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Job Demands-Resources Profiles and Work Capabilities: Effects on Early Childhood Development Practitioners' Functioning

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Title: Job Demands-Resources Profiles and Work Capabilities: Effects on Early Childhood Development Practitioners' Functioning
Language: English
Authors: Suzette C. Ragadu (ORCID 0000-0001-6945-3305), Sebastiaan Rothmann (ORCID 0000-0001-6065-4338)
Source: Early Childhood Education Journal. 2026 54(2):999-1014.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 16
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Early Childhood Education
Descriptors: Early Childhood Teachers, Stress Variables, Intention, Faculty Mobility, Foreign Countries, Teacher Attitudes, Work Attitudes
Geographic Terms: South Africa
Assessment and Survey Identifiers: Utrecht Work Engagement Scale
DOI: 10.1007/s10643-025-01902-1
ISSN: 1082-3301
1573-1707
Abstract: This study examined the associations between early childhood development practitioners' job demands-resources profiles, work capabilities, engagement, and intentions to leave. A cross-sectional survey was administered to a convenience sample (N = 426) of early childhood development practitioners in two provinces in South Africa. The Job Demands-Resources Scale (Rothmann et al., A psychometric evaluation of the job demands-resources scale in South Africa. SA Journal of Industrial Psychology, 32(4):76-86, 2006. https://hdl.handle.net/10520/EJC89107), Capability Set for Work Questionnaire (Abma et al., Scandinavian Journal Work, Environment and Health 42:34-42, 2016), Work Engagement Scale (Rautenbach and Rothmann, Journal of Psychology in Africa 27:303-309, 2017), and Intention to Leave Scale (Sjöberg and Sverke, Scandinavian Journal of Psychology 41:247-252, 2000) were administered. Latent profile analyses resulted in four job demands-resources profiles: high demands-low resources (33.18%), moderate demands-high resources (17.17%), moderate demands-low job resources (30.39%), and moderate demands-moderate resources (19.3%). Early childhood practitioners who were in moderate demands-high resources (rather than high demands-low resources or moderate demands-low job resources) jobs and had a robust capability set showed high work engagement and low intentions to leave their jobs. Job demands-resources profiles indirectly affected early childhood development practitioners' work engagement and intentions to leave via their capability sets.
Abstractor: As Provided
Notes: https://doi.org/10.17632/sr9mbztwdb.1
Entry Date: 2026
Accession Number: EJ1507362
Database: ERIC
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  Value: <anid>AN0191573913;5mx01feb.26;2026Feb17.02:11;v2.2.500</anid> <title id="AN0191573913-1">Job Demands-Resources Profiles and Work Capabilities: Effects on Early Childhood Development Practitioners' Functioning </title> <p>This study examined the associations between early childhood development practitioners' job demands-resources profiles, work capabilities, engagement, and intentions to leave. A cross-sectional survey was administered to a convenience sample (N = 426) of early childhood development practitioners in two provinces in South Africa. The Job Demands-Resources Scale (Rothmann et al., A psychometric evaluation of the job demands-resources scale in South Africa. SA Journal of Industrial Psychology, 32(<reflink idref="bib4" id="ref1">4</reflink>):76–86, 2006. https://hdl.handle.net/10520/EJC89107), Capability Set for Work Questionnaire (Abma et al., Scandinavian Journal Work, Environment and Health 42:34–42, 2016), Work Engagement Scale (Rautenbach and Rothmann, Journal of Psychology in Africa 27:303–309, 2017), and Intention to Leave Scale (Sjöberg and Sverke, Scandinavian Journal of Psychology 41:247–252, 2000) were administered. Latent profile analyses resulted in four job demands-resources profiles: high demands-low resources (33.18%), moderate demands-high resources (17.17%), moderate demands-low job resources (30.39%), and moderate demands-moderate resources (19.3%). Early childhood practitioners who were in moderate demands-high resources (rather than high demands-low resources or moderate demands-low job resources) jobs and had a robust capability set showed high work engagement and low intentions to leave their jobs. Job demands-resources profiles indirectly affected early childhood development practitioners' work engagement and intentions to leave via their capability sets.</p> <p>Keywords: Job demands; Job resources; Work capabilities; Functionings; Work engagement; Intention to leave; Early childhood education</p> <hd id="AN0191573913-2">Introduction</hd> <p>High-quality early childhood development (ECD) is widely acknowledged as enhancing children's development and affecting their adult well-being (Harrison, [<reflink idref="bib29" id="ref2">29</reflink>]; Reynolds et al., [<reflink idref="bib50" id="ref3">50</reflink>]). In South Africa, an early childhood development practitioner (ECDP) is "an individual who provides ECD programmes" (Department of Basic Education of the Republic of South Africa, [<reflink idref="bib14" id="ref4">14</reflink>], p. 4). Various ECD centers, namely government-run, private, non-governmental, faith-based, and community-based centers, are acknowledged in the Education White Paper 5 on Early Childhood Education in South Africa (Department of Education, [<reflink idref="bib12" id="ref5">12</reflink>]). According to the Department of Social Development ([<reflink idref="bib13" id="ref6">13</reflink>]), ECD programs encompass a range of services to facilitate care, development, and early learning from birth until children enter formal schooling. Early childhood development practitioners are critical in providing high-quality care and education (Lipscomb et al., [<reflink idref="bib37" id="ref7">37</reflink>]). Therefore, finding ways to harness, retain, and engage ECDPs is vital (Venter, [<reflink idref="bib65" id="ref8">65</reflink>]).</p> <p>The quality of ECD depends on how suitably trained, qualified, motivated, and engaged the ECDPs are (Harrison, [<reflink idref="bib29" id="ref9">29</reflink>]). However, the workforce may experience the ECD sector as stressful, with the inherent requirements of the job affecting their engagement and retention (Farewell et al., [<reflink idref="bib17" id="ref10">17</reflink>]). Poverty, inequality, and inadequate resources hinder early childhood development programs in South Africa (Visser et al., [<reflink idref="bib66" id="ref11">66</reflink>]). In 2020/21, only 0.5% of public expenditure and 0.15% of the gross domestic product (GDP) were allocated to these programs (Dulvy et al., [<reflink idref="bib16" id="ref12">16</reflink>]). Seventy-eight per cent of ECDPs lack proper training, and they face high job demands due to a 1:31 practitioner-to-children ratio, insufficient resources, poor infrastructure, and deprived child backgrounds (Baloyi & Makhubele, [<reflink idref="bib5" id="ref13">5</reflink>]). Additionally, poor government management exacerbates these issues (Smit et al., [<reflink idref="bib60" id="ref14">60</reflink>]; Visser et al., [<reflink idref="bib66" id="ref15">66</reflink>]).</p> <p>Internationally, and in South Africa, the jobs of ECDPs are often characterized by low pay and poor working conditions, e.g., long working hours, emotional demands, low control, and a high risk of infectious disease (Farewell et al., [<reflink idref="bib17" id="ref16">17</reflink>]; Visser et al., [<reflink idref="bib66" id="ref17">66</reflink>]). These challenging conditions relate to a high risk for injuries and other occupational hazards that can have an impact on employees' psychological, emotional, and physical health and may also affect the turnover rate (Farewell et al., [<reflink idref="bib17" id="ref18">17</reflink>]). Totenhagen et al. ([<reflink idref="bib62" id="ref19">62</reflink>]) reported that the national ECD workforce turnover rate in the United States varied between 24 and 40% annually. While high employee turnover has been attributed to low pay and poor benefits, compensation is not the only indicator of high turnover (Wells, [<reflink idref="bib68" id="ref20">68</reflink>]). Early childhood development practitioners' primary duties involve providing infants and toddlers with a stimulating, caring, inclusive, safe, and hygienic milieu (Chepsiror, [<reflink idref="bib8" id="ref21">8</reflink>]). The ECD workforce, especially those serving from birth to age five, is often described as "under-professionalized, under-valued and under-compensated" (Kwon et al., [<reflink idref="bib33" id="ref22">33</reflink>], p. 1). However, this workforce has a substantial impact on society, and it is, thus, crucial to understand and address the factors contributing to ECDP engagement and retention (Chepsiror, [<reflink idref="bib8" id="ref23">8</reflink>]; Harrison, [<reflink idref="bib29" id="ref24">29</reflink>]; Lipscomb et al., [<reflink idref="bib37" id="ref25">37</reflink>]).</p> <p>The job demands-resources (JD-R) model has been used to study employees' engagement and retention in different jobs and organizational contexts (Kwon et al., [<reflink idref="bib32" id="ref26">32</reflink>]). The central proposition of the JD-R model is that all jobs have specific demands and resources. An imbalance of job demands and job resources can influence ECDPs' decisions to engage or leave the profession (Conley & You, [<reflink idref="bib9" id="ref27">9</reflink>]). However, questions are raised regarding the application of the JD-R model. Firstly, scientific information regarding the combination of job demands and resources affecting ECDPs' work engagement and intentions to leave is lacking. Secondly, while the JD-R model contributes to understanding the complexities of ECDPs' work, recent studies (Barnard et al., [<reflink idref="bib6" id="ref28">6</reflink>]; Murangi et al., [<reflink idref="bib43" id="ref29">43</reflink>]) have shown that considering work capabilities is essential to understanding the effects of job demands and resources on individual and organizational outcomes (Buzzelli, [<reflink idref="bib7" id="ref30">7</reflink>]).</p> <p>This study links ECDPs' job demands and resources with their functioning (i.e., work engagement and intention to leave) via their work capabilities (Murangi et al., [<reflink idref="bib43" id="ref31">43</reflink>]; Van der Klink et al., [<reflink idref="bib64" id="ref32">64</reflink>]). The uniqueness of the study is that it investigates JD-R profiles using a person-centered rather than a variable-centered approach (see Murangi et al., [<reflink idref="bib43" id="ref33">43</reflink>]; Van den Broeck et al., [<reflink idref="bib63" id="ref34">63</reflink>]). Aligned with a person-centered approach, we argue that naturally occurring patterns between demands and resources can be categorized and explained by profiling the ECDPs rather than analyzing different job demands and resources in isolation using a variable-centered approach. Variable-centered studies of job demands and resources have been conducted in educational contexts in Southern Africa, primarily focusing on educators in primary and secondary schools (Janik & Rothmann, [<reflink idref="bib31" id="ref35">31</reflink>]; Murangi et al., [<reflink idref="bib43" id="ref36">43</reflink>]). However, the relationships between JD-R profiles, capabilities, and the functioning of ECDPs in South Africa have not been explored. This study aims to fill this gap in the literature by examining the associations between JD-R profiles, work capabilities, and individual and organizational outcomes (see Gloss et al., [<reflink idref="bib21" id="ref37">21</reflink>]; Murangi et al., [<reflink idref="bib43" id="ref38">43</reflink>]).