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Abstract

The COVID-19 pandemic presented significant job engagement challenges for the nursing workforce with increased pressures and workplace changes. Nursing staff shortages have increased nurse anxiety, burnout, fear, low morale and intentions to leave the profession. Nursing care is inherently stressful and at times complex, with stress often due to work inconsistencies, a lack of role clarity, workloads and time pressures. This study explores nurses job engagement, by looking specifically at nurses social-emotional attributes – Occupational Commitment, Self-efficacy Beliefs, Collective Efficacy Beliefs, Resilience, Adaptability and Emotional Labour. This protocol describes a mixed methods convergent parallel study, incorporating a survey questionnaire. The survey comprised of quantitative and qualitative questions, with data collected simultaneously, analysed separately, and integrated in the final analysis step. The survey design used validated social-emotional items, sorting and ranking questions and short answer responses. Analysis will involve individual and comparative analysis of the two participants groups, they are: Australian nurses (n = 86) and New Zealand Nurses (n = 275). Data collection was conducted during two different time periods – Australian pilot (2020-21) and in New Zealand (2022–2023). Recruitment involved the use of professional and personal nursing networks, newsletters and social media communications. Ethics approval was obtained through participating universities in both countries. Results will be disseminated through peer-reviewed publications, conferences, blogs, newsletters and reports to nursing networks. The study will provide valuable insights into nurses’ social-emotional attributes and the role they play in job engagement.

Keywords

mixed methods convergent parallel design survey questionnaire integrating qualitative and quantitative data analysis social-emotional attributes nurse job engagement

Introduction

Nursing is inherently stressful and at times complex, particularly in challenging work conditions (i.e., COVID-19) (Cook et al., 2021; Middleton et al., 2021). The pandemic presented a significant operational challenge for nursing staff (Halcomb et al., 2020; Juan et al., 2020; Labrague & De los Santos, 2020) and a heightened awareness of the psychological impact upon health workers in their ‘frontline’ roles (Abdulah & Mohammed, 2020; Ku et al., 2023; Lenzo et al., 2022; Septianingrum et al., 2021; Teo et al., 2022). This toll continues to impact the job engagement of nursing staff worldwide (Al Sabei et al., 2022; Sirois & Owens, 2021). There are ongoing concerns globally about nurse recruitment and retention (de Vries et al., 2023; World Health Organisation, 2020), with workplace stress for nurses well documented (e.g., Armstrong et al., 2022; Badu et al., 2020; Hu et al., 2020).

Experiences of New Zealand and Australian Nurses

The COVID-19 pandemic led to an increased workload for nurses and heightened stress (Armstrong et al., 2022; Cook et al., 2021), adding to an already existing nursing shortage (Lopez et al., 2022). In New Zealand strict border controls and internal isolation practices prevented community transmission of the COVID-19 virus until August 2021. In 2021 New Zealand established a national strategy, moving from one of elimination to mitigation (Jefferies et al., 2020; Vattiato et al., 2023). At the height of the global pandemic 77.5% of the New Zealand nurses reported moderate levels of stress, 69.4% reported high levels of anxiety, and 67.2% reported poor psychological wellbeing (Slykerman et al., 2022). Despite New Zealand’s stringent public health response, nurses were still negotiating a sense of chaos in workplaces, feelings of uncertainty, fear, and separation from their families (Cook et al., 2021).

Similarly, Australian nurses were experiencing moderate to high levels of depression and anxiety, as well as burnout, with individual attributes and organisational (environmental) resources identified as helpful in managing workplace adversity (Badu et al., 2020). Australian nurses’ levels of anxiety were considerably higher than international counterparts (56.5% vs. 27%) (Fernandez et al., 2021). Stress was linked to staff shortages, problems with a lack of role clarity, increasing complexity of nursing roles, workloads pressures, and job uncertainty (Ahorsu et al., 2021; Lucchini et al., 2023). High anxiety levels were seen to impact nurses’ ability to cope in the workplace (Fernandez et al., 2021; Middleton et al., 2021). An Australian survey of 302 frontline nurses found an increased number of nurses were leaving the profession (Shaffer et al., 2022). Worldwide, COVID-19 compounded existing stressors, leading to an increase in anxiety, burnout, fear, low morale and intentions to leave the profession (e.g., Hu et al., 2020; Labrague & De Los Santos, 2020; Nyashanu et al., 2020). Studies found that fear related to COVID-19 increased nurses’ intention to leave (Khattak et al., 2021; Labrague & de Los Santos, 2021).

