Solving for Engagement: A Systematic Review of Task Variation and Problem-Solving Demands in Motivating Employees

Abstract

While previous scholarly work has focused on addressing the relationship between task variation and employee motivation, the functional relations between problem-solving demands at work and employee engagement remain underexplored. This systematic review examines how task variation and problem-solving opportunities influence employee engagement, motivation, and performance. Adhering to the PRISMA 2020 guidelines, we performed structured searches in Academic Research Ultimate, Business Source Elite, PsycINFO, CINAHL, ERIC, Web of Science, and Scopus databases limited to peer-reviewed results in English published after 2009. Thirteen studies met our search criteria, although they employed diverse methodologies to explore how purposeful task variation and problem-solving affect observable work behavior. Key findings include (a) positive feedback enhances engagement in promotive tasks, while negative feedback may boost motivation in preventive tasks; (b) moderate boredom fosters adaptive problem solving, but excessive monotony reduces engagement; (c) active refocusing across task domains supports sustained performance; (d) perceived variation in pace, task type, and location facilitates recovery and engagement; and (e) flexible work arrangements improve information processing but may reduce support access. Our results highlight the importance of designing work processes that balance task variation and structured problem-solving, supported by tailored feedback and restorative conditions. Future research should quantify these effects across diverse organizational contexts.

1. Employee Engagement in the Workplace

Engagement in the workplace is often regarded as a key factor for both well-being and high performance (Wood & de Menezes, 2011). However, organizations often struggle to understand what truly fosters and sustains this engagement, which can pose challenges for employees (see Federman, 2009). In a workday increasingly characterized by demands for flexibility and continuous learning, it is therefore important to understand how to motivate employees in a sustainable manner. Previous research has identified several factors that influence employee engagement and motivation, such as job autonomy, social support, and the experience of mastery (Bakker & Demerouti, 2008). However, uncertainty remains regarding how task variation and the opportunity to solve problems independently affect engagement. Beyond its role in motivation, task variation may contribute to adaptive performance and innovation in modern organizations. In complex and changing environments, the ability to vary tasks and engage in flexible problem-solving is, therefore, relevant not only for engagement but also for learning, innovation, and sustaining organizational functioning.

1.1. Observable Work Behavior

Observable work behavior is defined as engagement, performance, achievement, and other concrete variables that can be measured and influence employees’ work behavior. Notably, job performance is a dynamic act rather than a static condition (see Dalal et al., 2014). In a study of professional service workers in a European hospital, Avgerinos and Gokpinar (2018) noted that “concurrent exposure to variety has a positive impact on focal productivity; non-concurrent exposure to variety has a negative impact on it” (p. 1368). However, reducing problem-solving variance may improve predictability (Paul et al., 1991), which many would argue is a positive feature of safe work environments.

The positive association between task variation and employee motivation has been supported through several studies in the organizational behavior literature. Among these, Hafeez et al. (2023) found a positive impact of task variation on engagement among nurses (echoed by George et al., 2020), but they also identified a mediating role of engagement to both happiness and stress, which undermines the notion that increased variation always leads to more positive results. In another study, job variation informed engagement indirectly through the construct of meaningful work, which was also informed by expectations, development opportunities, and autonomy (Albrecht et al., 2021).

1.2. Variation and Variability

In this section, we distinguish between the concepts of variation and variability, as they pertain to two different levels of analysis and answer different types of scientific questions (see also Machado & Tonneau, 2012). Task variation refers to changes in work tasks that may occur through alterations in pace, location, content, or method. This can include differences in workload, work setting, task type, and how the work is carried out. Problem-solving variables, on the other hand, concern the conditions that influence how employees identify and manage challenges in their work. Examples of such variables in the included studies are regulatory focus (Smith et al., 2009; Bledow et al., 2026), feedback format (Van Dijk & Kluger, 2011), and the ability to adjust and allocate effort across tasks (Rotundo et al., 2012; Schaefer & Bormann, 2025).

Problem-solving variability refers to how employees adjust their own behavior over time, whereas task variation depends on the employer. When examining within-person job performance variability, Dalal et al. (2020) found that personality and affective states functioned as motivational antecedents. Moreover, problem-solving demands influence employees’ thriving through challenge appraisal (Ma et al., 2023). Riyanto et al. (2021) explored multiple types of influence of work motivation and job satisfaction on employee performance and found a mediating role of employee engagement.

1.3. Engagement and Its Relation to Variability

Employee engagement is generally associated with performance that exceeds formal role requirements and may foster innovation as well as more effective approaches to task accomplishment. Engagement is defined as a positive, work-related psychological state characterized by vigor, dedication, and absorption (Schaufeli et al., 2002). It extends beyond mere job satisfaction and reflects an active investment of personal resources into work roles.

Engagement is facilitated not only by the presence of varied job tasks, as emphasized in the Job Characteristics Model (Hackman & Oldham, 1976), but also by opportunities for behavioral variability. Behavioral variability, as conceptualized by Neuringer (2002), refers to the capacity to perform tasks in multiple ways and to generate novel behavioral patterns. Enabling such variability may stimulate exploration, creativity, and adaptive performance.

Engagement is therefore related to variation in two distinct but complementary ways: first, through task variation embedded in job design, which enhances motivation and reduces monotony; and second, through the encouragement of variability in task execution, which supports creativity and innovation. Together, these mechanisms suggest that fostering both structural and behavioral forms of variation is important for sustaining high levels of engagement and performance.

1.4. Aim and Scope

Given the complex relationships among the concepts introduced above, we conducted a systematic review of how task variation and problem-solving opportunities influence employee engagement, motivation, and performance. We aimed to examine the impact of task variation and problem-solving opportunities on engagement among employees in various work environments. While engagement represents our central outcome, we include other constructs that are considered antecedents, correlates, or consequences, based on their ability to influence or reflect engagement. We represent these main relationships in Figure 1.

2. Method

We adopted a systematic literature review methodology to explore task variation and map how different solutions can strengthen employee engagement, thereby increasing employee motivation and performance. We addressed this research topic through a structured process of identifying, selecting, evaluating, and analyzing relevant research (Kitchenham, 2004).

We followed the PRISMA 2020 guidelines for systematic reviews and structured the review according to the PRISMA 2020 Checklist (Page et al., 2021). Prior to conducting the review, we completed a registration form for a generalized systematic review and deposited it on the Open Science Framework at the following project link: https://osf.io/vqyfn (accessed on 21 May 2026).

2.1. Inclusion and Exclusion Criteria

The inclusion criteria for this study were peer-reviewed journal articles published in the last 15 years and written in English. The studies needed to explore the effects of task variation and problem-solving variables on employee engagement in organizational or workplace settings. Moreover, the studies had to examine the effects of task variation on motivation in real-world scenarios, ensuring that the findings had documented practical relevance. We excluded articles lacking practical trials or objective findings in favor of those with apparent applied significance.

According to our exclusion criteria, we excluded articles focusing solely on theoretical frameworks without empirical evidence or those lacking relevance to engagement or productivity in the workplace. We also excluded studies that presented techniques outside the defined scope, such as those lacking a behavioral component (e.g., purely cognitive). Book chapters, conference papers, reports, and dissertations were excluded, as these often lack peer review or sufficient empirical grounding. We further excluded studies published before 2010. This timeframe was chosen based on an exploratory search in Google Scholar prior to screening, which revealed that most relevant and influential articles were published from 2009 onward.

