According to statistics from the National Health Commission of the People’s Republic of China, in 2014, there were 212.24 million elders in China, accounting for 15.50% of the total population. As of now, the number of China’s elderly people over 60 years old has reached nearly 250 million. Among them, more than 40 million elderly people are disabled.1 Elderly people, consequent to the growing life expectancy, changing population structure, and improved medical insurance policies, require a greater hospital capacity in terms of size and quality. Meanwhile, nosocomial infections are difficult to prevent.2 Infections which occur in the respiratory tract, urinary tract, skin, and soft tissues remain the focus of geriatric care in hospitals and cause difficulties in hospital management in many countries.3 As elders advance further in age, their immune systems undergo degradation, and this degradation, on some occasions, causes chronic diseases, frequently-occurring diseases, cancer, and immobility, thereby further increasing their chances of developing infections.4 Being a main contributor to patients’ physical deterioration and death,5 infections consume more medical resources and make patients suffer both physically and financially.6
Every link involved in infection prevention and control including disinfection, quarantine, aseptic operation, rational use of antibacterial drugs, and monitoring,7,8 according to the World Health Organization (WHO), is closely related to nursing work. Nurses are the most direct and continuous participants in the execution of nursing procedures, and they are responsible for the execution of every aspect of nursing work. Therefore, they are qualified to make recommendations and ought to be provided with adequate opportunities to contribute to the primary prevention of infections through evidence-based practices.9 There are literature, home and abroad, assessing nurses’ knowledge, attitude, and practice in relation to nosocomial infections.10,11 There is, however, a severe limitation in the amount of literature which delves into nurses’ knowledge and attitude on how to prevent nosocomial infections in elderly patients.12 Besides, no questionnaires are found to evaluate nurses’ performance in this regard. Yet, obtaining this information will help safeguard elderly patients from infections in hospitals. This study, therefore, aims to design a questionnaire assessing nurses’ knowledge, attitude, and practice on nosocomial infections in elderly patients, inspire nursing educators and managers for their targeted key performance indicator (KPI) and, above all, reduce the incidence of nosocomial infections in elderly patients.
To ensure the reliability and validity of the questionnaire, interviewees should be 5–10 times13 the number of questionnaire items. The sample size should be further expanded by 10.00%, given the possibility that there may be invalid responses and given the conduct of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). There are 38 items in the final version of the questionnaire. 700 copies are distributed and 692 (98.86%) collected. Excluding invalid questionnaires, 681 are left with an efficiency rate of 97.29%, which is in line with the designated sample size. The 681 copies are then randomly divided into two groups (
Sample inclusion criteria: (1) Nurses who have worked in the adult clinical department for >1 year and obtained the nursing qualification certificate, and (2) nurses who voluntarily participate in the study.
Sample exclusion criteria: (1) Interns, visiting students, students who have not passed the Standardized Training of Residents exam and those who have not yet obtained professional qualification certificates, and (2) nurses working in such departments as pediatrics, neonatology, obstetrics, and gynecology, without elderly patients.
According to Ajzen’s Health Belief Model14 (Figure 1), nursing staff’s knowledge and beliefs about nosocomial infections of elderly patients are shaped by cognition.15 Nurses should know about basic nursing practice, clinical knowledge, compliance awareness, infection prevention, and control.16 Obtaining knowledge and information about elderly patients constitutes their personal expertise and know-how. In this process, nursing staff’s formed attitude towards the prevention of nosocomial infections and exercise of control over elderly patients helps form the latter’s right infection-prevention behaviors such as good hand hygiene.17
Health belief model.
Based on
From January to April, 2019, two rounds of expert inquiries were conducted via email and on-site investigation. The first round of inquiry focuses on the following aspects: (1) introducing the research question and significance of this study; (2) assessing the importance and feasibility of each item in the questionnaire with a 5-point scale (5 = very important, 1 = least important); (3) experts’ suggestions towards each item; and (4) sociodemographic information associated with the experts (age, gender, professional title, years of service, etc.). After this, the second round of expert inquiry was conducted based on the revised inquiry from the first round. Ultimately, 20 items were deleted and 11 were revised. The final version of the questionnaire consists of 3 dimensions with 38 items: 18 for knowledge, 10 for attitudes, and 10 for practice.
The feasibility of this questionnaire is determined by a pilot study of approximately 30 subjects.18 The points to consider while determining feasibility include time taken to fill the questionnaire, simplicity of the format, clarity of the questions, ease of scoring, and result interpretation. Thirty copies of the questionnaire were distributed following a convenience sampling method to nursing staff for a pilot study with 14–17 min for filling-in. The preliminary survey turned out to be satisfying since all of the mentioned aspects were acceptable to participants.
