The performance management process should be a joint effort of the organisation and the nurses (Francis, Bin Ahmad & Binti Abdullah 2021). Not all nurses, unfortunately, understand what the assessment process entails (Katsinde, Tsododo & Katsinde 2021). If the process is poorly managed, nurses will be dissatisfied, and there will be high staff turnover. Challenges in the performance management systems are highlighted in the steps of the process, as it is indicated that managers often fail to observe their subordinates’ performance, provide delayed and unsupportive feedback, and do not appropriately address incentive systems for high achievers, while nurses also express dissatisfaction with the reward schemes linked to their performance appraisals (Francis et al. 2021; Homauni, Mosadeghrad & Jaafaripooyan 2021; Madlabana & Petersen 2020).

The researcher observed that in the designated hospital, professional nurses often complained about the steps in the performance interview, poor feedback afterwards and lack of incentives for their outcomes reached. It was thus unclear what the best experiences of professional nurses were on the performance process in the hospital.

According to Polit and Beck (2022), assumptions derived from a worldview or paradigm are concepts scientists accept as the truth based on logic or reason. There is no need for scientific validation of the assumption. The constructivist paradigm’s assumptions were used in this research. The constructivist paradigm presupposes a subjectivist epistemology (knower and respondent co-create understandings), a relativist ontology (there are multiple realities) and a naturalistic (in the natural world) set of methodological procedures (Denzin & Lincoln 2003).

Concerns regarding the nature of reality are ontological assumptions (Klenke, Martin & Wallace 2015). The constructivist paradigm’s ontological premise highlighted the variety of perspectives on performance management. The researcher assumed that participants’ perceptions of performance management varied and that there were multiple realities (Denzin & Lincoln 2003).

The epistemological premise of the constructivist paradigm is that the participants and the researcher engage in an interactive process in which each influences the other (Mertens 2023). During focus group interviews, the participants and the researcher co-created the data.

The procedures of gathering and analysing data are determined by the methodological assumptions of research paradigms (Polit & Beck 2022). Data were collected using focus group discussions. The data analysis employed a thematic approach, forming themes and subthemes based on similar codes. The participants were free to explore and explain the ideal performance management process in a natural setting.

The 5-D Appreciative Inquiry (AI) model (refer to Figure 1), developed by Cooperrider and Srivasta (1987), was utilised as a theoretical framework to guide the data collection process and during the data analysis stage. LoBiondo-Wood and Haber (2018) describe a theoretical framework as a structure that creates a path for conducting the research. Merriel et al. (2022:1) describe AI as an encouraging change intervention organisations can use to enhance organisational culture. It encourages organisations to concentrate on the positive and investigate the best of ‘what is’ before considering ‘what could be’, opting for ‘what should be’, and experiencing ‘what can be’. It is an opportunity-based approach that enables managers and researchers to focus on what is right instead of identifying what is wrong in an institution. As Armstrong, Holmes and Henning (2020) indicated, AI is a legitimate way to deal with helping people and systems move from a deficit-based paradigm to a strength-based perspective.

A descriptive, qualitative design using AI was adopted as the research design uses the principles of qualitative research as a positive framework to engage participants in transforming their environment (Reed 2007).

The study was conducted in a private hospital in Gauteng, South Africa, with a bed capacity of 141 patients. The hospital renders medical, surgical, obstetrical, neonatal, paediatric, critical and emergency care services.

At the time of the study, all the permanent professional nurses of the designated hospital formed part of the bi-annual, compulsory performance appraisal process. The study population comprised 56 professional nurses employed at the designated private hospital. Twenty-five professional nurses were selected purposively as they could provide rich data in line with the research questions (Grove & Gray 2019). They met the inclusion criteria requiring all potential participants to be professional nurses who were permanently employed at the hospital and had participated in at least one performance management cycle.

Focus group discussions were utilised in this study, as they allowed the participants to describe their experiences with one another. Participants interviewed in a focus group usually share similar roles and experiences (Holloway 2016). The researcher used focus group discussions to obtain the perspectives of a diverse group of professional nurses who participated in a performance management cycle at the designated hospital. The focus group discussion helped the participants clarify their views in a way that was less likely to occur in individual interviews (Grove & Gray 2019). It allowed professional nurses of different backgrounds to share their experiences. Focus group discussions took place during ‘off duty’ times and were arranged between the researcher and participants to ensure services rendered were not affected. Each focus group comprised five professional nurses, and the focus group discussions were conducted over 3 weeks. The focus group discussions were conducted in a private boardroom assigned to the researcher by the hospital management to ensure participant privacy. Participants were requested to keep the information shared during the focus group discussions confidential. Grove and Gray (2019) stated that confidentiality and comfort may result in richer dialogue and data. Each focus group discussion lasted between 60 min and 80 min.

The interview guide was drawn from the 5-D AI model concerning the performance management of professional nurses. The following questions guided the interview process; ‘What does performance management mean to you?’ (define). ‘What are the best parts of the current performance management process that you value?’ (discovery). ‘What are your wishes for the performance management process in the hospital?’ (dream). ‘What are the best steps to ensure the ideal performance management process?’ (design). ‘How can these steps ensure that your vision of the performance management process is sustainable?’ (destiny). The researcher used probing during the focus group discussions to ensure that rich data were obtained from the participants (Robinson 2023).

The researcher facilitated the focus group discussions with the assistance of a research assistant. The research assistant captured the information that could not be audio recorded in field notes, that is, nonverbal communication and seating of the participants. During the first meeting with the participants, the researcher described the study, explained AI and asked if they were interested in participating. They then completed the information and consent document. The researcher asked the questions, and the participants described their positive personal experiences with the current performance management process. The insights from the discovery phase helped the participants envision a desired future and co-create and share ideas about potential ways to bring what was envisioned into being. During the dream phase, all participants were asked to discuss their ideal dream for a performance management process. During the design and destiny phases, the participants were asked to discuss the actions to be implemented to meet their desired expectations regarding the performance management of professional nurses.