2.2. Literature Search

The systematic literature search was conducted individually using electronic databases between 24 January and 26 January 2025. We selected articles from PsycINFO, Business Source Elite, and Academic Search Ultimate. Searches in PsycINFO were conducted via Ovid, while those in Business Source Elite and Academic Search Ultimate were performed via EBSCOHost. We chose these databases to enable a broad and reliable search for relevant articles. To address limitations related to sample size, topic coverage, and temporal recency, we conducted an additional search between 12 April and 15 April 2026. This second search used the same strategy as the original but included four new databases, in addition to the original three, and covered articles published from 2009 onward. The four newly reviewed databases were CINAHL, ERIC, Web of Science, and Scopus.

The search terms used included variation, variability, task, problem solving, employee, and workplace, combined with Boolean operators. We saved the results and imported them into EndNote version 21 for duplicate removal and appraisal. The Appendix A includes the complete search history and results.

2.3. Data Extraction and Selected Variables

Data were extracted to assess the effects of task variation and problem-solving variables on employee engagement. Measurements capturing changes in employee motivation, job performance, or related variables such as engagement were of primary interest, as were studies with clearly defined measures of engagement and productivity, such as questionnaires or performance metrics. In addition to the main outcomes, we collected data on participants’ work context (e.g., industry and job type) and study design (e.g., experimental or observational), when available.

During the literature search across all databases, we initially screened results based on title and/or abstract to exclude studies that did not explore the impact of task variation on engagement or productivity in the workplace. The selection process was conducted individually. After the initial screening, we read the remaining articles in full and assessed them against the inclusion and exclusion criteria.

We evaluated the included studies based on methodological design, operationalization of task variation and engagement, and reporting quality. Only studies that met the predefined inclusion criteria and contained empirical data were included in the analysis.

2.4. Inter-Rater Agreement

Following the original selection process, a fellow student was recruited as a co-rater to calculate interrater reliability based on a sample of excluded and included articles included resulting from the original search performed in 2025. To this end, 30 articles from the first literature search, six of which were included, were sent without disclosing which had been selected. The co-rater was informed of the search terms and inclusion and exclusion criteria and was asked to assess whether each article was suitable.

The interrater agreement score showed consensus on 26 out of 30 articles, corresponding to 86.6% agreement. According to McHugh (2012), an agreement rate of 80% is considered the minimum recommended threshold for most texts, and this result was therefore not deemed problematic. Following the more recent search conducted in 2026 another fellow student was recruited to calculate interrater reliability. This time there were also 30 articles, but seven of them were included. The 2026 interrater agreement score showed consensus on 25 out of 30 articles, corresponding to 83.3% agreement.

2.5. Risk of Bias

Due to the heterogeneity of the included studies, we used the Mixed Methods Appraisal Tool (MMAT; Hong et al., 2018) to assess the risk of bias across the included articles. While other risk of bias tools appraise bias by domain (e.g., ROBINS-E; Higgins et al., 2024), the MMAT evaluates methodological quality across design categories using design-specific criteria. In our case, we used the initial two screening questions followed by five additional questions applicable to quantitative descriptive studies, which cover sampling, non-response, and measurement biases, for our twelve quantitative studies. For the remaining study (Ejlertsson et al., 2018), we used the initial two screening questions followed by five additional questions applicable to qualitative studies. The results from the risk of bias appraisal are reported in the Supplementary Materials.

Furthermore, we conducted a comprehensive bias assessment for each article individually using the accompanying MMAT Microsoft Excel template and categorized the overall risk of bias as low risk, some concerns, high risk, or very high risk. Additionally, we performed a general descriptive critical appraisal of all studies at a general level, considering aspects such as study design, sample characteristics, and potential sources of bias. The findings were primarily used to support broader patterns identified across the evidence base rather than as stand-alone evidence.

2.6. Appraisal of Methodological Heterogeneity

In order to account for the methodological heterogeneity of the included studies, we applied a triangulation approach during the synthesis process to strengthen interpretive rigor and transparency, allowing recurring patterns related to task variability and problem-solving demands to be identified (Bekhet & Zauszniewski, 2012). The included articles differ substantially in terms of design, context, and analytical focus, including experimental studies, survey-based research, qualitative inquiry, and mathematical modeling. Given the substantial variability, a statistical or directly comparative synthesis was not appropriate. Instead, the review employed a structured, concept-driven synthesis aimed at identifying recurring patterns and mechanisms across heterogeneous studies rather than estimating comparable effect sizes.

This triangulation process involved comparing how task variation and problem-solving demands were examined across different study types, populations, and outcome variables. For example, experimental studies and surveys contributed findings related to motivational responses and perceived engagement under varying task conditions, while qualitative studies provided contextual insight into how workers experience flexibility, recovery, and adaptation in real work situations.

By integrating findings from these different forms of evidence, we aimed to identify similar tendencies rather than identical effects. This approach allowed for a broader interpretation of the literature by considering both common patterns and contextual differences in how task variation and problem-solving demands relate to employee engagement and related organizational outcomes.

3. Results

3.1. Search Results and Article Selection

The literature search across the seven databases yielded a total of 3002 articles: 190 from PsycINFO, 399 from Academic Search Ultimate, 254 from Business Source Elite, 126 from CINAHL, 28 from ERIC, 710 from Web of Science, and 1295 from Scopus. After removing duplicates, 1924 unique articles remained. In the initial screening process, all articles were assessed based on title, abstract, and keywords. Of these, 37 relevant articles were selected for full-text review. Twenty-four met the inclusion criteria but were excluded after full-text review.

Among these, Nuamah (2024) investigated how repeated exposure to stress-inducing tasks can improve employees’ ability to handle similar challenges in the future. This article was ultimately excluded because it did not directly explore employee performance or motivation in relation to task variation or workplace variables. Instead, it focused on the stress-reducing effects of repeated exposure to stressful tasks. The conclusions from Nuamah (2024) addressed enhancing job performance by improving stress management but did not examine employee motivation in response to repetitive tasks.

Following the final selection process, thirteen articles were included: one from PsycINFO, two from Academic Search Ultimate, four from Business Source Elite, one from CINAHL, one from ERIC, two from Web of Science, and two from Scopus. The PRISMA flow diagram summarizing all results for each step of the selection process is reproduced in Figure 2.

3.2. Study Results

3.2.1. Synthesis of Findings

The included articles exhibit considerable methodological diversity, ranging from mathematical modeling to controlled experiments and qualitative focus groups, with study designs skewed toward cross-sectional or lab-based work. They also differ notably in context, sample, and focus. There is a heavy reliance on WEIRD (Western, Educated, Industrialized, Rich, and Democratic) samples, with only two studies conducted in non-Western contexts (Sun et al., 2020; Taibah & Ho, 2023). This imbalance substantially limits the cultural and contextual generalizability of the observed patterns and should be taken into account when interpreting the scope of the findings.

Despite these differences, most findings converge on the idea that task variation and adaptive problem-solving strategies are key factors in enhancing employee motivation and engagement. The main characteristics of the included articles are summarized in

Table 1. Overview of the Data Extracted from Each of the Included Studies.

