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SA Journal of Industrial Psychology

versão On-line ISSN 2071-0763
versão impressa ISSN 0258-5200

SA j. ind. Psychol. vol.42 no.1 Johannesburg  2016

http://dx.doi.org/10.4102/sajip.v42i1.1301 

ORIGINAL RESEARCH

 

Enhancing the well-being of support services staff in higher education: The power of appreciation

 

 

Laurika van Straaten; Annelize du Plessis; S.P. (Fanus) van Tonder

School of Higher Education Studies, University of the Free State, South Africa

Correspondence

 

 


ABSTRACT

ORIENTATION: A literature search for studies on the well-being of support staff of higher education institutions (HEIs) produced very little results. Appreciation was then used to identify elements that might enhance the well-being of a selected HEI's support staff.
RESEARCH PURPOSE: The aim was to explore the strengths of a selected HEI that might serve as driving forces for enhancing its support staff's well-being
MOTIVATION FOR THE STUDY: The lack of research on the well-being of support staff motivated the study. A need was identified to explore driving forces that might enhance their well-being.
RESEARCH DESIGN, APPROACH AND METHOD: A literature review guided by theoretical perspectives and theories on staff well-being was conducted. Subsequently, a qualitative action research design involving an Appreciative Inquiry (AI) workshop with support staff of an institution was followed.
MAIN FINDINGS: The following strengths that might serve as driving forces for enhancing the well-being of the institution's support services staff were identified: hard-working and dedicated support staff, positive relations among colleagues, a willingness to adapt to change, good remuneration and benefits, job security and a supportive work environment. Appreciative Inquiry was found to be well suited for identifying such strengths, as opposed to methods that focus on identifying problems or weaknesses of an organisation. As a result of this study, the relevant institution might react and build on these identified strengths towards promoting the well-being of its support staff.
PRACTICAL/MANAGERIAL IMPLICATIONS: Institutions should make an effort to enhance staff well-being. The results of the study could also be used to encourage HEIs to use AI to establish optimal staff well-being.
CONTRIBUTION/VALUE ADD: The study confirmed the power of appreciation to identify the strengths that might serve as driving forces for enhancing the well-being of support staff of an HEI.


 

 

Introduction

Higher education institutions (HEIs) play an important role in the ongoing transformation of society in South Africa, and as such, they present an interesting context for studying matters of well-being (Field & Buitendach, 2011). Research has been conducted into the well-being of academics and the factors influencing their well-being (Bezuidenhout & Cilliers, 2010; Johnsrud, 1996; Rothmann & Jordaan,2006; Zuber-Skerritt, 1992). However, a literature search for research studies on the well-being of support staff of HEIs produced very little results.

Employees worldwide, to an increasing extent, rely on their work to define their own meaning in life (Beukes & Botha, 2013; Burger, Crous & Roodt,2012; Ghoshal & Bartlett, 1994; Heil, Bennis & Stephens, 2000; Seligman, 2011). Their levels of job satisfaction are affected by their morale, levels of engagement in their work and their performance (Johnsrud, Heck & Rosser, 2000; Upadhyah & Gupta, 2012). Sufficient job resources, such as growth opportunities, organisational support and career advancement, also have proved to positively affect the levels of staff's engagement in their work (Rothmann & Jordaan, 2006).

Organisations expect of their employees to perform optimally and to be committed to the organisation and its cause (Bakker & Schaufeli, 2008). However, employees' productivity, performance, job satisfaction and organisational commitment, amongst others, are influenced by various factors related to their well-being (Field & Buitendach, 2011). Hence, organisations should turn their focus to enhancing the well-being of their staff. Staff morale and perceived job security, for instance, are influenced by factors such as a high staff turnover, which in turn leads to a loss of expertise and organisational stability (Theron, Barkhuizen & Du Plessis, 2014; Westover, Westover & Westover, 2010). When employees do not experience job satisfaction, there is a drop in their levels of engagement at work, their stress levels increase and their chances of burning out become much higher (Schaufeli & Bakker, 2004). Therefore, it is critical to enhance the well-being of employees in every possible manner.

Bezuidenhout and Cilliers (2010) researched the reasons for burnout, a lack of engagement and sense of coherence in female academics in HEIs in South Africa. Their study confirms that female academics' well-being are influenced by their sense of belonging. In order to ensure optimal well-being of staff, it thus is important to ensure that they have a sense of belonging and that they feel valued and appreciated. This might also be true for support staff of HEIs.

