demographic characteristics; pp: Comparison of practice scores between different demographic characteristics.
Knowledge, Attitude, and Practice Dimensions
The mean knowledge, attitude, and practice scores were 20.60±3.22 (maximum of 32; 64.38%), 48.57±8.31 (maximum of 60; 80.95%), and 28.62±6.67 (maximum of 45; 63.60%), respectively. The knowledge scores varied among health sciences students of different genders, the nature of the diplomas, programs, majors, and chronic pain education (all p<0.05) (Table 1). In the knowledge dimension, the highest correct rate was observed for item K12 (correct in 81.01%; “Chronic pain in the older adults leads to a decline in daily living abilities”). The lowest correct rate was found for item K5 (correct in 42.58%; “Chronic pain can be cured”). (Table S2). The health sciences students with different grades, programs, majors, and chronic pain education had different attitude scores (all p<0.05) (Table 1). The attitude item with the highest score was A1 (80.73% positive; “I believe that chronic pain in older adults may lead to limitations and reductions in their participation in social activities”), while the lowest score was observed for A11 (65.53% positive; “I have confidence in my professional competence”). (Table S3). There were significant differences in practice scores among health sciences students with different majors and chronic pain education (all p<0.05) (Table 1). The practice item with the highest score was P9 (68.63% consistent; “I would recommend the older adult person to seek professional treatment at a hospital”), while the lowest score was seen for P3 (26.61% consistent; “I have participated in team care practice for chronic pain in older adults, such as collaborating with other healthcare professionals”). (Table S4).
Correlations Analysis
The knowledge scores were positively correlated to the attitude (weak correlation, r=0.321, p<0.001) and practice (weak correlation, r=0.180, p<0.001) scores. The attitude scores were positively correlated to the practice scores (weak correlation, r=0.367, p<0.001).
Multivariable Logistic Regression Analysis
Studying in the health management department was negatively associated with knowledge, while <1 year of chronic pain education, 1–2 years of chronic pain education, and >2 years of chronic pain education were positively associated with the knowledge (Table 2). The female gender and sophomore grade were negatively associated with attitude, while knowledge scores, junior and above grade, living expenses >2000, 1–2 years of chronic pain education, and >2 years of chronic pain education were positively associated with attitude (Table 3). The attitude scores, majoring in geriatric health and management, <1 year of chronic pain education, 1–2 years of chronic pain education, and >2 years of chronic pain education were positively associated with practice (Table 4). Tables S1–S5 presents the differences in baseline demographic characteristics between groups with knowledge, attitude, and practice levels ≥ 70% and < 70%.
Table 2.
Univariable and Multivariable Analysis for the Knowledge Dimension
| Variables | Univariable Analysis | Multivariable Analysis | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p | OR | 95% CI | p | |
| Gender | ||||||
| Male | Ref. | |||||
