The Journal of Continuing Education in Nursing

Original Article 

Self-Efficacy and Research Capacity of Clinical Nurses in China

Wenhui Jiang, PhD, RN; Yuan Yuan, MSN, RN; Lanfang Zhang, MSN, RN

Abstract

Background:

Research capacity is essential to nursing profession development. Literature about the research capacity of Chinese nurses is scarce, especially regarding self-efficacy.

Method:

A cross-sectional design with a cluster random sample of 780 clinical nurses was recruited from five tertiary hospitals in China. Self-reported data were collected with a Demographic Data Form, General Self-Efficacy Scale, and Self-Rating Scale of Nurses' Research Capacity.

Results:

The majority (60.9%) of the nurses' research capacity was at a low level. A positive correlation was found between self-efficacy and research capacity among clinical nurses (r = .287, p < .01). Multiple linear regression analyses indicated that educational level, self-efficacy, support level, and position were predictors that explained 31.9% of the variance of research capacity.

Conclusion:

Chinese nurses' research capacity is insufficient. Educational level, self-efficacy, support level, and position contributed to nurses' research capacity. Nurse administrators should engage in improving Chinese nurses' self-efficacy to facilitate research capacity. It is necessary to develop continuing education to enhance Chinese nurses' research capacity. [J Contin Educ Nurs. 2019;50(11):509–516.]

Abstract

Background:

Research capacity is essential to nursing profession development. Literature about the research capacity of Chinese nurses is scarce, especially regarding self-efficacy.

Method:

A cross-sectional design with a cluster random sample of 780 clinical nurses was recruited from five tertiary hospitals in China. Self-reported data were collected with a Demographic Data Form, General Self-Efficacy Scale, and Self-Rating Scale of Nurses' Research Capacity.

Results:

The majority (60.9%) of the nurses' research capacity was at a low level. A positive correlation was found between self-efficacy and research capacity among clinical nurses (r = .287, p < .01). Multiple linear regression analyses indicated that educational level, self-efficacy, support level, and position were predictors that explained 31.9% of the variance of research capacity.

Conclusion:

Chinese nurses' research capacity is insufficient. Educational level, self-efficacy, support level, and position contributed to nurses' research capacity. Nurse administrators should engage in improving Chinese nurses' self-efficacy to facilitate research capacity. It is necessary to develop continuing education to enhance Chinese nurses' research capacity. [J Contin Educ Nurs. 2019;50(11):509–516.]

Research capacity is critical to the nursing profession and necessary for continuing advancements that promote optimal nursing care (Spoelstra, Wierenga, & Buckwalter, 2018). Clinical nurses, as the main force to perform nursing research, are supposed to have an active role in the research process (Dorgan, 2018). However, previous studies pointed to the continued lack of research capacity among nurses across several countries (Duffy et al., 2015). In China, the number of nurses in the country has increased dramatically and reached 3.80 million in 2018 (People's Health Network, 2018). However, there is a dearth of literature related to the research capacity of Chinese nurses.

Developing nursing research capacity is a challenge facing the profession worldwide (Spoelstra et al., 2018). The primary step toward this goal is to determine the factors related to research capacity among clinical nurses. Previous studies found that the factors influencing research capacity are complex because it involves individual and organizational factors (Segrott, McIvor, & Green, 2006). Most studies reported the factors at all organizational levels, which include the need to implement strategies to foster a research-oriented culture, to identify priorities in existing areas of research, as well as to appraise the relevance of research for funding (Moore, Crozier, & Kite, 2012). However, self-efficacy has been indicated as a significant predictor of individual career performance (Dan et al., 2018), and little information is available regarding the relationship between self-efficacy and research capacity among clinical nurses.

Therefore, the aim of this study was to (a) identify the level of self-efficacy and research capacity, (b) explore the relationship between self-efficacy and research capacity, and (c) find predictors of research capacity among clinical nurses in China.