Maslow (1943) described the third major need in his hierarchy of needs as the need to belong and feel valued. More recent studies on well-being by Nadler, Malloy and Fischer (2008) as well as Bezuidenhout and Cilliers (2010) reveal that the need to belong, feel valued and appreciated is still real and valid in today's society and that it affects the well-being of people in the workplace. Nadler et al. (2008) point out that every individual needs to have a sense of belonging and that an unmet need to belong leads to anxiety. Although issues of well-being are very complex, they need to be addressed in order to benefit organisations.

Research purpose and objectives

The nature of this study was not problem-based, but rather focused on identifying the strengths, or positive core, of the organisation under research (Cooperrider, Whiney & Stavros, 2008) that serve as driving forces for the enhancement of its support staff's well-being. For this purpose, the framework of Appreciative Inquiry (AI) was used to investigate an affirmative topic during an AI workshop. In this way, conversations about people's desired future could be evoked. The AI method also made a positive discourse possible in the research process. This was established by determining what gives life to or what optimises the well-being of the relevant organisation's support staff (Cooperrider et al., 2008).

The affirmative topic for the research conducted for this study was the following: Exploring the possible enhancement of support services staff's well-being at [name of institution] by means of an Appreciative Inquiry approach. This topic was chosen in order to explore the particular strengths of the institution that serve as driving forces for enhancing the well-being of its support staff.

The research objectives supporting the affirmative topic included the following:

conducting a literature review on current perspectives on staff well-being and AI, specifically within higher education;

finding out what strengths could enhance the well-being of support staff in the specific organisation and why it would enhance their well-being (Cooperrider & Whitney, 2005);

discovering both existing and envisaged strengths pertaining to the well-being of support staff, as well as the wishes of support staff of the particular institution for their improved well-being; and

ensuing from the research, to draw conclusions and to identify the implications of the research findings for the enhancement of support services staff's well-being.

Literature review

This study was aimed at addressing the identified gap in the literature as explained in the introduction. Therefore, the literature review included a study of current perspectives and theories on staff well-being. From the literature review on staff well-being, it became evident that well-being is indeed a broad concept.

 

Optimal well-being

Keyes (2002) states that optimal well-being could include various elements at the emotional, social and psychological levels, whilst Seligman, Steen, Park and Peterson (2005) argue that well-being is influenced by aspects such as having positive emotions, feeling valued or appreciated, living a meaningful life, being engaged in one's work, experiencing job satisfaction, having a high morale and all kinds of elements that relate to flourishing in life. In the absence of these and other elements such as a sense of belonging, happiness and trust, well-being is affected negatively and this, amongst others, could lead to a high staff turnover (Bothma & Roodt, 2012; Mendes & Stander, 2011), low morale (Bezuidenhout & Cilliers, 2010; Ngambi, 2011), depression (Keyes, 2002; Seligman et al., 2005), a decline in one's health (Schaufeli & Bakker, 2004) and burnout (Barkhuizen, Hoole & Rothmann, 2004; Rothmann & Jordaan, 2006).

When staff members are valued and appreciated, a sense of belonging is created (Baumeister & Leary, 1995; Bezuidenhout & Cilliers, 2010; Dunlap,2004; Nadler et al., 2008; Seligman, 2002, 2011). Seligman et al. (2005) identify appreciation as one of 24 character strengths of adults around the world that is required to experience optimal well-being.

It becomes clear that happiness and life satisfaction are no longer perceived to be the only elements that affect human well-being; neither are they regarded as the ultimate goal of well-being theory, but rather as factors that are related to the element of positive emotion (Seligman, 2011). Thus, happiness does not equal optimal, or total, well-being (Keyes, 2002).

Figure 1 contextualises staff well-being. It lists the aspects pertaining to staff well-being that were investigated in the literature review, namely the different theories on, elements, causes, benefits and components of well-being and the elements of Seligman's PERMA model of well-being as applied in the research (PERMA = Positive emotions; Engagement; Relationships; Meaningful life and Accomplishment) (Seligman, 2011). The arrows indicate how the research process unfolded. It further points to the AI workshop that was conducted and the steps followed during the workshop. On completion of the AI workshop, the research findings were once again verified with the literature available on staff well-being.