</p> <hd id="AN0191573913-3">Job Demands and Resources: Towards a Person-Centered Perspective</hd> <p>The job demands-resources (JD-R) model (Demerouti et al., [<reflink idref="bib11" id="ref39">11</reflink>]) holds that all jobs have demands and resources, affecting two psychological processes: stress and motivation. A lack of job resources and high demands trigger stress (Bakker & Demerouti, [<reflink idref="bib4" id="ref40">4</reflink>]). Ample resources ignite motivation and, through work engagement, lead to outstanding performance and organizational commitment (Schaufeli, [<reflink idref="bib54" id="ref41">54</reflink>]). <emph>Job demands</emph> refer to "aspects of the job that require sustained physical or mental effort and are therefore associated with certain physiological and psychological costs" (Demerouti et al., [<reflink idref="bib11" id="ref42">11</reflink>], p. 501). <emph>Job resources</emph> are described as "aspects of the job that may do any of the following: (a) be functional in achieving work goals; (b) reduce job demands and the associated physiological and psychological costs; (c) stimulate personal growth and development" (Demerouti et al., [<reflink idref="bib11" id="ref43">11</reflink>], p. 501).</p> <p>Many scholars have used the JD-R model to predict work engagement (Hakanen et al., [<reflink idref="bib26" id="ref44">26</reflink>]; Lee et al., [<reflink idref="bib34" id="ref45">34</reflink>]; Xanthopoulou et al., [<reflink idref="bib71" id="ref46">71</reflink>]). These studies have shown that job demands and resources are crucial elements linked to employees' work engagement. Hakanen et al. ([<reflink idref="bib27" id="ref47">27</reflink>]) found that job demands caused teacher burnout, while job resources resulted in engagement. According to Hakanen et al. ([<reflink idref="bib27" id="ref48">27</reflink>]), job resources can protect employees against the negative effects of job demands. Kwon et al. ([<reflink idref="bib32" id="ref49">32</reflink>]) used the JD-R model as a conceptual framework for studying the well-being of ECDPs. They reported low wages, limited access to employer-provided health insurance, substantial physical work demands, and various work-related stressors. Linnan et al. ([<reflink idref="bib36" id="ref50">36</reflink>]) and Farewell et al. ([<reflink idref="bib17" id="ref51">17</reflink>]) found that job demands (e.g., work overload) and a lack of job resources (e.g., salary and working conditions, job control, role clarity, and supervisor relations) challenged ECDPs' well-being. Despite having limited access to resources at work, the ECD workforce seems to have a strong work ethic and commitment. Research by Dicke et al. ([<reflink idref="bib15" id="ref52">15</reflink>]) showed that supervisor support and information access were important job resources for teachers. Aldridge and Fraser ([<reflink idref="bib2" id="ref53">2</reflink>]) and Lee and Quek ([<reflink idref="bib35" id="ref54">35</reflink>]) reported that relationships with colleagues and managers were critical to the well-being of ECDPs.</p> <p>Most studies on the JD-R model have adopted a variable-centered approach (Bakker & Demerouti, [<reflink idref="bib3" id="ref55">3</reflink>]). According to Van den Broeck et al. ([<reflink idref="bib63" id="ref56">63</reflink>]), the co-occurrence of job demands and resources, as in previous empirical studies, showed different outcomes (positive, negative, and non-significant) of the relationships between job demands and job resources. A person-centered approach may reveal the relationship between job demands and resources and demonstrate to what extent resources can limit the escalation of job demands (Van den Broeck et al., [<reflink idref="bib63" id="ref57">63</reflink>]). A person-centered approach may provide insights into the intricate joint outcomes of job demands and resources (Murangi et al., [<reflink idref="bib43" id="ref58">43</reflink>]).</p> <p>Granziera et al. ([<reflink idref="bib24" id="ref59">24</reflink>]) studied the well-being of teachers using both variable- and person-centered approaches based on JD-R theory. In their person-centered analysis, they identified four distinctive profiles, labeled as follows: adaptive profile (high resources and low role conflict), maladaptive profile (low resources and high role conflict), average profile (average levels of resources and demands), and mixed resourced profile (slightly higher useful collaboration, slightly lower role conflict, near-average self-efficacy, and high useful professional development and adaptability).</p> <hd id="AN0191573913-4">The Added Value of Work Capabilities to the JD-R Model</hd> <p>Considering ECDPs' work capabilities as conceptualized in the capability approach (CA) (Van der Klink et al., [<reflink idref="bib64" id="ref60">64</reflink>]) adds value to understanding the effects of job demands and resources on ECDPs' work engagement and intentions to leave. Work capabilities refer to a person's freedoms or opportunities to achieve functionings (Robeyns, [<reflink idref="bib51" id="ref61">51</reflink>]).</p> <p>The CA (Nussbaum, [<reflink idref="bib46" id="ref62">46</reflink>]; Sen, [<reflink idref="bib57" id="ref63">57</reflink>]) emphasizes what individuals are able to do and to be – their real freedoms and opportunities. It goes beyond the provision of resources to consider how those resources enable individuals to achieve meaningful and valued outcomes in their lives (Van der Klink et al., [<reflink idref="bib64" id="ref64">64</reflink>]). While job resources (such as supervisor support, relationships with co-workers, and role clarity) are important because they can enhance work engagement and retention of employees, they do not necessarily reflect whether individuals can convert these resources into valued functioning and outcomes. Focusing on capabilities makes it possible to better understand how individuals use available resources to achieve their personal and professional goals (Robeyns, [<reflink idref="bib51" id="ref65">51</reflink>]). This perspective highlights the role of individual agency, empowerment, and the ability to make choices that affect individuals' work attitudes and behaviors (Van der Klink et al., [<reflink idref="bib64" id="ref66">64</reflink>]). Although the JD-R model is highly relevant to understanding the effects of work attitudes and behaviors, considering only job resources might overlook the variations in how individuals utilize these resources based on their personal values, contexts, and skills (Gloss et al., [<reflink idref="bib21" id="ref67">21</reflink>]).</p> <p>We argue that the CA can add value beyond the JD-R model. First, the JD-R model may overlook individual differences and needs by focusing broadly on job demands and resources, potentially leading to a one-size-fits-all approach. In contrast, the CA emphasizes the intrinsic value of each person (Robeyns, [<reflink idref="bib51" id="ref68">51</reflink>]) and treats individuals as ends in themselves rather than means to an end (Orton, [<reflink idref="bib47" id="ref69">47</reflink>]; Sen, [<reflink idref="bib56" id="ref70">56</reflink>]). Recognizing people as ends in themselves involves acknowledging and addressing their unique work capabilities, i.e., their values, enablements, and achievements (Van der Klink et al., [<reflink idref="bib64" id="ref71">64</reflink>]). Secondly, there is a pressing need for social justice interventions regarding ECDP jobs. While job resources are crucial, they may not fully capture individuals' structural and systemic barriers in different contexts. This involves advocating for better pay, improving working conditions, ensuring professional recognition, providing access to ongoing professional development, and establishing robust support systems and policies. The CA provides a relevant social justice framework (Nussbaum, [<reflink idref="bib46" id="ref72">46</reflink>]; Sen, [<reflink idref="bib58" id="ref73">58</reflink>]) and a moral guide for conducting social justice interventions by focusing on work capabilities. In the third place, capabilities offer a way to parsimoniously incorporate psychological and socio-structural empowerment of ECDPs (Maynard et al., [<reflink idref="bib39" id="ref74">39</reflink>]). Social-structural and psychological aspects of empowerment are strongly associated with work capabilities (Gloss et al., [<reflink idref="bib21" id="ref75">21</reflink>]).</p> <p>The conceptualization and measurement of capabilities have been identified as the most pressing challenges for the CA (Gloss et al., [<reflink idref="bib21" id="ref76">21</reflink>]). Developing a list of relevant capabilities may involve combining a list derived deductively with a list derived inductively. Empirically validated taxonomies of capabilities, needs, values, and goals could inform the list of capabilities (e.g., Abma et al., [<reflink idref="bib1" id="ref77">1</reflink>]; Gheaus & Herzog, [<reflink idref="bib20" id="ref78">20</reflink>]; Grouzet et al., [<reflink idref="bib25" id="ref79">25</reflink>]; Prilleltensky & Prilleltensky, [<reflink idref="bib48" id="ref80">48</reflink>]; Ryan et al., [<reflink idref="bib53" id="ref81">53</reflink>]). A study by Abma et al. ([<reflink idref="bib1" id="ref82">1</reflink>]) identified seven work values in a capability set, namely, using knowledge and skills, developing new knowledge and skills, involvement in decision-making, building and maintaining meaningful relationships at work, setting own goals, earning a good income, and contributing something valuable. Work values that are enabled and achieved become capabilities (Abma et al., [<reflink idref="bib1" id="ref83">1</reflink>]; Van der Klink et al., [<reflink idref="bib64" id="ref84">64</reflink>]).</p> <hd id="AN0191573913-5">Functionings: Work Engagement and Intention to Leave</hd> <p>A functioning is "the various things a person may value doing or being" (Sen, [<reflink idref="bib57" id="ref85">57</reflink>], p. 75). The functioning of the ECDPs affects each young child's life, the institution where they work, and the community and society in which they operate. Work engagement and intention to leave are critical functionings that affect the outcomes of the ECD environment.</p> <p>Work engagement refers to a strong feeling of fulfilling connectedness to one's work that involves high energy levels and a positive association with one's work. It is a psychological state of being invested in one's work and integrates vigor, dedication, and absorption. <emph>Vigor</emph> refers to resilience and energy levels, while <emph>dedication</emph> is the pride, meaningfulness, and enthusiasm that the work brings out in the individual, and <emph>absorption</emph> implies the employees' concentration and being happily captivated by work-related activities. Vigor and dedication are regarded as core aspects of the work engagement construct, whereas absorption functions as an outcome of engagement (González-Romá et al., [<reflink idref="bib22" id="ref86">22</reflink>]; Lipscomb et al., [<reflink idref="bib37" id="ref87">37</reflink>]; Mazzetti et al., [<reflink idref="bib40" id="ref88">40</reflink>]; Schaufeli & Bakker, [<reflink idref="bib55" id="ref89">55</reflink>]). Work engagement is a major predictor of intent to stay in the ECD field, job satisfaction, and organizational citizen conduct. Furthermore, it is the only factor that predicts intent to remain in the teaching field for older and younger teachers (Lipscomb et al., [<reflink idref="bib37" id="ref90">37</reflink>]; Tayama et al., [<reflink idref="bib61" id="ref91">61</reflink>]). The study of Lipscomb et al. ([<reflink idref="bib37" id="ref92">37</reflink>]) assessed work engagement as a positive dimension of employee well-being among ECDPs across different home-based and center-based workplaces.