| Female | 1.243 | 0.985–1.569 | 0.067 | |||
| Age | 1.036 | 0.939–1.144 | 0.486 | |||
| Residence | ||||||
| Rural | Ref. | |||||
| Urban | 0.935 | 0.770–1.135 | 0.496 | |||
| Professional nature | ||||||
| 3-year diploma | Ref. | |||||
| 5-year diploma | 0.700 | 0.488–0.998 | 0.0497 | |||
| Other | 1.297 | 0.809–2.106 | 0.285 | |||
| Grade | ||||||
| Freshman | Ref. | |||||
| Sophomore | 1.122 | 0.922–1.367 | 0.251 | |||
| Junior and above | 0.956 | 0.615–1.485 | 0.840 | |||
| College | ||||||
| Nursing college | Ref. | Ref. | ||||
| Pharmacy college | 0.823 | 0.620–1.092 | 0.176 | 0.765 | 0.496–1.177 | 0.224 |
| Medical technology department | 1.950 | 0.417–13.674 | 0.427 | 1.734 | 0.349–12.645 | 0.526 |
| Medical department | 0.853 | 0.662–1.099 | 0.218 | 0.742 | 0.489–1.120 | 0.157 |
| Health management department | 0.633 | 0.497–0.806 | <0.001 | 0.603 | 0.401–0.901 | 0.014 |
| Major | ||||||
| Nursing | Ref. | Ref. | ||||
| Geriatric health and management | 0.896 | 0.576–1.398 | 0.626 | 0.718 | 0.456–1.132 | 0.152 |
| Other | 0.770 | 0.626–0.947 | 0.014 | 1.069 | 0.721–1.592 | 0.740 |
| Living expenses (CNY) | ||||||
| <1000 | Ref. | |||||
| 1000-1500 | 1.052 | 0.817–1.355 | 0.694 | |||
| 1500-2000 | 1.032 | 0.778–1.369 | 0.827 | |||
| >2000 | 1.301 | 0.821–2.076 | 0.264 | |||
| Presence of older adults in the family | ||||||
| Yes | Ref. | |||||
| No | 0.828 | 0.625–1.097 | 0.189 | |||
| Family members with chronic pain | ||||||
| Yes | Ref. | |||||
| No | 0.907 | 0.751–1.096 | 0.313 | |||
| Duration of chronic pain education | ||||||
| Never received | Ref. | Ref. | ||||
| <1 year | 1.957 | 1.602–2.393 | <0.001 | 1.984 | 1.620–2.433 | <0.001 |
| 1-2 years | 2.682 | 1.805–4.043 | <0.001 | 2.677 | 1.792–4.058 | <0.001 |
| >2 years | 1.904 | 1.193–3.071 | 0.007 | 1.899 | 1.187–3.074 | 0.008 |
Abbreviations: CNY, Chinese yuan; OR, odds ratio; CI, confidence interval; Ref., reference category.
Table 3.
Univariable and Multivariable Analysis for Attitude Dimension
| Variables | Univariable Analysis | Multivariable Analysis | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p | OR | 95% CI | p | |
| Knowledge | 1.184 | 1.142–1.229 | <0.001 | 1.193 | 1.149–1.241 | <0.001 |
| Gender | ||||||
| Male | Ref. | Ref. | ||||
| Female | 0.614 | 0.482–0.784 | <0.001 | 0.576 | 0.439–0.758 | <0.001 |
| Age | 0.931 | 0.833–1.038 | 0.206 | |||
| Residence | ||||||
| Rural | Ref. | Ref. | ||||
| Urban | 1.301 | 1.056–1.603 | 0.013 | 1.205 | 0.962–1.508 | 0.104 |
| Professional nature | ||||||
| 3-year diploma | Ref. | Ref. | ||||
| 5-year diploma | 1.456 | 1.003–2.095 | 0.045 | 1.098 | 0.690–1.725 | 0.688 |
| Other | 1.337 | 0.808–2.168 | 0.246 | 0.861 | 0.485–1.493 | 0.602 |
| Grade | ||||||
| Freshman | Ref. | Ref. | ||||
| Sophomore | 0.698 | 0.558–0.869 | 0.001 | 0.624 | 0.489–0.793 | <0.001 |
| Junior and above | 2.036 | 1.306–3.170 | 0.002 | 1.935 | 1.119–3.354 | 0.018 |
| College | ||||||
| Nursing college | Ref. | Ref. | ||||
| Pharmacy college | 1.298 | 0.958–1.752 | 0.089 | 1.130 | 0.809–1.571 | 0.469 |
| Medical technology department | 15.057 | 2.551–285.258 | 0.012 | 8.128 | 1.205–162.116 | 0.064 |
| Medical department | 1.218 | 0.927–1.598 | 0.155 | 1.003 | 0.735–1.364 | 0.983 |
| Health management department | 0.950 | 0.726–1.241 | 0.710 | 0.892 | 0.666–1.191 | 0.443 |