 

 

The power of a positive focus

This paper firstly attempts to provide an overview and basis of well-being theory, causes of well-being as well as the various elements or components of staff well-being. It also explores the positive elements of well-being as revealed through the literature review. These include all elements of well-being that lead to a flourishing life, as derived from the AI theory of Cooperrider and Srivastva (1987), the positive psychology theory of Seligman (1998), the flourishing theory of Keyes (2002) and the well-being theory and PERMA model of Seligman (2011). However, details pertaining to the aforementioned theories and model are beyond the limited scope of this article.

Nevertheless, positive psychology theory focuses on the things that make life worth living, and on optimal human functioning, also referred to asflourishing (Seligman & Csikszentmihalyi, 2000). Flourishing people are happy and satisfied, they feel that their lives have a purpose, they experience some degree of mastery and accept themselves, they experience a sense of personal growth, they have a sense of autonomy and internal locus of control and they choose to take responsibility for their own lives instead of being victims of life (Keyes, 2002). Fredrickson and Losada (2005, p. 678) define the concept of 'flourishing' as living 'within an optimal range of human functioning, one that connotes goodness, generativity, growth and resilience'.

Positive emotion is a subjective variable, defined by one's thoughts and emotions (Seligman, 2011). There are various benefits related to positive emotions, positive moods and positive sentiments. For instance, good feelings speed up recovery, alter frontal brain asymmetry, increase immune function, alter people's mindsets, widen their scope of attention, broaden behavioural repertoires and result in an increase in intuition and creativity (Fredrickson & Losada, 2005). Other benefits of positive emotions and positive affect are that they improve the ability to make decisions (Isen, 2000), predict mental and physical health outcomes, and that frequent positive affect increases longevity (Fredrickson & Losada, 2005). All these benefits affect people's well-being in that they improve their lives in various ways.

 

Research design

Research approach

A qualitative approach was used to achieve the research objectives. The research was conducted in the field of Higher Education Studies, with a focus on the research category of institutional management (Tight, 2012). It was guided by a social constructionist discourse and the belief that multiple realities exist (Mertens, 2010). The core of social constructionism as a research paradigm is the belief that reality is constructed by our language and that language is a form of social construction (Terre Blanche, Durrheim & Painter, 2006). Our language contains our constructions of the world and ourselves. We create stories about our lives that influence how we construct our future (McNamee & Gergen, 1999). Thus, the AI process was aimed at interpreting the social world of the research participants (i.e. the institution's support staff), in order to understand their reality in terms of the language they used during the interviews between pairs of participants conducted during the Discovery phase of an AI workshop held for purposes of this research (Terre Blanche et al., 2006). Hence, the study sought to gain a deep understanding of the reality constructed by the research participants through the language they used and the self-reflection that was brought on through discourse that opened participants' thinking to alternative forms of understanding (Cooperrider & Whitney, 2005; Terre Blanche et al., 2006). Moreover, through positive, appreciative conversation, an appreciation of the power of language and discourse of all types was gained through the stories that the participants shared during the Discovery phase of the AI cycle (Cooperrider & Whitney, 2005).

Research strategy

Traditional studies on matters of well-being such as staff morale indicate that change in an organisation should be brought about by investigating the problem within the organisation and finding a solution to such a problem (Hammond, 1998). However, more recent research proves that, in order to bring about desired change, one should search for the best in people rather than focusing on problems (Cooperrider & Whitney, 2012).

The case investigated in this study is the well-being of support services staff of a selected HEI. In order to attend to the gap identified in the literature review, namely the limited research available pertaining to the well-being of support services staff of HEIs, the single case of support services staff at a South African HEI was explored. Although there might be similarities between different HEIs, transferability of the findings of the single case was not a major aim of this study.

Research method

Research setting

The research proposal for this study was evaluated and approved by the Ethics Committee of the Faculty of Education, University of the Free State. Participants were fully informed of the research process. Participation was voluntary, and written informed consent was obtained.