</p> <p>The relationship between ECDPs and young children is a special bond, and practitioner turnover can be disruptive and have an adverse effect not only on the practitioner-child relationship (Lipscomb et al., [<reflink idref="bib37" id="ref93">37</reflink>]), but also on the parents of the affected children, the co-workers of those who leave, the institution itself, and the recruitment process (Kwon et al., [<reflink idref="bib33" id="ref94">33</reflink>]). According to Kwon et al. ([<reflink idref="bib33" id="ref95">33</reflink>]), 90% of participants in their study indicated that their workplaces experienced turnover issues. Predictors of intention to leave that were investigated included the following: individual attributes, including stress, poor well-being, and job-related characteristics, such as low compensation; poor working conditions; poor relationships with children, families, or co-workers; and workplace instability (Hall-Kenyon et al., [<reflink idref="bib28" id="ref96">28</reflink>]; Wells, [<reflink idref="bib68" id="ref97">68</reflink>]; Whitebook & Sakai, [<reflink idref="bib70" id="ref98">70</reflink>]). Early childhood development practitioners with a negative experience of their working environment are likely to seek another childcare center or a different career field to experience a more positive environment (Grant et al., [<reflink idref="bib23" id="ref99">23</reflink>]). Moreover, ECDPs who report high stress levels and emotional exhaustion show a greater inclination to leave rather than stay.</p> <p>The study by Kwon et al. ([<reflink idref="bib33" id="ref100">33</reflink>]) showed that two-thirds of their participants had mixed feelings about leaving or staying in their work in the ECD environment. Participants in Kwon et al.,'s [<reflink idref="bib33" id="ref101">33</reflink>] study reported that their decisions had changed several times during their tenure at work, depending on their situation and working conditions. Their study found that ECDPs' reasons to leave or stay were multifaceted, as they were not based on only one reason. Deciding to leave was fluid, as individuals constantly assessed their current circumstances and working conditions. The same study also identified five themes on which the decision to leave was based: the nature of their work; conflict, tension, and a negative work environment; feeling about change; pay and benefits; and having to move or spend time at home with family members (Kwon et al., [<reflink idref="bib33" id="ref102">33</reflink>], p. 5).</p> <hd id="AN0191573913-6">Current Study</hd> <p>This study investigated the JD-R profiles of the ECD workforce in South Africa. Furthermore, it explored how the different profiles related to the work capabilities and functionings of the ECD workforce (i.e., work engagement and intention to leave). The following hypotheses were proposed:</p> <hd id="AN0191573913-7">Hypothesis 1</hd> <p>A JD-R profile with moderate job demands and high job resources is statistically significantly and positively associated with ECDPs' capability set (Hypothesis 1a) and work engagement (Hypothesis 1b) and statistically significantly and negatively associated with ECDPs' intentions to leave (Hypothesis 1c).</p> <hd id="AN0191573913-8">Hypothesis 2</hd> <p>ECDPs' capability set is statistically significantly and positively associated with work engagement (Hypothesis 2a) and negatively associated with intentions to leave (Hypothesis 2b).</p> <hd id="AN0191573913-9">Hypothesis 3</hd> <p>A JD-R profile with moderate job demands and high job resources indirectly affects work engagement positively via ECDPs' capability set (Hypothesis 3a) and indirectly and negatively affects the intention to leave via their capability set (Hypothesis 3b).</p> <hd id="AN0191573913-10">Method</hd> <p></p> <hd id="AN0191573913-11">Participants</hd> <p>Table 1 portrays the demographic characteristics of the participants. The sampling population of this study comprised districts within the Gauteng and North West provinces.</p> <p>Table 1 Characteristics of the participants (N = 436)</p> <p> <ephtml> <table rules="groups"><thead><tr><th align="left"><p>Variable</p></th><th align="left"><p>Grouping</p></th><th align="left"><p><italic>n</italic></p></th><th align="left"><p>%</p></th><th align="left"><p>Variable</p></th><th align="left"><p>Grouping</p></th><th align="left"><p><italic>n</italic></p></th><th align="left"><p>%</p></th></tr></thead><tbody><tr><td align="left" rowspan="4"><p>Gender</p></td><td align="left"><p>Female</p></td><td align="left"><p>419</p></td><td align="left"><p>96.10</p></td><td align="left" rowspan="9"><p>Age</p></td><td align="left"><p>17 to 19</p></td><td align="left"><p>6</p></td><td align="left"><p>1.38</p></td></tr><tr><td align="left"><p>Male</p></td><td align="left"><p>4</p></td><td align="left"><p>0.90</p></td><td align="left"><p>20 to 29</p></td><td align="left"><p>83</p></td><td align="left"><p>19.04</p></td></tr><tr><td align="left"><p>Missing values</p></td><td align="left"><p>13</p></td><td align="left"><p>3.00</p></td><td align="left"><p>30 to 39</p></td><td align="left"><p>96</p></td><td align="left"><p>22.02</p></td></tr><tr><td align="left" /><td align="left" /><td align="left" /><td align="left"><p>40 to 49</p></td><td align="left"><p>83</p></td><td align="left"><p>19.04</p></td></tr><tr><td align="left" rowspan="4"><p>Province</p></td><td align="left"><p>North West</p></td><td align="left"><p>210</p></td><td align="left"><p>48.20</p></td><td align="left"><p>50 to 59</p></td><td align="left"><p>63</p></td><td align="left"><p>14.45</p></td></tr><tr><td align="left"><p>Gauteng</p></td><td align="left"><p>223</p></td><td align="left"><p>51.10</p></td><td align="left"><p>60 to 65</p></td><td align="left"><p>10</p></td><td align="left"><p>2.29</p></td></tr><tr><td align="left"><p>Missing values</p></td><td align="left"><p>3</p></td><td align="left"><p>0.70</p></td><td align="left"><p>Older than 65</p></td><td align="left"><p>2</p></td><td align="left"><p>0.46</p></td></tr><tr><td align="left" /><td align="left" /><td align="left" /><td align="left" rowspan="2"><p>Missing values</p></td><td align="left" rowspan="2"><p>93</p></td><td align="left"><p>21.33</p></td></tr><tr><td align="left" rowspan="6"><p>Race</p></td><td align="left"><p>Black</p></td><td align="left"><p>285</p></td><td align="left"><p>65.40</p></td><td align="left" /></tr><tr><td align="left"><p>White</p></td><td align="left"><p>103</p></td><td align="left"><p>23.60</p></td><td align="left" rowspan="5"><p>Employment status</p></td><td align="left"><p>Casual work</p></td><td align="left"><p>24</p></td><td align="left"><p>5.50</p></td></tr><tr><td align="left"><p>Colored</p></td><td align="left"><p>39</p></td><td align="left"><p>8.90</p></td><td align="left"><p>Full-time</p></td><td align="left"><p>366</p></td><td align="left"><p>83.95</p></td></tr><tr><td align="left"><p>Indian</p></td><td align="left"><p>2</p></td><td align="left"><p>0.50</p></td><td align="left"><p>Part-time</p></td><td align="left"><p>27</p></td><td align="left"><p>6.19</p></td></tr><tr><td align="left"><p>Other</p></td><td align="left"><p>4</p></td><td align="left"><p>0.90</p></td><td align="left"><p>Self-employed</p></td><td align="left"><p>14</p></td><td align="left"><p>3.21</p></td></tr><tr><td align="left"><p>Missing values</p></td><td align="left"><p>3</p></td><td align="left"><p>0.70</p></td><td align="left"><p>Missing values</p></td><td align="left"><p>5</p></td><td align="left"><p>1.15</p></td></tr><tr><td align="left" rowspan="6"><p>Tenure at current center</p></td><td align="left"><p>Less than 6 months</p></td><td align="left"><p>62</p></td><td align="left"><p>14.20</p></td><td align="left" rowspan="6"><p>Job level</p></td><td align="left"><p>Top management</p></td><td align="left"><p>23</p></td><td align="left"><p>5.30</p></td></tr><tr><td align="left"><p>6 months to 2 years</p></td><td align="left"><p>111</p></td><td align="left"><p>25.50</p></td><td align="left"><p>Supervisor</p></td><td align="left"><p>14</p></td><td align="left"><p>3.20</p></td></tr><tr><td align="left"><p>3 to 5 years</p></td><td align="left"><p>96</p></td><td align="left"><p>22.00</p></td><td align="left"><p>ECDP</p></td><td align="left"><p>249</p></td><td align="left"><p>57.10</p></td></tr><tr><td align="left"><p>6 to 10 years</p></td><td align="left"><p>77</p></td><td align="left"><p>17.70</p></td><td align="left"><p>Assistant ECDP</p></td><td align="left"><p>78</p></td><td align="left"><p>17.90</p></td></tr><tr><td align="left"><p>More than 10 years</p></td><td align="left"><p>81</p></td><td align="left"><p>18.60</p></td><td align="left"><p>ECD administration</p></td><td align="left"><p>17</p></td><td align="left"><p>3.90</p></td></tr><tr><td align="left"><p>Missing values</p></td><td align="left"><p>9</p></td><td align="left"><p>2.10</p></td><td align="left"><p>Other</p></td><td align="left"><p>55</p></td><td align="left"><p>12.61</p></td></tr><tr><td align="left" rowspan="6"><p>Highest qualification</p></td><td align="left"><p>Lower than Grade 12</p></td><td align="left"><p>65</p></td><td align="left"><p>14.90</p></td><td align="left" rowspan="9"><p>Institution type</p></td><td align="left"><p>Public school</p></td><td align="left"><p>160</p></td><td align="left"><p>36.70</p></td></tr><tr><td align="left"><p>Grade 12</p></td><td align="left"><p>111</p></td><td align="left"><p>25.50</p></td><td align="left"><p>Private school</p></td><td align="left"><p>164</p></td><td align="left"><p>37.60</p></td></tr><tr><td align="left"><p>1-year vocation certificate</p></td><td align="left"><p>44</p></td><td align="left"><p>10.10</p></td><td align="left"><p>Non-governmental organization (NGO)/Non-profit organization (NPO)</p></td><td align="left"><p>69</p></td><td align="left"><p>15.80</p></td></tr><tr><td align="left"><p>Diploma/Degree (or higher)</p></td><td align="left"><p>153</p></td><td align="left"><p>35.10</p></td><td align="left"><p>Other</p></td><td align="left"><p>35</p></td><td align="left"><p>8.00</p></td></tr><tr><td align="left"><p>Other</p></td><td align="left"><p>56</p></td><td align="left"><p>12.80</p></td><td align="left" rowspan="5"><p>Missing values</p></td><td align="left" rowspan="5"><p>8</p></td><td align="left" rowspan="5"><p>1.80</p></td></tr><tr><td align="left"><p>Missing values</p></td><td align="left"><p>7</p></td><td align="left"><p>1.60</p></td></tr><tr><td align="left" rowspan="3"><p>Union</p></td><td align="left"><p>Yes</p></td><td align="left"><p>98</p></td><td align="left"><p>22.5</p></td></tr><tr><td align="left"><p>No</p></td><td align="left"><p>329</p></td><td align="left"><p>75.5</p></td></tr><tr><td align="left"><p>Missing values</p></td><td align="left"><p>9</p></td><td align="left"><p>2.1</p></td></tr></tbody></table> </ephtml> </p> <p>Most of the participants were female (96%). Concerning age, it was noted that 21.3% of the participants opted not to declare their age. Of those who declared their age, the participants under 40 accounted for 42.44% of the total group of participants, while 36.2% were 40 years and older. Regarding employment status, almost 84% indicated that they were permanently employed, while 11.7% indicated that they worked casually or part time. Regarding qualifications, 13.5% of the participants indicated that they had a qualification less than Grade 12, while those with Grade 12 comprised 25.5%. Furthermore, 29.8% indicated a three-year diploma or degree, and 10.1% revealed a one-year vocational qualification. Early childhood development practitioners comprised 57.1% of the participants, and 17.9% were assistant ECDPs. The tenure at the current center showed that 61% of the participants had been employed there for five years or less, and almost 40% had been employed for less than two years. Participants from public schools comprised 36.7%, those from private schools made up 37.6%, and participants from NPOs and other institutions made up 23.8%. A total of 75.5% of the participants did not belong to a union.