Nurse Job Engagement–Social-Emotional Attributes

The COVID-19 pandemic increased nurses’ experience of negative situations which in turn, increased their perception of organisational obstruction and decreased their professional commitment, accelerating job turnover (Juan et al., 2020; Labrague & De los Santos, 2020). Resilience and adaptability along with other social-emotional resources appear to play an important role in nurse retention (Labrague & De los Santos, 2020; Yu et al., 2019). Nurse work engagement is dependent upon factors such as optimism, self-efficacy, work environments and personal learning (Garcia-Sierra et al., 2016). In Australia, nurse managers identified long working hours and increases in anxiety as impacting nurses’ ability to cope and ultimately commit to their organisations (Middleton et al., 2021). While in New Zealand, the less experienced nurses, were seen to be more likely to leave the profession (Shayestehazar et al., 2022).

Personal and work-related factors – staff burnout, absenteeism and turnover can increase anxiety for nurses. Increased levels of stress and anxiety in nurses effect their motivation, ability to function in the workplace, confidence, and capacity to plan, to concentrate and organise (Fisher et al., 2020). Attributes such as adaptability and resilience are seen to reduce job stress and issues of retention (Arrogante & Aparicio-Zaldivar, 2017; Badu et al., 2020). Studies have found that resilience helps nurses to reduce the effects of stress and burnout (Guixia & Hui, 2020; Labrague & De los Santos, 2020; Yu et al., 2019). Nurses’ capacity to manage the inherently stressful and complex nature of nursing practice is essential for job engagement and retention (Delgado et al., 2017, 2021).

While the focus is often on the individual nurse experiences – their work lives, it is also important to consider nurses’ collective efficacy (Considine et al., 2021; Zhao et al., 2021). Nurses work demands, work pressure and emotional labour are consistently related to job stress and are the strongest predictors of nurses’ intention to leave the job (McVicar, 2016). This study explicitly draws on the social and emotional attributes of nurses (i.e., Occupational Commitment, Self-efficacy Beliefs, Collective Efficacy Beliefs, Resilience, Adaptability and Emotional Labour) and considers the role they play in nurses’ job engagement.

Methodology

To achieve this aim, we seek to answer the following research questions (RQ):

(1) What emotions – positive and negative, do nurses most commonly feel when completing work related activities?

(2) What strategies do nurses commonly adopt to support self and others to alleviate negative emotions in the workplace?

(3) What are the relationships between key attributes of wellbeing (Adaptability, Resilience), motivation/confidence (Self-efficacy& Collective Efficacy Beliefs), and occupational commitment to nurses’ engagement to the nursing profession in a disruptive working climate?

(4) What are the relationships between the positive and negative emotions to the social-emotional attributes being investigated.

Research questions 1 and 2 will be answered by the qualitative data obtained from the open-ended and ranking items of the survey while research questions 3 will be answered by structural equation modelling of the self-report of nurses obtained from quantitative items in the survey. Question 4 integrates the results of qualitative and quantitative data analyses.

Study Setting

Case 1 – Australian Nurses (Pilot)

Australian nurses and midwives are the largest clinical workforce in the country with over 450,000 registered with the national regulatory body, and approximately 80 percent of this number are nurses (Department of Health and Aged Care, 2023). Health Workforce Australia (2023) projects a shortage of more than 100,000 nurses by 2025, increasing to 123,000 by 2030. Population ageing and rising morbidity of chronic disease demands an increase in nursing skill and staffing. Shortages will continue to impact the nurse workforce as high numbers of nurses reach retirement age.

Case 2 – New Zealand Nurses

New Zealand Nurses are a diverse culture group – Māori 7.5%, Pacific ethnicity 4%, Asian 25% and European 60% with 30.8% of actively practicing nurses in New Zealand (in 2022) have international qualifications (IQNs). There are concerns about a shortage of nurses to meet the health needs of the country’s population. Inequitable access to health care, particularly New Zealand’s indigenous people (Māori) and other minority groups is a concern alongside a steadily aging population and a growth in chronic health conditions (Health and Disability System, 2020; Nursing Advisory Group, 2022).