The research methodology applied was action research, also known as participatory research or collaborative inquiry (O'Brien, 1998). The aim was to get participants to participate in the process of inquiry and co-learning. The AI approach was applied as an action research method, and common themes (as opposed to problems) were identified, as well as the strengths of the institution that drive the well-being of support staff, and how such strengths could be used to bring about their desired future (Cooperrider & Whitney, 2005). Action research enabled collaboration with support services staff of the institution in identifying the strengths of the institution in relation to staff well-being, support staff's dreams in terms of becoming a flourishing support services staff component and the role of AI in bringing about desired, sustainable change pertaining to their well-being. AI lends itself to action research, as it entails collaboration from the research participants in the research process (Cooperrider & Srivastva, 1987). Thus, action research (as research methodology) and AI (as research method) complemented one another in this research process.

AI is described as a search for the best in people and their organisations. In the context of this study, it involved being inquisitive and making a discovery of what makes the support staff of the institution 'feel most alive, most effective, and most capable in economic, ecological, and human terms' (Cooperrider & Whitney, 2005, p. 2). Therefore, affirmative, positive questions were asked during the AI workshop held for purposes of this study, as a means of discovering the strengths that drive support staff's well-being (Cooperrider & Whitney, 2005, 2012). Positive, provocative propositions, rather than problems, created a positive context or climate for the participants within which to work. This resulted in positive findings rather than complaints as are often found to be the case with other types of staff surveys.

Entrée and researcher roles

As a support services staff member of the institution with a vision to contribute to positive change at the institution, the first researcher was interested in the effect that AI, and an appreciative focus on the institution and its current strengths, could have on the well-being of support services staff members of the institution, which would also positively affect the institutional climate.

As a participant observer, this researcher was responsible for conducting the AI workshop, but made a conscious effort to remain as objective as possible throughout the workshop by applying McMillan and Schumacher's ideas on disciplined subjectivity and reflexivity (McMillan & Schumacher, 2006). The other researchers are not affiliated with the institution under research, and therefore rather acted as critical co-researchers and co-interpreters of the qualitative data obtained during the workshop.

Sampling

The research participants were support services staff of an HEI and were purposefully selected from a total of 480 support services staff members within the entire institution. The inclusion criteria were that they had to be information-rich and had to vary with regard to race, gender, age and functions within the institution as well as their post levels. The sample size was limited to 20 participants on the one campus of the HEI (n = 20), because the available venue could only seat a limited number of people and because funds were restricted. This sample size is in line with what Durrheim (in Terre Blanche et al., 2006) proposes, namely that in interpretive, qualitative research, samples should consist of smaller groups. Because this study was performed within the ambit of a social constructionist paradigm, it is also interpretive in nature.

 

Data collection methods and recording

This study acknowledged voluntary participation, and participants were actively involved in the half-day AI research workshop - the reason being not to interrupt their normal work and activities within the HEI. Therefore, the privilege of focusing on each of the phases of the AI cycle for an entire day was not possible, as would typically be done during an AI summit.

For purposes of the study, various data collection methods were used towards establishing triangulation. An AI workshop interview guide for the entire workshop, with an answering sheet with space for participants' responses to open-ended questions was used during the Discovery, Dream, Design, and Destiny phases of the AI workshop. Appreciative interviews were held between pairs of participants during the Discovery phase of the AI workshop, whilst elements of the Nominal Group Technique (NGT) of Dobbie, Rhodes, Tysinger and Freeman (2004) were applied during the Dream phase of the AI workshop. Small-group discussions were encouraged during the Discovery, Dream and Design phases of the AI workshop, and discussions with the entire group of 20 participants took place during the Dream and Design phases of the AI workshop. Furthermore, observation and note-taking by the researcher as workshop facilitator took place during the Discovery, Dream, Design and Destiny phases of the AI workshop.

A digital audio recording of the AI workshop proceedings was made, and permission was obtained from participants to take photos of each session of the AI workshop. Finally, a reflective journal was kept throughout the study period on relevant literature, data collection techniques, the pilot of the AI workshop interview guide and the AI workshop itself. On completion of the workshop, the responses to each of the questions by each of the participants were typed, and elements pertaining to staff well-being that were identified from the responses were marked and analysed.

 

Strategies employed to ensure data quality and integrity

As was mentioned previously, 20 support services staff members representing all the different post levels of support staff within the HEI, were purposefully selected and invited to participate in the AI workshop on a voluntary basis. All participants signed a confidentiality and informed consent agreement. Participants were involved in the analysis of all data collected during the AI workshop by means of the identification of top stories related to their well-being that were shared during the interviews between pairs of participants during the Discovery phase, the identification of the positive themes that represented the positive core of the organisation and that drive the enhancement of support staff's well-being during the Discovery phase, the adapted NGT process applied during the Dream phase and the analysis of data gathered during small-group sessions and sessions with the entire group of participants (Discovery, Dream and Design phases). No field workers or other interviewers assisted with the interviews between pairs of participants. The pairs of participants took turns to interview one another.