</p> <hd id="AN0191573913-12">Measuring Instruments</hd> <p>This study used four measuring instruments: an adapted version of the Job Demands-Resources Scale, the Capability Set for Work Questionnaire, the Work Engagement Scale, and the Intention to Leave Questionnaire.</p> <p>An adapted version of the <emph>Job Demands-Resources Scale</emph> (JDRS) (Rothmann et al., [<reflink idref="bib52" id="ref103">52</reflink>]) was used to measure job demands and resources as perceived by ECDPs. The adapted JDRS contains 22 items. These items include the following: the pace and amount of work and mental load (four items, e.g., "Do you have too much work to do?"); emotional load (three items, e.g., "Does your work put you in emotionally upsetting situations?"); relationships with colleagues (three items, e.g., "Do you get on well with your colleagues?"); relationship with immediate supervisor (three items, e.g., "Can you count on your supervisor when you come across difficulties in your work?"); role clarity (three items, e.g., "Do you know exactly for what you are responsible and which areas are not your responsibility?"); access to information (three items, e.g., "Do you receive sufficient information on the purpose of your work?"); and job insecurity (three items, e.g., "Do you need to be more secure that you will keep your current job in the next year?"). The items are rated on a five-point scale, ranging from 1 (<emph>never</emph>) to 5 (<emph>always</emph>). Rothmann et al. ([<reflink idref="bib52" id="ref104">52</reflink>]) established the construct validity and measurement invariance of the JDRS. The internal consistency of this instrument ranged from 0.76 to 0.92 (Rothmann et al., [<reflink idref="bib52" id="ref105">52</reflink>]), signifying the acceptable reliability of the subscales of the JDRS.</p> <p>The <emph>Capability Set for Work Questionnaire</emph> (CSWQ) (Abma et al., [<reflink idref="bib1" id="ref106">1</reflink>]) was administered to establish work values, enablement, and ability to achieve (three components of the capability set) in terms of the following dimensions: (a) use of knowledge and skills; (b) development of knowledge and skills; (c) involvement in important decisions; (d) building and maintaining meaningful contacts at work; (e) setting own goals; (f) earning a good income; and (g) contributing to something valuable. A worker's capability set is determined based on whether each aspect is considered valuable, enabled, and realized (e.g., "It is important for me to be able to use my knowledge and skills in my work", "I have enough opportunity in my work to use my knowledge and skills", and "I regularly succeed in using my knowledge and skills in my work"). Five response options range from 1 (<emph>not at all</emph>) to 5 (<emph>very much so</emph>). Abma et al. ([<reflink idref="bib1" id="ref107">1</reflink>]) uncovered that the capability set and the overall capability items were significantly related to work functioning.</p> <p>The Work Engagement Scale was extracted from the <emph>Flourishing at Work Scale – Short Form</emph> (FAWS-SF) (Rautenbach & Rothmann, [<reflink idref="bib49" id="ref108">49</reflink>]). Three items gauged engagement (e.g., "During the past month at work, how often did you feel energized when you worked?"). The scale ranges from 1 (<emph>never</emph>) to 6 (<emph>every day</emph>). Participants account for the frequency of specific aspects within the three dimensions of well-being of workplace occurrences during the past month. Rautenbach and Rothmann ([<reflink idref="bib49" id="ref109">49</reflink>]) found an internal consistency of 0.82 to 0.90, indicating acceptable reliability of the work engagement scale obtained from the FAWS-SF.</p> <p>The <emph>Intention to Leave Questionnaire</emph> (ILQ) (Sjöberg & Sverke, [<reflink idref="bib59" id="ref110">59</reflink>]) assessed ECDPs' intentions to leave. The ILQ consists of three items (e.g., "I am actively looking for other jobs"). The scale ranges from 1 (<emph>totally disagree</emph>) to 6 (<emph>totally agree</emph>). Moller and Rothmann ([<reflink idref="bib42" id="ref111">42</reflink>]) used this questionnaire in the South African context on managers from agribusiness and found a Cronbach's alpha coefficient of 0.83, an acceptable reliability score.</p> <hd id="AN0191573913-13">Research Procedure</hd> <p>The research proposal was submitted to the Research Committee, and the ethics clearance application was presented to the Economic and Management Sciences' Ethics Committee at North-West University. Ethics clearance was granted, and Ethics Number NWU-00918–21-A4 was issued. When the gatekeepers (the Department of Basic Education in Gauteng and North West) granted permission, the questionnaire was finalized, and an expert meeting was convened. After that, the collection phase commenced. The provisions and requirements of the gatekeepers were strictly adhered to. Research assistants were recruited and trained to collect data and overcome possible language barriers. The research assistants were trained and collected data with the researcher under her supervision. It was challenging to obtain responses only via the online system. Hence, the study employed online and physically administered hard-copy (printed) questionnaires. The response rate of physical administration of the hard copy of the questionnaire yielded a better response rate. Participants had to give informed consent, formally and in writing, and the participants were given assurance that the data would be kept confidential and anonymous.</p> <hd id="AN0191573913-14">Statistical Analyses</hd> <p>The Mplus 8.8 program (Muthén & Muthén, [<reflink idref="bib44" id="ref112">44</reflink>]–2018) was used for latent profile analysis (LPA) to determine the JD-R profiles. For the LPA models, several steps were followed: (a) the optimal number of latent profiles, (b) the classification of the latent profiles, (c) the labeling of the latent profiles, and (d) predictions about latent profile membership. Several models were evaluated with increasing latent profiles. When a model improved over the reference model, it was retained.</p> <p>To compare the models, the Akaike information criterion (AIC), Bayesian information criterion (BIC), and sample-size adjusted BIC (ABIC) were used. Selected models with the lowest AIC, BIC, and ABIC values were used. Geiser ([<reflink idref="bib19" id="ref113">19</reflink>]) used BIC values to determine the number of classes. For latent profile analyses, the entropy value equals 1; less than 0.60 signifies an unacceptable classification (Geiser, [<reflink idref="bib19" id="ref114">19</reflink>]). A combined analysis of the Lo-Mendell-Rubin (LMR LR) (Lo et al., [<reflink idref="bib38" id="ref115">38</reflink>]), adjusted LMR LR (ALMR), and bootstrapped likelihood ratio test (BLRT) (Wang & Wang, [<reflink idref="bib67" id="ref116">67</reflink>]) was conducted. According to Geiser ([<reflink idref="bib19" id="ref117">19</reflink>]), latent profile assignment probabilities should be considered for each participant. Solutions are considered viable when they have a main diagonal value greater than 0.80.</p> <p>Confirmatory factor analysis (CFA) was used in Mplus 8.8 (Muthén & Muthén, [<reflink idref="bib44" id="ref118">44</reflink>]–2018) to test a measurement model of job demands and resources. A robust maximum likelihood estimator (MLR) was used. Model fit was evaluated using the chi-square value (χ<sups>2</sups>), comparative fit index (CFI), Tucker‒Lewis index (TLI), standardized root mean residual (SRMR), and root mean square error of approximation (RMSEA) (West et al., [<reflink idref="bib69" id="ref119">69</reflink>]). CFI and TLI values are recommended to exceed 0.90. Scores above 0.95 indicate an excellent fit. Model-data fit is indicated by RMSEA and SRMR values below 0.08 (West et al., [<reflink idref="bib69" id="ref120">69</reflink>]). AIC and BIC were used to assess alternative measurement models. Models with the lowest AIC and BIC indicate the best fit. In addition, SPSS 27.0 (IBM Corp., [<reflink idref="bib10" id="ref121">10</reflink>]) was applied to calculate the descriptive statistics.</p> <p>The variables were correlated using Pearson correlation coefficients. Multiple regression analyses were conducted to determine the effects of job demands, resource profiles, and capabilities on work engagement and intentions to leave. Mplus 8.8 (Muthén & Muthén, [<reflink idref="bib44" id="ref122">44</reflink>]–2018) was used to perform simple mediation analyses (Hayes, [<reflink idref="bib30" id="ref123">30</reflink>]).</p> <hd id="AN0191573913-15">Results</hd> <p></p> <hd id="AN0191573913-16">Confirmatory Factor Analysis</hd> <p>Confirmatory factor analysis was employed to test the fit of the measurement model of the JDRS and the work engagement and intention to leave scales. Model 1a consisted of seven (first-order) latent variables indicating job demands and resources: (a) work overload (four items); (b) emotional demands (three items); (c) co-worker relationships (three items); (d) relationship with supervisor (three items); (e) role clarity (three items); (f) information accessibility (three items); and (g) job security (three items), work engagement (three items), and intentions to leave (three items). Model 1b consisted of two job demands and resources latent variables, namely, job demands (seven items) and job resources (15 items), and one latent variable with six items measuring work engagement and intention to leave. The models were created with 431 observations, and the model estimation terminated normally.</p> <p>Table 2 shows that Model 1a (consisting of two job demands and four job resources factors) fits the data better than Model 1b (consisting of one job demand and one job resources factor). The fit statistics of the measurement model are within an acceptable range: χ<sups>2</sups> = 9788.47 (<emph>df</emph> = 300, <emph>p</emph> < 0.01); RMSEA = 0.07 [0.06, 0.07]; CFI = 0.95; TLI = 0.94; SRMR = 0.06. All the model fit indices show acceptable fit. The standardized factor loadings are good: workload: λ = 0.66 to 0.82 (mean = 0.73); emotional load: λ = 0.67 to 0.79 (mean = 0.71); relationship with colleagues at work: λ = 0.72 to 0.80 (mean = 0.77); relationship with immediate supervisor: λ = 0.77 to 0.90 (mean = 0.82); role clarity: λ = 0.63 to 0.74 (mean = 0.64); information accessibility: λ = 0.73 to 0.86 (mean = 0.80); job insecurity: λ = 0.87 to 0.96 (mean = 0.91).