Author(s), Year	Topic	Study Type	Study Design	Number of Participants	Country	Study Summary	Measurement Operation	Conclusion
Azizi et al. (2013)	Boredom, modeling, task variation, and motivation	Quantitative (modeling)	Mathematical models in case study	17	UK/Canada	Apply mathematical models and a Bayesian framework to measure and predict workplace boredom, and its impact on motivation and performance	Model-based: Quantifies how moderate levels of boredom trigger adaptive responses and task variation, which increase motivation and engagement. High boredom weakens these mechanisms.	Moderate boredom stimulates adaptive responses and task variation that increase motivation, while excessive boredom impairs problem-solving and engagement.
Bledow et al. (2026)	Creativity, self-regulation, problem-solving	Quantitative	Multilevel study (employee-manager dyads)	104 dyads	Belgium	Investigates how self-regulation processes influence creative performance	Measures exploration (divergent thinking), planning and outcome focus (convergent processes), and links these to manager-rated creative performance in innovation projects	Effective problem-solving depends on balancing exploratory and goal-directed processes
Ejlertsson et al. (2018)	Recovery, task variation, social support, and control	Qualitative	Focus groups	50	Sweden	Use qualitative focus groups to identify variation, community, and manageability as key factors for recovery in the workplace	Qualitative classification: Identifies themes such as variation and control as key factors for recovery and engagement.	Variation in work tasks and a supportive work culture promote recovery and increase perceived engagement through improved mastery and creative problem-solving.
Herrmann and Felfe (2013)	Leadership, task novelty, personal initiative, creativity	Quantitative	Experimental study	241	Germany	Examines moderating effects of task novelty and initiative on creativity	Manipulates task novelty experimentally and measures creativity through idea generation tasks, while assessing personal initiative as an individual difference variable	Task novelty and personal initiative strengthen employees’ ability to respond to task demands with creative problem-solving
Knight et al. (2025)	Hybrid work design, autonomy, support, well-being	Quantitative	Cross-sectional (latent profile analysis)	386	Australia	Identifies work design profiles across locations	Measures autonomy, support, workload, and monitoring through self-reports and uses latent profile analysis to identify patterns linked to well-being	The impact of task demands depends on broader work design conditions, which shape how employees experience and respond to variability
Narayanan et al. (2009)	Task variety, specialization, learning, productivity	Quantitative	Field study	88	USA	Examines balance between task variety and specialization	Uses objective task allocation data to calculate degree of task variety and specialization, and links these to individual productivity outcomes	Task variability supports learning and performance, but optimal outcomes depend on balancing variation with task specialization
Rotundo et al. (2012)	Refocusing, task variation, and job security	Quantitative	Longitudinal data analysis	737	Canada	Analyze the redistribution of effort across tasks using data from professional basketball, exploring how such refocusing affects performance and job security	Quantitative indicator: Measures refocusing as a form of adaptive problem-solving linked to job security and engagement.	Players who refocus their efforts have increased job security, suggesting that the ability to vary tasks and solve problems contributes to higher engagement.
Schaefer and Bormann (2025)	Illegitimate tasks, task variability, job crafting, meaningful work	Quantitative	Diary study	252	Germany	Examines how variability in illegitimate tasks influence job crafting and meaningful work over time	Measures day-to-day fluctuations in illegitimate tasks and links these to self-reported job crafting behaviors and perceived work meaningfulness	Variability in task demands can trigger adaptive task modification (job crafting), which enhances perceived meaning and supports engagement
Smith et al. (2009)	Regulatory focus, task variation, and intrinsic motivation	Quantitative	Laboratory experiment with students	73	USA	Investigate how a person’s regulatory focus influences the degree of task variation during monotonous work, with implications for intrinsic motivation	Measured task variation: Records the number of strategies used to vary a repetitive task, as an indicator of creative problem-solving and intrinsic motivation linked to engagement.	Promotive focus leads to increased task variation and intrinsic motivation, while preventive focus results in lower variation. Active problem-solving strengthens engagement.
Stasielowicz (2020)	Cognitive ability and performance adaptation	Quantitative	Meta-analysis	37.963	Multiple countries (USA, Germany, Australia, Norway, Singapore)	Examine relationship between cognitive ability and adaptation	Aggregates correlations between cognitive ability and performance adaptation, including moderator analyses based on task complexity and measurement type	Higher cognitive ability supports adaptation to changing and complex task demands, especially in dynamic environments
Sun et al. (2020)	Job crafting, task demands, creativity	Quantitative	Diary study (10 days)	91	China	Examines how employees craft job demands and their relation to creativity	Measures daily job crafting behaviors (changes in task demands) and links these to daily creative output	Actively modifying task demands enhances creativity and supports engagement with challenging or variable tasks
Taibah and Ho (2023)	Flexible work options, empowerment, and performance	Quantitative	Cross-sectional survey (online questionnaire)	109	Saudi Arabia/Malaysia	Explore how flexible work options affect performance and motivation among Generation Z employees using an online survey	Classifies empowerment dimensions: Task variation is manifested through moderation effects on access to support, information, and opportunities, which affect contextual performance and engagement.	Flexible work options moderate the relationship between empowerment and performance, enhancing the effect of information (increased engagement) and weakening the effect of support.
Van Dijk and Kluger (2011)	Feedback, regulatory focus, and task type	Quantitative	Scenario/laboratory experiment	315 (motivation)–55 (performance)	Israel	Examine how task type moderates the effects of positive and negative feedback on motivation and performance	Assesses task variation through feedback effects: Positive feedback in promotively oriented tasks stimulates creative problem-solving and variation, while negative feedback may be more helpful for preventive tasks.	Positive feedback increases motivation and performance in promotively oriented tasks, while negative feedback is more beneficial for preventive tasks.

Note: “Measurement Operation (Task Variation/Motivation/Performance)” refers to how the studies operationalize and measure the key variables in each article.

.

-

Task variation refers to changes in work strategies, such as the number of methods used to modify a repetitive task or changes in effort distribution across tasks.

-

Motivation is measured through self-report scales, behavioral measures, or selected parameters.

-

Performance is considered measurable outcomes, either objectively or experimentally.

The distinction is made between variability and variation:

-

Variability is the gradual change in a measurable variable over time, such as changes in motivation due to task type or feedback.

-

Variation refers to differences in approaches, strategies, or methods used to solve a task, reflecting creative problem-solving and adaptation.

Our synthesis indicates that task variation is beneficial for fostering creative problem-solving and strengthening intrinsic motivation, which in turn can enhance engagement. Adaptive problem-solving strategies, activated through positive feedback, moderate boredom, or targeted refocusing, are beneficial for maintain high engagement. Flexible work arrangements can facilitate task variation but require a balanced approach to ensure sustained engagement. Collectively, the studies suggest a link between the ability to vary tasks, problem-solving capacity, and perceived engagement, which can be applied across various work environments to improve both performance and well-being.

It is noteworthy that task variation is framed almost exclusively as beneficial, except for Azizi et al. (2013), who highlighted how higher boredom may lead to impaired problem-solving. Possible downsides of this interpretation include a potential bias toward positive or compensatory roles of task variation, such as cognitive overload and role ambiguity.