The questionnaire consists of two parts: participants’ sociodemographic information (department, gender, age, education, professional title, years of service, etc.) and their knowledge, attitude, and practice in relation to the prevention of nosocomial infections in elderly patients. 18 items are designed for assessing nurses’ knowledge in this regard (1 = right answer, 0 = unanswered or incorrect answer). 10 items review nursing staff’s attitude through a Likert-4 scale (4 = very important, 1 = least important). For the rest of the 10 items, participants’ practices are evaluated with “never,” “sometimes,” and “always.” The three options are counted 1, 2, and 3 points, respectively. Notably, there are “reversed items” in this dimension, meaning the higher the score is, the better the nurse’ s practice is towards infection prevention in elderly patients.
In this study, six trained investigators who were evenly grouped into 3 sub-groups, participated in distributing and collecting the questionnaires. When investigators handed out the questionnaires, they explained the purpose and precautions of the investigation to the respondents. After the respondents filled out the questionnaires, they recalled them on the spot, numbered each copy, and excluded invalid ones to ensure that the feasibility and validity of the data obtained from the survey were not adversely affected.
A total of 700 copies of this questionnaire were distributed following a convenience sampling method to clinical nurses simultaneously, and 692 were collected (98.86%). After excluding invalid ones, 681 (97.29%) valid questionnaires were studied. Of all the participants, 334 (49.04%) are from the department of internal medicine and 347 (50.96%) are from the department of surgery.
This study aims to test the reliability and validity of a designed questionnaire that assesses nurses’ knowledge, attitude, and practice on preventing nosocomial infections in elderly patients. To this end, Epidata 3.1 is used to input data and SPSS22.0 and AMOS 22.0 are used to analyze them. The basic findings are described through the constituent ratio. Further, the reliability and validity of the questionnaire are observed through Cronbach’s α coefficient, test–retest reliability, content validity index (CVI), EFA, correlation coefficient and CFA.19
The experts selected in this study come from nine first-class hospitals that are situated across three regions of Anhui Province. They are all experienced in the prevention and control of the nosocomial infection. The basic information pertaining to the experts is presented in Table 1.
Experts’ sociodemographic information.
Basic information | Total number ( |
|
---|---|---|
Number | Proportion (%) | |
<40 | 2 | 13.3 |
40–50 | 9 | 60.0 |
>50 | 4 | 26.7 |
10–20 | 2 | 13.3 |
>20 | 13 | 86.7 |
PhD | 3 | 20.0 |
Master | 4 | 26.7 |
Scholar | 8 | 53.3 |
Professional | 7 | 46.7 |
Associate | 8 | 53.3 |
Clinical nursing | 5 | 33.3 |
Clinical medical echnology | 4 | 26.6 |
Nosocomial infection | 6 | 40.0 |
Experts’ enthusiasm towards the study is shown by how many questionnaires are collected after being distributed.20 In this study, 15 questionnaires are distributed in each round. 15 (100.00%) copies, subsequently, in each round are found to be collected, suggesting a high level of zeal towards this study among all experts who participated in it. The authority of this study is notated by Cr, which is determined by the coefficient of determination (Ca) and experts’ familiarity (Cs) in this field.21 The expert authority coefficient (Cr) is calculated with Cr = (Ca + Cs)/2, as is shown in Table 2.
Expert authority coefficient.
Indicators | Expert inquiry | ||
---|---|---|---|
Ca | Cs | Cr | |
Result | 0.9215 | 0.8895 | 0.9055 |
The questionnaire has high consistency and credibility if the Cronbach’ s α coefficient is >0.7. This study (
Reliability-testing statistics (
Items | Item number | Cronbach’s α coefficient | ICC |
---|---|---|---|
Questionnaire | 38 | 0.851 | 0.877 |
Knowledge | 18 | 0.803 | 0.851 |
Attitude | 10 | 0.886 | 0.899 |
Practice | 10 | 0.774 | 0.801 |
ICC, intraclass correlation coefficient.
The questionnaires are randomly divided into 2 groups, and the EFA (
The Kaiser–Meyer–Olkin (KMO) statistic is 0.718 (>0.7) and Bartlett’s test is <0.001 in this dimension, suggesting adequacy for factor analysis. Varimax with Kaiser normalization is thereafter applied to extract 5 factors from 18 items. The 5 factors are the basic knowledge of nosocomial infection in elderly patients F1 (K1–K5), clinical knowledge F2 (K6–K9), infection prevention F3 (K10–K12), infection control F4 (K13–K15), and compliance awareness F5 (K16–18). According to our calculation, a total of 78.486% variance is explained. The detailed information regarding this is shown in Table 4.
