Ask, but You Might not Receive: Unanswered Supervisor Support Scale Development and a Daily Diary Study

Abstract

Supervisor support is widely studied in the organizational literature, yet existing measures tend to exclusively focus on either the provision or the seeking of support, while overlooking instances where employees seek support but do not receive it – an experience termed unanswered supervisor support (USS). In Study 1 (N = 312 employees), we developed a measure of the experience of USS and examined its reliability and validity. In Study 2, we provided further support for the measure and, using a diary methodology, examined daily fluctuations in the experience and consequences of USS. Drawing from self-determination theory, we expected that need satisfaction and frustration would mediate the effects of USS on emotional exhaustion, perceived leadership effectiveness, and helping behavior. For five workdays, 199 employees completed a survey at the end of each workday. As predicted, on days when employees experienced USS, they had greater need frustration and emotional exhaustion. They also had lower need satisfaction and perceived their supervisor as a less effective leader. The association between USS and emotional exhaustion was mediated by need frustration – in particular, frustration of the needs for competence and relatedness. Further analyses showed that relatedness frustration mediated the effects of USS on employees’ perceptions of their leader’s effectiveness. The experience of USS in daily work life has implications for employees’ well-being and the way they perceive their supervisor. Thus, employees, supervisors, and organizations need to be aware of the impact of USS and how to prevent and manage its occurrence.

Social support from a supervisor can be an important resource at work due to its positive impact on employee and organizational functioning. For this reason, supervisor support has received considerable attention from researchers. Indeed, several meta-analyses have demonstrated the beneficial outcomes of receiving support and the detrimental outcomes of not receiving support (Barak et al., 2009; Luchman & González-Morales, 2013; Mathieu et al., 2019; Ng & Sorensen, 2008). Although the support process involves both a giver (i.e., the supervisor) and a receiver (i.e., the employee), the existing literature has tended to focus on whether or not the supervisor provides support, while neglecting to consider the employee’s own motivations and interpretations with regard to this support. Consideration of both the giver and receiver is important, as it is possible for there to be a mismatch between the support that is given and the support that is desired. For example, an employee may desire and actively seek support from their supervisor for a particular problem or challenge they are facing, but not receive it. This experience has been termed unanswered supervisor support (USS). USS is defined as an interpersonal interaction in which an employee actively asks their supervisor for support, but the supervisor does not provide the requested support (McIlroy et al., 2021a, b). Thus, there are two key elements in the USS process: the employee’s request for support, and the supervisor’s failure to provide support. We focus on unanswered support within the dynamic of the employee-supervisor relationship, because having access to support from different sources in the workplace (e.g., supervisor vs co-worker) can produce different effects, and supervisor support is a stronger predictor of employee outcomes compared to co-worker support (Dormann & Zapf, 1999; Hämmig, 2017; Mathieu et al., 2019). When an employee expects to receive support, yet their request goes unanswered, this lack of support may be more detrimental, compared to when support is not sought and is likely not expected.

Consider the following scenario: An employee receives a last-minute, urgent request to deliver a report to a client. The employee quickly drafts the report and emails it to their supervisor for feedback. After hours pass without receiving a reply, the employee then tries calling their supervisor, but to no avail. In this scenario, the employee probably expects that, by reaching out to their supervisor, their supervisor will reply and provide feedback on the report. However, not receiving a response will likely negatively impact the employee’s affect, the way they perceive their supervisor, and their behavior in the workplace (e.g., they may be unable to finalize the report to meet the client’s deadline). Therefore, in the present research, we consider the employee’s perspective in the process of seeking support, because the employee’s own motivations may influence how they interpret a lack of supervisor support. Across two studies, we develop and validate a measure to assess the experience of USS and examine the consequences of USS as it occurs in daily work life.

Our research contributes to the broader literature on supervisor support by taking a closer look at the phenomenon of USS. Here, we make five important contributions. First, we extend on the supervisor support literature by simultaneously examining the request and subsequent lack of support. As demonstrated in a recent review (McIlroy et al., 2021a), literature that incorporates supervisor support as an available job resource tends to examine employees’ access to supervisor support, without considering their active efforts to seek support. Conversely, research on proactive employee behavior and supervisor support mobilization examines the outcomes of employees showing initiative in increasing their own access to supervisor support (e.g., asking a supervisor for advice), regardless of the actual provision of support. Thus, we integrate and extend on these perspectives by studying specific instances where employees’ attempts to access supervisor support are unsuccessful. To our knowledge, only one study to date has examined the phenomenon of USS (McIlroy et al., 2021b). As such, one of the aims of this research is to replicate and build on these findings by using a diary study to ensure the results are reproducible and generalizable.

Second, we develop a new measure of USS to reliably assess the extent to which employees experience USS in their work lives. Across both studies, we examine the reliability and validity of this measure, including both general and day-level measures. Existing supervisor support measures assess either employees’ perceptions of supervisor support availability (e.g., Lawrence et al., 2007; Peeters & Le Blanc, 2001; Peeters et al., 1995), or the actions employees take to acquire support (e.g., Lawrence et al., 2015; Morrison, 1993; Petrou et al., 2012), but these measures fail to capture situations where employees’ requests for support go unanswered. Thus, a measure of USS is needed to capture the nuanced dynamics of requesting but failing to receive support.

Third, in Study 2, using a diary study methodology, we examine daily fluctuations in USS and the associated consequences. While prior between-person experimental research has established the construct of USS and demonstrated its consequences for employees’ well-being, performance, and relational outcomes (McIlroy et al., 2021b), the present research extends on this by examining the within-person process of USS as it occurs in daily work life (Fisher & To, 2012). The benefit of this method is that it allows us to capture day-to-day fluctuations in USS that are not captured using cross-sectional research methods. It also offers greater ecological validity by examining experiences of USS as they occur in real life, rather than in a laboratory setting (Ohly et al., 2010). Diary research on supervisor support provides indirect evidence that USS may also vary on a day-to-day basis (Xanthopoulou et al., 2009).

Fourth, drawing on self-determination theory (SDT; Deci & Ryan, 2000; Deci et al., 2017; Ryan & Deci, 2000b), we simultaneously examine need satisfaction and need frustration as mediators in the USS process in Study 2. Need satisfaction and need frustration have been identified as distinct dimensions with unique antecedents and consequences (B. Chen et al., 2015; Coxen et al., 2023), so we examine if USS has different effects on the outcomes via these alternate pathways. This will provide a more comprehensive understanding of the mechanisms of USS compared to prior research that has examined only need satisfaction (McIlroy et al., 2021b).

Finally, in Study 2, we consider how other job demands and resources in the work environment may influence the effects of USS by examining workload and co-worker support as potential moderators. As prior research on USS has not been able to robustly identify moderators of the USS process (McIlroy et al., 2021b), we aim to understand if having access to co-worker support minimizes the consequences of USS, and conversely, if having a higher workload exacerbates the consequences. Identifying viable moderators will help inform strategies in the workplace to mitigate the consequences of USS.

Study 1: Unanswered Supervisor Support Scale Development

The aim of Study 1 was to develop and validate a new measure of USS following best practice recommendations (e.g., Boateng et al., 2018; Hinkin, 1995). To understand how USS fits into the broader literature and why a new measure is needed, we draw from research on similar constructs, including supervisor support and the highly related construct of leader-member exchange, proactive employee behaviors such as job crafting and information seeking, as well the construct of abusive supervision. Table 1 summarizes what we consider to be the conceptual similarities and differences between USS and these constructs. In the next section, to position USS within the existing literature, we evaluate the theory on these related constructs.