</p> <p>Table 2 CFA of the JD-R and FAWS-SF (Work Engagement) and ITL (Intention to Leave)</p> <p> <ephtml> <table rules="groups"><thead><tr><th align="left"><p>Model</p></th><th align="left"><p>χ<sup>2</sup></p></th><th align="left"><p><italic>df</italic></p></th><th align="left"><p>CFI</p></th><th align="left"><p>TLI</p></th><th align="left"><p>RMSEA</p></th><th align="left"><p>SRMR</p></th></tr></thead><tbody><tr><td align="left"><p>1a</p></td><td char="." align="char"><p>615.93<sup>**</sup></p></td><td align="left"><p>188</p></td><td align="left"><p>.95</p></td><td align="left"><p>.94</p></td><td align="left"><p>.07<sup>*</sup> [.07,.08]</p></td><td align="left"><p>.06</p></td></tr><tr><td align="left"><p>1b</p></td><td char="." align="char"><p>2317.96<sup>**</sup></p></td><td align="left"><p>208</p></td><td align="left"><p>.76</p></td><td align="left"><p>.73</p></td><td align="left"><p>.15<sup>*</sup> [.15,.16]</p></td><td align="left"><p>.15</p></td></tr><tr><td align="left"><p>2a</p></td><td char="." align="char"><p>16.35<sup>**</sup></p></td><td align="left"><p>8</p></td><td align="left"><p>.99</p></td><td align="left"><p>.99</p></td><td align="left"><p>.05 [.01,.08]</p></td><td align="left"><p>.02</p></td></tr><tr><td align="left"><p>2b</p></td><td char="." align="char"><p>417.81<sup>**</sup></p></td><td align="left"><p>9</p></td><td align="left"><p>.92</p></td><td align="left"><p>.86</p></td><td align="left"><p>.33<sup>*</sup> [.30,.35]</p></td><td align="left"><p>.18</p></td></tr></tbody></table> </ephtml> </p> <p>*<emph>p</emph> <.05; **<emph>p</emph> <.01</p> <p>Table 2 also shows that Model 2a (consisting of one engagement factor and one intention to leave factor) fits the data better than Model 2b (consisting of one engagement and intention to leave factor). The fit statistics of the measurement model are within an acceptable range: χ<sups>2</sups> = 9788.47 (<emph>df</emph> = 300, <emph>p</emph> < 0.01); RMSEA = 0.07 [0.06, 0.07]; CFI = 0.95; TLI = 0.94; SRMR = 0.06. The model fit indices show acceptable fit, with highly acceptable standardized factor loadings: work engagement: λ = 0.80 to 0.91 (mean = 0.84); and intention to leave: λ = 0.80 to 0.94 (mean = 0.88).</p> <hd id="AN0191573913-17">Descriptive Statistics, Reliability, and Correlations</hd> <p>Presented in Table 3 are the omega reliabilities, means, standard deviations, and Pearson correlations for each variable in the present study. All scales obtained acceptable reliability coefficients above 0.70 (Nunnally & Bernstein, [<reflink idref="bib45" id="ref124">45</reflink>]).</p> <p>Table 3 Descriptive Statistics, Reliabilities, and Correlations of the Scales</p> <p> <ephtml> <table rules="groups"><thead><tr><th align="left" colspan="2"><p>Variable</p></th><th align="left"><p>ω</p></th><th align="left"><p>Mean</p></th><th align="left"><p><italic>SD</italic></p></th><th align="left"><p>1</p></th><th align="left"><p>2</p></th><th align="left"><p>3</p></th><th align="left"><p>4</p></th><th align="left"><p>5</p></th><th align="left"><p>6</p></th><th align="left"><p>7</p></th><th align="left"><p>8</p></th><th align="left"><p>9</p></th></tr></thead><tbody><tr><td align="left"><p>1.</p></td><td align="left"><p>Workload</p></td><td align="left"><p>.68</p></td><td align="left"><p>3.82</p></td><td align="left"><p>.86</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>2.</p></td><td align="left"><p>Emotional load</p></td><td align="left"><p>.70</p></td><td align="left"><p>2.82</p></td><td align="left"><p>1.07</p></td><td align="left"><p>.45**</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>3.</p></td><td align="left"><p>Co-worker relations</p></td><td align="left"><p>.73</p></td><td align="left"><p>4.02</p></td><td align="left"><p>.90</p></td><td align="left"><p>.04</p></td><td align="left"><p>−.14**</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>4.</p></td><td align="left"><p>Supervisor relations</p></td><td align="left"><p>.79</p></td><td align="left"><p>4.09</p></td><td align="left"><p>.98</p></td><td align="left"><p>−.06**</p></td><td align="left"><p>−.30**</p></td><td align="left"><p>.44**</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>5.</p></td><td align="left"><p>Role clarity</p></td><td align="left"><p>.61</p></td><td align="left"><p>3.98</p></td><td align="left"><p>.85</p></td><td align="left"><p>−.04</p></td><td align="left"><p>−.10*</p></td><td align="left"><p>.29**</p></td><td align="left"><p>.50**</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>6.</p></td><td align="left"><p>Information access</p></td><td align="left"><p>.79</p></td><td align="left"><p>3.77</p></td><td align="left"><p>1.06</p></td><td align="left"><p>−.02</p></td><td align="left"><p>−.19**</p></td><td align="left"><p>.25**</p></td><td align="left"><p>.57**</p></td><td align="left"><p>.61**</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>7.</p></td><td align="left"><p>Job insecurity</p></td><td align="left"><p>.90</p></td><td align="left"><p>3.71</p></td><td align="left"><p>1.30</p></td><td align="left"><p>.08</p></td><td align="left"><p>.01</p></td><td align="left"><p>.06</p></td><td align="left"><p>.14*</p></td><td align="left"><p>.11*</p></td><td align="left"><p>.23**</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>8.</p></td><td align="left"><p>Capability set</p></td><td align="left"><p>.81</p></td><td align="left"><p>.50</p></td><td align="left"><p>.33</p></td><td align="left"><p>−.15**</p></td><td align="left"><p>−.37**</p></td><td align="left"><p>.46**</p></td><td align="left"><p>.66**</p></td><td align="left"><p>.69**</p></td><td align="left"><p>.70**</p></td><td align="left"><p>.22**</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>9.</p></td><td align="left"><p>Work engagement</p></td><td align="left"><p>.81</p></td><td align="left"><p>5.35</p></td><td align="left"><p>.89</p></td><td align="left"><p>.00</p></td><td align="left"><p>−.31**</p></td><td align="left"><p>.50**</p></td><td align="left"><p>.57**</p></td><td align="left"><p>.53**</p></td><td align="left"><p>.49**</p></td><td align="left"><p>.32**</p></td><td align="left"><p>.31**</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>10.</p></td><td align="left"><p>Intention to leave</p></td><td align="left"><p>.88</p></td><td align="left"><p>2.49</p></td><td align="left"><p>1.20</p></td><td align="left"><p>.15**</p></td><td align="left"><p>.26**</p></td><td align="left"><p>−.30**</p></td><td align="left"><p>−.38**</p></td><td align="left"><p>−.36**</p></td><td align="left"><p>−.38**</p></td><td align="left"><p>−.18**</p></td><td align="left"><p>−.26**</p></td><td align="left"><p>−.48**</p></td></tr></tbody></table> </ephtml> </p> <p>**<emph>p</emph> <.01; *<emph>p</emph> <.05; <emph>r</emph> <.30 = small effect;.30 < <emph>r</emph> <.50 = medium effect;<emph> r</emph> >.50 = large effect</p> <p>Table 3 shows that the capability set is statistically significantly associated with all job resources, job demands, engagement, and intention to leave. The capability set is positively associated with co-worker relations, supervisor relations, role clarity, and information access (all large effects) and is negatively associated with emotional demands (medium effect). Work engagement is statistically significantly and negatively associated with emotional load (medium effect) and statistically significantly and positively related to all job resources (medium to large effects). Intention to leave is statistically significantly related to all job demands and resources.</p> <hd id="AN0191573913-18">Latent Profile Analysis</hd> <p>Latent profiles of job demands and resources were analyzed by applying factor scores saved from the measurement model. Table 4 illustrates the results of the six job demands and resources (JD-R) profiles.</p> <p>Table 4 Comparison of JD-R Profiles of ECDPs</p> <p> <ephtml> <table rules="groups"><thead><tr><th align="left"><p>Profile</p></th><th align="left"><p>AIC</p></th><th align="left"><p>BIC</p></th><th align="left"><p>ABIC</p></th><th align="left"><p>LMR LR (<italic>p</italic>)</p></th><th align="left"><p>ALMR LR (<italic>p</italic>)</p></th><th align="left"><p>BLRT (<italic>p</italic>)</p></th><th align="left"><p>Entropy</p></th><th align="left"><p>Smallest class membership</p></th></tr></thead><tbody><tr><td align="left"><p>1</p></td><td char="." align="char"><p>5761.49</p></td><td char="." align="char"><p>5818.42</p></td><td char="." align="char"><p>5773.99</p></td><td align="left"><p>n/a</p></td><td align="left"><p>n/a</p></td><td align="left"><p>n/a</p></td><td align="left"><p>-</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>2</p></td><td char="." align="char"><p>4817.52</p></td><td char="." align="char"><p>4906.97</p></td><td char="." align="char"><p>4837.16</p></td><td align="left"><p> <.001**</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left"><p>.89</p></td><td align="left"><p>194</p></td></tr><tr><td align="left"><p>3</p></td><td char="." align="char"><p>4410.46</p></td><td char="." align="char"><p>4532.45</p></td><td char="." align="char"><p>4437.24</p></td><td align="left"><p>.006**</p></td><td align="left"><p>.006<sup>**</sup></p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left"><p>.90</p></td><td align="left"><p>79</p></td></tr><tr><td align="left"><p>4</p></td><td char="." align="char"><p>4112.22</p></td><td char="." align="char"><p>4266.74</p></td><td char="." align="char"><p>4146.15</p></td><td align="left"><p>.002**</p></td><td align="left"><p>.002<sup>**</sup></p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left"><p>.93</p></td><td align="left"><p>55</p></td></tr><tr><td align="left"><p>5</p></td><td char="." align="char"><p>3977.35</p></td><td char="." align="char"><p>4164.39</p></td><td char="." align="char"><p>4018.41</p></td><td align="left"><p>.098</p></td><td align="left"><p>.102</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left"><p>.91</p></td><td align="left"><p>43</p></td></tr><tr><td align="left"><p>6</p></td><td char="." align="char"><p>3882.79</p></td><td char="." align="char"><p>4102.36</p></td><td char="." align="char"><p>3930.99</p></td><td align="left"><p>.097</p></td><td align="left"><p>.100</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left"><p>.90</p></td><td align="left"><p>40</p></td></tr></tbody></table> </ephtml> </p> <p> <emph>AIC</emph> Akaike information criterion, <emph>BIC</emph> Bayesian information criterion, <emph>ABIC</emph> Adjusted Bayesian information criterion, <emph>LMR LR</emph> Lo-Mendell-Rubin test, <emph>ALMR LR</emph> Adjusted Lo-Mendell-Rubin test, <emph>BLRT</emph> Bootstrapped likelihood ratio test **<emph>p</emph> <.01</p> <p>Table 4 indicates that the two-profile solution fits the data better than the one-profile solution (ΔAIC = − 943.97, ΔBIC = − 911.45, and ΔABIC = − 936.83). The three-profile solution is significantly better than the two-profile solution (ΔAIC = − 407.06; ΔBIC = − 374.52; ΔABIC = − 399.92). Furthermore, the four-profile solution is a better fit than the three-profile solution (ΔAIC = -298.24; ΔBIC = − 265.71; ΔABIC = − 291.09). The five-class solution is better than the four-profile solution (ΔAIC = − 134.87; ΔBIC = − 102.35; ΔABIC = − 127.74), but not significantly so. The six-profile solution is also better than the five-profile solution (ΔAIC =− 94.56; ΔBIC = − 62.03; ΔABIC = − 87.42), but not significantly. The LMR LR (<emph>p</emph> < 0.01), ALMR LR (<emph>p</emph> < 0.01), and BLRT (<emph>p</emph> < 0.01) of Profiles 2, 3, and 4 are statistically significant. This indicates that, in comparison with Profile 1, Profile 2 fits the data significantly better; the same is true when Profiles 2 and 3 and 3 and 4 are compared. Although the LMR LR and ALMR LR values for Profiles 4 and 5, as well as 5 and 6, are not statistically significant, the BLRT results are statistically significant (<emph>p</emph> < 0.01). The entropy value ranges between 0.89 and 0.93, which indicates acceptable classification (Wang & Wang, [<reflink idref="bib67" id="ref125">67</reflink>]). The four profiles are illustrated in Fig. 1.