About the Author(s)

Shiksha Gallow Email symbol
Graduate School of Business Leadership, University of South Africa, Johannesburg, South Africa

Jo Nel symbol
Department of English Studies, University of Limpopo, Polokwane, South Africa

Adri Williams symbol
Edupark, Polokwane, South Africa


Gallow, S., Nel, J., & Williams, A. (2020). A conceptual model to retain non-professionals in a private healthcare setting. SA Journal of Human Resource Management/SA Tydskrif vir Menslikehulpbronbestuur, 18(0), a1281. https://doi.org/10.4102/sajhrm.v18i0.1281

Original Research

A conceptual model to retain non-professionals in a private healthcare setting

Shiksha Gallow, Jo Nel, Adri Williams

Received: 27 Sept. 2019; Accepted: 21 Apr. 2020; Published: 07 July 2020

Copyright: © 2020. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background: Non-professionals are carriers of institutional knowledge and are essential to the effective functioning of healthcare institutions. However, most studies on retention in the healthcare environment focus on professionals.

Objective: The aim of this study was to develop a conceptual model pertaining to the retention of non-professionals in the healthcare sector.

Methods: A total of 72 non-professional and, for the purpose of contract, 116 professional employees were surveyed. The independent variables were job characteristics, job satisfaction and career anchors. The dependent variables were organisational commitment and intention to quit. The analysis focused on the way the independent variables correlated with the dependent variables.

Results: It was possible to identify individual elements in the independent variables that relate to the dependent variables. It was thus possible to extrapolate and develop a conceptual model for the retention of non-professionals in the healthcare sector. The results also revealed that, for the professionals, the independent variables were less effective in predicting retention.

Conclusion: A retention strategy that focuses on the specific variables could be effective for the retention of non-professionals. Also, the independent variables used in this study do not predict retention in the professional group. It may thus be necessary to address retention for non-professionals and professionals in the healthcare sector differently.

Keywords: retention; conceptual model; pathology; job retention; career anchors.



There are obvious reasons why staff turnover in the healthcare environment should be minimised. Mazurenko, Gupte and Shan (2015) refer to important consequences: ‘decreased patient access, patient safety and quality of care leading to adverse outcomes’ of high staff turnover (p. 48). Most studies on retention in the healthcare environment focus on professionals (e.g. Geun, Redman, & McCullagh, 2016; Hayward, Bungay, Wolff, & MacDonald, 2016; Kaye & Jordan-Evans, 2014; Yu & Kang, 2016). This may have unintended and acute consequences, as the support staff – that is, the non-professionals – are carriers of institutional knowledge and are essential to the effective functioning of healthcare institutions (Encinares & Pullan, 2003; Lin, Yu, & Zhang, 2014; Vlastarakos & Nikolopoulos, 2008). In this regard, selected previous research has shown that retention models for those on different staff levels differ (Staggs & Dunton, 2012; Wheeler, Halbesleben, & Harris, 2012).

Retention (in general) has been associated with many antecedents, for example, task, organisational, personality and demographic factors (Shahnawaz & Jafri, 2009). Task factors, such as job characteristics (Chang, Wang, & Huang, 2013), organisational factors, for example, role conflict (Tiplic, Brandmo, & Elstad, 2015), opportunities for career advancement and procedural fairness (Shahzad, Hayat, Abbas, & Bashir, 2011), as well as the work environment (Duffield, Roche, Blay, & Stasa, 2011; Mi, 2016) and management leadership (Leveck & Jones, 1996) are said to influence turnover. Factors such as locus of control, perceived organisational support, job satisfaction and organisational commitment (Chiu, Lin, Tsai, & Hsiao, 2005), and demographic factors, such as age (Buengeler, Homan, & Voelpel, 2016) and age coupled with tenure similarity amongst employees (Chang et al., 2013), have demonstrated an influence on retention. Retention has been associated with compensation and benefits (Jordan, 2009).

Research purposes and objectives

Within the domain of healthcare, retention was specifically associated with affective professional commitment, job satisfaction, organisational commitment and intention to change professions (Parry, 2008). Barak, Nissly and Levin (2001) point to burnout, job dissatisfaction, availability of employment alternatives, low organisational and professional commitment, stress and lack of social support as strong predictors of turnover or intention to leave. Lack of career development and lack of training opportunities are also related to retention in the healthcare field (Chipeta, 2014). Jooste (2009) also states that healthcare professionals ‘expect that their performance will correlate with the rewards received from the organisation’ (p. 288). Furthermore, Race and Skees (2010) report that retention within the healthcare domain is associated with good mentoring as is preceptorship (Yonge, Myrick, Billay, & Luhanga, 2007). In the past, job characteristics (Ghosh, Rai, Chauhan, Gupta, & Singh, 2015; Uruthirapathy & Grant, 2015), job satisfaction (Hudgins, 2016) and career anchors (Guan et al., 2014; Wen & Liu, 2015) were also used in empirical research as antecedents to retention. The purpose of this study was to test the importance of job characteristics, job satisfaction and career anchors, in retaining non-professional in the private healthcare system.