All data collected were safely kept electronically through password protection or by locking hard copies in a cabinet, and participants remained anonymous. To ensure saturation of collected data, the data were read and reread by the researchers during the analysis so as not to overlook any important information. The literature study confirmed the applicability of AI as a method of identifying the strengths of organisations and applying those strengths to bring about positive change within organisations, specifically related to the well-being of staff (Cooperrider & Whitney, 2012). The research process and findings are reported in this paper by means of thick descriptions of evidence to ensure, as far as possible, transferability of the research findings so that any reader would be able to understand and apply the research findings in other contexts, if possible.

To establish the dependability of the research findings, detailed descriptions are given in this paper on how the study was conducted and how the data were collected, recorded and analysed. To this effect, a reflective journal was kept whilst conducting the literature study, the empirical research and whilst collecting and interpreting the data. In the reflective journal, the thoughts, reflections and reasons for choosing the particular research design, the sample selection, the questions for the workshop interview guide, the pilot study done on the workshop interview guide prior to the research, the data collection and how the researchers went about to interpret the data were recorded. All information gathered by means of the interviews between pairs of participants and the workshop interview guide used during the different phases of the AI cycle performed during the research workshop was recorded by means of a digital voice recorder. Furthermore, research participants were involved in the analysis and interpretation of data gathered during the AI workshop, that is, data collected during the interviews between pairs of participants, small-group and large-group (involving all the participants) activities. All these were done consciously in order to strengthen the credibility, validity and dependability of the research findings.

The strategies of disciplined subjectivity and reflexivity (McMillan & Schumacher, 2006) were also constantly applied by the researchers in an attempt to increase the confirmability of the study.

 

Data analysis

The qualitative data emanating from the AI workshop were finally analysed and interpreted by the researchers through identifying central themes. Although the data collected were interpreted and linked to the researchers' own background and life experiences, every effort was made by the researchers to avoid bias and being influenced by own experiences in the interpretation of the data. This is in accordance with the ideas of McMillan and Schumacher on disciplined subjectivity and reflexivity that needs to be applied by qualitative researchers (McMillan & Schumacher, 2006). This strategy also assisted in gaining a deeper understanding of the world and experiences of participants, as shared by the participants.

However, most of the data analysis was initially done by the research participants during the AI workshop through the adapted NGT process followed during the Dream phase, and during small-group sessions (i.e. on completion of the Discovery phase and during the Design phases) and large-group sessions (on completion of the Discovery phase, and during the Dream and Design phases). Additional information gathered during the interviews between pairs of participants and the rest of the AI workshop was finally interpreted by the researchers. The method of content analysis and interpretation of the data that the researchers used comprised the following four steps, as proposed by Anderson (2009):

understanding and assessing the data collected;

reducing the data to manageable chunks;

exploring themes and patterns, and coding the data and

formulating meaningful conclusions.

The qualitative data analysis was done for interpretive purposes, and towards understanding the relevant social phenomenon and the world of the research participants from their point of view, as proposed by Lincoln and Guba (in Mertens, 2010).

In the first step (understanding and assessing the data collected), the researchers asked questions about the essence of what the data communicated. The collected data were read and reread to gain a clear understanding of what the participants had shared. The type of language used by participants was studied carefully to gain an understanding of participants' own reality in terms of the language they used. Words that described their emotions, points of view and their own reality were marked as part of a search for meaning.

In the second step (reducing the data to manageable chunks), the data were interpreted by attempting to form a clear meaning of what participants had communicated. The types of discourse used by participants and how the discourse opened up their thinking were studied (Cooperrider & Whitney, 2005; Terre Blanche et al., 2006). The information gathered during the interviews between pairs of participants and written down on the workshop interview guide was then reduced to manageable chunks by searching for words that were related to the elements of well-being as identified during the literature review. Thereafter, the identified elements of well-being were grouped together into fitting categories.