| Major | ||||||
| Nursing | Ref. | |||||
| Geriatric health and management | 0.611 | 0.348–1.027 | 0.073 | |||
| Other | 1.078 | 0.862–1.351 | 0.514 | |||
| Living expenses (CNY) | ||||||
| <1000 | Ref. | Ref. | ||||
| 1000-1500 | 0.865 | 0.656–1.145 | 0.306 | 0.831 | 0.621–1.116 | 0.215 |
| 1500-2000 | 1.084 | 0.800–1.474 | 0.603 | 1.046 | 0.756–1.450 | 0.786 |
| >2000 | 2.217 | 1.387–3.545 | 0.001 | 2.112 | 1.269–3.520 | 0.004 |
| Presence of older adults in the family | ||||||
| Yes | Ref. | |||||
| No | 0.879 | 0.639–1.194 | 0.416 | |||
| Family members with chronic pain | ||||||
| Yes | Ref. | |||||
| No | 0.901 | 0.734–1.106 | 0.316 | |||
| Duration of chronic pain education | ||||||
| Never received | Ref. | Ref. | ||||
| <1 year | 1.222 | 0.983–1.520 | 0.071 | 1.177 | 0.928–1.494 | 0.178 |
| 1-2 years | 1.740 | 1.166–2.576 | 0.006 | 1.607 | 1.040–2.467 | 0.031 |
| >2 years | 2.472 | 1.541–3.953 | <0.001 | 2.089 | 1.256–3.461 | 0.004 |
Abbreviations: CNY, Chinese yuan; OR, odds ratio; CI, confidence interval; Ref., reference category.
Table 4.
Univariable and Multivariable Analysis for Practice Dimension
| Variables | Univariable Analysis | Multivariable Analysis | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p | OR | 95% CI | p | |
| Knowledge | 1.118 | 1.081–1.157 | <0.001 | 1.007 | 0.968–1.048 | 0.740 |
| Attitude | 1.140 | 1.121–1.159 | <0.001 | 1.140 | 1.121–1.160 | <0.001 |
| Gender | ||||||
| Male | Ref. | |||||
| Female | 0.797 | 0.624–1.021 | 0.070 | |||
| Age | 1.049 | 0.943–1.164 | 0.375 | |||
| Residence | ||||||
| Rural | Ref. | |||||
| Urban | 1.216 | 0.987–1.497 | 0.066 | |||
| Professional nature | ||||||
| 3-year diploma | Ref. | |||||
| 5-year diploma | 1.181 | 0.806–1.709 | 0.384 | |||
| Other | 1.132 | 0.676–1.846 | 0.628 | |||
| Grade | ||||||
| Freshman | Ref. | |||||
| Sophomore | 1.012 | 0.817–1.253 | 0.910 | |||
| Junior and above | 1.523 | 0.962–2.382 | 0.068 | |||
| College | ||||||
| Nursing college | Ref. | |||||
| Pharmacy college | 0.831 | 0.606–1.130 | 0.243 | |||
| Medical technology department | 2.852 | 0.624–14.576 | 0.172 | |||
| Medical department | 1.025 | 0.782–1.341 | 0.855 | |||
| Health management department | 0.830 | 0.636–1.079 | 0.167 | |||
| Major | ||||||
| Nursing | Ref. | Ref. | ||||
| Geriatric health and management | 1.768 | 1.119–2.774 | 0.014 | 2.260 | 1.331–3.820 | 0.002 |
| Other | 1.069 | 0.853–1.342 | 0.565 | 1.090 | 0.847–1.405 | 0.506 |
| Living expenses (CNY) | ||||||
| <1000 | Ref. | |||||
| 1000-1500 | 0.871 | 0.663–1.150 | 0.326 | |||
| 1500-2000 | 1.101 | 0.814–1.492 | 0.534 | |||
| >2000 | 1.375 | 0.849–2.209 | 0.191 | |||
| Presence of older adults in the family | ||||||
| Yes | Ref. | |||||
| No | 0.774 | 0.559–1.057 | 0.113 | |||
| Family members with chronic pain | ||||||
| Yes | Ref. | |||||
| No | 0.866 | 0.707–1.062 | 0.167 | |||
| Duration of chronic pain education | ||||||
| Never received | Ref. | Ref. | ||||
| <1 year | 1.938 | 1.552–2.424 | <0.001 | 1.834 | 1.433–2.350 | <0.001 |
| 1-2 years | 3.227 | 2.178–4.778 | <0.001 | 2.759 | 1.771–4.298 | <0.001 |
| >2 years | 6.471 | 3.993–10.684 | <0.001 | 5.623 | 3.271–9.857 | <0.001 |
Abbreviations: CNY, Chinese yuan; OR, odds ratio; CI, confidence interval; Ref., reference category.