In sum, task variation is treated as an adaptive response and is conceptualized as an indicator of engagement, a coping mechanism, or a strategy to enhance performance in nearly every included paper. Conversely, problem-solving is treated as an outcome of task variation, not an independent construct measured with standardized tools. As most studies do not directly measure problem-solving, proxies are used instead, taking the form of strategic refocusing (Rotundo et al., 2012) and feedback-driven adaptations (Van Dijk & Kluger, 2011), among others.

3.2.2. Task Variability, Feedback, and Motivation

Van Dijk and Kluger (2011) investigate how the effects of positive and negative feedback on both self-reported motivation and actual performance vary depending on whether the assigned task is promotion-focused (emphasizing growth and gain) or prevention-focused (emphasizing accuracy and risk reduction). The study uses scenario experiments and laboratory setups in which participants are presented with tasks designed either to stimulate creativity and problem-solving (promotion-focused) or to require precision and risk aversion (prevention-focused). The authors suggest that when employees are given opportunities to vary tasks and apply creative problem-solving strategies, the work is perceived as more meaningful and stimulating. This aligns with findings showing that individuals generate more creative ideas when challenged with new tasks, resulting in improved motivation and more efficient self-management (Sun et al., 2020).

For prevention-focused tasks, negative feedback was found to increase motivation and performance. However, the study also indicates that a lack of task variation and creative problem-solving options may limit engagement, as employees in such setups reported performing more repetitive or less challenging tasks. Similarly, Smith et al. (2009) demonstrate how individuals actively vary monotonous tasks, showing that participants with a promotion focus used significantly more varied strategies than those with a prevention focus. In an experiment involving 73 students, randomly assigned to one of three conditions (promotion focus, prevention focus, or no focus), participants in the promotion focus group received instructions encouraging them to explore different ways of completing the task, while those in the prevention focus group were instructed to prioritize accuracy and avoid errors. Results showed that participants with a promotion focus used significantly more varied strategies (1.67 on average) than those with a prevention focus (0.76). Thus, task variation and regulatory focus influence how employees engage with tasks and regulate their effort.

Smith et al. (2009) suggest that the benefits of task variation, especially for those with a promotion focus, can significantly enhance interest in the task and increase effort toward task completion. Azizi et al. (2013) use mathematical models to describe and predict the development of boredom in repetitive tasks, examining how changes in boredom levels affect work motivation and employee engagement. The results indicate that at moderate levels of boredom, motivation increases relatively quickly over time, suggesting that a certain degree of boredom may act as a signal for the need for change, triggering a desire for greater task variation and leading to more flexible problem-solving strategies.

However, at higher levels of boredom, a slower and less effective change in motivation was observed. This implies that excessive boredom may hinder motivation to initiate task variation, either due to apathy or a perceived lack of autonomy to change tasks. In this way, high boredom levels can lead to lower engagement and less effective problem-solving. Azizi et al. (2013) argue that models incorporating task variation as an intervention generally produced higher motivation levels among employees. This aligns with findings suggesting that while task variability can support learning and creativity, its effects are not linear and depend on maintaining an appropriate balance (Narayanan et al., 2009).

3.2.3. Task Variability, Recovery, and Work Experience

Ejlertsson et al. (2018) conducted a qualitative study using eight focus groups with a total of 50 participants. The study aimed to identify factors that promote recovery (restoration of mental, physical, and emotional capacity) during the workday, focusing on variation, manageability, and community as key categories.

Across the focus groups, participants emphasized that task variation helps break up the monotony of the workday. Small changes, such as switching work areas or receiving new tasks, were described as restorative. Manageability of tasks also positively affected recovery, with control over one’s schedule helping to offset heavy workloads.

These findings are supported by research suggesting that employees actively respond to varying task demands through job crafting and resource reallocation (Schaefer & Bormann, 2025). Employees may seek to create more meaningful work experiences by modifying their tasks, even when those tasks are initially perceived as less meaningful. Community and appreciation were also highlighted as important for increasing motivation and recovery, suggesting that social context interacts with task variability in shaping engagement.

3.2.4. Refocusing and Adaptive Performance

Rotundo et al. (2012) explore how changes in the distribution of effort across different tasks, referred to as refocusing, affect individual performance over time and job security. Refocusing is used as an indicator of employees actively adapting and reallocating their effort to meet changing demands. The study employs a longitudinal design using data from 737 professional basketball players over 11 years, analyzing performance across multiple seasons.

Refocusing was measured by identifying shifts in effort allocation across different performance metrics. The findings showed that players who refocused their effort were more likely to remain in the league the following season, suggesting a more flexible approach to task management. Most notably, between season 4 and season 5, players who refocused were 4.74 times more likely to stay in the league compared to those who did not.

Research on adaptive performance similarly indicates that successful responses to changing task demands depend on both cognitive abilities and the capacity to regulate behavior (Stasielowicz, 2020). Rather than task variability directly increasing adaptation, exposure to changing task demands may place greater cognitive and regulatory demands on employees, which in turn can support adaptation and performance. Adaptive performance has been conceptualized as involving multiple processes, including recognizing change, diagnosing task requirements, and adjusting behavior accordingly.

In addition, research on creative performance suggests that effective problem-solving involves the interplay between exploratory and goal-directed processes, which together enable employees to generate and implement solutions (Bledow et al., 2026). These findings suggest that problem-solving is not only a task requirement, but also a key mechanism through which employees respond to task variability by actively adapting their behavior to changing demands.

3.2.5. Contextual and Individual Factors Influencing Task Variability

Taibah and Ho (2023) conducted an online survey with 109 participants to investigate how flexible work arrangements moderate the relationship between structural empowerment and job performance among employees aged 15 to 27. Structural empowerment was measured through access to opportunities (e.g., career growth), access to necessary knowledge, and access to guidance, support, and feedback from supervisors and colleagues.

According to the survey results, access to information had a positive moderating effect, while lack of access to information had a negative effect on the relationship between structural empowerment and job performance. Access to support, however, showed no significant moderating effect. These findings suggest that flexible work arrangements enhance the impact of information access on contextual performance, allowing employees to use their knowledge more effectively when given sufficient autonomy.

Conversely, Taibah and Ho (2023) found that increased flexibility appeared to diminish the positive effect of support, indicating that too much autonomy may weaken guidance from supervisors and peers. Flexible work arrangements showed no significant moderating effect on the relationship between access to opportunities and contextual performance, suggesting that flexibility alone does not directly influence how development opportunities affect employee engagement. Similarly, Knight et al. (2025) suggest that high levels of autonomy and support combined with low monitoring are associated with more positive outcomes, while low autonomy and high monitoring are linked to poorer well-being and lower motivation.

3.3. Task Variability and Proactive Work Adjustment

Across the included studies, a consistent pattern suggests that task variability and problem-solving demands function as central mechanisms through which employees regulate motivation, engagement, and performance. Rather than acting as isolated job characteristics, these factors appear to operate through dynamic processes of adaptation, self-regulation, and task modification across different work contexts.

Several studies indicate that task variability may stimulate proactive adjustments to work tasks, particularly through mechanisms such as job crafting, resource reallocation, and adaptive responses to changing demands (Schaefer & Bormann, 2025; Sun et al., 2020; Narayanan et al., 2009). Employees appear to respond to varying task demands by actively modifying their work, which may enhance perceived meaning, creativity, and self-regulation. Findings suggest that individuals generate more creative ideas when challenged with new tasks, resulting in improved motivation and more efficient self-management while solving these challenges. At the same time, findings indicate that the relationship between task variability and performance is non-linear. While exposure to varied tasks can support learning and creativity, achieving optimal productivity requires balancing task variation and task specialization (Narayanan et al., 2009).