Methods

Research Design

This study adopted a mixed methods approach using a convergent parallel design (Creswell & Clark, 2017). Quantitative and qualitative data were collected simultaneously, analysed separately, and integrated in the final analysis (Clark & Ivankova, 2015). This provides a detailed and coherent picture of nurses’ social-emotional experiences. The survey comprises of qualitative and quantitative sections, including demographic information. The next section comprises of validated scales: Occupational Commitment items (Hackett et al., 2001); Self-efficacy items (Riggs & Knight, 1994); Collective Efficacy items (Riggs & Knight, 1994); Resilience and Adaptability items (Wei & Taormina, 2014); and Emotional Labour questions (Patulny, 2015; Patulny, et al., 2015, 2019). Each set of items ends with an open-ended question (see Appendix A).

Occupational Commitment

The first set of scales asks nurse participants for their level of agreement with Occupational Commitment items. Hackett et al., (2001) denotes this as the strength of a person’s motivation to work in a chosen career. This involved a total of 10 items, using a Likert, 5-point scale of: 1 = Strongly disagree, 3 = Undecided, 5 = Strongly agree. Examples include: “If I could do it all over again, I would not choose to work in the nursing profession”, and “I like this vocation too well to give it up again.” In the short-answer question that follows they are asked: “What has impacted your occupational commitment?”

Self-Efficacy Beliefs

The second set of scales asks nurse participants their level of agreement with Self-efficacy Beliefs items (Riggs & Knight, 1994). In their study efficacy beliefs are the ‘judgments that individuals make concerning their ability to do whatever is required to successfully perform their jobs’ (Riggs & Knight, 1994, p. 755). This involving a total of 10 items involved a Likert, 6-point scale of: 1 = Strongly disagree to 6 = strongly agree was used for these items. There was a total of 10 items. Examples include: “I have all the skills needed to perform my job very well.” and “When my performance is poor, it is due to my lack of ability.” Following this the participants were asked: “What has impacted your confidence in your ability to complete aspects of your work?”

Collective Efficacy Beliefs

The third set of scales asks for nurse participant’s level of agreement with collective efficacy beliefs items (Riggs & Knight, 1994). In their study Collective Efficacy refers to members' perceptions on the ability of the group members to perform essential behaviours both collectively and individually. This involved a Likert, 6-point scale of: 1 = Strongly disagree to 6 = strongly agree was used for these items. There was a total of 7 items. Examples include: “This department is poor compared to other departments doing similar work” and “Some members in this department cannot do their jobs well.” Following this the participants were asked: “What impacted your confidence regarding the staff in your unit/ward being able to complete their work successfully?”

Resilience and Adaptability

The fourth set of scales asks for nurse participant’s level of agreement with Resilience and Adaptability constructs (Wei & Taormina, 2014). In their study resilience and adaptability involved multiple components, with personal resilience, being a ‘multifaceted construct that includes a person’s determination and ability to endure, to be adaptable and to recover from adversity’ (Wei & Taormina, 2014, p. 347). This involved a 5-point scale was used 1 = strongly agree to 5 = strongly disagree. There were four parts to this section, with 10 items for each – they included: 1). Determination e.g., “I will not let things stop me from achieving my goals when faced with a difficult situation, I find ways to solve it”; 2). Endurance e.g., “I can stay with something even though there may be trouble”; 3). Adaptability e.g., “I am able to handle new situations”; and 4). Recuperability e.g., “Even if I have been hit hard by something, I quickly recover”. After each part, participants were asked: “What impacted their ability to (1. persist; 2. cope; 3. adapt; and 4. recover) at work lately?