Component matrix* of knowledge.
Items | Component | ||||
---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | |
K1. What’s the definition of nosocomial infection? | 0.872 | ||||
K2. What’s the definition of the outbreak of nosocomial infection? | 0.834 | ||||
K3. How do multiple drug-resistant organisms transmit? | 0.873 | ||||
K4. What’s the definition of occupational exposure? | 0.859 | ||||
K5. What’s the bed space of elderly patients infected with the same pathogen? | 0.735 | ||||
K6. Elderly patients will not develop nosocomial infection when going out for physical checks. | 0.864 | ||||
K7. Elders who cannot take care of themselves are prone to nosocomial infections. | 0.914 | ||||
K8. Elders with diabetes are prone to nosocomial infections. | 0.727 | ||||
K9. Bedridden elders are not prone to hypostatic pneumonia. | 0.909 | ||||
K10. What are the external factors causing nosocomial infections in elders? | 0.975 | ||||
K11. What are measures to prevent elders from nosocomial infections? | 0.962 | ||||
K12. What are elders’ own factors contributing to nosocomial infections. | 0.976 | ||||
K13. What are quarantines measures for seriously-ill elderly patients? | 0.938 | ||||
K14. Elderly patients’ wards should open windows regularly for ventilation. | 0.829 | ||||
K15. Ensuring their skin, mouth, eyes, perineum, and anus are clean can prevent the occurrence of nosocomial infections in elderly patients. | 0.848 | ||||
K16. Elderly patients attach great importance to hygiene and they are not prone to nosocomial infections. | 0.915 | ||||
K17. Elderly patients have deep dependence on disposables. | 0.890 | ||||
K18. Elderly patients understand quick and well, and educating them about nosocomial infection knowledge is effective. | 0.954 | ||||
Eigenvalue | 3.551 | 3.002 | 2.893 | 2.844 | 2.623 |
Total variance explained (%) | 18.691 | 15.798 | 15.228 | 14.966 | 13.803 |
rotation converges in 5 iterations.
The KMO (0.906) and Bartlett’s test (
Component matrix* of attitude.
Items | Component |
---|---|
A1. Is it important to prevent nosocomial infections in elderly patients? | 0.745 |
A2. Is it important to implement a management system to prevent nosocomial infections? | 0.805 |
A3. Is it important to timely report elderly nosocomial infection cases? | 0.779 |
A4. Is the right use of antibacterial drugs important to prevent nosocomial infections in elderly patients? | 0.710 |
A5. Is the right implementation of hand hygiene important to prevent nosocomial infections in elderly patients? | 0.809 |
A6. Is it important to keep elderly patients’ skin, mouth, eyes, perineum, and anus clean? | 0.799 |
A7. Is multidisciplinary cooperation important to prevent nosocomial infections in elderly patients? | 0.720 |
A8. Is knowing hospital infection and preventive measures important to prevent nosocomial infection in elderly patients? | 0.777 |
A9. Is it important to strengthen the knowledge and education of nosocomial infection among elderly patients and their families? | 0.740 |
A10. Is avoiding falling over in elderly patients important for preventing nosocomial infections? | 0.519 |
Eigenvalue | 5.545 |
Total variance explained (%) | 55.455 |
rotation converges in 3 iterations.
In terms of practice, factor analysis is also successfully carried out as the KMO (0.817) and Bartlett’s test (
Component matrix* of practice.
Items | Component | |
---|---|---|
1 | 2 | |
P5 You will wear masks and other protective gears when performing nursing operations on elderly patients. | 0.772 | |
P6 You will encapsulate with single-layered packaging medical wastes of patients suspected of infectious disease or with non-infections disease but under quarantine. | 0.815 | |
P7 You will observe cleaning standard when the ward is occupied with multiple elderly patients. | 0.640 | |
P8 You will arrange patients with open wounds or immune suppression to be placed in the same ward when the ward is insufficient. | 0.808 | |
P9 For elderly patients with respiratory symptoms (cough, runny nose, stuffy nose), visitors and medical staff need to observe respiratory etiquette. | 0.703 | |
P10 If your hand skin is damaged, you will wear single-layered gloves amidst treating and caring for elderly patients, during which you are likely to contact their blood and other body fluid. | 0.698 | |
P1 You will not wash or sanitize your hands after the treatment and care of elderly patients are completed. | 0.813 | |
P2 You will point out their mistakes when your colleagues don’t wash hands before treating patients. | 0.865 | |
P3 You will repeatedly teach hand hygiene and other knowledge to elderly patients and their families. | 0.869 | |
P4 you will attach greater importance to hand hygiene when caring for elderly patients. | 0.859 | |
Eigenvalue | 3.332 | 2.966 |
Total variance explained (%) | 33.318 | 29.656 |
rotation converges in 3 iterations.