The third step (exploring themes and patterns and coding the data) was addressed by the participants as part of the Discovery phase of the research workshop, and through the application of elements of the NGT during the Dream phase. During the Discovery phase, participants identified the top stories shared during interviews between pairs of participants. During the Dream phase, participants explored the key positive themes that drive the enhancement of their own well-being, and the data were coded according to the prescriptions of the NGT. Key themes that had emerged from the Design and Destiny phases were explored in a similar manner by identifying the themes related to support services staff's well-being and coding the data accordingly. All the data gathered as part of the different phases of the AI cycle (Discovery, Dream, Design and Destiny) were eventually analysed by the researchers by means of grouping the data under the different identified elements of well-being, as they had emerged from the literature review.

The final step entailed the formulation of meaningful conclusions from the data collected. The repetitive nature of the qualitative data analysis enabled the formulation of research conclusions based on the evidence found (Anderson, 2009). Conclusions were then justified from the data analysis process followed.

 

Reporting style

The phases of the 5-D AI cycle (Definition, Discovery, Dream, Design and Destiny) and the AI questions asked during each phase are used in this paper as a framework for reporting the research process and findings in relative detail.

 

Findings

Definition phase

For the Definition phase, the researchers identified an affirmative topic prior to the workshop. This affirmative topic, together with detail about the AI process and all its different phases and the emphasis on the positive, was shared with all the participants prior to the workshop, in order for them to gain a clear understanding of what AI entails and about the different phases of the AI cycle that would be used as research method during the research workshop. This ensured that individuals were focused on having positive dialogue and conversation during the Discovery phase. By doing so, participants were eventually able to reach consensus on what the organisation was aspiring to and to embrace a shared vision for the organisation. This also ensured that participants bonded socially with one another (Cooperrider et al., 2008).

Discovery phase

During the Discovery phase, appreciative interviews were held between pairs of participants. Valuable data were gathered whilst participants answered the interview questions and shared stories about times when they felt positive and alive in the organisation. Participants were encouraged to share their stories as richly as possible and to avoid 'Yes' and 'No' answers. AI emphasises the importance of the very first question asked to attendees, as this question sets the tone for the conversations to follow. The first appreciative interview question was formulated by the researchers prior to the workshop, being fully aware of its importance and the positive focus required. The question was:

Tell me about a time when you were flourishing here at [name of institution] - a time when you felt positive, most alive, engaged, or really proud of yourself or your work here at [name of institution]. What was it about you, the situation and/or the leadership that allowed you to have that positive experience?

The open-ended nature of the questions asked during the interviews allowed participants to answer the questions in their own words. Participants were grouped in pairs to save time, while ensuring that people that might know one another would not be grouped together. Pairing and grouping was also done with good variation in mind pertaining to post level occupied, age, race, gender and years of service at the institution. Ten pairs of two participants each were formed in the Discovery phase. Time allocated for these interviews was 1 h, allowing 30 min per interview. During the Discovery phase, the participants' excitement was stimulated by the positive stories and experiences that they shared. In the interviews between pairs of participants, interviewers wrote down the stories told by interviewees, and thereafter, they switched roles.

The appreciative interviews between pairs of participants were followed by a group phase as proposed by Lewis (2008), during which the most popular themes around the best stories shared between pairs of interviewees were identified. The four small groups with four to six members each had to choose two top stories, which were subsequently shared within the larger (i.e. the entire) group of participants during the Dream phase.

From the Discovery phase, participants identified the following:

elements of their well-being;

requirements for feeling valued and/or appreciated;

elements of the work environment and/or employer they valued most;

aspects valued most about colleagues;

what they, as support services staff members, valued about themselves;

what they believe makes the institution unique;

the circumstances contributing to the most extraordinary accomplishments and/or experiences of support services staff;

what could be done towards establishing a flourishing support services staff component; and

their hopes and/or wishes for the institution.

Dream phase

During the Dream phase, participants identified the top themes - also known as the positive core (Cooperrider et al., 2008) of the institution - that serve as driving forces for the enhancement of staff well-being, by making use of elements identified through the NGT. Participants formed groups, and each group again chose two of the top themes. This was done by writing the themes on a flip chart, followed by a presentation by an elected group facilitator for each of the four groups, on their two top stories or themes identified. Participants listened carefully to the presentations made by group facilitators, and encouraged them whilst they shared their stories. The positive atmosphere created by the sharing of these stories was tangible and the positivity continued throughout the AI workshop. This is evidence of the power of AI as a tool to promote focusing on the positive and creating enthusiasm (Cooperrider et al., 2008). It transpired that through its positive core, the institution might have the potential to enhance the well-being of its support services staff.