The focus group discussions were audio-recorded with the participant’s permission. Audio recordings enable the researchers to revisit the data collected during the transcription (Osborne & Grant-Smith 2021). The researcher continued discussions with participants over the 3 weeks of data collection until data saturation was reached (LoBiondo-Wood & Haber 2018).

The 5-D model of AI guided the deductive data analysis process; however, all the other data that did not fit the AI model for analysis were analysed inductively. Five stages of data analysis were followed:

Step one – familiarisation: The audio recordings and field notes of the focus group discussions were transcribed. The transcripts were checked for accuracy by reading each focus group discussion transcript while listening to the audio recording. Anonymising of participants was ensured in that their names and places were not identifiable to maintain confidentiality (Gibbs & Flick 2018). Participants were then referred to as Participant 1, Focus Group Discussion 1, Participant 2 and Focus Group Discussion 2. Step two – identifying a thematic framework: Once the researcher was familiar with the data, themes were developed. Step three – coding: The researcher coded the transcripts using in-vivo codes according to the domains of the AI model (deductive analysis) and did thematic coding (inductive analysis) to analyse data that could not be analysed using the 5-D AI model. Stage four – mapping: The researcher assembled similar codes and created subcategories. Alignment of similar subcategories was then carried out to form categories. Stage five – interpretation: The researcher summarised the coded data, excerpts from the transcripts and information related to the research question and presented it as the study findings.

The Lincoln and Guba (1985) framework, as described by Polit and Beck (2022), was utilised to ensure trustworthiness. The credibility of the findings was ensured through data saturation (Ahmed 2024). The research assistant took field notes to capture non-verbal cues and ensure that all pertinent data were analysed. To ensure confirmability, the researcher, through ongoing reflection, verified that the findings were the voice of the participants and not his own experiences influencing the participants. Dependability was ensured when data were analysed meticulously and consistently, and the methods used were clearly described. The researcher fully described the context of the study to qualify readers to weigh the applicability and transferability of the findings to other contexts.

All study participants gave informed consent voluntarily. Ethical clearance was obtained from respective research ethics committees: the private hospital group (CRIP-10052023/15) and the University of Pretoria (71/2023). Permission to collect data from the participants was sought from the private hospital group and the management of the designated hospital. All procedures followed the ethical principles as informed by the Belmont report (LoBiondo-Wood & Haber 2018). The researcher ensured that the participants’ rights to freedom from harm and discomfort were respected. They were not subjected to harm, and their right to protection from exploitation was ensured. The information provided was not used against them, and their human dignity was respected. The participants were allowed to withdraw at any time without negative consequences. Their right to full disclosure was protected, and the research process was discussed thoroughly to enable them to make informed decisions. The researcher ensured that the participants were treated fairly and that their privacy rights were respected. Confidentiality was ensured by using pseudonyms. Data were stored safely on a password-protected computer. No data were shared in reports that may have led to them being associated with the data.

There were 25 professional nurses in total. Twenty-one had a diploma in nursing, and four had a 4-year bachelor’s degree in different fields of nursing. Five participants had between 1 and 10 years of experience, and 20 had 11 or more years of experience.

Five themes and 13 subcategories emerged from data analysis.

The theme relates to the ‘define phase’ of the 5-D AI Model. The three sub-categories under this theme include setting goals and rating performance, evaluating the achievement of goals and enabling professional nurses’ development. These subcategories addressed how participants understood and described the definition of performance management.

This theme relates to the ‘discovery phase’ of the 5-D AI model and addresses the aspects of performance management that the participants appreciated. These aspects refer to the positive influence of unit managers, the incentives the participants received, how the managers treated them and how developing skills, training and leadership positions motivated the participants to perform well.

This theme focusses on the participants’ dreams of what ideal performance management should look like. The participants focussed mainly on what can make the process run seamlessly. Most participants reported a fair and equitable performance management process. However, a few incidents relating to a negative work environment, mostly criticism, were noted as barriers to effective communication. They mentioned the need for mutual respect between the managers and professional nurses and a fair performance management process to prevent bias and favouritism. Participants voiced the need for the managers to lead by example and be transparent in assessing and rewarding performance.

This theme relates to the ‘design phase’ of the 5-D AI Model. It focusses on interventions that should be implemented to ensure that the process becomes feasible. It comprises the following subcategories: training for performance management, cooperative development of tools for performance management and implementing positive change.

This theme addresses the ‘deliver phase’ of the 5-D AI Model and, therefore, focusses on positive solutions to ensure that the performance management process remains sustainable. Performance management should be the responsibility of all stakeholders of different disciplines in the designated hospital. The three subcategories that emerged from the data include stakeholder involvement, effective communication and enabling relationships.

Recommendations are based on the findings of the study. The following recommendations are for the practice: Management should recognise professional nurses’ role in quality patient care and ensure a sound reward system by providing regular feedback, fostering a supportive environment, and practising fair and transparent decision-making. Policies should be reviewed to ensure the appraisal tool is unit-specific, fair and easy to understand. The performance management process is to be introduced early. Hospital management should establish clear and achievable performance standards, implement a comprehensive evaluation system, promote a culture of continuous improvement and provide constructive feedback and support.

The following areas for future research are proposed: To explore the challenges surrounding the performance management needs of nurse managers and the benefits of engaging other relevant stakeholders in performance management. In addition, regulatory guidelines or an effective model should be developed to guide performance management and ensure sustainability.

The study had limitations as it was limited to professional nurses of one hospital in Gauteng province in South Africa.