The nursing staff’s KMO is 0.762 and Bartlett’s test of the questionnaire is <0.001, and 8 factors are extracted from 38 items using varimax rotation. The 8 factors involve nursing staff’s knowledge, attitude, and practice towards nosocomial infections in elderly patents. Among these factors, factor 1 pertains to attitude, factor 2 to basic knowledge (F1), factor 4 to clinical knowledge (F2), factor 6 to infection prevention (F3), factor 7 to infection control (F4), factor 8 to compliance awareness (F5), factors 5 to standard precaution (F6), and factor 3 to hand hygiene (F7). A total of 69.536% variance is explained in this regard. The dimensional structure constructed is consistent with the premeditated structure. For specific results, see Table 7.
Component matrix* of the questionnaire.
Items | Component | |||||||
---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
A1 | 0.740 | |||||||
A2 | 0.796 | |||||||
A3 | 0.779 | |||||||
A4 | 0.686 | |||||||
A5 | 0.793 | |||||||
A6 | 0.801 | |||||||
A7 | 0.709 | |||||||
A8 | 0.773 | |||||||
A9 | 0.747 | |||||||
A10 | 0.532 | |||||||
K1 | 0.866 | |||||||
K2 | 0.823 | |||||||
K3 | 0.868 | |||||||
K4 | 0.853 | |||||||
K5 | 0.729 | |||||||
P5 | 0.740 | |||||||
P6 | 0.800 | |||||||
P7 | 0.670 | |||||||
P8 | 0.812 | |||||||
P9 | 0.717 | |||||||
P10 | 0.673 | |||||||
K6 | 0.863 | |||||||
K7 | 0.910 | |||||||
K8 | 0.903 | |||||||
K9 | 0.721 | |||||||
P1 | 0.805 | |||||||
P2 | 0.839 | |||||||
P3 | 0.842 | |||||||
P4 | 0.859 | |||||||
K10 | 0.950 | |||||||
K11 | 0.933 | |||||||
K12 | 0.953 | |||||||
K13 | 0.714 | |||||||
K14 | 0.820 | |||||||
K15 | 0.846 | |||||||
K16 | 0.901 | |||||||
K17 | 0.880 | |||||||
K18 | 0.946 | |||||||
Eigenvalue | 5.623 | 3.648 | 3.358 | 3.036 | 3.018 | 2.915 | 2.899 | 2.622 |
Total variance explained (%) | 14.419 | 9.354 | 8.610 | 7.784 | 7.738 | 7.474 | 7.433 | 6.724 |
rotation converges in 6 iterations.
Structural Equation Modeling (SEM) is essentially a path analysis on latent variables.21 Each variable in the path model is measured by multiple indicators to evaluate the effectiveness and reliability of the structure. Taking F1–F5 (knowledge), F6 (attitude), and F7 (practice) as latent variables, 38 items as observed variables, this study, using AMOS 22.0, draws a second-order equation path diagram and compares it to the data of the other group (
Path diagram of nursing staff’s knowledge, attitude, and practice on nosocomial infections (
In terms of goodness of fit, the absolute fit index is adopted for the structural evaluation of knowledge, attitude, and practice. The following is what the study finds: χ2/df < 5, goodness-of-fit index (GFI)>0.8, adjusted goodness-of-fit index (AGFI)>0.9, root mean square error of approximation (RMSEA)<0.08, normed fit index (NFI)>0.8, and comparative fit index (CFI)>0.9. These indicators suggest that the model fits fairly well (Table 8).
GFI indicators for confirmatory factors (
Indicators | χ2/df | GFI | AGFI | CFI | RMSEA |
---|---|---|---|---|---|
Knowledge (CFA) | 3.986 | 0.911 | 0.903 | 0.901 | 0.061 |
Attitude (CFA) | 2.262 | 0.969 | 0.946 | 0.958 | 0.043 |
Practice (CFA) | 3.322 | 0.918 | 0.898 | 0.902 | 0.059 |
Correlation analysis reflects the degree of correlation among dimensions and between each dimension and the questionnaire. It can be seen from that the correlation coefficient among dimensions is 0.09–0.34, which is lower than the coefficient between each dimension and the questionnaire (0.42–0.68). All dimensions have a weak or moderate correlation with each other, while each dimension also has a high correlation with the questionnaire. The correlation coefficient is 0.18–0.48 between knowledge, attitude, and belief, showing a moderate degree of correlation. The correlation coefficient between each dimension and the questionnaire is 0.67–0.69, suggesting a high degree of correlation (Table 9 and Table 10).