Background

Self-Efficacy

Self-efficacy, as a key element in Bandura's social cognitive theory, is generally defined as judgment of how well one can execute courses of action required to handle prospective situations (Bandura, 2006), and it can be modified via personal factors and the external environment (Reid, Jones, Hurst, & Anderson, 2018). Self-efficacy is the individual's belief about what he or she can achieve in a given context. These beliefs influence the choices of action, how much effort is expended on an activity, and how long people will persevere when confronting obstacles (Bandura, 2006, 2018). High levels of self-efficacy stimulate greater effort and persistence which in turn promotes positive perceptions of one's own capabilities (Bandura, 2006, 2018). Individuals with high levels of self-efficacy tend to regard difficult tasks as challenges, whereas those who doubt their capabilities tend to consider difficult tasks as threats (Bandura, 2018).

Several studies found that the self-efficacy of nurses in hospitals is insufficient or at a moderate level (Dan et al., 2018; Hu, Yu, Chang, & Lin, 2018; Reid et al., 2018). Self-efficacy has been an important research construct in relation to nurse's professional values, social support, job satisfaction, job burnout, self-regulation, and thinking ability for the past decade (De Simone, Planta, & Cicotto, 2018; Hu et al., 2018; Wang, Tao, Bowers, Brown, & Zhang, 2018). Perceived self-efficacy has also been found to be related to the perceived enhancement of nursing management, nursing practice, and patient care (Chang et al., 2018; Dan et al., 2018; McCabe, McDonald, Connolly, & Lipman, 2019; Wang et al., 2018). In addition, it was reported that self-efficacy was a significant predictor of performances or competences among clinical nurses or nursing students (Bhatti, Alshagawi, & Juhari, 2018; Mohamadirizi, Kohan, Shafei, & Mohamadirizi, 2015). However, there is a paucity of studies on the relationship between self-efficacy and research capacity of Chinese nurses.

Research Capacity

Research capacity can be defined as the ability to conduct, utilize, and sustain research within a professional group (Spoelstra et al., 2018). Research capacity is an emerging area in which nurses can contribute a variety of skills and experiences to the nursing science (Segrott et al., 2006). Currently, research initiated by clinical nurses is becoming increasingly more common (Mitchell, 2012; Priest, Segrott, Green, & Rout, 2007). However, research capacity is typically not among the traditional responsibilities of an entry-level nurse. Many clinical nurses are involved in either direct patient care or administrative aspects of health care. As clinical nurses constitute the majority of the research workforce, supporting them to improve and enhance research capacity has been a global priority (Moore et al., 2012; O'Byrne & Smith, 2011).

Strengthening research capacity is complex because it involves individual and organizational level factors. Regarding the individual level, research capacity is associated with the level of knowledge and skills, research need and interest, and time to engage in research (Cooke & Green, 2000; Dorgan, 2018). Organizationally, the factors involve research support, research infrastructures, research culture, and research training (Edwards, Webber, Mill, Kahwa, & Roelofs, 2009; Moore et al., 2012). Together, individual and organizational research capacities contribute to research productivity. However, there is a deficiency of studies on the predictors of research capacity among Chinese nurses.

Theoretical Framework

The theoretical framework of the study was guided by Bandura's (2018) self-efficacy theory. Self-efficacy is conceived as an individual's perceived confidence and ability to conduct the needed tasks to accomplish desired results. Low self-efficacy is associated with negative feelings such as anxiety, depression, or helplessness, as well as reduced academic performance or low self-motivation (Themanson, Pontifex, Hillman, & McAuley, 2011). Conversely, individuals with high self-efficacy can improve their confidence in overcoming setbacks, set higher career goals, mobilize all useful resources to achieve those goals, and persevere in efforts toward success and achievement (Dan et al., 2018; Federici & Skaalvik, 2012).

Self-efficacy is not dependent on one's abilities; it depends instead on what one believes might be accomplished with one's personal skill. Thus, self-efficacy is often a better predictor of success than prior accomplishments, skills, or knowledge (Bandura, 2018). Such self-efficacy influences individuals' pursued courses of action, effort expended in given endeavors, persistence in the confrontation of obstacles, and resilience to adversity (Genuino, 2018). Therefore, nurses with high self-efficacy may demonstrate awareness and interest of research, persistence in the confrontation of research obstacles, and effort expended in given endeavors. In addition, research capacity may also be determined by other individual and organizational factors, such as educational level, position, and support level (Dorgan, 2018; Duffy et al., 2015). Considering the individual and organizational factors of research capacity, the theoretical framework of the current study is presented in Figure 1.