</p> <p>Graph: Fig. 1 JD-R Profiles of Early Childhood Development Practitioners</p> <p>The four profiles can be described as follows: (a) high demands-low resources (33.18%): ECDPs in this profile experience higher demands and lower resources than in the other profiles. Workload and emotional load are moderate to high, while job resources, such as supervisor and co-worker relations, information accessibility, and role clarity, are low. (b) Moderate demands-high resources (17.17%): ECDPs experience moderate job demands and have the most resources in this profile. The highest resource is access to information, followed by positive supervisor relations, role clarity, and colleague support at work. The lowest scores are job insecurity, emotional load, and work overload. (c) Moderate demands-low job resources (30.39%): ECDPs in this profile experience moderate demands and moderate to low resources. The highest demand is emotional load, while the lowest resources are supervisor relations, role clarity, and information. (d) Moderate demands-moderate resources (19.3%): ECDPs experience relatively moderate demands and resources. The highest resource is information access, followed by supervisor relations, role clarity, and colleagues at work.</p> <hd id="AN0191573913-19">Multiple Regression Analyses</hd> <p>Multiple regression analyses were executed with JD-R profiles and work capabilities as independent variables and work engagement and intention to leave as dependent variables. Dummy variables were created for the different JD-R profiles using Profile 4 as the comparison profile. Dummy variables are applied when categorical variables have more than two categories (Field, [<reflink idref="bib18" id="ref126">18</reflink>]) and enable the representation of the profile of groups using only zeros and ones, so it is possible to apply possible categorical variables in regression analysis.</p> <p>A multiple regression analysis with JD-R profiles as independent variable and the capability set as dependent variable was conducted (see Table 5). For engagement and intentions to leave, multiple regression analyses were conducted in two steps. In Step 1, JD-R profiles were entered as independent variables. In Step 2, JD-R profiles and the capability set were entered into the regression equation (see Table 5).</p> <p>Table 5 Multiple regression analyses of JD-R Profiles, Capabilities, and Functionings</p> <p> <ephtml> <table rules="groups"><thead><tr><th align="left"><p>Variables</p></th><th align="left"><p>ß</p></th><th align="left"><p><italic>SE</italic></p></th><th align="left"><p><italic>p</italic></p></th><th align="left"><p><italic>R</italic><sup><italic>2</italic></sup></p></th><th align="left"><p><italic>F</italic></p></th><th align="left"><p><italic>p</italic></p></th></tr></thead><tbody><tr><td align="left"><p>Capability set</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left"><p>.55<sup>**</sup></p></td><td char="." align="char"><p>60.82</p></td><td align="left"><p> <.001<sup>**</sup></p></td></tr><tr><td align="left"><p>High demands-low resources job</p></td><td align="left"><p>−.35</p></td><td align="left"><p>.04</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-high resources job</p></td><td align="left"><p>.25</p></td><td align="left"><p>.04</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-low resources job</p></td><td align="left"><p>−.30</p></td><td align="left"><p>.03</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Work engagement</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left"><p>.27<sup>**</sup></p></td><td char="." align="char"><p>52.50</p><p><italic>df</italic> (3, 427)</p></td><td align="left"><p> <.001<sup>**</sup></p></td></tr><tr><td align="left"><p>High demands-low resources job</p></td><td align="left"><p>−.37</p></td><td align="left"><p>.09</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-high resources job</p></td><td align="left"><p>.25</p></td><td align="left"><p>.08</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-low resources job</p></td><td align="left"><p>−.21</p></td><td align="left"><p>.06</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Work engagement (Step 2)</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left"><p>.30<sup>**</sup></p></td><td char="." align="char"><p>46.56</p><p><italic>df</italic> (4, 426)</p></td><td align="left"><p> <.001<sup>**</sup></p></td></tr><tr><td align="left"><p>High demands-low resources job</p></td><td align="left"><p>−.26</p></td><td align="left"><p>.10</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-high resources job</p></td><td align="left"><p>.17</p></td><td align="left"><p>.08</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-low resources job</p></td><td align="left"><p>−.13</p></td><td align="left"><p>.07</p></td><td align="left"><p>.008<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Capability set</p></td><td align="left"><p>.25</p></td><td align="left"><p>.05</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Intentions to leave (Step 1)</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left"><p>.15<sup>**</sup></p></td><td char="." align="char"><p>23.53</p><p><italic>df</italic> (3, 401)</p></td><td align="left"><p> <.001<sup>**</sup></p></td></tr><tr><td align="left"><p>High demands-low resources job</p></td><td align="left"><p>.22</p></td><td align="left"><p>.18</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-high resources job</p></td><td align="left"><p>−.25</p></td><td align="left"><p>.16</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-low resources job</p></td><td align="left"><p>.10</p></td><td align="left"><p>.13</p></td><td align="left"><p>.059</p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Intentions to leave (Step 2)</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left"><p>.24<sup>**</sup></p></td><td char="." align="char"><p>30.75</p><p><italic>df</italic> (4, 400)</p></td><td align="left"><p> <.001<sup>**</sup></p></td></tr><tr><td align="left"><p>High demands-low resources job</p></td><td align="left"><p>.10</p></td><td align="left"><p>.18</p></td><td align="left"><p>.050<sup>*</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-high resources job</p></td><td align="left"><p>−.16</p></td><td align="left"><p>.16</p></td><td align="left"><p>.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Moderate demands-low resources job</p></td><td align="left"><p>−.01</p></td><td align="left"><p>.13</p></td><td align="left"><p>.918</p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left"><p>Capability set</p></td><td align="left"><p>−.36</p></td><td align="left"><p>.19</p></td><td align="left"><p> <.001<sup>**</sup></p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr></tbody></table> </ephtml> </p> <p>*<emph>p</emph> ≤.05; **<emph>p</emph> ≤.01. The change in R-square was statistically significant</p> <p>Table 5 shows that all three JD-R profiles (compared with a moderate demands-moderate resources job) predict the capability set (<emph>F</emph> = 60.82, <emph>df</emph> = 3, 427, <emph>p</emph> < 0.001). The standardized beta coefficients are as follows: ß = − 0.35 (<emph>p</emph> < 0.001) for a high demands-low resources job; ß = 0.25 (<emph>p</emph> < 0.001) for a moderate demands-high resources job; and ß = − 0.30 (<emph>p</emph> < 0.001) for a moderate demands-low resources job.</p> <p>The following results are evident regarding predicting work engagement and intention to leave. All three JD-R profiles (compared with a moderate demands-moderate resources job) predict work engagement (<emph>F</emph> = 52.50, <emph>df</emph> = 3, 427, <emph>p</emph> < 0.001). The standardized beta coefficients vary between − 0.37 (<emph>p</emph> < 0.001) for a high demands-low resources job and − 0.21 (<emph>p</emph> < 0.001) for a moderate demands-low resources job. In Step 2, JD-R profiles and the capability set statistically significantly predict work engagement (<emph>F</emph> = 46.56, <emph>df</emph> = 4, 426, <emph>p</emph> < 0.001). The standardized beta coefficients are statistically significant (<emph>p</emph> < 0.01): ß = − 0.26 (high demands-low resources job), ß = 0.17 (moderate demands-high resources job), ß = -0.13 (moderate demands-low resources job), and ß = 0.25 (capability set).</p> <p>Two JD-R profiles (compared with the moderate demands-moderate resources job profile) predict intention to leave (<emph>F</emph> = 23.53, <emph>df</emph> = 3, 401, <emph>p</emph> < 0.001). The standardized betas vary between − 0.25 (<emph>p</emph> < 0.001) for a moderate demands-high resources job and 0.22 (<emph>p</emph> < 0.001) for a high demands-low resources job. In Step 2, JD-R profiles and the capability set statistically significantly predict intention to leave (<emph>F</emph> = 30.75, <emph>df</emph> = 4, 400, <emph>p</emph> < 0.001). The following standardized beta coefficients are statistically significant: ß = 0.10 (high demands-low resources job), ß = − 0.16 (moderate demands-high resources job), and a low capability set (ß = − 0.36).</p> <p>Based on the above-mentioned results, Hypotheses 1a, 1b, and 1c are accepted. Therefore, a JD-R profile with moderate job demands and high job resources is statistically significantly and positively associated with ECDPs' capability set and work engagement and statistically significantly and negatively associated with their intentions to leave. Furthermore, Hypotheses 2a and 2b are accepted. ECDPs' capability set is statistically significantly and positively associated with work engagement and negatively associated with their intentions to leave.</p> <p>JD-R profiles explained 55% of the variance in the capability set of ECDPs. Furthermore, JD-R profiles and the capability set explained 30% and 24% of the variance in work engagement and intention to leave, respectively.</p> <hd id="AN0191573913-20">Indirect Effects</hd> <p>For this study, the procedure suggested by Hayes ([<reflink idref="bib30" id="ref127">30</reflink>]) was used to determine how JD-R profiles affected work engagement and intentions to leave via the work capability set of ECDPs. Bootstrapping was used to construct two-sided bias-corrected 95% confidence intervals (CIs) for indirect effects.