Table 1 Study 1 comparison of unanswered supervisor support with related constructs

Supervisor Support

Social support refers to the sharing of psychological or material resources in an interpersonal relationship (Cohen & Wills, 1985). Supervisors can provide different types of support to employees, including emotional (provision of empathy and care), instrumental (provision of practical help), informational (provision of general information), and appraisal support (provision of information that helps employees evaluate themselves; House, 1981). Research shows these various types of support are highly correlated and produce similar effects (e.g., Barling et al., 1988; Mathieu et al., 2019). Therefore, we also conceptualize supervisor support as an aggregate of these four types of support.

Several theoretical frameworks help explain why supervisor support is beneficial for employees and organizations. For instance, the job demand-control-support (JDCS) model and job demand-resources (JDR) model propose that supervisor support is an important job resource that needs to be available to employees to reduce stress and increase motivation (Bakker & Demerouti, 2007; Demerouti et al., 2001; Johnson & Hall, 1988; Johnson et al., 1989). Similarly, conservation of resources (COR) theory proposes that employees aim to acquire and maintain job resources, like supervisor support, and that employees experience stress when these resources are threatened or lost (Hobfoll, 1989; Hobfoll et al., 2018). SDT also considers supervisor support to be an important job resource, and proposes that having access to such resources satisfies employees’ psychological needs for autonomy, competence, and relatedness, and in doing so enhances motivation, social development, and well-being (Deci & Ryan, 2000; Ryan & Deci, 2000a; Van den Broeck et al., 2016). Thus, these theories conceptualize supervisor support as a resource that employees perceive as being either available or not, and employees experience negative consequences when they feel as though they do not have access to support. It is worth noting that supervisor support is also incorporated in other theories, such as leader-member exchange, organizational support theory, and social exchange theory (Cropanzano & Mitchell, 2005; Graen & Uhl-Bien, 1995; Rhoades & Eisenberger, 2002). These frameworks examine employees’ overall perceptions that their supervisor is supportive and underscore the importance of these positive perceptions in fostering employees’ motivation and willingness to contribute to their work environment. To guide the development of our operationalization of USS, we adopt the first conceptualization, where supervisor support is viewed as a resource that employees request and either do or do not receive, rather than focusing on employees’ overall perceptions of their supervisor or broader work environment.

Although USS involves a lack of supervisor support, it is distinct from low levels of support for two key reasons. First, the supervisor support literature tends to focus on employees passively receiving support, whereas USS considers that employees act as agents to increase their own access to support. Second, literature on supervisor support and the highly related construct of leader-member exchange are grounded in the notion that employees form a global perception about their supervisor and the support they provide, while USS is a specific occurrence that may have negative consequences, independent of general levels of support. For example, an unanswered request for support may have negative consequences for an employee at that moment, even if the employee generally believes that their supervisor is supportive overall. Although we propose that USS and low levels of supervisor support are distinct constructs, we expect that there will be a strong correlation between them, given that they both reflect insufficient levels of supervisor support. Thus, we hypothesize:

• Hypothesis 1: USS will be negatively correlated with (a) supervisor support and (b) leader-member exchange.

Proactive Employee Behavior

Given that USS involves the active seeking of support, it also draws parallels to theories on proactive employee behavior, including job crafting and information seeking. Job crafting refers to the active behaviors employees engage in to change aspects of their job (Tims & Bakker, 2010; Wrzesniewski & Dutton, 2001). Social resources are one aspect that employees can craft, for example, by asking their supervisor for feedback or information (Morrison, 1993; Tims et al., 2012). However, the literature on job crafting and information seeking has an underlying assumption that the seeking of social resources is fulfilled, such that supervisors provide support when it is requested of them. Indeed, research shows that employees who request support are more likely to receive it, resulting in positive outcomes (Ellis et al., 2017; Lim et al., 2020; Tims et al., 2013). Therefore, this literature does not consider specific situations when requests go unanswered, and the consequences this lack of support may have for employees. In such situations, we would expect USS to negatively impact employees because they were unsuccessful in acquiring their desired social resources. Thus, we hypothesize:

• Hypothesis 2: USS will be negatively correlated with (a) job crafting and (b) information seeking behaviors.

Abusive Supervision

Finally, employees who experience USS may feel as though they were mistreated or that their supervisor was inconsiderate for not providing support, which is similar to the construct of abusive supervision. Abusive supervision refers to employees’ perceptions about their supervisor’s “hostile verbal and nonverbal behaviors, excluding physical contact” (Tepper, 2000, p. 178). Like abusive supervision, USS could involve inconsiderate or hostile behavior from the supervisor (e.g., the supervisor intentionally ignoring the employee’s request). However, this is not always the case, as the supervisor might have intended to reply, but simply forgot. Thus, the consequences of USS may depend on how the employee interprets the situation. For example, the consequences might not be as detrimental if the employee believes their supervisor did not provide support because they were particularly busy, compared to an employee who believes their supervisor intentionally ignored them. In this way, USS is distinct from abusive supervision where, by definition, the supervisor’s behavior is always perceived to be hostile. Nevertheless, in general, we hypothesize:

• Hypothesis 3: USS will be positively correlated with abusive supervision.

Overall, the supervisor support and abusive supervision literatures tend to focus on the supervisor’s behavior, whereas the job crafting and information seeking literatures focus on the employee’s behavior. The construct of USS builds on these literatures by considering the dynamic interplay between both the employee’s and the supervisor’s actions. Specifically, USS considers the employee’s agency in seeking support in addition to the supervisor’s subsequent failure to provide support. A recent literature review demonstrated that there is an absence of research examining situations where support is requested but is not received (McIlroy et al., 2021a). This demonstrates the need for a new measure to capture the nuance of requesting but not receiving support.

Method

Item Generation

Given the lack of existing USS measures, we developed a new scale using a combination of deductive and inductive approaches (Hinkin, 1995). We started with a deductive approach, which involved conducting a comprehensive literature review. In line with the theoretical framework of USS proposed by McIlroy et al. (2021a), the new items were informed by the literature on related constructs, including supervisor support (e.g., Peeters & Le Blanc, 2001), job crafting (e.g., Petrou et al., 2012), and information seeking (e.g., Morrison, 1993). The items were also designed to capture the four types of social support proposed by House (1981; informational, instrumental, appraisal, and emotional), consistent with other supervisor support measures (Lawrence et al., 2007, 2015; Peeters & Le Blanc, 2001; Peeters et al., 1995). To generate the items, we used existing measures of supervisor support, job crafting, and information seeking as a basis, and adapted these items to incorporate both of the key elements of USS (i.e., the active request for support and the subsequent lack of support). We also included various phrasings to ensure the items were as clear as possible for participants. For example, “my attempts to talk to my supervisor about problems or difficulties at my work are unsuccessful” and “when I approach my supervisor to discuss difficulties or problems at my work, I do not get the support I seek” both reflect unanswered requests for emotional support, so it was important to include different variations of the items to help identify the most effective wording.