Design phase

During the Design phase of the AI workshop, participants co-constructed the organisation's future by answering the following question: What is required to make our dream come true?

This question was first answered in writing by each individual participant in the space provided on the workshop interview guide. The answers were subsequently discussed in the four small groups. Each group then agreed on the most important actions that were required to make their dream of a flourishing support services staff component come true. In answering this question, each small group participated in designing a provocative, inspiring statement of intention, written in the present tense and based on what had worked well in the past, combined with new, envisioned ideas for the organisation's future (Cooperrider et al., 2008). Each group consisting of four to six staff members then chose a provocative proposition for the institution and was subsequently given an opportunity to present this provocative proposition to the larger group, stating why they had decided on the particular proposition. The four provocative propositions identified and presented by the four groups to the larger group, inspired everyone. They were the following:

[name of institution] is an eagle;

[name of institution] is an employer of choice;

[name of institution] is a growing tree; and

[name of institution] is a tiger.

Participants nodded their heads in support of the provocative propositions shared by other teams. This brought a sense of belonging amongst participants, realising that they were part of one big 'family' of support services staff at this institution.

Destiny phase

The final phase of the AI workshop was the Destiny phase. The Destiny phase is all about innovation, taking action and creating a sustainable future (Cooperrider et al., 2008). During this phase, it is determined how ready the organisation is to embrace the proposed changes. Recommendations are made, and changes embraced by the organisation are implemented to bring about the desired change (Cooperrider et al., 2008).

The momentum that is established through the AI process empowers members of the organisation to move forward and closer to an ideal work situation. As this ideal is grounded in realities, it empowers the organisation to make things happen by seeking new ways of doing things, gaining a fresh perspective and being appreciative (Cooperrider et al., 2008). During the Destiny phase of the AI workshop, each participant was asked to commit him or herself to making a contribution towards a flourishing support services staff component at the institution by completing the following AI statement: 'I commit myself to do the following in order to make [name of institution] support services staff members flourish: ' (Van Straaten 2014:27)

Some of the responses recorded included:

'I commit myself to always have a positive attitude and assist other people; then we will see positive things happening at [name of institution].' [Participant A, Female, Committee Services Manager, 37 years of age]

'I commit myself to work hard; be dedicated; to do what is needed to improve myself; and to execute my duties with passion and commitment.' [Participant B, Female, Language Practitioner, 28 years of age]

'I commit myself to say "thank you" more often, and to give compliments to colleagues regularly.' [Participant C, Female, Senior Analyst, 35 years of age]

These actions and innovations proposed by participants, to which they committed themselves, may indeed ensure the sustainability of their dreams for the institution.

 

Discussion

The aim of this study was to explore the strengths related to the well-being of support staff of an HEI. More specifically, the researchers sought to determine the elements of well-being as identified by support services staff, their wishes and dreams towards improved well-being through AI as a tool - not only in determining their current well-being but also as having the potential to effect transformation and optimisation of their well-being at all levels (Van Straaten, 2014).

Outline of the findings

The participants identified the positive core of the organisation that drives the enhancement of the support staff's well-being to be its hard-working and dedicated staff; a willingness of staff to adapt to change; positive relations among colleagues, supervisors and subordinates, good remuneration and benefits offered to staff; job security; and a supportive work environment. Furthermore, the participants revealed that through its positive core, the institution could enhance the well-being of support services staff by valuing and acknowledging contributions made by support services staff, by establishing equality between support services and academic staff, appointing adequate support services staff to do the work, ensuring manageable workloads, creating opportunities for promotion of support services staff and by doing more to address the overall well-being (physical, psychological, social, emotional and financial well-being) of support services staff.

The findings outlined above are echoed by the principles of AI and its power to transform organisations (Cooperrider & Whitney, 2012), the findings of Whitney and Trosten-Bloom (2010) and Cooperrider and Whitney (2005, 2012) on the power and effect of appreciation on staff's well-being, the principle of equality as contained in the Constitution of the Republic of South Africa (1996), the evidence of the influence of workload on staff's well-being as revealed by Demerouti and Bakker (2011), the effect of promotion on staff's well-being (Robyn & Du Preez, 2013; Rothmann & Rothmann, 2010; Theron et al., 2014) and the importance of addressing well-being in its totality, as identified by Keyes (2002) and Seligman (2011).