</p> <p>The results showed that a high demands-low resources job (β = − 0.11, <emph>SE</emph> = 0.03, <emph>p</emph> < 0.001, [− 0.16, − 0.06]) indirectly and negatively affected work engagement via a weak capability set. A moderate demands-high resources job (β = 0.08, <emph>SE</emph> = 0.02, <emph>p</emph> < 0.001, [0.05, 0.13]) indirectly and positively affected work engagement via a strong capability set. A moderate demands-low resources job (β = − 0.08, <emph>SE</emph> = 0.02, <emph>p</emph> < 0.001, [− 0.12, − 0.05]) indirectly and negatively affected work engagement via a weak capability set. Furthermore, a high demands-low resources job (β = 0.18, <emph>SE</emph> = 0.03, <emph>p</emph> < 0.001, [0.12, 0.24]) indirectly affected intention to leave via a weak capability set. A moderate demands-high resources job (β = − 0.14, <emph>SE</emph> = 0.03, <emph>p</emph> < 0.001, [− 0.20, − 0.09]) indirectly and negatively affected intention to leave via a strong capability set. A moderate demands-low resources job (β = 0.13, <emph>SE</emph> = 0.02, <emph>p</emph> < 0.001, [0.09, 0.19]) indirectly affected intentions to leave via a weak capability set. Hypotheses 3a and 3b are accepted. A JD-R profile with moderate job demands and high job resources indirectly affects work engagement positively via ECDPs' capability set and indirectly and negatively affects their intentions to leave via their capability set.</p> <hd id="AN0191573913-21">Discussion</hd> <p>This study aimed to study the relationship between JD-R profiles (based on workload, emotional load, colleagues at work, supervisor relations, role clarity, accessibility of information, and job security), work capabilities, work engagement, and intention to leave as functionings of ECDPs. The study established four JD-R profiles through latent profile analysis. The JD-R profiles were related to the work capabilities of ECDPs, and this combination resulted in predictions of large percentages of variance in work engagement and a moderate percentage in intention to leave. Using these profiles may help the managers and supervisors of ECDPs to clarify the role of job demands and resources and assist them in recognizing ECDPs who are likely to become more engaged or to leave their jobs (Van den Broeck et al., [<reflink idref="bib63" id="ref128">63</reflink>]).</p> <hd id="AN0191573913-22">Job Demands-Resources Profiles of ECDPs</hd> <p>The four JD-R profiles for ECDPs established through latent profile analysis for this study were as follows: (a) <emph>high demands-low resources job</emph>, characterized by slightly higher demands than the rest of the profiles and very low resources. The high demands-low resources job profile suggested that the ECDPs in this group might experience stress due to their limited job resources and high job demands (Schaufeli, [<reflink idref="bib54" id="ref129">54</reflink>]); (b) <emph>moderate demands-high resources job</emph>, which exhibited relatively lower demands and access to relatively high resources; (c) <emph>moderate demands-low resources job</emph>, which displayed relatively higher job demands and slightly more job resources than the high demands-low resources job, with mostly negative scores; and (d) the <emph>moderate demands-moderate resources job</emph>, which revealed slightly lower demands and slightly more resources. These findings are aligned with recent studies that showed similar JD-R profiles in different jobs (Barnard et al., [<reflink idref="bib6" id="ref130">6</reflink>]; Granziera et al., [<reflink idref="bib24" id="ref131">24</reflink>]; Murangi et al., [<reflink idref="bib43" id="ref132">43</reflink>]).</p> <p>Participants were unequally distributed among the four profiles, with the high demands-low resources job having the largest membership (33.2%), followed by the moderate demands-low resources job (30.4%), and then the moderate demands-moderate resources job (19.2%), and the moderate demands-high resources job had the fewest members (17.2%). A moderate demands-high resources job indicated that sufficient job resources could lessen job demands, but it did not mean that there would be no job demands. Many ECDPs work under high demands, but insufficient resources (Farewell et al., [<reflink idref="bib17" id="ref133">17</reflink>]; Visser et al., [<reflink idref="bib66" id="ref134">66</reflink>]). Even when the demands are not as extreme, the lack of resources can still have an impact on individuals' intentions to leave and abilities to maintain engagement effectively. The unequal distribution of practitioners among these profiles highlighted the challenges ECDPs faced in these settings, where resource constraints (rather than high job demands) were prevalent.</p> <hd id="AN0191573913-23">Job Demands and Resources, Work Engagement, and Intentions to Leave</hd> <p>The study found that emotional overload, a significant job demand, was negatively associated with the engagement of ECDPs. Experiences of emotional overload that had a negative impact on the work engagement of ECDPs often stemmed from the continuous demands of managing young children's emotional needs, behavior, and developmental challenges, particularly in communities characterized by poverty and inequality, where our study was conducted (Baloyi & Makhubele, [<reflink idref="bib5" id="ref135">5</reflink>]; Visser et al., [<reflink idref="bib66" id="ref136">66</reflink>]). As ECDPs experienced more emotional demands, their enthusiasm, energy, and dedication to their work diminished, which could result in less effective teaching and care for children.</p> <p>We found that several job resources – relationship with work colleagues, relationship with immediate supervisor, role clarity, information accessibility, and job security – significantly affected ECDPs' work engagement and intentions to leave. Specifically, the high demands-low resources and moderate demands-low resources profiles were negatively associated with ECDPs work engagement and positively associated with their intentions to leave. Moderate demands-moderate resources and moderate demands-high resources profiles (compared to the other profiles) were associated with higher levels of work engagement and lower levels intentions to leave. A lack of job resources is particularly pertinent in South African ECD, where practitioners often face challenging working conditions (Baloyi & Makhubele, [<reflink idref="bib5" id="ref137">5</reflink>]; Harrison, [<reflink idref="bib29" id="ref138">29</reflink>]). Enhancing job resources can significantly improve their work engagement and retention.</p> <hd id="AN0191573913-24">Job Demands-Resources and Work Capabilities of ECDPs</hd> <p>A positive and significant association was found between co-worker relationships and the capability set. This indicated that the quality of interactions and relationships among ECDPs influenced their capability sets. Supportive and collaborative relationships with colleagues could foster a motivating environment where ECDPs felt capable. Furthermore, the relationship with immediate supervisors was positively and significantly associated with the capability set of ECDPs. Effective supervision, characterized by clear communication, training, and evaluation, could enhance ECDPs' capabilities. This is particularly important in South Africa, where ECDPs often work in challenging conditions (Baloyi & Makhubele, [<reflink idref="bib5" id="ref139">5</reflink>]).</p> <p>Role clarity and information accessibility had positive and significant relationships with the capability set of ECDPs. The associations between role clarity and the capability set indicated that having a clear understanding of job roles and easy access to information was crucial for ECDPs to feel capable. Lack of role clarity and information might reinforce the negative effects of work overload and emotional demands that ECDPs experienced. Work overload and emotional load might stifle capabilities due to the stress they added to the ECD workforce. Having sufficient job resources would enhance ECDPs' capabilities. These capabilities were related to the immediate supervisor, role clarity, and information accessibility. Our results align well with the findings of previous studies (Meerman et al., [<reflink idref="bib41" id="ref140">41</reflink>]; Murangi et al., [<reflink idref="bib43" id="ref141">43</reflink>]; Van den Broeck et al., [<reflink idref="bib63" id="ref142">63</reflink>]).</p> <hd id="AN0191573913-25">Effects of JD-R Profiles and Work Capabilities</hd> <p>The results revealed that a moderate demands-high resources job affected the work engagement of ECDPs significantly, positively, and more strongly than the moderate demands-moderate resources profile. The high demands-low resources and moderate demands-low resources job profiles affected work engagement significantly more negatively than the moderate demands-moderate resources profile. This negative impact underscored the detrimental effects of insufficient resources when faced with job demands, highlighting the importance of resource availability for sustaining work engagement (Barnard et al., [<reflink idref="bib6" id="ref143">6</reflink>]; Van den Broeck et al., [<reflink idref="bib63" id="ref144">63</reflink>]).</p> <p>Beyond the direct effects of JD-R profiles on work engagement, the results showed that the work capability set also significantly predicted work engagement (even when JD-R profiles were controlled for). These capabilities included using knowledge and skills, developing new knowledge and skills, making important decisions, building and maintaining meaningful relationships, setting goals, and contributing to something valuable. These findings underscored the multifaceted nature of work engagement, indicating that both the structural aspects of the job (i.e., demands and resources) and the individual's capabilities within the work environment were critical determinants of engagement levels. Aligned with our findings, Meerman et al. ([<reflink idref="bib41" id="ref145">41</reflink>]) argued that resources hold significance only when they enable the realization of value. Inequality in capabilities among individuals may result from a lack of resources, as well as from varying levels of conversion factors. The results suggested that enhancing these capabilities could lead to higher work engagement among ECDPs, thus informing strategies for organizational development and employee support.</p> <p>All the JD-R profiles and the capability set significantly predicted the intention to leave. These findings are aligned with the findings of Murangi et al. ([<reflink idref="bib43" id="ref146">43</reflink>]). JD-R profiles characterized by moderate demands coupled with high resources significantly and negatively affected the intentions to leave of ECDPs more than the moderate demands-moderate resources profile. The availability of higher resources in a job setting could substantially prevent ECDPs' intentions to leave. Conversely, a JD-R profile with high demands and low resources led to significantly higher intentions to leave than the moderate demands-moderate resources profile. This negative impact underscored the detrimental effects of insufficient resources when faced with job demands, highlighting the importance of resource availability for reducing intentions to leave.</p> <p>The findings suggested that job resources and capabilities uniquely contributed to work engagement and intentions to leave. Job resources such as co-worker and supervisor support and role clarity were vital for staff engagement and retention. However, work capabilities added an additional dimension, indicating that having the freedom and ability to use these resources effectively further enhanced engagement and reduced intentions to leave. The significant contribution of work capabilities, even when controlling for job resources, highlighted their incremental value. Both work capabilities and job resources are critical in shaping individual and organizational outcomes. The synergy between having the capabilities to perform one's job (Abma et al., [<reflink idref="bib1" id="ref147">1</reflink>]) and JD-R profiles creates an environment conducive to high work engagement and low turnover intention. Conversely, deficiencies in either capabilities or JD-R profiles can lead to disengagement and higher turnover rates.