The items were also informed by inductive research conducted by McIlroy et al. (2021b), where, using a recall study design, employees were asked to write about a time when they experienced USS. This research showed that employees largely sought the four types of support proposed by House (1981), and so we also used the participants’ qualitative responses to inform the new scale. Thus, based on our analysis of the supervisor support, job crafting, and information seeking literatures, as well as employees’ written experiences of USS, the four types of support proposed by House were deemed to be the best indicators of USS and as such, were reflected in the USS items. After using both deductive and inductive approaches, the authors (three experts in the field of social support) generated and refined a pool of 51 items. The items were then critically evaluated by three PhD students trained in social and organizational psychology. They were provided with a definition of USS and were asked to assess the extent to which the items reflected the construct. After discussing the items in depth, and based on their expertise, 11 items were modified (e.g., changed “I seek advice from my supervisor, but do not receive it” to “when I seek advice from my supervisor, I do not receive it” for greater clarity) and 24 items were removed after being deemed less relevant, leaving a pool of 27 items. We then included these 27 items in an online survey to assess their reliability and validity.

Participants and Procedure

Participants were 330 full-time employees in the United Kingdom who had a work supervisor. They were recruited via Prolific Academic and received £1.09 for completing an online survey. Data from 18 participants were excluded due to failing an attention check item (“for data quality purposes, please respond 'strongly disagree' to this item”; Meade & Craig, 2012), leaving a final sample of 312. The sample had a mean age of 35.42 years (SD = 10.59), and 65% were female. On average, participants worked 38.87 h per week (SD = 6.79) and had job tenure of 5.26 years (SD = 5.86). Of the participants, 32% held a supervisory role. Participants worked in a variety of industries, including education and training (19.9%), public administration and safety (11.5%), healthcare and social assistance (10.6%), retail (9.0%), financial and insurance services (6.7%), and professional, scientific, and technical services (6.4%).

Participants completed the online survey, where they responded to a general measure of our newly developed USS scale, as well as measures of theoretically related constructs for validation purposes. After completing the general measures, participants then responded to all USS items again, only this time at the day-level, such that they were asked to indicate the extent to which they agreed with the items based on their workday today. This was to help inform the daily diary research we planned to conduct in Study 2, and to ensure the item wording was suitable for daily measurement. All measures were rated on a 7-point scale (1 = strongly disagree, 7 = strongly agree).

Measures

Unanswered Supervisor Support

The 27-item general measure of USS included the four dimensions of support: informational support (e.g., “I do not get the necessary information from my supervisor when I ask for it”); instrumental support (e.g., “I do not receive help from my supervisor when I ask for it”); appraisal support (e.g., “I do not receive feedback from my supervisor when I ask for it”); and emotional support (e.g., “when I approach my supervisor to discuss difficulties or problems at my work, I do not get the support I seek”). For the daily measure of USS, we modified the wording of the 27 items, such that participants were asked to think about their workday today (e.g., “today at work, I did not get the necessary information from my supervisor when I asked for it”).

Supervisor Support

Supervisor support was measured with four items (e.g., “my supervisor pays attention to my feelings and problems”; Peeters & Le Blanc, 2001; Peeters et al., 1995).

Leader-member Exchange

Leader-member exchange was measured with seven items (e.g., “my supervisor recognizes my potential”; Graen & Uhl-Bien, 1995).

Job Crafting

Job crafting was measured using four items from the seeking resources scale by Petrou et al. (2012). The items were adapted to reflect social resources sought specifically from a work supervisor, for example, by changing ‘colleagues’ to ‘supervisor’ (e.g., “I ask my supervisor for advice”).

Information Seeking

Information seeking was measured with three items (e.g., “I ask my supervisor how to perform specific aspects of my job”; Morrison, 1993).

Abusive Supervision

Abusive supervision was measured with five items (e.g., “my supervisor ridicules me”; Mitchell & Ambrose, 2007; Tepper, 2000).

Item Reduction

An exploratory factor analysis (EFA) using principal component analysis with direct oblimin rotation revealed that all 27 general USS items loaded strongly onto a single factor (Table 2). This is consistent with previous research showing that different types of supervisor support are highly related and produce similar effects (e.g., Barling et al., 1988; Mathieu et al., 2019). Given that we included different variations of wording for the same dimensions of USS and that the intercorrelations between the items were quite high, we proceeded to reduce the scale down to four items to avoid redundancy, make the scale more parsimonious, and minimize response bias for future studies (Hinkin, 1995). One item was retained to reflect each of the four dimensions, consistent with similar measures of supervisor support (e.g., Peeters & Le Blanc, 2001; Petrou et al., 2012). In addition to considering the item content, we selected the final four items based on having higher factor loadings to strengthen construct validity, higher contributions to reliability, generating sufficient variance in responses, and having lower intercorrelations (r < 0.85) to avoid redundancy (Hinkin, 1995). The final items were: “I do not receive feedback from my supervisor when I ask for it” (appraisal support); “I do not receive help from my supervisor when I ask for it” (instrumental support); “I do not get the necessary information from my supervisor when I ask for it” (informational support); and “when I approach my supervisor to discuss difficulties or problems at my work, I do not get the support I seek” (emotional support).

Table 2 Study 1 exploratory factor analysis loadings of the general unanswered supervisor support items

Results and Discussion

Descriptive Statistics and Reliabilities

We examined the descriptive statistics, correlations, and reliabilities using the retained 4 item USS measure, which are presented in Table 3. Both the general and daily USS measures demonstrated adequate reliability (α = 0.92 and 0.93, respectively). On average, general USS (M = 2.18, SD = 1.21) appeared to be experienced to a lesser extent than some of the other measures, such as supervisor support (M = 5.45, SD = 1.27) and leader-member exchange (M = 5.34, SD = 1.12). This is not surprising, given the relatively low occurrence rate of USS identified in prior experimental research using a recall method (McIlroy et al., 2021b). However, USS and abusive supervision (M = 1.57, SD = 0.90), which is also a negative set of supervisory behaviors, are reported as being experienced to a similar extent. This is consistent with diary research on affective events, which suggests that negative work events, such as negative interpersonal interactions, occur less frequently than positive work events, like positive interpersonal interactions (Ohly & Schmitt, 2015).

Table 3 Study 1 descriptive statistics, correlations, and reliabilities (on diagonal)

Scale Validation

We investigated the correlations (Table 3) and conducted a confirmatory factor analysis (CFA) to examine the convergent and discriminant validity of our USS measure. General USS was negatively correlated with supervisor support, leader-member exchange, job crafting, and information seeking, supporting Hypotheses 1a, 1b, 2a, and 2b, respectively. Further, general USS was positively correlated with abusive supervision, supporting Hypothesis 3. This demonstrates evidence of convergent validity, as our USS measure was related to theoretically similar constructs in the expected directions. While there were high correlations between USS and some of the variables, this is not surprising, as the other constructs were also highly correlated with one another. For example, the strongest correlation was between leader-member exchange and supervisor support, followed by leader-member exchange and job crafting.