Structural Equation Modeling Analysis
The fit of the SEM model yielded good indices demonstrating an acceptable model fit (Table 5), and the results imply that knowledge may influence attitude (β=0.91, p<0.001) and practice (β=0.15, p=0.002), while attitude may influence practice (β=0.31, p<0.001). Knowledge may directly influence attitude (β=0.91, p<0.001) and practice (β=0.14, p=0.002) and may indirectly influence practice (β=0.28, p<0.001), while attitude may directly influence practice (β=0.30, p<0.001) (Table 6 and Figure 1).
Table 5.
Fit Indices of the SEM Analysis
| Indicators | Reference | Results |
|---|---|---|
| RMSEA | <0.08 is good | <0.001 |
| SRMR | <0.08 is good | <0.001 |
| TLI | >0.8 is good | >0.999 |
| CFI | >0.8 is good | >0.999 |
Abbreviations: RMSEA, root mean square error of approximation; SRMR, standardized root mean squared residual; TLI, Tucker-Lewis index; CFI, comparative fit index.
Table 6.
SEM Analysis
| Model Paths | Total Effects | Direct Effect | Indirect Effect | ||||
|---|---|---|---|---|---|---|---|
| β (95% CI) | p | β (95% CI) | p | β (95% CI) | p | ||
| Attitude <- | Knowledge | 0.91 (0.79, 1.02) | <0.001 | 0.91 (0.79, 1.02) | <0.001 | — | — |
| Practice <- | Attitude | 0.30 (0.27, 0.34) | <0.001 | 0.30 (0.27, 0.34) | <0.001 | — | — |
| Knowledge | 0.42 (0.33, 0.52) | <0.001 | 0.14 (0.05, 0.24) | 0.002 | 0.28 (0.23, 0.32) | <0.001 | |
Abbreviation: CI, confidence interval.
Figure 1.
Structural equation modeling analysis. Assumption: knowledge (Ksum) influences attitude (Asum), knowledge (Ksum) influences practice (Psum), and attitude (Asum) influences practice (Psum). The measured variables are drawn in rectangular shapes. The circles with the caption starting with “ε” indicate measurement errors in each observed variable. Solid straight lines refer to direct effects, while curved solid lines represent indirect effects. Each number on the arrows indicates an individual standardized regression coefficient of each dependency.
Discussion
The results suggest that health sciences students have moderate knowledge, positive attitudes, and moderate practice toward chronic pain in older adults. Education about chronic pain in older adults should be provided in the training curriculum of future healthcare providers.
Few studies are available on the KAP of pain management for older adults. Liyew et al21 reported that nurses in Ethiopia had good knowledge and a lower level of attitude toward pain management, but the study did not examine pain management in older adults, and the nurses were working at a hospital. Gorawara-Bhat et al22 reported that nurses perceived several challenges in assessing older patients’ pain in the emergency department. A moderate KAP was reported in Irish and Jordanian nurses toward pain management in older adults.23 Still, those studies were performed on participants who completed their training and had work experience. In addition, the participants were working in hospitals and attended to inpatients or patients visiting the emergency department. Many healthcare providers work in the community, and examining the KAP of students who might work in the community is relevant to determining their needs for education about pain management in older adults. One study revealed that final-semester nursing students in Eritrea had insufficient knowledge and attitude toward pain management in general,9 and no data were available for China.