3.4. Problem-Solving Demands and Adaptive Performance

Problem-solving demands are closely linked to creative and self-regulatory processes that may support performance under changing conditions. Evidence indicates that successful adaptation depends on both cognitive abilities and the capacity to regulate behavior in response to task demands, particularly in changing environments (Stasielowicz, 2020).

Rather than task variability directly increasing adaptation, findings suggest that exposure to changing task demands may place greater cognitive and regulatory demands on employees, which in turn can support adaptation as well as general performance (Stasielowicz, 2020). In addition, research on creative performance suggests that effective problem-solving involves cooperation between exploratory and goal-directed processes, which together enable employees to generate and implement solutions (Bledow et al., 2026). These findings suggest that problem-solving may function as one mechanism through which employees respond to task variability by actively adapting their behavior to changing demands.

3.5. Contextual and Individual Moderators

Importantly, several studies highlight that the effects of task variability and problem-solving are contingent on contextual and individual factors. Task novelty and personal initiative influence how employees respond to task demands, particularly in relation to creative outcomes (Herrmann & Felfe, 2013).

Findings suggest that the effects of work characteristics on creative outcomes are strengthened under conditions of high task variety, whereas more routine tasks may limit these effects. In addition, individual factors such as personal initiative appear to enhance employees’ responsiveness to task demands, indicating that individuals who are more proactive are better able to translate variability and problem-solving opportunities into creative outcomes (Herrmann & Felfe, 2013).

3.6. Work Design and Structural Conditions

Broader work design factors, including autonomy, monitoring, and organizational support, also shape how employees experience and respond to task variability across different work settings (Knight et al., 2025). Rather than being determined only by work location, these factors appear to create distinct patterns that influence employee well-being and engagement. High levels of autonomy and support, combined with low monitoring, are linked to more positive outcomes, while low autonomy and support combined with high monitoring are associated with poorer well-being and lower motivation.

This suggests that the effects of variability in the workplace and problem-solving demands depend on the overall work design, which can either support or limit employees’ ability to adapt. Employees who experienced greater autonomy and support appear better able to manage varying task demands, while environments characterized by close monitoring and limited support may reduce flexibility and engagement.

Altogether, the findings point toward potentially meaningful associations between task variability, problem-solving capabilities, and employee engagement across different contexts. At the same time, their effects appear to depend on factors such as task intensity, cognitive demands, and the balance between stability and change, highlighting the importance of considering context when interpreting their role in organizational settings.

3.7. Triangulation Results

Given the methodological heterogeneity of the included studies, findings were synthesized through triangulation by comparing patterns across quantitative and qualitative contributions. In line with the recommendation of Denzin (1978), this approach entails a view of theory and methods as concept sensitizers, useful for capturing relevant and important elements of reality. Rather than treating the studies as directly comparable, the synthesis focused on identifying recurring tendencies related to task variability and problem-solving capabilities across different contexts and methodological approaches. Despite substantial heterogeneity across the included studies, several recurring patterns suggest that task variability and problem-solving demands may function as key mechanisms influencing motivation, engagement, and performance, although their effects appear highly context-dependent. The results of the triangulation that we applied are summarized in

Table 2. Triangulation of the Included Studies.

Study	Method	Context	Main Focus	Key Contribution
Azizi et al. (2013)	Mathematical modeling	Theoretical/simulation-based	Task allocation and problem-solving under varying demands	Contributes to a theoretical perspective on how task structures may affect performance efficiency
Bledow et al. (2026)	Qualitative multilevel study	Employees and managers (innovation projects)	Creative problem-solving, self-regulation processes	Demonstrates that effective problem-solving depends on balancing exploratory and goal-directed processes
Ejlertsson et al. (2018)	Qualitative study	Employees in workplace setting	Recovery, flexibility, and adaptation	Offers contextual insight into how workers experience changing demands and adjustment processes
Herrmann and Felfe (2013)	Experimental study	Student participants	Task novelty, personal initiative, creativity	Shows that task novelty and individual initiative strengthen creative responses to task demands
Knight et al. (2025)	Quantitative cross-sectional study	Hybrid workers	Work design (autonomy, support, monitoring), well-being	Demonstrates that work design conditions shape how employees experience and respond to task demands
Narayanan et al. (2009)	Quantitative field study	Software employees (organizational setting)	Task variety, specialization, productivity	Shows that both task variety and specialization improve performance, but optimal outcomes require balance
Rotundo et al. (2012)	Survey-based quantitative study	Working adults	Engagement, task characteristics, and performance	Provides correlational evidence linking task characteristics to perceived engagement and work outcomes
Schaefer and Bormann (2025)	Quantitative diary study	Employees (workplace setting)	Task variability (illegitimate tasks), job crafting, meaningful work	Shows that variability in task demands can trigger job crafting and increase perceived meaning in work
Smith et al. (2009)	Experimental/survey-based study	Young workers/students	Task variation, boredom, and cognitive engagement	Highlights how variation may influence attentional and motivational processes
Stasielowicz (2020)	Quantitative meta-analysis	Multiple contexts	Cognitive ability and performance adaptation	Provides evidence that cognitive ability supports adaptation, especially in complex and changing tasks
Sun et al. (2020)	Quantitative diary study	Employees	Job crafting, task demands, creativity	Shows that actively modifying task demands enhances creativity and engagement
Taibah and Ho (2023)	Applied empirical study	Professional/organizational setting	Problem-solving capability and adaptive performance	Adds recent evidence on how problem-solving demands relate to adaptation in applied work contexts
Van Dijk and Kluger (2011)	Experimental study	Student participants	Task variation and motivational responses	Provides controlled evidence on how task variation may influence motivation under changing task conditions

.

The quantitative studies (Van Dijk & Kluger, 2011; Azizi et al., 2013; Rotundo et al., 2012; Smith et al., 2009; Sun et al., 2020; Narayanan et al., 2009; Stasielowicz, 2020) indicate that opportunities for task variation may support both motivation and performance by enabling adaptive responses to changing demands. For example, Van Dijk and Kluger (2011) show that positive feedback in promotion-oriented tasks stimulates creative problem-solving, which may strengthen intrinsic motivation, engagement, and performance. Similarly, Sun et al. (2020) demonstrate that employees generate more creative outcomes when engaging with changing task demands, while Narayanan et al. (2009) highlight that a balance between task variation and specialization is necessary to optimize productivity. In addition, Stasielowicz (2020) shows that cognitive ability plays a key role in performance adaptation, particularly under dynamic task conditions, reinforcing the importance of problem-solving demands in complex environments.

Azizi et al. (2013) suggest that moderate levels of boredom can trigger adaptive responses such as task variation and innovative problem-solving, which in turn increase motivation. However, when boredom becomes too intense, this response diminishes, illustrating the dual role of task variation: it can both enhance and reduce engagement depending on the level of boredom.