We then conducted a CFA to examine the factor structure of our general measure of USS and theoretically related constructs. The factor loadings are presented in Table 4 and demonstrate that the USS items load strongly onto their respective factor. The model had acceptable fit, χ² = 843.44, df = 309, p < 0.001, CFI = 0.92, TLI = 0.91, RMSEA = 0.08, SRMR = 0.05. The second job crafting item (“I ask my supervisor for feedback on my job performance”) had a low factor loading and a high cross-loading with the information seeking factor. Removing this one job crafting item significantly improved the overall model fit, χ² = 595.39, df = 284, p < 0.001, CFI = 0.95, TLI = 0.95, RMSEA = 0.06, SRMR = 0.04; Δχ² = 248.08, df = 25, p < 0.001. The factor structure and model fit demonstrate evidence of discriminant validity, such that our USS measure is distinct from these related constructs. Overall, this study provides initial evidence of construct validity for our new USS measure. By conducting correlations and factor analyses, we demonstrated that USS was significantly related to, yet distinct from, theoretically similar constructs, including supervisor support, leader-member exchange, job crafting, information seeking, and abusive supervision.

Table 4 Study 1 confirmatory factor analysis loadings

Study 2: Daily Diary Study

In Study 2, we further validate our new USS measure and examine the daily experience and consequences of USS by conducting a diary study. To better understand the construct and consequences of USS, it is first important to understand the benefits of supervisor support. Overall, the supervisor support literature generally suggests that receiving supervisor support reduces stress and increases motivation, resulting in positive affective, social, and behavioral outcomes. Employees who receive supervisor support are less emotionally exhausted (De Lange et al., 2004; Gray et al., 2023; Lambert et al., 2010), perceive their supervisor more favorably (Gkorezis, 2015; Penning de Vries et al., 2020; Zhang et al., 2008), and engage in more helping behaviors (C.-C. Chen & Chiu, 2008; Mathieu et al., 2019; Shanock & Eisenberger, 2006). Likewise, employees lacking supervisor support experience detrimental outcomes, including poorer health and well-being (Hämmig, 2017; Rugulies et al., 2006; Sinokki et al., 2009, 2010). But what happens when an employee’s request for support goes unanswered?

When Requests for Support Go Unanswered

Given that low or no supervisor support is one aspect of the USS process, the supervisor support literature provides indirect evidence that USS may have negative implications for employees. Further, although research on USS is limited (McIlroy et al., 2021a), preliminary experimental research has shown that instances of USS negatively affect employees’ well-being, as well as their behavioral and relational outcomes (McIlroy et al., 2021b). Thus, consistent with the literature on both USS and supervisor support, USS will likely have detrimental effects for employees in their daily work lives. As discussed previously, in the context of USS, employees’ agency in seeking support may influence how they interpret and experience a lack of support, potentially exacerbating the consequences for employees’ own well-being, the way they perceive their supervisor, and their helping behavior in the workplace.

First, we expect that experiences of USS will reduce employees’ well-being, because they may feel hurt and excluded after not receiving a response from their supervisor. Employees may then ruminate on the negative situation and wonder when, if at all, they will receive a response, which is likely to be draining (Kemp et al., 2013). Second, the negative experience could affect employees’ perceptions of their supervisor, such that they view their supervisor in a less favorable light. For example, employees will likely perceive their supervisor as being an ineffective leader for not providing adequate support (Gyensare et al., 2019). Finally, because employees were not supported themselves, they may retaliate by being less helpful to others. As their supervisor failed to provide support, employees could be less motivated to reciprocate positive behavior in the workplace, and subsequently engage in fewer helping behaviors (Mathieu et al., 2019; Shanock & Eisenberger, 2006). Therefore, we examine the experience of USS in daily work life and its effects on three important outcomes: employees’ emotional exhaustion, perceptions of their leader’s effectiveness, and helping behavior. Consistent with the above explanations and the supervisor support and USS literature, we hypothesize:

• Hypothesis 4 (H4): On a day-level, USS will be (a) positively associated with emotional exhaustion, (b) negatively associated with perceived leadership effectiveness, and (c) negatively associated with helping behavior.

Basic Psychological Needs as Mechanisms of Unanswered Supervisor Support

In the context of USS, because employees exhibit agency by actively requesting support, we turned to motivational theories to understand how USS is related to these consequences. SDT is one potential framework that can help understand the outcomes of USS, through the process of lower satisfaction and greater frustration of basic psychological needs. SDT proposes that people have three fundamental psychological needs. The need for autonomy reflects peoples’ need to have choice and control over their own behavior. Competence reflects the need to feel efficacious and capable. Relatedness reflects the need to feel close and connected to others (Deci & Ryan, 2000). As previously mentioned, having access to job resources, like supervisor support, satisfies these needs and enhances human flourishing (Deci et al., 2017; Deci & Ryan, 2000; Van den Broeck et al., 2016). While receiving supervisor support satisfies psychological needs, not receiving support when requested may also elicit more threatening reactions by frustrating these needs. Need frustration is a stronger, more aversive experience than merely the absence of satisfaction (Vansteenkiste et al., 2020). Autonomy frustration involves feeling controlled or pressured. Competence frustration reflects feelings of failure and self-doubt. Relatedness frustration involves feelings of exclusion and loneliness (B. Chen et al., 2015). Both need satisfaction and need frustration have been shown to be important mechanisms in how a supervisor’s support affects employees (Deci et al., 2017). For example, supervisor support increases need satisfaction and reduces need frustration, resulting in more positive attitudes (Gillet et al., 2013), and greater motivation (Chih Ho, 2017), and well-being (Ebersold et al., 2019; Gillet et al., 2012; Van den Broeck et al., 2008).

Taken together, the SDT literature suggests that employees who request support but do not receive it will experience less satisfaction and greater frustration of their psychological needs, and subsequently experience negative outcomes. Thus, the experience of USS in daily work life may result in poorer well-being, perceptions of the supervisor, and helping behavior via two distinct psychological processes: lower need satisfaction and greater need frustration. We expect that employees who experience USS will have a less satisfied and more frustrated need for autonomy, because they feel as though they have no control over when, if at all, they will receive support. Further, because employees may lack the necessary social resources to perform certain aspects of their job, they will likely be unable to continue working in the way they would prefer, threatening their volition and causing them to feel controlled. In a similar vein, the lack of resources may result in employees being unable to complete work tasks, reducing the satisfaction of, and frustrating their need for, competence. Employees may also feel less valued by their supervisor because they were ignored, threatening their self-esteem and making them feel inadequate. Finally, having their request ignored is likely to negatively impact employees’ relationship with their supervisor, resulting in their need for relatedness being less satisfied and more frustrated. This may threaten the connection they have with their supervisor and lead them to feel hurt and rejected. Therefore, we expect that USS will impact the satisfaction and frustration of all three needs, consistent with research grounded in SDT (McIlroy et al., 2021b; Van den Broeck et al., 2016).

Lower need satisfaction and higher need frustration, in turn, should negatively affect employees’ well-being, social development, and motivation (Deci et al., 2017; Ryan & Deci, 2000a). The lower satisfaction and greater frustration of the basic needs will likely heighten stress arousal, increasing emotional exhaustion (Gillet et al., 2015; McIlroy et al., 2021b; Van den Broeck et al., 2008). Because the supervisor’s interpersonal treatment of the employee affects the employee’s needs, there may also be social consequences, such that the employee perceives their supervisor less favorably (McIlroy et al., 2021b). Finally, lower satisfaction and greater frustration of the needs may impede employees’ self-determined motivation to contribute to the workplace, resulting in less helping behaviors (McIlroy et al., 2021b; Sedlářík et al., 2023). Consistent with these explanations and the SDT literature, we propose the following hypotheses about a mediated relationship:

• Hypothesis 5 (H5): On a day-level, USS will be (a) negatively associated with need satisfaction, and (b) positively associated with need frustration.