Theoretical framework.

Figure 1.

Theoretical framework.

Method

Design

This cross-sectional study was a descriptive correlation research design to verify the self-efficacy and research capacity of clinical nurses in China.

Participants

The samples were determined by the cluster random sampling method. A total of 915 RNs were recruited from five tertiary hospitals, which were randomly selected from 14 tertiary hospitals in Xi'an, China. The inclusion criteria were clinical nurses who were RNs; full-time employees for more than 1 year; and willing to participate in the study. Nurses with mental impairments were excluded.

Statistical power analysis was used to determine the sample size of this study. On the basis of Cohen's recommendation, when using multiple linear regression analysis with an estimate of nine independent variables, a minimum of 780 participants would be needed to achieve the small effect size at a statistical power of 80% and a significance level of .05. Assuming an 85% response rate, the sample size was estimated to be 915 participants.

Instruments

Demographic Data Questionnaire. A self-designed questionnaire was used to obtain the participants' demographic data, which included age, gender, marital state, educational level, employment, position, years in a clinical career, and support level.

General Self-Efficacy Scale (GSES). Self-efficacy was measured using the GSES, which consisted of 10 items with four possible responses, ranging from 1 = absolutely incorrect to 4 = absolutely correct (Luszczynska, Scholz, & Schwarzer, 2005; Schwarzer, Mueller, & Greenglass, 1999). Response to all 10 items produces a total score ranging from 10 to 40, with a higher score indicating higher positive self-efficacy (Luszczynska et al., 2005; Schwarzer et al., 1999). The GSES has been widely used in various populations and translated into Chinese and validated among nurses (Villegas Barahona, González García, Sánchez-García, Sánchez Barba, & Galindo-Villardón, 2018). The Chinese version of the GSES has good validity and reliability with the internal consistency of .91 (Zhang & Schwarzer, 1995). Cronbach's alpha value for the overall scale was .88 in this study.

Self-Rating Scale of Nurses' Research Capacity (SSNRC). Research capacity was measured by the SSNRC, which was designed to assess the level of research capacity of nurses (Liu, 2004). There are four dimensions in the scale, which includes basic research knowledge (13 items), statistical analysis (11 items), software operation (seven items), and writing skill (nine items). All items of research capacity were easy to understand. For example, there were nine items related to writing skill on the scale. The questions were listed as “Can you write an abstract?” “Can you write an introduction?” “Can you write a research method?” The scale consists of a 40-item, 4-point Likert-style scale (0 = rarely capable to 3 = completely capable). The total score ranges from 0 to 120, with higher scores indicating the high level of research capacity. The scale demonstrated good content validity and construct validity, with a Cronbach's alpha of .97, ranging from .95 to .97 for the subscales (Liu, 2004). In the current study, the Cronbach's alpha was .98 for the total scale and ranged from .96 to .98 for the subscales.

Data Collection

The study was conducted at five randomly selected tertiary hospitals in Xi'an, China. In the beginning, the researcher asked permission from the directors of the nursing department in each hospital, and then potential participants were approached and screened. After informed consent was obtained upon the nurses' agreement to participate in the study, the questionnaires were distributed to the participants to complete based on their actual situation. It took each participant approximately 20 minutes to complete the questionnaires. The completed questionnaires were double checked by the researchers to ensure the data were complete.

Data Analysis

Data were analyzed using SPSS® version 22.0 statistical software. Descriptive statistics were used to describe the demographic characteristics, self-efficiency, and research capacity of the participants. Pearson correlation coefficient analysis was performed to detect the relationship between the self-efficiency and research capacity of Chinese nurses. A multiple linear regression using a stepwise method was performed to identify the predictors of research capacity. A p value of less than .05 was considered significant for all statistical tests.

Ethical Consideration

This study was approved by the Ethics Board of Xi'an Jiaotong University. The eligible participants were informed in the consent form regarding the study and a written consent form was obtained prior to the study. It was highlighted to the participants that participation in this study was voluntary and their refusal to participate in the study would not lead to any negative consequences. The anonymity and confidentiality of the responses were protected in the study.