The qualitative study by Ejlertsson et al. (2018) further contextualizes these patterns by showing how task variability and flexibility are experienced in real work settings. Structural variation in work tasks and environments appears to support a sense of control and mastery, which may contribute to recovery during the workday and thereby increase engagement. These findings are supported by Schaefer and Bormann (2025), who show that variability in work tasks can stimulate job crafting and enhance perceived meaningfulness through dynamic resource reallocation. Similarly, adaptive responses such as refocusing and flexible task management are associated with more stable work outcomes, suggesting that problem-solving capabilities may support persistence under changing conditions (Rotundo et al., 2012; Taibah & Ho, 2023).

Contextual factors also appear to influence how task variability and problem-solving demands are experienced. For example, Herrmann and Felfe (2013) show that task novelty and personal initiative strengthen creative outcomes, while Knight et al. (2025) demonstrate that broader work design characteristics such as autonomy, support, and monitoring shape employee well-being and engagement across different work settings.

Taken together, the findings suggest that task variability and problem-solving capabilities may support engagement through both direct motivational processes and indirect mechanisms related to adaptation, recovery, and contextual flexibility. However, these effects appear sensitive to factors such as task intensity, context, and individual responses.

3.8. Assessment of Evidence Certainty

The research supports the conclusion that flexible problem-solving strategies and task variation contribute to increased engagement. The comprehensive assessment suggests that the included studies provide relatively strong, though somewhat variable, evidence for the relationship between task variation, problem-solving, and employee engagement. In addition, the predominance of WEIRD samples constrains the external validity of the evidence base, as the observed relationships may not generalize to non-Western or structurally different labor market contexts.

Van Dijk and Kluger (2011) and Herrmann and Felfe (2013) use experimental designs with detailed effect sizes, ensuring high internal validity, though limiting external validity. Azizi et al. (2013) employ mathematical models that produce precise estimates, indicating high certainty in the evidence. Similarly, Stasielowicz (2020) provides meta-analytic evidence supporting the robustness of findings related to performance adaptation, while Narayanan et al. (2009) offer quantitative field data highlighting the importance of balancing task variety and specialization.

Ejlertsson et al. (2018) offer deeper insights through qualitative focus groups, though findings may be influenced by subjective interpretation, as may be the case for Bledow et al. (2026) due to it being a qualitative multilevel study. Rotundo et al. (2012) rely on objective, longitudinal data from professional athletes, providing strong evidence, though generalizability to other work environments is uncertain. Smith et al. (2009) and Taibah and Ho (2023) use experimental and cross-sectional designs with self-reported data, which may reflect subjective responses not fully representative of broader populations. In addition, studies such as Knight et al. (2025), Sun et al. (2020), and Schaefer and Bormann (2025) rely on survey- and diary-based designs, which capture real-world dynamics but may introduce variability due to self-reporting and contextual differences.

Despite variation in study design, data sources, and certainty levels, the results consistently point to a positive relationship between task variation, problem-solving, and engagement in the included studies. Due to substantial heterogeneity in study designs, contexts, and operationalizations, consistency should primarily be interpreted at the level of recurring directional patterns and underlying mechanisms rather than directly comparable effect estimates.

3.9. Assessment of Risk of Bias

Reporting bias occurs when studies with significant or desirable results are more likely to be published, while those with less significant or unfavorable findings may be underrepresented (Dwan et al., 2013). The included studies demonstrate thorough and systematic reporting, including both effect sizes and precision measures. No systematic omission of significant results was found across the studies. The primary risks of reporting bias are therefore linked to methodological challenges in self-reporting (Taibah & Ho, 2023) and subjective interpretation in qualitative research (Ejlertsson et al., 2018).

None of the included studies were assessed as having a significant risk of bias, though each has certain limitations. Van Dijk and Kluger (2011) and Herrmann and Felfe (2013) use scenario experiments and laboratory setups, which offer strong internal validity but limit external validity. This raises questions about the generalizability of the findings to real-world work environments. Smith et al. (2009) also conducted a lab-based experiment, where generalizability may be an issue. The average participant age was 21.37 years, considerably younger than the average age of full-time employees, potentially limiting the relevance of the findings for older, more experienced workers.

Taibah and Ho (2023) present a cross-sectional survey based on self-reported data from Generation Z employees, which introduces a risk of reporting bias due to subjective factors such as memory or perception. Similarly, Sun et al. (2020), Schaefer and Bormann (2025), and Knight et al. (2025) rely on self-reported or diary-based measures, which may introduce common method bias and subjective interpretation of work experiences. Rotundo et al. (2012), by contrast, use objective performance data from professional basketball players, reducing the risk of measurement error. However, the main concern here is whether the findings are applicable to other types of workplaces. Similarly, Narayanan et al. (2009) use archival performance data from a real work setting, which strengthens ecological validity but may limit control over confounding variables.

Ejlertsson et al. (2018) and Bledow et al. (2026) rely on qualitative studies, which carry a risk of interpretation bias, as conclusions depend on researchers’ interpretations. The study conducted by Ejlertsson et al. (2018) also relies on participants’ perceptions of workplace recovery, which may vary across individuals and contexts. Azizi et al. (2013) use a mathematical model that may carry bias in its assumptions, as the experience of boredom is subjective and influenced by individual and contextual factors that the model may not fully capture. Stasielowicz (2020), as a meta-analysis, reduces random error by aggregating findings across studies but may still be affected by publication bias and variability in how performance adaptation is measured across included studies.

4. Discussion

The aim of this study was to explore how task variation and different aspects of problem-solving affect employee engagement and motivation. The findings from the thirteen included studies collectively suggest that both a varied workday and the opportunity to apply diverse problem-solving techniques are associated with increased motivation, improved performance, and higher engagement. However, the methods and contexts varied across studies, allowing for a more nuanced interpretation. Problem-solving variables refer to factors that affect how employees identify, assess, and resolve challenges in their daily work, such as the ability to refocus effort across tasks (Rotundo et al., 2012), the use of strategic feedback (Van Dijk & Kluger, 2011), or the degree of regulatory focus guiding problem-solving strategies (Smith et al., 2009). These articles focus on adults in diverse workplaces, ranging from service and healthcare to sports and office work.

A key commonality among the included studies is their emphasis on employees’ subjective experiences, rather than focusing solely on practical outcomes. Whether through questionnaires, interviews, and focus groups or performance measurement in practice, the central focus is on employees’ own understanding and experience. This provides insight into how engagement encompasses both external conditions and the individual’s approach to managing their workday.

Furthermore, we highlight innovative perspectives that help explain why variation and problem-solving may enhance engagement. Psychological safety emphasizes that working in environments characterized by trust and support is crucial for employees to feel safe experimenting with new ways of working (Edmondson, 1999). Without this sense of safety, suggestions for variation or unconventional problem-solving strategies are likely to be met with resistance, potentially undermining engagement. Conversely, when employees know they can fail without being punished, their willingness to take initiative and the learning outcomes from task variation increase.

Based on the review of studies in the Section 3 various methodological approaches yield diverse but valuable insights. These include experimental designs (Van Dijk & Kluger, 2011; Smith et al., 2009; Herrmann & Felfe, 2013), mathematical modeling (Azizi et al., 2013), longitudinal analyses (Rotundo et al., 2012), meta-analytic, multilevel and field-based quantitative studies (Stasielowicz, 2020; Bledow et al., 2026; Narayanan et al., 2009), survey and diary designs (Taibah & Ho, 2023; Sun et al., 2020; Schaefer & Bormann, 2025; Knight et al., 2025), and qualitative focus groups (Ejlertsson et al., 2018). Together, these approaches highlight how flexible work arrangements and task design characteristics may shape the relationship between motivation, problem-solving, and performance, with implications for employee engagement.