• Hypothesis 6 (H6): On a day-level, need satisfaction will be (a) negatively associated with emotional exhaustion, (b) positively associated with perceived leadership effectiveness, and (c) positively associated with helping behavior.

• Hypothesis 7 (H7): On a day-level, need frustration will be (a) positively associated with emotional exhaustion, (b) negatively associated with perceived leadership effectiveness, and (c) negatively associated with helping behavior.

  Guided by our earlier theorizing and the component hypotheses presented (i.e., Hypotheses 5–7), a series of indirect effects were also expected:

• Hypothesis 8 (H8): Via the mechanism of lower need satisfaction, there will be (a) a positive indirect effect of USS on emotional exhaustion, (b) a negative indirect effect of USS on perceived leadership effectiveness, and (c) a negative indirect effect of USS on helping behavior.

• Hypothesis 9 (H9): Via the mechanism of higher need frustration, there will be (a) a positive indirect effect of USS on emotional exhaustion, (b) a negative indirect effect of USS on perceived leadership effectiveness, and (c) a negative indirect effect of USS on helping behavior.

Co-worker Support and Workload as Moderators of Unanswered Supervisor Support

Other characteristics in the work environment may influence the effects of USS. Consistent with previous SDT literature that has examined the role of job demands and resources in the need satisfaction and frustration process (e.g., Morin et al., 2023; Trépanier et al., 2015), we examine the potential moderating roles of co-worker support and workload in the present research. Both supervisors and co-workers can be important sources of social support in the workplace. In the case of USS, employees need assistance from their supervisor, but they do not receive the necessary support. However, if employees have access to other supportive relationships in their workplace, such as co-workers, they may be able to receive advice or guidance elsewhere, thus compensating for the unanswered request for supervisor support. Indeed, research examining the interactive effects of supervisor and co-worker support has shown that co-worker support can act as a substitute for supervisor support in predicting organizational citizenship behavior (Eby et al., 2015).

In a similar vein, USS could be considered a stressful event, and social support protects employees from stressful experiences, according to the stress-buffering hypothesis (Cohen & Wills, 1985). Research examining employees’ stressful interactions with their supervisor is consistent with this hypothesis. For example, Sloan (2012) found that employees who were treated unfairly by their supervisor, but who had greater support from their co-workers, had higher job satisfaction compared to those with less co-worker support. Similarly, co-worker support has been shown to buffer the effects of abusive supervision on perceived organizational support (Xu et al., 2018), career adaptability (Rasheed et al., 2021), and emotional exhaustion (Pradhan & Jena, 2018). Taken together, whether by acting as a substitute for the lack of supervisor support or acting as a buffer against the effects of a stressful experience, research suggests that employees may be able to use support from co-workers to mitigate the detrimental effects of USS.

Whereas co-worker support is a job resource that may minimize the consequences of USS, workload is a job demand that may exacerbate the consequences. In the context of USS, employees may lack the necessary social resources to cope with higher workloads. Therefore, having a higher workload may compound the effects of USS. This explanation is consistent with research on the JDR model. For example, Bakker et al. (2005) found that lower job resources (including relationship quality with the supervisor) and higher job demands (including workload) increased burnout. Further, when job resources were available, job demands had a weaker effect on burnout. Similarly, in a diary study, Goh et al. (2015) found that the negative relationship between daily workload and daily well-being was weaker for employees who had greater support from their supervisors compared to employees with less support. In relation to the present research, these findings suggest that, when employees actively seek support but fail to receive it, they may be less likely to cope with higher workloads due to a lack of social resources. Thus, on days of high workload, we expect that USS will have stronger negative effects. To sum up, other characteristics in the work environment, including co-worker support and workload, are likely to moderate the relationship between USS and need satisfaction and frustration, ultimately influencing the indirect effects of USS on emotional exhaustion, perceived leadership effectiveness, and helping behavior. This leads to our hypotheses about moderated mediation:

• Hypothesis 10 (H10): The indirect effects of USS on emotional exhaustion, perceived leadership effectiveness, and helping behavior via need satisfaction will be stronger for employees with (a) lower daily co-worker support and (b) higher daily workload.

• Hypothesis 11 (H11): The indirect effects of USS on emotional exhaustion, perceived leadership effectiveness, and helping behavior via need frustration will be stronger for employees with (a) lower daily co-worker support and (b) higher daily workload.

In summary, Study 2 aims to further validate our new measure of USS and examine the consequences of USS as it occurs in daily work life. The hypothesized model is presented in Fig. 1. We tested our hypothesized model by examining the daily experience of USS using a diary study. The hypotheses and procedures were pre-registered on the Open Science Framework prior to data analysis (McIlroy et al., 2021d), and the data and materials have been made publicly available (McIlroy et al., 2021c). Ethical clearance for the research was obtained from the University of Queensland’s human research ethics committee and informed consent was obtained from the participants.

Fig. 1

Study 2 hypothesized model of the unanswered supervisor support process

Method

Participants and Procedure

Participants were recruited via Prolific Academic. To be eligible, they needed to reside in the United Kingdom, have a work supervisor, and work full-time. For practical purposes, participants also needed to work regular hours of 9 to 5. This was so they could be sent the survey at a consistent time and complete it shortly after their workday ended to reduce recall bias. Further, to enhance data quality, participants were required to have a minimum of ten previous submissions on Prolific Academic, demonstrating their active and committed involvement. First, 230 participants completed a baseline survey to ensure they were eligible and available to participate in the daily diary study. Of these participants, eight were excluded due to failing at least one of two attention check items (“for quality control, please select ‘strongly disagree’ for this item”; Meade & Craig, 2012). A further ten were unavailable to participate in the daily diary study. The following week, from Monday to Friday, the 212 remaining participants who were eligible were invited to complete a daily survey at the end of each workday between 4 and 8 p.m. We opened and closed the survey at these respective times to prevent submissions outside this time window. Participants received £0.92 for completing the baseline survey and £0.40 for each daily survey they completed. To increase response rates, participants were informed that they would receive a bonus payment of £1.50 if they completed all five daily surveys. Of the 212 invited participants, 204 went on to complete at least one of the daily surveys. Because we were interested in examining within-person variation, participants were retained if they completed a minimum of two daily surveys. This left a final sample of 199.

Out of the retained participants, 73.4% completed all five surveys, and 91.5% of the daily surveys were completed. The mean number of daily surveys completed was 4.57 (SD = 0.80). The average age of respondents was 36.40 years (SD = 10.35), and 59.8% were female. On average, they worked 38.42 h per week (SD = 5.04) and had job tenure of 5.56 years (SD = 5.39). Most participants had at least a bachelor’s degree (71.4%) and 41.9% held a supervisory role. They worked in a variety of industries, including education and training (28.1%), healthcare and social assistance (10.6%), professional, scientific, and technical services (9.0%), financial and insurance services (8.0%), public administration and safety (5.5%), and administrative and support services (5.5%).

Measures

In the baseline survey, the same scales from Study 1 were used to measure general levels of USS, supervisor support, leader-member exchange, job crafting, information seeking, and abusive supervision. These measures were used to further validate our new measure of USS. We also included baseline measures of supervisor support, co-worker support, and workload to conduct exploratory cross-level sensitivity analyses.