The present study revealed that the health sciences students at one institution in China had a need for education about the etiology of chronic pain, the impact of chronic pain on the central nervous system, the possibility of curing chronic pain, the factors influencing chronic pain, and the impact of chronic pain. The participants who had received education about chronic pain in older adults showed higher scores in all three KAP dimensions. It also shows that the students who received education specifically on chronic pain had better practices than those who did not receive education, highlighting the need for and importance of education. Although the participants were at different progression levels in their training, and chronic pain education might occur later in the training curriculum, about half of the participants had received no education about chronic pain in older adults. Of course, having received training on chronic pain should lead to better practice related to chronic pain. In addition, majoring in geriatric health and management should also lead to better practice since chronic pain management is central in geriatrics. A lower knowledge score was observed for those studying health management, probably because patient care was not the focus of their studies. A lower attitude was observed in sophomores, but a higher attitude was seen in juniors, which could be related to the level of training. Higher living expenses were also associated with higher attitude scores. A major in geriatric health management was associated with better practice toward chronic pain in older adults, probably because of the training. Considering that knowledge influences attitude and practice and that attitude influences practice, efforts should be taken to improve knowledge in all students, which should translate into better practice24,25 and better patient outcomes.26,27
Hence, the teaching and training curriculum should be modified based on the results of the present KAP study to optimize the KAP toward chronic pain and its management in older Chinese adults. Such training could be based on the latest teaching techniques in health education. Future studies should design and evaluate such teaching and training based on the results of the present study. Longitudinal studies could also provide data on how KAP could evolve with teaching and training.
This study had limitations. It was performed at a single institution, resulting in a relatively small sample size (when considering the number of health sciences students in China), limiting generalizability. The participants were limited to a single geographical area, also limiting generalizability. The study was cross-sectional, and causality could not be analyzed. A SEM analysis was used as a surrogate for causality, but the results should be interpreted with caution since SEM analyses may imply causality, but it remains statistically inferred based on predetermined hypotheses.28–30 All data were self-reported. As such, all KAP analyses are at risk for the social desirability bias, which entails that some participants could be tempted to answer what they know they should think or do instead of what they are really thinking or doing.31,32
Conclusions
Health sciences students demonstrate a moderate level of knowledge, a positive attitude, and moderate practices concerning chronic pain in older adults. It is recommended that targeted educational interventions be integrated into the training curriculum to improve both knowledge and attitudes regarding chronic pain among future healthcare providers. Key points regarding recognizing and diagnosing chronic pain, managing chronic pain, and fostering realistic expectations regarding chronic pain should be emphasized.
Acknowledgments
The authors acknowledge the help of the Learning Group of Fujian Health College and teachers from the Department of Anatomy.
Funding Statement
This work was supported by the Fujian Health College Intramural Research Program (Grant No. MWY2022-1-02) to Zhen Shi.
Abbreviations
KAP, Knowledge, attitudes, and practices; SD, Standard deviations.
Data Sharing Statement
All data generated or analyzed during this study are included in this published article. Original data can be made available upon reasonable request to the corresponding author.
Ethics Approval and Informed Consent
This work has been carried out in accordance with the Declaration of Helsinki (2000) of the World Medical Association. This study was approved by the Ethics Committee of Fujian Health College (#RT2023-04), and all participants provided written informed consent.
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflict of interest in this work.