Correlation analysis between each variable and the questionnaire (
Item | F1 | F2 | F3 | F4 | F5 | F6 | F7 | Attitude | Score |
---|---|---|---|---|---|---|---|---|---|
Basic knowledge F1 | 1 | 0.093 | 0.094 | 0.144** | 0.143** | 0.188** | 0.054 | 0.106 | 0.451** |
Clinical knowledge F2 | 1 | 0.097 | 0.212** | 0.111 | 0.099 | 0.095 | 0.103 | 0.422** | |
Infection prevetion F3 | 1 | 0.115* | 0.104** | 0.092** | 0.337** | 0.159** | 0.482** | ||
Infection control F4 | 1 | 0.144* | 0.119* | 0.154** | 0.101 | 0.487** | |||
Compliance awareness F5 | 1 | 0.055 | 0.039 | 0.135* | 0.424** | ||||
standard precaution F6 | 1 | 0.182** | 0.116* | 0.489** | |||||
Hand hygiene F7 | 1 | 0.131* | 0.544** | ||||||
Attitude | 1 | 0.686** | |||||||
Score | 1 |
Significantly correlated at the 0.05 level (both sides).
Significantly correlated at the 0.01 level (both sides).
Correlation analysis between each dimension and the questionnaire (
Items | Items | Knowledge | Attitude | Practice | Score |
---|---|---|---|---|---|
Knowledge | Pearson | 1 | 0.177** | 0.475** | 0.683** |
sig | 0.001 | 0.000 | 0.000 | ||
Attitude | Pearson | 1 | 0.249** | 0.686** | |
sig | 0.006 | 0.000 | |||
Practice | Pearson | 1 | 0.673** | ||
sig | 0.000 | ||||
Score | Pearson | 1 |
Significantly correlated at the 0.01 level (both sides).
CVI evaluates whether the designed item can accurately describe the content or theme to be measured.22 Typically, the validity is based on expert comment. CVI is sub-categorized into item-level CVI (I-CVI) and scale-level CVI (S-CVI). I-CVI = the number of the experts scoring 4 or 5 for the importance of the research/total number of the experts. S-CVI = the number of items with a 4 or 5 scores/total number of items.23 In this research, the I-CVI is 0.73–1.00 and the S-CVI is 0.88.
The reliability of this study is observed through Cronbach’s a coefficient and test–retest reliability, and the validity mainly through CVI and factor analysis. The Cronbach’s a coefficient of knowledge, attitude, practice, and the questionnaire surpass 0.7, indicating a good internal consistency. The retest is conducted 3 weeks later and the Cronbach’s α coefficient of the questionnaire exceeds 0.7, showing sound stability and reliability.24 The higher the cumulative variance contribution rate of common factors, the greater the accuracy with which the total variance can be explained.25 The variance contribution rate of the questionnaire and each dimension is between 55.455% and 78.486%, indicating that the variation of variance can be explained effectively. The factor loading of each item in each dimension exceeds 0.4 after factor analysis. The KMO and Bartlett’s test of each dimension and the questionnaire are >0.7; the correlation coefficient among dimensions and between each dimension and the questionnaire >0.3, suggesting a high degree of correlation.
CFI is applied to verify the theoretical structure of the exploratory factors. The following is what the study finds: c2/df <5, GFI>0.8, AGFI>0.9, RMSEA<0.08, NFI>0.8, and CFI>0.9. These indicators corroborate the assumption that the model will fit well.26
To summarize, the designed questionnaire has good reliability and validity, and can reflect nurses’ knowledge, attitude, and practice on preventing and controlling nosocomial infections in elderly patients. Future studies can enlarge the sample size and use the questionnaire after testing its content and structure.
As the risk of nosocomial infections in elderly patients increases, higher demands are placed on nurses in the prevention and control aspects of nursing work. The implementation of these requirements is inseparable from the nurses’ knowledge of nosocomial infections. This questionnaire is constructed by following the Knowledge–Attitude–Practice (KAP) model for measurement. The layout and content of the questionnaire is reasonable and stable. For example, the filling-in time spans 14–17 min. The assessment of nursing staff’s knowledge about nosocomial infections of elderly patients can be identified without taking too much time because the options available are plain and clear. This questionnaire is a practical and convenient evaluation tool that should be accessible to hospital infection managers.
As elders advance further in age, their body functions and immunity decline, in consequence making them targeted groups for nosocomial infections. Nursing staff face a more daunting task and should meet higher requirements when caring for elderly patients.27