Literature review

Job characteristics (Ghosh et al., 2015) and job satisfaction (Adegoke, Atiyaye, Abubakar, Auta, & Aboda, 2015) are closely related to retention. Along similar lines, Schein’s career anchors are often used as a predictor of retention (Msondo, 2014; Osuji, Uzoka, Aladi, & El-Hussein, 2014). Equally, intention to quit (Lartey, Cummings, & Profetto-McGrath, 2014) and organisational commitment (Van Dyk & Coetzee, 2012) are often seen as proxies to retention. Given the aforementioned, three antecedents to retention, namely, job characteristics, satisfaction and career anchors, were identified, as were two proxies to retention, namely, organisational commitment and intention to quit.

According to the job-characteristic theory, skill variety (the range of tasks performed), task identity (the ability to complete the whole job from start to finish) and task significance (the impact of the job on others) contribute to the meaningfulness of the work, while autonomy (the extent of discretion and freedom an employee has over his or her tasks) and feedback (the extent to which the job provides the employee with information about the effectiveness of his or her performance) contribute to the motivation of the employee (Hackman & Oldham, 1975). Wall, Clegg and Jackson (1978), almost 40 years ago, found that job characteristics are related to intrinsic motivation, job performance, job satisfaction as well as absenteeism and the retention of employees. It could well be expected that those variables still influence a person’s intention to remain in an organisation or be committed to it.

The elements of job satisfaction, as proposed by Hackman and Oldham (1975), namely, job, pay, security, social, supervisor and growth satisfaction, as often referenced in academic literature (Behson, 2010; Debacker, 2013), are seldom explained in greater detail, and also not explained in the original instrument development document (Hackman & Oldham, 1974). However, it seems self-explanatory as is the link between satisfaction and turnover (Adegoke, 2014).

Schein (1975) identified eight career anchors. These are the following:

  • technical/functional (referring to individuals motivated by doing what they are good at and aim to grow in expertise in an area)
  • general managerial (referring to individuals who want to lead others and aspire to decision-making and motivating others)
  • autonomy/independence (referring to individuals who need a feeling of autonomy and independence and seek to work alone or in a situation which they can control)
  • security/stability (referring to individuals who try to avoid uncertainty and tend to seek stability in their workplace
  • entrepreneurial creativity (referring to those who are motivated by creating something new and bring new perspectives ideas to the fore)
  • service/dedication to a cause (referring to those who want to see themselves as being of value, to other people, helping people or to a cause, such as animal rights)
  • pure ch1allenge (referring to individuals who are motivated by success, promotion and recognition, as well as competing against others)
  • lifestyle (referring to those concerned with work–life balance and seeing work as a means for doing things they view as being of value).

From the aforementioned, it is evident that certain individuals would be attracted to certain work environments, while others would be repelled by a work environment that does not satisfy their needs. Career anchors are enduring and would not be relinquished, even if the employee is faced with difficult career choices (Gubler, Biemann, Tschopp, & Grote, 2015).

From the above, the link between these variables seems straightforward and well researched. However, studying the references to the variables, particularly those who make reference to the medical profession, it is evident that attention is only given to professionals in the field (Alam & Shahi, 2015; Warmelink, Wiegers, De Cock, Spelten, & Hutton, 2015). None of the research reports listed here make any reference to support or administrative staff. The focus of this research was to assess whether all staff are cut from the same cloth, and if managers should treat all employees similarly, when the aim is to retain them.

Research methods

Research design

The research was an exploratory study making use of a cross-sectional survey design. The aim was to assess the extent to which traditional antecedents to retention apply to non-professionals employed in the private healthcare environment.


The target population was all non-professional employees working in South Africa in the private healthcare domain. For the purpose of the study, privately owned pathology laboratories were targeted. A list of employees with all their information was acquired from the human resource department of the different laboratories. All employees (professional and non-professional) were invited to participate in the study.

Ethical consideration

Ethical approval for this study was granted by UNISA School of Business Leadership (UNISA SBL’s) ethics committee. No ethical breaches occurred during the study.