References
- 1.Reid MC, Eccleston C, Pillemer K. Management of chronic pain in older adults. BMJ. 2015;350(feb13 2):h532. doi: 10.1136/bmj.h532 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Abdulla A, Adams N, Bone M, et al. Guidance on the management of pain in older people. Age Ageing. 2013;42 Suppl 1:i1–57. doi: 10.1093/ageing/afs200 [DOI] [PubMed] [Google Scholar]
- 3.Patel KV, Guralnik JM, Dansie EJ, Turk DC. Prevalence and impact of pain among older adults in the United States: findings from the 2011 national health and aging trends study. Pain. 2013;154(12):2649–2657. doi: 10.1016/j.pain.2013.07.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Larsson C, Hansson EE, Sundquist K, Jakobsson U. Chronic pain in older adults: prevalence, incidence, and risk factors. Scand J Rheumatol. 2017;46(4):317–325. doi: 10.1080/03009742.2016.1218543 [DOI] [PubMed] [Google Scholar]
- 5.Henderson JV, Harrison CM, Britt HC, Bayram CF, Miller GC. Prevalence, causes, severity, impact, and management of chronic pain in Australian general practice patients. Pain Med. 2013;14(9):1346–1361. doi: 10.1111/pme.12195 [DOI] [PubMed] [Google Scholar]
- 6.Ai Z, Tang C, Peng P, Wen X, Tang S. Prevalence and influencing factors of chronic pain in middle-aged and older adults in China: results of a nationally representative survey. Front Public Health. 2023;11:1110216. doi: 10.3389/fpubh.2023.1110216 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Reardon DP, Anger KE, Szumita PM. Pathophysiology, assessment, and management of pain in critically ill adults. Am J Health Syst Pharm. 2015;72(18):1531–1543. doi: 10.2146/ajhp140541 [DOI] [PubMed] [Google Scholar]
- 8.Makris UE, Abrams RC, Gurland B, Reid MC. Management of persistent pain in the older patient: a clinical review. JAMA. 2014;312(8):825–836. doi: 10.1001/jama.2014.9405 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Okubai T, Fessehaye S, Gebray AY, Kahsay DT. Final-semester nursing studentś knowledge and attitude regarding pain management in resources limited setting. Intl J Afr Nurs Sci. 2023;18:100542. doi: 10.1016/j.ijans.2023.100542 [DOI] [Google Scholar]
- 10.American Society of Anesthesiologists Task Force on Chronic Pain Management. Practice guidelines for chronic pain management: an updated report by the American society of anesthesiologists task force on chronic pain management and the American society of regional anesthesia and pain medicine. Anesthesiology. 2010;112(4):810–833. doi: 10.1097/ALN.0b013e3181c43103 [DOI] [PubMed] [Google Scholar]
- 11.Bernardo S, Lukyanova V. Chronic pain management guidelines: time for review. AANA J. 2022;90(3):169–170. PMID: 35604858. [PubMed] [Google Scholar]
- 12.Zambelli Z, Halstead EJ, Iles R, Fidalgo AR, Dimitriou D. The 2021 NICE guidelines for assessment and management of chronic pain: a cross-sectional study mapping against a sample of 1000* in the community. Br J Pain. 2022;16(4):439–449. doi: 10.1177/20494637221083837 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Kaliyaperumal K. Guideline for Conducting a Knowledge, Attitude and Practice (KAP) Study. AECS Illumination. 2004;4:7–9. Available from: https://v2020eresource.org/content/files/guideline_kap_jan_mar04.pdf. Accessed August 20, 2025. [Google Scholar]
- 14.Okello G, Izudi J, Teguzirigwa S, Kakinda A, Van Hal G. Findings of a cross-sectional survey on knowledge, attitudes, and practices about COVID-19 in Uganda: implications for public health prevention and control measures. Biomed Res Int. 2020;2020(1):5917378. doi: 10.1155/2020/5917378 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Lee F, Suryohusodo AA. Knowledge, attitude, and practice assessment toward COVID-19 among communities in East Nusa Tenggara, Indonesia: a cross-sectional study. Front Public Health. 2022;10:957630. doi: 10.3389/fpubh.2022.957630 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Cheng C, Zhang W, Jin B, Yang S, Lu H, Ren Y. Knowledge, attitude, and practice (KAP) towards pulmonary nodules among Chinese adults: a mediation analysis. Sci Rep. 2024;14(1):28950. doi: 10.1038/s41598-024-79657-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Wang L, Abualfoul M, Oduor H, et al. A cross-sectional study of knowledge, attitude, and practice toward COVID-19 in solid organ transplant recipients at a transplant center in the United States. Front Public Health. 2022;10:880774. doi: 10.3389/fpubh.2022.880774 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Hong E, Mao J, Ke Z, Tao W. Knowledge, attitudes and practices towards community-acquired pneumonia and COVID-19 among general population: a cross-sectional study. Antimicrob Resist Infect Control. 2024;13(1):6. doi: 10.1186/s13756-023-01361-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Andrade C, Menon V, Ameen S, Kumar Praharaj S. Designing and conducting knowledge, attitude, and practice surveys in psychiatry: practical guidance. Indian J Psychol Med. 2020;42(5):478–481. doi: 10.1177/0253717620946111 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.World Health Organization. Advocacy, communication and social mobilization for TB control: a guide to developing knowledge, attitude and practice surveys. 2008. Available from: https://iris.who.int/handle/10665/43790. Accessed June 12, 2012.