</p> <p>The findings of the study highlighted the significant indirect effects of JD-R profiles on work engagement and intentions to leave through work capabilities. These results justified the critical role of work capabilities in influencing both engagement and retention of ECDPs, even when considering the direct impacts of job demands and resources. Work capabilities are essential for maintaining high levels of engagement. Employees can fully leverage their capabilities in resource-rich environments, leading to greater engagement. Conversely, insufficient resources undermine capability utilization, resulting in lower engagement (Meerman et al., [<reflink idref="bib41" id="ref148">41</reflink>]).</p> <hd id="AN0191573913-26">Theoretical and Practical Implications</hd> <p>Regarding international relevance, this study's findings provided robust evidence for the significant role of JD-R profiles and work capabilities in influencing work engagement and intentions to leave among ECDPs. By integrating the JD-R model with the CA, the research offered a comprehensive theoretical framework that underscored the importance of structural job characteristics and individual capabilities. These insights can inform organizational strategies to enhance work engagement and reduce turnover, ultimately contributing to more effective and supportive work environments.</p> <p>Capabilities align work with employees' personal values and aspirations, which can create a stronger connection to their roles and the organization. When employees feel that their work contributes to their broader life goals and values, they are more likely to be engaged and committed to staying with the organization. The CA encourages a long-term perspective on employee development and well-being. While job resources can address immediate needs, capabilities foster sustained engagement and retention by continuously enhancing employees' ability to grow, adapt, and find meaning in their work over time.</p> <p>Concerning the support of ECDPs in South Africa, it is crucial to address emotional overload due to its significant negative impact on their work engagement and retention. Strategies include providing emotional support through counseling and peer groups, professional development in emotional regulation and classroom management, and fostering a collaborative work environment. Enhancing work engagement also involves promoting positive relationships among colleagues and supervisors, clear communication of roles, easy access to information, and job security (Harrison, [<reflink idref="bib29" id="ref149">29</reflink>]). Policymakers should develop comprehensive human resource management policies with clear job analysis, role clarity, and supervisor training to support ECDPs' capabilities (Barnard et al., [<reflink idref="bib6" id="ref150">6</reflink>]). These measures are essential for managing job demands, providing resources, and fostering environments that enhance work capabilities, which mediate the effects of demands and resources on engagement and turnover intentions. This dual approach is vital for a resilient and motivated workforce.</p> <hd id="AN0191573913-27">Limitations and Recommendations for Future Research</hd> <p>A few limitations were experienced during this study. The study focused mainly on the teaching staff of the ECD workforce. The nature of the study and its title concerned the management staff of the centers and resulted in some having an attitude of suspicion, and in some cases, the researcher was met with resistance. Early childhood development practitioners, especially those dealing with babies, had very little time available. The researcher experienced a low response rate when questionnaires were left at schools and institutions. The strategy had to be adapted, and data collection became more time-consuming than anticipated. A convenience sample was used, and the data were collected in two different provinces.</p> <p>Although the cross-sectional survey was successful in this explorative study, a longitudinal study is recommended for future studies, as it may reveal more detail about the patterns of early childhood functioning and the impact of capabilities. The findings can inform strategies and practices to increase the number of ECDs in the moderate demands-high resources job profile. Future studies could also focus on designing appropriate interventions to assist ECD workforce management in developing job descriptions and balancing job demands and job resources so that ECDPs are enabled to achieve the capabilities required to enlarge the number of ECDPs in the moderate demands-high resources job profile.</p> <hd id="AN0191573913-28">Conclusion</hd> <p>This study examined the effects of JD-R profiles and work capabilities on work engagement and intention to leave. The results showed the predictive value that job demands and resources had on the work capabilities of ECDPs in South Africa. The moderate demands-high resources job profile established in this study may become the standard job profile for the ECD workforce to strive towards. This could significantly influence work engagement and reduce the intention to leave the sector.</p> <p>While job resources are essential for providing the necessary support and tools for employees to perform their jobs effectively, the capabilities approach uniquely contributes by empowering employees to use these resources in ways that align with their personal values and aspirations, fostering a deeper and more sustainable engagement and commitment to the organization.</p> <hd id="AN0191573913-29">Funding</hd> <p>Open access funding provided by North-West University.</p> <hd id="AN0191573913-30">Data Availability</hd> <p>Rothmann, Sebastiaan (2023), "Decent work, capabilities and well-being of early childhood education practitioners", Mendeley Data, V1, https://doi.org/10.17632/sr9mbztwdb.1</p> <hd id="AN0191573913-31">Declarations</hd> <p></p> <hd id="AN0191573913-32">Conflict of interest</hd> <p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p> <hd id="AN0191573913-33">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0191573913-34"> <title> References </title> <blist> <bibl id="bib1" idref="ref77" type="bt">1</bibl> <bibtext> Abma FI, Brouwer S, de Vries HJ, Arends I, Robroek SJW, Cuijpers MPJ, van der Wilt JG, Bültmann U, Van der Klink JJL. 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  Data: Job Demands-Resources Profiles and Work Capabilities: Effects on Early Childhood Development Practitioners' Functioning
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22Suzette+C%2E+Ragadu%22">Suzette C. Ragadu</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-6945-3305">0000-0001-6945-3305</externalLink>)<br /><searchLink fieldCode="AR" term="%22Sebastiaan+Rothmann%22">Sebastiaan Rothmann</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-6065-4338">0000-0001-6065-4338</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Early+Childhood+Education+Journal%22"><i>Early Childhood Education Journal</i></searchLink>. 2026 54(2):999-1014.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: Y
– Name: Pages
  Label: Page Count
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  Data: 16
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  Label: Publication Date
  Group: Date
  Data: 2026
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  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
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  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Early+Childhood+Teachers%22">Early Childhood Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Stress+Variables%22">Stress Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Intention%22">Intention</searchLink><br /><searchLink fieldCode="DE" term="%22Faculty+Mobility%22">Faculty Mobility</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Attitudes%22">Teacher Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Work+Attitudes%22">Work Attitudes</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22South+Africa%22">South Africa</searchLink>
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  Label: Assessment and Survey Identifiers
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  Data: <searchLink fieldCode="SU" term="%22Utrecht+Work+Engagement+Scale%22">Utrecht Work Engagement Scale</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s10643-025-01902-1
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1082-3301<br />1573-1707
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study examined the associations between early childhood development practitioners' job demands-resources profiles, work capabilities, engagement, and intentions to leave. A cross-sectional survey was administered to a convenience sample (N = 426) of early childhood development practitioners in two provinces in South Africa. The Job Demands-Resources Scale (Rothmann et al., A psychometric evaluation of the job demands-resources scale in South Africa. SA Journal of Industrial Psychology, 32(4):76-86, 2006. https://hdl.handle.net/10520/EJC89107), Capability Set for Work Questionnaire (Abma et al., Scandinavian Journal Work, Environment and Health 42:34-42, 2016), Work Engagement Scale (Rautenbach and Rothmann, Journal of Psychology in Africa 27:303-309, 2017), and Intention to Leave Scale (Sjöberg and Sverke, Scandinavian Journal of Psychology 41:247-252, 2000) were administered. Latent profile analyses resulted in four job demands-resources profiles: high demands-low resources (33.18%), moderate demands-high resources (17.17%), moderate demands-low job resources (30.39%), and moderate demands-moderate resources (19.3%). Early childhood practitioners who were in moderate demands-high resources (rather than high demands-low resources or moderate demands-low job resources) jobs and had a robust capability set showed high work engagement and low intentions to leave their jobs. Job demands-resources profiles indirectly affected early childhood development practitioners' work engagement and intentions to leave via their capability sets.
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  Data: As Provided
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  Data: https://doi.org/10.17632/sr9mbztwdb.1
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  Label: Entry Date
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  Data: 2026
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  Label: Accession Number
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  Data: EJ1507362
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      – SubjectFull: Early Childhood Teachers
        Type: general
      – SubjectFull: Stress Variables
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      – SubjectFull: Intention
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      – TitleFull: Job Demands-Resources Profiles and Work Capabilities: Effects on Early Childhood Development Practitioners' Functioning
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