Research plan

After gaining permission to conduct the research from the different managers of the laboratories, and getting ethical clearance for the university, all employees were approached to complete five questionnaires: three on antecedents to retention and two that acted as proxies to retention. Then, the data were captured and analysed to assess the level of overlap between the independent and the dependant variables. The results were used to develop a model for the retention of non-professional staff in the private healthcare environment.

In the analysis, a distinction was made between professional and non-professional staff. Those registered with statutory bodies such as the Health Professions Council of South Africa (HPCSA) or the South African Nursing Council (SANCA) were deemed to be professionals and the rest were considered to be non-professionals.

Measuring instrument

The Job Characteristic Scale forms part of the Job Diagnostic Survey (Hackman & Oldham, 1975) and consists of five sections, namely, skill variety, task identity, task significance, autonomy and feedback. The Job Diagnostic Survey (Hackman & Oldham, 1975) also contains a measure called the Job Satisfaction Scale, with sections called job, pay, security, social, supervisor and growth satisfaction. The Career Orientation Inventory (COI) was developed by Schein (1996) following De Long (1982). It measures eight career anchors, namely, technical/functional competence, general managerial competence, autonomy, security/stability, entrepreneurial creativity, service/dedication to a cause, pure challenge as well as the career anchor lifestyle. The Organizational Commitment Scale (Allen & Meyer, 1990) measures three-dimensional organisational commitment, focusing on affective, continuance and normative commitment. In this study, the focus will only be on the overall commitment score. The Intention to Quit Questionnaire, adopted from Arnold and Feldman (1982), measures the intention to quit with a unidimensional four-item scale.

All of these measures are well known in the organisational behaviour environment and display acceptable levels of reliability and validity and have been used in numerous studies.

Statistical analysis and decision-making

Statistical analysis focuses on correlations as well as on regression analysis. Correlations were calculated to identify which of the independent variables overlapped the most with the dependent variables. Statistically significant correlations (p < 0.01), with medium effect (R ≥ 0.30), as per Cohen (1988), will be deemed as practically significant and will be included in the conceptual model (i.e. retention strategy). Regression analysis will be used to identify how the group of variables (job characteristics, satisfaction and career anchors) together predict the dependent variables. R2 ≥ 0.20 would be deemed as practically significant; Cohen (1988) states that when shared variance is greater than 20%, it may be interpreted as practically meaningful.


In the section that follows, a description of the participants is provided as well as the results pertaining to the correlations between the constructs. The rest of the findings focus on the relationships between the independent (job characteristic, job satisfaction and career anchors) and dependent variables (organisational commitment and intention to quit).

Description of the participants

In total, 188 respondents answered the questionnaires. Amongst them, 53 (22.8 %) were male and 135 (71.8%) were female. The respondents’ ethnicity was as follows: 37.8% African, 23.9% Caucasian, 20.7% Asian and 17.6% mixed race. In total, 116 professionals and 72 non-professionals employees were surveyed.

Correlation between antecedents and proxies of retention

In Table 1, the correlation between job characteristics and intention to quit and organisational commitment per staff status are presented.

TABLE 1: Correlation between job characteristics and intention to quit and organisational commitment per staff status.

From Table 1, it can be deduced that most job characteristics predict intention to quit in the non-professional group. This is also reflected in the regression coefficients, which is practically significant. Providing skill variety, task significance and autonomy will retain employees. Indeed, the feedback from the job itself seems to coincide with non-professional employees wanting to quit their jobs. Note that none of the job characteristics seem to create commitment to the organisation, amongst the non-professionals.

None of these traditional predictors of retention seem to be effective in the professional group. This also applies to organisational commitment.

In Table 2, results pertaining to career anchors and the proxies to retention are presented.

TABLE 2: Correlation between career anchors and intention to quit and organisational commitment per staff status.

From Table 2, it can be inferred that an environment with high technical/functional competence, general managerial competence, security/stability and service/dedication to a cause retains employees (i.e. they do not want to quit). However, pure challenge seems to have a negative effect, causing employees to want to leave.

Even though none of the individual career anchors overlapped at a practical level with organisational commitment, the overall model, the regression model (see R2), suggests that it does indeed contribute to commitment. Career anchor is, however, a much weaker predictor of organisational commitment than intention to quit.

As was the case with job characteristics, none of the career anchor variables overlapped in a practical and meaningful manner with the proxies to retention in the professional group. Career anchors thus predict intention to quit and organisational commitment amongst non-professionals, but fail to do that amongst the professionals in the healthcare system.