- 21.Liyew B, Dejen Tilahun A, Habtie Bayu N, Kassew T. Knowledge and attitude towards pain management among nurses working at university of gondar comprehensive specialized hospital, Northwest Ethiopia. Pain Res Manag. 2020;2020:6036575. doi: 10.1155/2020/6036575 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Gorawara-Bhat R, Wong A, Dale W, Hogan T. Nurses’ perceptions of pain management for older-patients in the emergency department: a qualitative study. Patient Educ Couns. 2017;100(2):231–241. doi: 10.1016/j.pec.2016.08.019 [DOI] [PubMed] [Google Scholar]
- 23.Al Omari D, Alhabahbeh A, Subih M, Aljabery A. Pain management in the older adult: the relationship between nurses’ knowledge, attitudes and nurses’ practice in Ireland and Jordan. Appl Nurs Res. 2021;57:151388. doi: 10.1016/j.apnr.2020.151388 [DOI] [PubMed] [Google Scholar]
- 24.Alzghoul BI, Abdullah NA. Pain management practices by nurses: an application of the knowledge, attitude and practices (KAP) model. Glob J Health Sci. 2015;8(6):154–160. doi: 10.5539/gjhs.v8n6p154 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Nuseir K, Kassab M, Almomani B. Healthcare providers’ knowledge and current practice of pain assessment and management: how much progress have we made? Pain Res Manag. 2016;2016:8432973. doi: 10.1155/2016/8432973 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Glowacki D. Effective pain management and improvements in patients’ outcomes and satisfaction. Crit Care Nurse. 2015;35(3):33–41. quiz 43. doi: 10.4037/ccn2015440 [DOI] [PubMed] [Google Scholar]
- 27.Schroeder DL, Hoffman LA, Fioravanti M, Medley DP, Zullo TG, Tuite PK. Enhancing nurses’ pain assessment to improve patient satisfaction. Orthop Nurs. 2016;35(2):108–117. quiz 118-109. doi: 10.1097/NOR.0000000000000226 [DOI] [PubMed] [Google Scholar]
- 28.Beran TN, Violato C. Structural equation modeling in medical research: a primer. BMC Res Notes. 2010;3(1):267. doi: 10.1186/1756-0500-3-267 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Fan Y, Chen J, Shirkey G. Applications of structural equation modeling (SEM) in ecological studies: an updated review. Ecol Process. 2016;5(1):19. doi: 10.1186/s13717-016-0063-3 [DOI] [Google Scholar]
- 30.Kline RB. Principles and Practice of Structural Equation Modeling. Fifth Edition ed. New York: The Guilford Press; 2023. [Google Scholar]
- 31.Bergen N, Labonte R. “Everything is perfect, and we have no problems”: Detecting and limiting social desirability bias in qualitative research. Qual Health Res. 2020;30(5):783–792. doi: 10.1177/1049732319889354 [DOI] [PubMed] [Google Scholar]
- 32.Latkin CA, Edwards C, Davey-Rothwell MA, Tobin KE. The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland. Addict Behav. 2017;73:133–136. doi: 10.1016/j.addbeh.2017.05.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All data generated or analyzed during this study are included in this published article. Original data can be made available upon reasonable request to the corresponding author.