Emotional Labour

The fifth section involves a series of descriptive ranking and of sorting items and short answer responses. The qualitative questions were based on the work of (Patulny, 2015; Patulny, et al., 2015, 2019). Hochschild (1990) explains the term emotional labour as the emotion management performed as part of one’s paid work. The measure explores the nurses’ emotional labour associated with their current job roles. This provides understanding on the nurses’ emotions – positive and negative, and strategies that offer emotional support connected to their work-related activities. The first question involves selecting and then ranking from a list of emotions (positive – e.g., happy, enthusiastic, confident…; negative emotions – e.g., stressed, anxious, frustrated…). They are then asked to sort into work-related and not work-related emotions. The first set of questions focus on positive emotions. An open-ended question asked participants to: ‘Describe the last time you experienced your most common positive (top #1) emotion whilst working.’ Following on from this, participants are asked to identify the main thing they were doing when they experience that top positive emotion (10 choices + other). To finish the positive emotion questions, they were asked about their emotion regulation – (e.g., when feeling this positive emotion, “I worked to make myself feel that way” or…). A final open-ended question asks: “When you try to evoke or make yourself feel this common positive (top #1) emotion, is there something that typically works to help you do this?

A similar series of questions are repeated for the negative emotions looking specifically for emotional regulations and emotional enactments. The final question asks participants about emotional support strategies. Participants are asked: When you experienced this most negative (top #1) emotion and wanted to change it into something else, is there something that typically works to help you do this?

Participants

Recruitment in the Australian case used professional nursing networks, newsletters and social media communications to seek participants involvement. This process is being used in the New Zealand case. Ethics approval was sought and approved in both Australia and in New Zealand through the respective universities. The researchers were conscious of risks to participants, particularly distress during COVID-19, as such, ethical approval provided contact support details on the online consent and participation form. Participant consent is gained prior to accessing the survey. The benefit of this research outweighs potential risks as the research seeks to understand the role of social-emotional attributes for nurses’ job engagement.

In New Zealand, regionally based health services will also be approached through relationships with individual Directors of Nursing to seek permission to use local workforce communication networks. Recruitment via a standard email with a link to the survey will be provided to the organisation and/or individuals to distribute to the nursing workforce.

Data Collection

The survey tool was piloted with Australia nurses (2021-2022). The items used were from validated nursing studies (i.e., Hackett et al., 2001; Patulny, 2015; Patulny, et al., 2015; 2019; Riggs & Knight, 1994; Wei & Taormina, 2014). The Emotional Labour questions were contextualised to suit nurses (e.g., nurses’ jobs roles) and based on emotions literature (e.g., Patulny et al., 2019). The survey was tested with nursing and academic staff (n = 6) at an Australian University. The survey was then adapted for a New Zealand context. This involved member checking with other nurse/academics to ensure cultural and clinical practice were appropriate. Demographic data questions were altered to reflect a New Zealand centric approach. New Zealand data collection began in 2022 and is ongoing. The measures used remained consistent for both sites. Emotional Labour questions were reduced due to the length of the instrument when distributed in New Zealand.

Analytical Strategy

Data from the Qualtrics system will be downloaded into Excel format. Preliminary analysis of the data will identify outliers and missing data. Reponses rates for each data set reported. The quantitative ranking data will be downloaded into excel, with frequency and percentages to provide descriptive data. Short answer questions will be uploaded to NVivo for coding (RQs 1 & 2). Quantitative data will be imputed into SPSSv, and statistical testing will be conducted to report findings related to RQ.3.

Qualitative Data Analysis

Data concerning nurses’ emotions will be analyzed using (Braun, 2006, p. 87) six phases of thematic analysis. The short answer items will be coded initially against their related questions, this allows for inductive reasoning – from specific to general (Conner et al., 2014) and an opportunity to gain an overall sense of the ideas within the data set. The process that follows will involve abductive reasoning useful for making inferences which allows the construction of a claim – i.e., establishing codes and subsequent theme areas (Conner et al., 2014). To do this the researchers will use prefabricated codes drawn from the empirical and theoretical works on emotions (i.e., Grandey & Gabriel, 2015; Grandey & Melloy, 2017; Sutton, 2004). This provides a strong theoretical and empirical basis for code selection and for assigning code descriptions. Member checking will be used to ensure coding reliability. The focus of qualitative data analysis is to identify the emotional labour enacted by nurses while performing their job, and to consider aspects such as emotional regulation and support strategies in the workplace.