The results pertaining to satisfaction, on the one hand, and the proxies of retention, on the other hand, are presented in Table 3.

TABLE 3: Correlation between satisfaction and intention to quit and organisational commitment per staff status.

From Table 3, it is evident that high levels of pay, security, social and supervisory satisfaction contribute to employees not intending to quit the organisation. It is interesting to note that only the possibility of growth (growth satisfaction) contributes to commitment to the organisation. Not one of the other types of satisfaction, including pay satisfaction, contributed to commitment to the organisation.

As was the case with the other variables, no practically significant shared variance was found in the professional group. Job satisfaction is thus a poor predictor of proxies to retention amongst professionals in the healthcare system.

In Table 4, the results of the previous tables are combined to highlight where managers could focus their effort should the aim be to retain non-professional staff in the private healthcare sector.

TABLE 4: Retention model for non-professional workers in the private healthcare environment.

As can be noted from Table 4, managers need to provide more inducements in the case of negative correlations and fewer in the case of positive correlations to retain non-professional staff.


From the analysis presented, it can be observed that job characteristics, satisfaction and career anchors overlap with intentions to quit. The values were R2 = 0.473, 0.736 and 0.674, respectively. This suggests that meeting career anchor expectations could be the best strategy to prevent non-professional staff from quitting. It is also important to note that only job satisfaction contributes to organisational commitment, with opportunities for growth as the primary driver in this case.

It was possible to develop a retention strategy for non-professionals in the private healthcare sector. Managers are urged to focus on the elements highlighted in Table 4 when they strive to retain employees. Although it may be important to focus on certain aspects, managers also need to be aware of the factors that do not contribute to retention. It is recommended that with regard to job characteristics, improved skill variety, task significance and autonomy will contribute to reducing intentions to quit, while feedback from the job itself seems to promote intentions to quit. It thus seems that when considering job characteristics, it would be unwise to design jobs that automatically provide feedback, if retention is the aim. Considering the eight career anchors, five seem to influence the intention to quit. Improving conditions that will strengthen the technical, managerial, security and service career anchors will diminish the inclination to want to quit, while stimulating the challenge career anchor will have the opposite effect. While general satisfaction with the job does not affect intentions to quit amongst non-professionals, satisfaction regarding pay, security, supervision and social interactions does. Improving these conditions may curtail intentions to quit.

An important finding from this research is that not intending to quit does not equate to commitment to the organisation. It may be inferred from these results that the concepts may have different meanings to the respondents and it seems as if different antecedents influence the two variables.

Perhaps, the most striking finding of the research is the inability of the independent variables to predict the proxies to retention in the professional group. This was the case for all the predictors and on all the sub-scales. This suggests that traditional antecedents to retention fail as predictors for professionals in the private healthcare sector. The implication is that different strategies may be necessary for the retention of different categories of employees.


It has been noted from the existing literature that few retention strategies exist for public health workers, and more effective strategies are needed in South Africa. The findings for this article have been derived from valid and concise research methods, and provide empirically based evidence to this effect. As previously discussed, meeting career anchor expectations could be the best strategy to prevent non-professional staff from quitting. Alhassan and Poku (2018), Chipeta (2014), Jiang and Klein (1999), Lee and Park (2018), Muller, Bezuidenhout and Jooste (2009) and Weiss (2019) suggest that career-anchor-related interventions would influence retention. Managers are thus encouraged to focus on career anchor ‘fulfilment’ as the most effective strategy to retain non-professionals in the private healthcare system.

This study reinforces the idea that traditional retention strategies are suitable to retain non-professionals, and in addition highlights the importance of focussing on specific antecedents. It further accentuates the need to differentiate between retention strategies for professional and non-professionals. This is in line with the previous findings (see Staggs & Dunton, 2012; Wheeler et al., 2012). The contribution of this study is providing a retention model using and contrasting several variables, namely, career anchors, job characteristics, job satisfaction, organisational commitment and intention to quit, in relation to the retention of non-professionals. A retention model for the healthcare non-professionals was developed. This model not only contributes to the body of knowledge, but is also a useful managerial tool to manage non-professionals (and professionals) in the health sector.


The authors thank UNISA School of Business Leadership (UNISA SBL) for the support provided to conduct the study.

Competing interests

The authors have declared that no competing interest exists.

Authors’ contributions

S.G. was the main author, and the rest were co-authors.

Funding information

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Data availability statement

Data sharing is not applicable to this article as no new data were created or analysed in this study.


The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.


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