In the daily survey, we used abbreviated scales to lessen the burden on participants, which is preferred in diary research (Ohly et al., 2010). The abbreviated items were selected based on their use in previous research, and the wording of the daily measures was adapted, such that participants were asked to think about their workday today (e.g., “today at work…”). For need satisfaction, need frustration, emotional exhaustion, perceived leadership effectiveness, and workload, participants indicated their level of agreement on a 7-point scale (1 = strongly disagree, to 7 = strongly agree). For USS, supervisor support, co-worker support, and helping behavior, participants indicated the extent to which the statements occurred for them that day on a 7-point scale (1 = not at all, to 7 = all the time). We made the decision to change the response scale from an agreement scale to a frequency scale for these measures, because qualitative feedback obtained from participants during Study 1 showed that some participants were unsure how to respond to the daily measure of USS when they did not interact with their supervisor that day. For example, in such instances, some people selected ‘strongly disagree’ to the USS items, whereas others selected ‘neither agree nor disagree’. Changing the response scale to a frequency scale for the daily measure gives participants a clearer way of responding, such that they can select ‘not at all’ if they did not interact with their supervisor that day. For consistency, we used this same frequency scale for the other behavioral measures at the day-level. This decision is supported by the stress literature, which shows that there is no difference between using an agreement scale and using a frequency scale, but recommends using frequency scales for behaviors, including helping behaviors (Spector & Nixon, 2019; Spector et al., 2010).

Unanswered Supervisor Support

Daily USS was measured with the same four items used in Study 1 and the baseline survey, however, as described previously, it was adapted to be suitable for daily measurement.

Need Satisfaction and Need Frustration

Similar to prior diary research on basic psychological needs, the need satisfaction and need frustration subscales of autonomy, competence, and relatedness were measured with two items each from existing measures (B. Chen et al., 2015; La Guardia et al., 2000; Sheldon et al., 2001; Van den Broeck et al., 2010; Wang et al., 2020). The autonomy satisfaction items were “I felt free to be myself” and “I felt able to do things my own way”. The competence satisfaction items were “I felt competent and capable” and “I felt a sense of accomplishment”. The relatedness satisfaction items were “I felt loved and cared about” and “I felt close and connected with people important to me”. The autonomy frustration items were “I felt like I had to do things a certain way” and “I felt like I had to follow other people’s commands”. The competence frustration items were “I felt incompetent” and “I felt insecure about my abilities”. The relatedness frustration items were “I felt that people who are important to me were cold and distant” and “I felt disconnected from other people”.

Emotional Exhaustion

Emotional exhaustion was measured with three items from the Maslach Burnout Inventory-General Survey (e.g., "I felt emotionally drained from my work"; Demerouti et al., 2015; Schaufeli et al., 1996).

Helping Behavior

Helping behavior was measured with three items from the organizational citizenship behavior checklist (e.g., "I helped colleagues when they had too much work to do"; Fox et al., 2012), similar to previous diary research (e.g., Schreurs et al., 2012; Xanthopoulou et al., 2008).

Perceived Leadership Effectiveness

Perceived leadership effectiveness was measured with three items from the leadership effectiveness scale (Vecchio & Anderson, 2009). The items were adapted to reflect employees’ perceptions of their supervisor’s leadership effectiveness (e.g., changed “overall, I provide very effective leadership” to “my supervisor provided very effective leadership”).

Co-worker Support

Co-worker support was measured with the same four items used to measure supervisor support in Study 1 and the baseline survey, except the word ‘supervisor’ was replaced with ‘co-workers’ (e.g., “my co-workers paid attention to my feelings and problems”; Peeters & Le Blanc, 2001; Peeters et al., 1995).

Workload

Workload was measured with three items (e.g., “I had too much work to do”; Bakker et al., 2004; Demerouti et al., 2015).

Supervisor Support

We included a daily measure of supervisor support for use as an exploratory control variable in sensitivity analyses. Supervisor support was measured with the same four items used in Study 1 and the baseline survey, however, similar to daily USS, it was adapted to be suitable for daily measurement.

Results and Discussion

Scale Validation

Descriptive statistics, correlations, and reliabilities of the measures are presented in Table 5. These results followed a similar pattern to Study 1, such that the baseline measure of USS had high reliability (α = 0.93) and was negatively correlated with supervisor support, leader-member exchange, job crafting, and information seeking, and positively correlated with abusive supervision. This demonstrates further evidence of convergent validity, as our USS measure was related to theoretically similar constructs in the expected directions. As with Study 1, we then conducted a CFA that included all the baseline measures. The factor loadings are presented in Table 6 and demonstrate that the USS items loaded strongly onto their respective factor. With all items included in the model, not all fit indices achieved adequate fit, χ² = 852.53, df = 309, p < 0.001, CFI = 0.90, TLI = 0.88, RMSEA = 0.09, SRMR = 0.07. After removing the same job crafting item as Study 1 (item 2), the model fit significantly improved, χ² = 626.83, df = 284, p < 0.001, CFI = 0.93, TLI = 0.92, RMSEA = 0.08, SRMR = 0.05; Δχ² = 225.70, df = 25, p < 0.001. The factor structure and model fit were similar to Study 1, thus giving us greater confidence in the construct validity of the new USS measure.

Table 5 Study 2 descriptive statistics, correlations, and reliabilities (on diagonal) of baseline measures

Table 6 Study 2 confirmatory factor analysis loadings of baseline measures

Measurement Models and Analytical Approach

To test our hypotheses regarding the daily effects of USS, we planned to test three models: a direct effects only model (Model 1); an indirect effects model (Model 2); and a moderated mediation model (Model 3). Thus, we first conducted a series of multilevel CFAs on the daily survey measures to test the suitability of the measurement structure for each of these models. In all three multilevel CFA models, no error covariances or other alternative model specifications were included. Model 1 (i.e., USS, emotional exhaustion, perceived leadership effectiveness, and helping behavior) resulted in good fit according to Hu and Bentler's (1999) cutoff criteria, χ² = 220.54, df = 118, CFI = 0.976, TLI = 0.968, RMSEA = 0.031, SRMR_within = 0.031. All factor loadings were above 0.60 and all factor correlations were below 0.70. For Model 2, we included the basic psychological needs (i.e., satisfaction and frustration). Regarding the specification of basic psychological needs, consistent with typical approaches in SDT research (e.g., Bartholomew et al., 2011; Zamarripa et al., 2020), we first conducted a higher-order CFA, where six first-order factors (autonomy satisfaction, competence satisfaction, relatedness satisfaction, autonomy frustration, competence frustration, and relatedness frustration) served as indicators of two higher-order factors (need satisfaction and need frustration). The hypothesized model had acceptable fit for most of the criteria, but not all, χ² = 1249.62, df = 508, p < 0.001, CFI = 0.909, TLI = 0.893, RMSEA = 0.040, SRMR_within = 0.042. Factor loadings were acceptable and no factor correlations were above 0.70. A CFA specifying six separate need factors had good fit, χ² = 845.57, df = 460, p < 0.001, CFI = 0.953, TLI = 0.938, RMSEA = 0.030, SRMR_within = 0.032, with acceptable factor loadings and no factor correlations above 0.70. We initially report the results where the needs are conceived as two higher-order factors, according to our pre-registered hypotheses and typical approaches to the treatment of basic psychological needs in SDT research. However, for completeness, we also report supplementary sensitivity analyses at the end of the results section where the needs are conceived as six separate first-order factors. We discuss the implications of these findings for the measurement of daily need satisfaction and frustration further in the discussion section. For Model 3, a CFA including the proposed moderators of co-worker support and workload was conducted. These factors were added to the model with higher-order needs: χ² = 1996.94, df = 860, p < 0.001, CFI = 0.904, TLI = 0.890, RMSEA = 0.038, SRMR_within = 0.043. Once again, factor loadings were acceptable and no factor correlations were above 0.70.