Practical implications

As there are limited studies on the well-being of support services staff at HEIs, this study aimed to make a contribution to the body of knowledge in the field of staff well-being in the context of higher education. It is anticipated that the institution will realise the importance of the role of support services staff as the gears that keep the machine running and that their well-being should be a matter of high priority. The relevant institution also needs to attend to its positive core and the actions identified by the participants to sustain and enhance its support staff's well-being and take note of the power that appreciation might have in future actions aimed at enhancing its positive core and transforming the institution.

Limitations and recommendations

The following limitations applied to this study:

the limited sample size;

participants were limited to support services staff members on only one of the campuses of the particular HEI; and

only a 4 h AI workshop could be conducted for the empirical research and not a summit of three to four days.

Based on the research findings, the following recommendations for future research are made:

Similar studies should be conducted at other HEIs to test the credibility and transferability of the research findings of this study.

Because this study was limited to 20 support services staff members of the particular HEI, the transferability of the findings could be increased by doing a similar study across a larger sample of support services staff from various HEIs.

Research samples should include both academic and support services staff to gain an idea of the factors influencing the well-being of all HEI staff.

AI should be explored by HEIs as a method of exploring their positive core, bringing about organisational change and improving the well-being of their academic and support services staff.

Because AI has a positive focus and values the inputs made by all the participants during AI summits and/or workshops and because it focuses on the positive core of organisations to build upon and towards desired results, it should be further explored for bringing about desired change in terms of organisational structures, functions, organisational climate changes and improving the well-being of HEI's staff and management.

 

Conclusion

This study explored, by means of AI, the strengths of a South African HEI that drive the well-being of its support services staff. It eventually became evident that AI, with its focus on identifying the strengths and the positive core of organisations, can be an effective tool in identifying driving forces for transforming organisations and improving the well-being of their staff.

It is further evident from this research and the literature review conducted that staff well-being remains a relevant topic in today's society and that it affects organisations at all levels. The benefits of staff experiencing optimal well-being are numerous, and organisations can benefit tremendously from having flourishing staff components. Support staff members are an integral part of HEIs and also affect the outputs of HEIs in various ways. Hence, HEIs should do more to improve the well-being of their support staff components. It is anticipated that the institution under study will realise the importance of the role of support staff as the gears that keep the machine running and that their well-being should be prioritised.

The findings emanating from the empirical study indicate that there are definite strengths within the organisation that drive the well-being of its support staff such as its innovations; the remuneration and benefits offered to staff; the culture of openness and transparency that exists; positive relations among colleagues; and quality education offered, quality of its staff and more. These positive developments were identified by support staff themselves, as discussed earlier.

The study was underpinned by the research paradigm of social constructionism and the belief that reality is socially constructed through language. The applicability of AI as a research method in such a study was illustrated, as the statement of positive, provocative propositions rather than problems created by a positive context or climate for the participants within which to work, which resulted in positive findings rather than complaints as often is found to be the case with other types of staff surveys.

As there are limited studies available pertaining to the well-being of support services staff at HEIs, this study will also contribute to the body of knowledge within the field of support staff's well-being in the context of higher education. The study was thus aimed at benefitting South African HEIs in terms of their management of strategic human resources and, more specifically, their support services staff. However, because well-being is a relative topic in today's society, it could benefit all organisations that employ people. Hence, the study, albeit intended to be to the advantage of support services staff of HEIs, may also benefit organisations striving to improve the well-being of their staff.

 

Acknowledgements

With much appreciation to the HEI that provided financial support to conduct this study.

Competing interests

The authors declare that they have no financial or personal relationships which may have inappropriately influenced them in writing this article.

Authors' contributions

The research is based on the master's study of L.V.S. that was completed in 2014. This article presents a part of the research. L.V.S. conducted the research. A.D.P. was the supervisor. S.P.V.T. was the co-supervisor. L.V.S. wrote the initial manuscript.

 

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Correspondence:
Laurika van Straaten
lvstraat@cut.ac.za

Received: 31 Aug. 2015
Accepted: 19 Apr. 2016
Published: 28 July 2016

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