Results

Demographic Data

A total of 915 eligible nurses who met the study criteria were approached. Of these, 780 participants consented and completed the qualified questionnaires. The participants' demographic characteristics are summarized in Table 1. The majority of participants (99.2%) were female, nearly half (49.1%) were between 26 and 35 years old, and more than half (57.6%) were married. In terms of education level, most nurses received a college degree (58.3%), followed by a bachelor's degree (37.9%), diploma (3.3%), and master's degree (0.4%). As for the position, most were staff nurses (92.3%) and few were head nurses (7.7%). Among all of the participants, nearly half (51.2%) had been employed at the hospital for less than 5 years, and 69.5% had a strong support level (i.e., perceived overall support is strong).

Demographic Characteristics of Clinical Nurses (N = 780)

Table 1:

Demographic Characteristics of Clinical Nurses (N = 780)

Level of Self-Efficacy

The self-efficacy scores of clinical nurses ranged from 10 to 40, with a mean score of 24.80 ± 6.11. The overall self-efficacy of clinical nurses was at a moderate level.

Level of Research Capacity

The research capacity scores of clinical nurses ranged from 12 to 106, with a mean score of 28.76 ± 23.53. The overall research capacity of clinical nurses was at a low level. As described in Figure 2, the majority of clinical nurses (60.9%) showed a low level of research capacity, and others had moderate (35.9%) and high (3.2%) levels of research capacity. The score of each dimension from the lowest to the highest was statistical analysis (3.82 ± 4.49), software operation (4.98 ± 6.48), writing skill (9.44 ± 7.31), and basic research knowledge (10.46 ± 9.05), respectively (Figure 3).

Level of research capacity of clinical nurses (N = 780).

Figure 2.

Level of research capacity of clinical nurses (N = 780).

The score of each dimension of research capacity in clinical nurses (N = 780).

Figure 3.

The score of each dimension of research capacity in clinical nurses (N = 780).

Relationship Between Self-Efficacy and Research Capacity

Pearson's correlation was performed to examine the relationship between self-efficacy and research capacity. As shown in Table 2, self-efficacy was positively correlated with research capacity (r = .287, p < .01), as well as each dimension of research capacity including software operation (r = .245, p < .01), writing skill (r = 0.235, p < .01), research knowledge (r = .261, p < .01), and statistical analysis (r = .235, p < .01), respectively.

Correlation between Perceived Self-Efficacy and Each Dimension of Research Capacity (N = 780)

Table 2:

Correlation between Perceived Self-Efficacy and Each Dimension of Research Capacity (N = 780)

Predictors of Research Capacity

The influence factors of the research capacity of clinical nurses were education level, position, and support level, as shown in Table 3. Clinical nurses with higher education level (F = 19.009, p < .01), higher position (t = 5.842, p < .01), and stronger support level (F = 7.437, p < .01) reported a high level of research capacity. There were no significant differences in research capacity based on other demographic variables, including age, gender, marital status, employment, and years in a clinical career. Multiple regression analysis indicated that the education level (α = 0.328, p < .01), self-efficacy (α = 0.205, p < .01), support system (α = 0.102, p < .01), and position (α = 0.094, p < .01) entered the equation. The four variables together explained 31.9% of the variance in the research capacity of Chinese clinical nurses (Table 4).

Influencing Factors of Research Capacity of Clinical Nurses (N = 780)

Table 3:

Influencing Factors of Research Capacity of Clinical Nurses (N = 780)

Multiple Regression Analysis for Predictors of Research Capacity Among Clinical Nurses (N = 780)

Table 4:

Multiple Regression Analysis for Predictors of Research Capacity Among Clinical Nurses (N = 780)

Discussion

To the best of the researchers' knowledge, few studies are being conducted to examine the self-efficacy and research capacity of clinical nurses. This study indicated that the research capacity of Chinese nurses is insufficient and that there was a positive relationship between self-efficacy and research capacity. These findings highlight the importance of self-efficacy in increasing nurses' research capacity. Furthermore, multiple regression analysis indicated that educational level, support level, and position were also found to contribute to nurses' research capacity. These results provide information to assist nursing administrators to enhance nurses' research capacity in their organizations. Future research capacity development program for nurses should emphasize not only self-efficacy but also educational level, support level, and position.