4.1. General Interpretation in Light of Previous Research

4.1.1. Task Variation and Engagement

Task variation emerges as a key mechanism for maintaining motivation and preventing boredom. In Smith et al. (2009), participants with a promotion focus used more strategies to vary a monotonous task, leading to higher intrinsic motivation. This supports earlier research, such as Self-Determination Theory (Ryan & Deci, 2000), which identifies autonomy and variation as central sources of motivation and well-being. Ryan and Deci argue that when individuals experience freedom to choose and vary their tasks, and feel competent in performing them, their natural development is enhanced. Conversely, controlling environments that limit task autonomy can hinder personal growth.

Ejlertsson et al. (2018) also support the idea that perceived variation, through changes in task type, pace, and physical environment, contributes significantly to recovery and a sense of mastery. In a diary study, Demerouti et al. (2012) found that work-related flow, a state of deep focus and absorption, positively affects energy levels during and after work, provided there is sufficient time for recovery. Such flow experiences help build personal resources by promoting positive states and reducing exhaustion. Our findings suggest that task variation not only reduces monotony but also serves as an active source of increased engagement, albeit within predominantly WEIRD contexts.

Azizi et al. (2013) further reinforce this interpretation by modeling workplace boredom and showing that moderate boredom can activate adaptive problem-solving strategies. This aligns with previous research on flow and optimal challenges, such as Engeser and Rheinberg (2008), who argue that a balance between challenge and skill leads to increased cognitive activation, learning, and engagement. However, their model also shows that high levels of boredom result in lower motivation and performance, highlighting the need for individualized task design.

4.1.2. Problem-Solving as a Resource for Mastery and Performance

Several of the included studies emphasize the importance of allowing employees to actively engage in problem-solving during the workday. Van Dijk and Kluger (2011) show that feedback tailored to task type and regulatory focus enhances both motivation and performance. Positive feedback is especially effective for promotion-oriented tasks, while negative feedback can be motivating in prevention-oriented tasks. This suggests that a flexible, task-sensitive feedback strategy promotes learning and engagement by reinforcing a sense of mastery.

Rotundo et al. (2012) demonstrate that individuals who actively refocus their effort across different work dimensions perform better over time and experience greater job security. Although the study was conducted with professional basketball players, the findings are transferable to other workplaces. According to Bakker and Demerouti (2008), the ability to adjust and adapt effort is a key component of employee motivation and engagement. They argue that when employees use adaptive strategies to manage varying demands and challenges, they strengthen both personal and job-related resources. This adaptability enhances the sense of mastery and can lead to increased engagement.

Bakker and Demerouti (2008) further assert that employees who effectively allocate their resources, such as refocusing effort across tasks, achieve a better balance between job demands and available resources. This reduces the risk of burnout and increases intrinsic motivation. Thus, the ability to redistribute energy can be seen as a problem-solving strategy that promotes goal achievement and builds the resources necessary to sustain high levels of engagement. In this way, Rotundo et al. (2012) support Bakker and Demerouti’s findings by showing that adaptive adjustment strategies are beneficial for maintaining stable performance and job security, which in turn can lead to increased engagement.

4.1.3. Workplace Culture, Flexibility, and Facilitation

Flexibility and structural facilitation can both promote and hinder task variation and engagement, depending on how they are implemented. Taibah and Ho (2023) argue that flexible work arrangements enhance the positive effect of access to information on contextual performance. At the same time, flexibility reduces the effect of social support, indicating that freedom and variation must be balanced with structure and access to assistance. This aligns with literature on empowerment and psychological safety, which emphasizes that autonomy must be supported by clear communication and access to resources to yield positive outcomes.

Edmondson (1999) defined psychological safety as the shared belief within a group that it is safe to take interpersonal risks without fear of negative consequences and maintained that a high degree of psychological safety is essential for fostering open communication and learning in work teams. In a safe environment, employees feel comfortable sharing information and seeking help, which can strengthen overall group performance. Edmondson warned that if flexible work arrangements are not balanced with structural elements that ensure clear communication and support, perceived psychological safety may be weakened. Therefore, it is crucial to design flexible work systems that maintain stable social safety, where access to information and social support is preserved.

4.2. Overall Assessment

Overall, the findings of this literature review suggest that both task variation and the opportunity to apply diverse problem-solving strategies contribute to increased employee engagement. Despite methodological differences, the included studies consistently indicate that varied work, facilitated through tailored feedback, active refocusing, or flexible work arrangements, promotes motivation, engagement, and performance.

This relationship is supported by other theoretical frameworks in organizational psychology and motivation research, where elements such as autonomy, feedback, and psychological safety (Ryan & Deci, 2000; Bakker & Demerouti, 2008; Edmondson, 1999) play a central role.

The results also show that the effects of task variation and problem-solving are not universal but vary across different contexts. For example, studies involving students and professional athletes reveal different strengths and limitations of adaptive strategies, suggesting that work environment and leadership strategies moderate the impact of these factors on engagement. This variation highlights the need for context-sensitive interventions tailored to the workplace and its employees. More specifically, the transferability of these findings depends strongly on the work context, such as task complexity and degree of autonomy. In knowledge-intensive or creative roles, task variation may enhance learning and innovation, whereas in more standardized environments, opportunities for variation may be limited by established demands (Van Dijk & Kluger, 2011).

Leadership style and performance evaluation systems further influence whether task variation is encouraged or penalized. For instance, environments emphasizing error avoidance may discourage experimentation, limiting the engagement-enhancing potential of task variation (Edmondson, 1999). These contextual differences highlight that task variation and problem-solving strategies are most effective when aligned with organizational culture, job design, and leadership practices (Bakker & Demerouti, 2008). Moreover, differences in team interdependence and decision-making autonomy may further shape how task variation and problem-solving opportunities are perceived and utilized by employees (Edmondson, 1999).

4.3. Limitations

Although this review was conducted in accordance with PRISMA 2020 guidelines, certain limitations in the execution process should be acknowledged. First, data collection was limited to seven databases (PsycINFO, Academic Search Ultimate, Business Source Elite, CINAHL, ERIC, Web of Science, and Scopus), which may have excluded relevant studies published elsewhere. The search terms and inclusion criteria may also have excluded studies with potentially relevant findings, particularly if published in languages other than English. Additionally, search terms were adapted to each database. More specific engagement-related terms were used in PsycINFO for work- and employee-related searches to reduce the high volume of psychologically oriented but contextually irrelevant results. In the remaining databases, broader workplace-related terms were used due to their generally stronger organizational and business focus compared to PsycINFO.

There may also have been a degree of subjectivity in the selection process. Although interrater agreement was calculated with the help of two neutral peers for the searches, disagreements about which studies to include may have influenced the final evidence base. Despite an agreement rate of 86.7% and 83.3%, respectively, it should be noted that this was measured only once for each search. According to McHugh (2012), an agreement rate of 80% or higher is recommended for most texts, and the findings were therefore included despite the possibility of chance influencing the agreement score.