We next conducted a variance components analysis to inspect the intraclass correlation coefficients (ICC) of the daily survey measures. The descriptive statistics, ICCs, reliabilities, and correlations of the daily measures are shown in Table 7. To account for the nested structure of the data (i.e., daily diaries nested within individuals), we modelled the hypothesized direct (Model 1) and indirect (Model 2) effects at both the within-level and between-level using a 1–1-1 design in Mplus 8 (Muthén & Muthén, 1998–2017; Preacher et al., 2010). We tested the multilevel moderated mediation model using interaction terms at the within-level to examine if daily co-worker support and daily workload moderated the relationship between USS and need satisfaction and frustration, ultimately influencing the indirect effects of USS on the outcomes (Model 3).

Table 7 Study 2 descriptive statistics, ICC, reliabilities, and correlations of daily measures

Hypothesis Testing

Direct Effects and Mediation

To test Hypotheses 4–7, we conducted a series of multilevel path models. In Model 1, USS, emotional exhaustion, perceived leadership effectiveness, and helping behavior were entered to examine the direct effects of USS on the outcomes. In Model 2, need satisfaction and need frustration were added to test the hypothesized mediation. The direct and indirect effects at the within-level are presented in Table 8. We only interpret the indirect effects when both component paths are significant (i.e., USS predicts need satisfaction/frustration, and need satisfaction/frustration predicts the outcome; Yzerbyt et al., 2018).

Table 8 Study 2 direct and indirect effects from the multilevel models at the within-level

In Model 1, as expected, daily USS (M = 1.48, SD = 1.02) was positively related to emotional exhaustion (M = 3.61, SD = 1.73; b = 0.13, SE = 0.04, 90% CI [0.04, 0.21], p = 0.004) and negatively related to perceived leadership effectiveness (M = 4.38, SD = 1.60; b = -0.13, SE = 0.05, 90% CI [-0.23, -0.02], p = 0.017), meaning that employees who experienced USS that day were more strained and viewed their supervisor as a less effective leader. USS was not related to helping behavior (M = 2.68, SD = 1.43; b = 0.07, SE = 0.04, 90% CI [-0.01, 0.16], p = 0.079). Thus, Hypotheses 4a and 4b were supported, while Hypothesis 4c was not. In Model 2, after adding need satisfaction and need frustration, USS was negatively related to need satisfaction (M = 4.88, SD = 0.99; b = -0.14, SE = 0.06, 90% CI [-0.26, -0.01], p = 0.033) and positively related to need frustration (M = 2.93, SD = 1.05; b = 0.21, SE = 0.05, 90% CI [0.11, 0.32], p < 0.001), which is consistent with Hypotheses 5a and 5b. Need satisfaction was negatively related to emotional exhaustion (b = -0.15, SE = 0.06, 90% CI [-0.27, -0.02], p = 0.023) and positively related to perceived leadership effectiveness (b = 0.28, SE = 0.06, 90% CI [0.17, 0.39], p < 0.001) and helping behavior (b = 0.19, SE = 0.05, 90% CI [0.09, 0.28], p < 0.001), consistent with Hypotheses 6a, 6b, and 6c. Need frustration was positively related to emotional exhaustion (b = 0.22, SE = 0.05, 90% CI [0.11, 0.32], p < 0.001), but was not related to perceived leadership effectiveness (b = -0.00, SE = 0.05, 90% CI [-0.10, 0.10], p = 0.961) or helping behavior (b = -0.01, SE = 0.05, 90% CI [-0.11, 0.10], p = 0.920). Thus, Hypothesis 7a was supported, while Hypotheses 7b and 7c were not. There were no indirect effects of USS on emotional exhaustion (b = 0.02, SE = 0.01, 90% CI [-0.00, 0.04], p = 0.173), perceived leadership effectiveness (b = -0.04, SE = 0.02, 90% CI [-0.07, -0.00], p = 0.063), or helping behavior (b = -0.03, SE = 0.01, 90% CI [-0.05, -0.00], p = 0.064) via lower need satisfaction. Thus, Hypotheses 8a, 8b and 8c were not supported. The indirect effect of USS on emotional exhaustion via higher need frustration was significant (b = 0.05, SE = 0.02, 90% CI [0.02, 0.07], p = 0.005), supporting Hypothesis 9a. There were no indirect effects via higher need frustration on perceived leadership effectiveness (b = -0.00, SE = 0.01, 90% CI [-0.02, 0.02], p = 0.961) or helping behavior (b = -0.00, SE = 0.01, 90% CI [-0.02, 0.02], p = 0.920). Thus, Hypotheses 9b and 9c were not supported. It is worth noting that, after adding need satisfaction and need frustration in Model 2, the direct effect of USS on emotional exhaustion became non-significant, and a positive direct effect on helping behavior became significant.

Moderated Mediation

Co-worker support (M = 3.29, SD = 1.40) did not moderate the relationship between USS and need satisfaction, b = 0.28, SE = 0.19, 95% CI [-0.10, 0.65], p = 0.153, or need frustration, b = 0.05, SE = 0.18, 95% CI [-0.30, 0.40], p = 0.767. Similarly, workload (M = 3.80, SD = 1.65) did not moderate the relationship between USS and need satisfaction, b = -0.18, SE = 0.36, 95% CI [-0.88, 0.52], p = 0.617, or need frustration, b = -0.50, SE = 0.35, 95% CI [-1.18, 0.18], p = 0.148. Thus, Hypotheses 10a, 10b, 11a, and 11b were not supported.

Sensitivity Analyses

Controlling for Daily Supervisor Support

We considered that low supervisor support might co-occur with the experience of USS, so in sensitivity analyses, we accounted for daily supervisor support to examine the unique effects of USS. As recommended by Becker (2005), given we did not specify control variables in the hypotheses, we re-analyzed the data, controlling for supervisor support. Consistent with the main analyses, we ran a series of multilevel CFAs for each model that included supervisor support, including a version of Model 2 that specified two higher-order need factors. The addition of the supervisor support items and factor did not change the model fit statistics already reported (Model 1: χ² = 544.02, df = 218, p < 0.001, CFI = 0.958, TLI = 0.947, RMSEA = 0.041, SRMR_within = 0.01; Model 2: χ² = 1760.41, df = 700, p < 0.001, CFI = 0.910, TLI = 0.895, RMSEA = 0.041, SRMR_within = 0.045). All four supervisor support items loaded significantly and above 0.80 on their factor. Importantly, the within-person correlation between USS and supervisor support was not significant (r = 0.02, p = 0.78). All other factor correlations remained below 0.70.