Our study found that the majority (60.9%) of Chinese nurses showed a low level of research capacity, and the score of each dimension from the lowest to the highest was statistical analysis, software operation, writing skill, and basic research knowledge, respectively. These findings are consistent with previous studies (Li & Ding, 2013; Wang, Gu, Yu, Li, & Chen, 2015; Wang & Yang, 2013), which reported the majority of Chinese nurses had a low level of research capacity and their statistical analysis and software operation were insufficient. In fact, the lack of research capacity among nurses is a nationwide problem in China (Lyu, Li, Li, & Li, 2016; Peng & Hui, 2011). A Chinese study from 22 provinces investigated 27,335 nurses' research capacity in Chinese tertiary hospitals and found that Chinese nurses' research capacity should be improved (Shang et al., 2018). The principal reason of this situation may contribute to the low education level, which may limit nurses' involvement in research (Cooke & Green, 2000; Wang, Whitehead, & Bayes, 2016; Wong, Chan, & Yeung, 2000). In our study, most nurses received a college degree (58.3%), followed by a bachelor's degree (37.9%), diploma (3.3%), and master's degree (0.4%). Both diplomas and college degrees in China are designed to offer technical skills training but lack preparation of research capacity, and a baccalaureate degree offers a broad nursing foundation with associated sciences involving basic knowledge related to research capacity (Wang et al., 2016). Nurses with master's degrees have systemic research training and demonstrate good or excellent research capacity (Li, Chen, Wang, Kong, & Ying, 2019). Therefore, the research capacity of clinical nurses in China is insufficient, and there is an urgent need to improve and enhance research capacity among nurses to promote the development of nursing science in China.

The results of our study also confirmed that self-efficacy was positively correlated with research capacity (r = .287, p < .01). Although previous studies reported associations between self-efficacy and learning ability, career achievement, and job satisfaction (De Simone et al., 2018), there is a dearth of studies to explore the relationship between self-efficacy and research capacity. It was reported that nurses who possess higher levels of self-efficacy may have stronger research intentions (Wright & Holttum, 2012). However, little information is available regarding the relationship between self-efficacy and research capacity among clinical nurses. The results of the current study indicated that high self-efficacy predicted higher levels of research capacity and that strengthening the self-efficacy of nurses may improve their research capacity.

Furthermore, we examined the demographic variable influencing research capacity and found that educational level, support level, and position were significant contributions to research capacity. Multiple regression analysis also indicated that the education level, self-efficacy, support level, and position together explained 31.9% of the variance in the research capacity of Chinese nurses. It is possible that nurses with a higher educational level usually had an opportunity to receive systemic research training and thus demonstrated a stronger research capacity (Cooke & Green, 2000). The support level from hospitals and families was essential for personal development in the future (Florin, Ehrenberg, Wallin, & Gustavsson, 2012). The head nurse group reported a higher score of research capacity compared with the staff nurse group. This may be because head nurses generally have a better educational background and much more opportunities to be involved in nursing research (Ma, 1993). Therefore, educational level, self-efficacy, support level, and position were the predictors of research capacity of clinical nurses in China.

Limitations

The participants' recruitment from five tertiary hospitals in Xi'an, a northwestern city in China, could limit the generalization of the results. Considering the interest in diversity, future research should include nurses from diverse backgrounds and multiple geographical regions. In addition, self-report measures in the current study might limit the accuracy of responses. It is possible that response bias and the mood of participants might affect the results of this study. Future research is suggested to use multiple measures, as well as peer rating, to assess examined variables.

Conclusion

The self-efficacy and research capacity of Chinese nurses were at a moderate and low level, respectively. A positive correlation was found between self-efficacy and research capacity among Chinese nurses. Educational level, self-efficacy, support level, and position were the predictors of research capacity of clinical nurses in China. These findings emphasize the necessity of improving the research capacity of Chinese nurses and highlight the importance of self-efficacy, as well as educational level, support level, and position in promoting nurses' research capacity. A future career development program for clinical nurses should consider the factors of self-efficacy, educational level, support level, and position.