Another challenge is that 24 additional studies initially met the inclusion criteria but were later excluded after full-text analysis. This may have narrowed the perspective, although the interrater agreement suggests that these exclusions were generally beneficial for the overall quality of the review. Moreover, it was not possible to perform a meta-analysis or a quantitative summary of effects because of a lack of empirical quantitative data on this topic. The main issue appears to be the difficulty in operationalizing and quantifying task variation, especially as this varies substantially based on profession, sector, level of responsibility, and other factors.

Limitations of the Included Studies

Although the thirteen included articles provide valuable insights into the relationship between task variation, problem-solving, and employee engagement, several limitations must be considered when interpreting the findings. One key limitation is the heterogeneity across studies, which has been presented as beneficial for exploring the application of strategies (e.g., engagement irrespective of task, age, etc.) but may also affect the interpretation and validity of the findings. The studies in our final selection feature heterogeneous contexts, samples, and focus. While we did not purposefully restrict our analysis to a specific setting, spanning too widely across settings complicates the synthesis and weakens the generalizability of the findings.

The methodologies vary significantly. Experimental studies such as Van Dijk and Kluger (2011) and Smith et al. (2009) use laboratory and scenario experiments, which offer high internal validity but may limit external validity. This also applies to the experimental work by Herrmann and Felfe (2013), where controlled conditions may not fully capture real-world work complexity. For instance, the student sample in Smith et al. (2009) may not fully reflect the work experiences of seasoned employees. Similarly, the objective but specific context in Rotundo et al. (2012) raises questions about generalizability beyond professional athletes. Quantitative field-based, multilevel and meta-analytical studies (e.g., Narayanan et al., 2009; Bledow et al., 2026; Stasielowicz, 2020) provide broader evidence, though they may still be limited by contextual or operational constraints.

Azizi et al. (2013) use mathematical models to examine responses to boredom, but the underlying assumptions may oversimplify psychological processes, limiting the depth of the analysis. Ejlertsson et al. (2018) base their findings on qualitative focus groups, which may be subject to interpretation bias, affecting the reliability of the results. The study by Taibah and Ho (2023) relies on self-reported data, which introduces a risk of response bias. This type of data makes it difficult to distinguish meaningful relationships from random findings, as the basis for participants’ responses may be unclear. Similarly, diary- and survey-based studies (e.g., Sun et al., 2020; Schaefer & Bormann, 2025; Knight et al., 2025) capture dynamic work experiences but remain dependent on subjective reporting and contextual variation.

An additional methodological concern relates to how employee engagement is operationalized across studies. Engagement is often inferred indirectly through related constructs such as motivation, performance, job security, or recovery, rather than measured as a distinct psychological state. While these constructs are theoretically connected, Bakker and Demerouti (2008) emphasize that engagement is a varied and dynamic process shaped by the interaction between job demands and resources, rather than a static outcome. Consequently, improvements in performance or motivation may reflect effective resource allocation or skill utilization rather than heightened engagement.

Qualitative approaches, such as those used by Ejlertsson et al. (2018), provide rich insight into subjective experiences related to engagement, recovery, and manageability at work, but are inherently vulnerable to interpretation bias and limited generalizability. Quantitative studies relying on self-reported measures, including those examining motivation and empowerment (Smith et al., 2009; Taibah & Ho, 2023), may also be influenced by response tendencies, as participants’ evaluations may be shaped more by momentary perceptions than by stable work characteristics. These inconsistencies complicate direct comparisons across studies and highlight the need for future research to adopt longitudinal and multimethod approaches. Such approaches would better capture engagement as an evolving process that develops over time and is influenced by cumulative work experiences and recovery opportunities (Bakker & Demerouti, 2008; Demerouti et al., 2012).

4.4. Further Avenues of Research

Our findings highlight the importance of designing work tasks to include a degree of variation. Rotundo et al. (2012) illustrate how the ability to refocus effort can lead to increased job security and improved performance. To leverage this insight, organizations should facilitate job design that allows for individual adaptation. Implementing flexible work arrangements, as discussed by Taibah and Ho (2023), can give employees the freedom to choose work schedules and methods that best support their personal rhythms and learning needs.

A balanced work environment, where flexibility is combined with structured support systems, can help employees perform better and experience greater job satisfaction and engagement. Overall, these approaches suggest that investing in adaptive leadership and task design can be highly valuable for both individual well-being and organizational productivity.

From a policy perspective, labor unions and regulatory bodies could advocate for the implementation of systems that support regular, personalized feedback and flexible work arrangements. These systems should accommodate employees’ problem-solving needs while ensuring access to structured support. Such guidelines could improve workplace quality, reduce the risk of burnout and stress, and ultimately lead to higher productivity.

Although the existing literature provides a strong foundation, this review identifies several areas for further investigation. Future studies could explore how task variation is operationalized across different industries and cultures to better understand contextual differences. There is a need for more longitudinal research to determine whether the observed effects on engagement and job security persist over time. Research could also build on the adaptive models proposed by Azizi et al. (2013) to examine which individual traits moderate the impact of boredom on problem-solving and motivation. Finally, future studies could investigate how digital tools and modern work methods enhance task variation and engagement, especially in light of the increasing use of new technologies in the workplace.

5. Conclusions

This systematic review examined how task variation and problem-solving demands are associated with employee engagement across a heterogeneous body of empirical literature. Taken together, the findings suggest that task variation and problem-solving are often linked to engagement-related outcomes (e.g., motivation, learning, creativity, and adaptive performance), but that these relationships are neither uniform nor unconditional.

Across studies, task variation appears most consistently beneficial when it is moderate, meaningful, and supported by broader work design features such as autonomy, feedback, and social support. Several contributions indicate that variability in task demands can stimulate adaptive responses, including exploratory problem-solving, job crafting, and refocusing of effort. At the same time, the evidence points to important limits: excessive variability, poorly structured novelty, or illegitimate task demands may undermine motivation or well-being, particularly when employees lack sufficient control or resources to respond effectively.

More specifically, opportunities for task variation are associated with higher self-reported motivation and performance through tailored feedback, flexible work arrangements, or adaptive responses to moderate boredom. Conversely, a lack of variation has been shown to reduce engagement (Smith et al., 2009). In line with Van Dijk and Kluger (2011), several findings suggest that feedback aligned with employees’ regulatory focus may foster more effective and creative problem-solving. Together, these results indicate that feedback processes and task design features may shape how employees experience and respond to variability, rather than task variation being inherently motivating.

The reviewed literature further highlights that problem-solving is best understood as a dynamic process rather than a single capability or outcome. The contributions converge in suggesting that engagement is linked to employees’ ability to recognize changing demands, balance exploratory and goal-directed strategies, and adjust their behavior over time. Individual differences (e.g., regulatory focus, cognitive ability, personal initiative) and contextual factors (e.g., leadership, hybrid work design, and feedback systems) appear to shape when and how task variation translates into adaptive or engaging experiences. Importantly, given that the vast majority of included studies are based on WEIRD samples, the generalizability of these patterns beyond Western and highly industrialized contexts remains uncertain.

Overall, this review suggests that understanding task variation and problem-solving demands may be beneficial not only for fostering employee engagement, but also for enabling the behavioral flexibility required for innovation and adaptation in dynamic organizational systems. However, given the methodological diversity and predominance of cross-sectional and self-report designs, these conclusions should be interpreted as indicating patterns of association rather than strong causal effects, thus, as indicative rather than broadly generalizable across cultural and institutional settings.