The emotion ranking questions involve a different analysis process. Each question will be downloaded into an excel file, response rates and frequency will provide descriptive data to support findings from the short answer questions.

Quantitative Data Analysis

For the quantitative data, we will calculate the reliability coefficients, means, standard deviations, skewness, and kurtosis for the predictor and outcomes variables to further explore the data. SPSSv26 will be used to conduct these preliminary analyses. Following this, the data will be judged as succeeding analysis, with a confirmatory factor analysis (CFA) performed to provide measurement support and to obtain latent correlations among factors. The final analysis will be performed using structural equation modelling using Robust maximum likelihood (MLR) and Mplus version 8 (Muthén et al., 2017). Apart from the demographics of nurses, the countries will be used as covariates. This will provide evidence if their location influences and the associations of the constructs studied. The full information maximum likelihood (FIML) estimator will be used to handle missing data. Conventional fit indices will be used to evaluate the model fit including chi-square statistics, Root Mean Square Error of Approximation (RMSEA; Steiger & Lind, 1980), Standardized Root Mean Square Residual (Jöreskog & Sörbom, 1979), Comparative Fit Index (Bentler, 1990), Tucker Lewis Index (Tucker & Lewis, 1973), and the Weighted Root Mean Square Residual (Muthén & Muthén, 1998–2012) following the conventional cut-off values. The indices used have been proven through simulation with data performing reasonably well with categorical and ordinal model estimation (Beauducel & Herzberg, 2006; Muthén & Muthén, 1998–2012; Yu & Muthén, 2002), and hence will fit well with our ordinal data.

Integrating Qualitative and Quantitative Results

In the final analysis, the results of qualitative and quantitative data analysis will be integrated. Individual and comparative analysis of the two cases will be conducted. Then overlay of the emotional data will be based on the model of the associations of the constructs under investigation. This process requires iterative steps, linking nurses’ emotions to their well-being, motivation, occupational commitment, and engagement. It involves deductive reasoning – reasoning that allows the researchers to arrive at conclusions of certainty (Conner et al., 2014). We will theorise the interactions of nurse emotions with these constructs, which could either be inhibiting or enhancing (RQ4.).

Ethical and Cultural Considerations

Research has a key role in addressing inequalities within health and research in both Australia and New Zealand. In the New Zealand context ethical obligation involved upholding the principles inherent within Te Tiriti o Waitangi/The Treaty of Waitangi. As part of the ethical approval process, all research is expected to demonstrate how it is likely to advance Māori health. By gaining understanding on the social-emotional experiences of nurses it is hoped that more can be done to recruit and retain nurses who are a key element in providing a health service that is accessible to all.

Dissemination

Reciprocity will involve reports to distribution sites, particularly in New Zealand as they were instrumental in increasing response rate and distribution of the questionnaire. In Australia, association aided distribution. As such, opportunities for providing newsletters and blogs will be utilised. Results will be published individually for each site and a comparison publication and academic conference.

Future Directions and Conclusion

Understanding how nurse workforces' experience social-emotional attributes as they engage in their professional roles can help to prepare current nurse workforces to better manage disruptions like COVID-19. In addition, to managing the daily stresses of the nursing job. A clear understanding of nurses’ social-emotional experiences is crucial for retaining and supporting the nurse workforce. Future directions and research will need to focus on nurses’ emotional labour, and the power (benefit) of the collective in maintaining and nurturing nurse job engagement.

Supplemental Material

Supplemental Material - Australian and New Zealand Nurses: Social and Emotional Attributes and Work Engagement

Supplemental Material for Australian and New Zealand Nurses: Social and Emotional Attributes and Work Engagement by Lynn Sheridan, Lynere Wilson, Dennis Alonzo and Rebekkah Middleton in International Journal of Qualitative Methods

Footnotes

Acknowledgements

The authors would like to thank Professor Roger Patulny for support in the design of the Emotional Labour items used in this survey questionnaire. In addition, we would like to thank the nurse participants, the regional health services, individual Directors of Nursing and those nurses and nurse academics involved in data collection.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Lynn Sheridan

Dennis Alonzo

Supplemental Material

Supplemental material for this article is available online.

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