Implications for Staff Development and Continuing Education

Our results suggest that nursing administrators should adopt targeted strategies focused on predictors of research capacity to increase the research capacity of clinical nurses. Nurse administrators should engage in improving self-efficacy of clinical nurses as a professional means of facilitating research capacity in the clinical setting. Furthermore, the administrators should be aware of the importance of educational level, support level, and position in relation to nurses' research capacity and engage in enhancing these aspects of clinical nurses, especially in advanced education. Furthermore, the development of continuing education should be considered to promote clinical nurses' research capacity in China, and statistical analysis, software operation, writing skill, and basic research knowledge should be emphasized.

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Demographic Characteristics of Clinical Nurses (N = 780)

Characteristicn%
Age (years)
  ≤ 2527535.3
  26 to 3538349.1
  36 to 44759.6
  ≥ 45476
Gender
  Female77499.2
  Male60.8
Marital status
  Single32341.4
  Married44957.6
  Divorced/widowed81
Educational level
  Diploma263.3
  College degree45558.3
  University degree29637.9
  Master's degree30.4
Position
  Staff nurse72092.3
  Head nurse607.7
Employment
  Permanent27835.6
  Contract50264.4
Years in clinical career
  ≤ 539951.2
  6 to 1526533.9
  16 to 257810
  ≥ 26384.9
Support level
  Strong54269.5
  Middle18023.1
  None587.4

Correlation between Perceived Self-Efficacy and Each Dimension of Research Capacity (N = 780)

DimensionSelf-Efficiency

rp
Software operation0.245.008*
Writing skill0.235.009*
Research knowledge0.261.007*
Statistical analysis0.235.009*
Total research capacity0.287.006*

Influencing Factors of Research Capacity of Clinical Nurses (N = 780)

VariableResearch CapacityF/tp
Age (years)0.927.427
  ≤ 2528.89 ± 23.96
  26 to 3527.73 ± 22.95
  36 to 4431.05 ± 24.77
  ≥ 4532.72 ± 23.77
Gender0.015.904
  Male59.17 ± 25.29
  Female28.53 ± 23.38
Marriage status1.719.180
  Single28.41 ± 23.58
  Married29.27 ± 23.53
  Divorced/widowed14.00 ± 18.31
Education level19.009.000**
  Diploma19.88 ± 18.94
  College degree25.01 ± 21.25
  Bachelor's degree34.70 ± 25.22
  Master's degree88.33 ± 8.74
Position5.842.001**
  Staff nurses28.32 ± 23.24
  Head nurses54.83 ± 25.31
Employment0.592.442
  Permanent31.47 ± 23.84
  Contract31.47 ± 23.84
Years in clinical career0.717.542
  ≤ 528.15 ± 23.91
  6 to 1628.42 ± 22.44
  17 to 2532.12 ± 24.92
  ≥ 2630.66 ± 24.26
Support level7.437.001**
  Strong35.33 ± 29.18
  Middle29.81 ± 23.46
  None23.49 ± 20.74

Multiple Regression Analysis for Predictors of Research Capacity Among Clinical Nurses (N = 780)

VariableBSDβtp
Constant term63.52319.1903.310.001**
Education level8.6071.5320.3285.619.000**
Self-efficacy5.3651.6610.2054.277.000**
Support level2.8600.9610.1022.976.003**
Position8.3233.1630.0942.632.009**
Authors

Dr. Jiang is Associate Professor, School of Nursing, Health Science Center, Xi'an Jiaotong University, Ms. Yuan is Lecturer, Xi'an Siyuan University, and Ms. Zhang is Lecturer, School of Nursing, Air Force Medical University, Xi'an, China.

This study was supported by The National Social Science Fund of China.

The authors have disclosed no potential conflicts of interest, financial or otherwise.

Address correspondence to Wenhui Jiang, PhD, RN, Associate Professor, School of Nursing, Health Science Center, Xi'an Jiaotong University, Yanta West Road #76, Xi'an 710061, China; e-mail: jiangwenhui@mail.xjtu.edu.cn.

Received: March 01, 2019
Accepted: June 10, 2019

10.3928/00220124-20191015-07

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