We then ran two multilevel path models, where USS, supervisor support, emotional exhaustion, perceived leadership effectiveness, and helping behavior were entered in Model 1, and need satisfaction and need frustration were added in Model 2. The direct and indirect effects at the within-level controlling for supervisor support are presented in Table 9. The effects of USS remained the same after adding supervisor support to the analyses, including the indirect effect on emotional exhaustion via need frustration. This indirect effect was not found for supervisor support, but rather, supervisor support had positive indirect effects on perceived leadership effectiveness and helping behavior via need satisfaction. Considered together, these results show that USS explains unique variance in the outcomes beyond daily levels of supervisor support, and that the effects of USS and supervisor support in daily work life are driven by alternate pathways.

Table 9 Study 2 direct and indirect effects from the multilevel models at the within-level, controlling for daily supervisor support

Cross-level Moderation

As exploratory analyses, we tested if the baseline survey measures, that captured general levels of supervisor support, co-worker support, and workload, moderated the daily within-person effects of USS on the outcomes (i.e., daily emotional exhaustion, perceived leadership effectiveness, helping behavior) and the mediators (i.e., daily need satisfaction and frustration). To do this, we specified a random slopes model, allowing the within-level associations to vary, and then attempted to predict this variation in the slopes with the between-person variables (i.e., as measured at baseline). As this analysis involved cross-level moderation, the between-person variables (i.e., workload, co-worker support, and supervisor support) were centered at the grand (or sample) mean, and the within-person predictor (USS) was centered at each participant’s mean (Aguinis et al., 2013; Ohly et al., 2010). We probed significant interaction effects using the methods set out by Preacher et al. (2006).

The cross-level moderation results are summarized in Table 10. Out of 15 possible cross-level moderations, only one was significant, whereby the daily effect of USS onto perceived leadership effectiveness depended on baseline (i.e., general levels of) supervisor support (see Fig. 2). Simple slopes analyses revealed a significant negative effect of daily USS on perceived leadership effectiveness at high levels of baseline supervisor support, B = -0.18(SE = 0.05), p < 0.001, while there was no effect at low levels of baseline supervisor support, B = 0.04 (SE = 0.012), p = 0.752. As there was no moderation of the effects of USS onto need satisfaction and need frustration, this means there was no possibility to examine cross-level moderated mediation. To sum up, these additional analyses show that our within-person effects previously reported are fairly robust to participants’ pre-existing levels of general supervisor support, co-worker support, and workload, albeit, the negative effect of daily USS on perceived leadership effectiveness is stronger for employees who reported having a generally supportive supervisor at baseline.

Table 10 Study 2 cross-level moderation of the effects of daily unanswered supervisor support on daily outcomes and mediators, moderated by baseline levels of workload, co-worker support, and supervisor support

Fig. 2

Study 2 cross-level moderation. Note. N = 199 individuals and 909 observations

Independent Effects of Need Satisfaction and Frustration Subscales

As an exploratory analysis, we also examined the direct and indirect effects for each need satisfaction and need frustration subscale separately in the multilevel mediation analyses to examine their unique effects. As previously reported in the method, a CFA model specifying six separate need factors had acceptable fit. The descriptive statistics and correlations are presented in Table 11, and the mediation results are presented in Table 12. Again, we only interpret the indirect effects when both component paths are significant.

Table 11 Study 2 descriptive statistics and correlations of daily measures with separate need satisfaction and frustration subscales

Table 12 Study 2 direct and indirect effects for each need subscale at the within-level

Need Satisfaction

The pathways from USS to each need satisfaction subscale were not significant. As such, it was evident that neither autonomy, competence, nor relatedness satisfaction mediated the effects of USS on the outcomes. This is consistent with the mediation results previously reported, where need satisfaction was conceived as a higher-order factor.

Need Frustration

USS positively predicted all three need frustration subscales. All three need frustration subscales, in turn, positively predicted emotional exhaustion. The indirect effects of USS on emotional exhaustion via competence frustration and relatedness frustration were significant, whereas the indirect effect via autonomy frustration was not significant. These findings suggest that the mediating effect of need frustration onto emotional exhaustion previously reported, where need frustration was conceived as a higher-order factor, was driven by the frustration of the specific needs for competence and relatedness.

Neither autonomy frustration nor competence frustration predicted perceived leadership effectiveness, indicating that there were no indirect effects of USS via these needs. However, there were significant negative direct and indirect effects for relatedness frustration onto perceived leadership effectiveness. The significant indirect effect suggests that, when examining the unique effects of relatedness frustration alone (rather than examining the higher-order need frustration factor), employees who experienced USS perceived their supervisor to be a less effective leader via the frustration of their need for relatedness.

Neither autonomy frustration nor competence frustration predicted helping behavior, indicating that these needs did not mediate the effects of USS. Similarly, while there was a significant negative direct effect of relatedness frustration on helping behavior, the indirect effect was not significant. These findings are consistent with the mediation results reported previously, where need frustration was conceived as a higher-order factor.

Lagged Effects

Finally, we created lagged variables to control for the effects of USS and the outcomes from the previous day. The results from the hypothesis testing were not affected when controlling for these lagged variables, suggesting that day-to-day changes in the variables did not influence the observed within-day effects already reported. Further, we ran a series of lagged analyses to examine the relationships between variables from the previous day and variables on the following day. This allowed us to test whether USS from the previous day had a delayed effect on the mediators and outcomes the next day. A summary of the results is presented in Table 13. USS from the previous day negatively predicted USS the next day, and perceived leadership effectiveness from the previous day negatively predicted perceived leadership effectiveness the next day. There were no other significant lagged effects. Because previous day USS did not predict the mediators or outcomes the following day, the findings suggest that the effects of USS are quite a momentary, within-day phenomenon.

Table 13 Study 2 lagged effects at the within-level

General Discussion

The aim of the present research was to develop and validate a new measure of USS and to examine the consequences of daily experiences of USS. Across two studies, we presented evidence of construct validity, demonstrating that USS is related to, yet distinct from, supervisor support, leader-member exchange, job crafting, information seeking, and abusive supervision. Further, in Study 2, we used a diary study methodology to assess the effects of USS on employees’ emotional exhaustion, the perceived effectiveness of their leader, and helping behavior, and the mediating roles of need satisfaction and need frustration. We also examined contextual factors, including workload and co-worker support, as potential moderators of these indirect effects. The results showed that, on days when employees experienced USS, their psychological needs were less satisfied and more frustrated, they were more emotionally exhausted, and they had more negative perceptions about their supervisor’s leadership effectiveness. Need frustration, and in particular, frustration of the needs for competence and relatedness, explained the effect of USS on emotional exhaustion. Further, frustration of the need for relatedness explained the effect of USS on employees’ perceptions of their leader’s effectiveness. These effects remained after controlling for daily levels of supervisor support, indicating that USS has unique consequences beyond low supervisor support. The fact that USS uniquely predicted the outcomes above and beyond daily supervisor support also demonstrates the criterion validity of our new USS measure.

Theoretical Implications

Our research makes several important contributions to the literature. First, we developed and validated a new measure of USS. This construct has been neglected in the supervisor support, proactive employee behavior, and abusive supervision literatures, despite research demonstrating the importance of considering employees’ agency in acquiring support in addition to the subsequent receipt of support (McIlroy et al., 2021a, b). This measure may help researchers examine USS to better understand its antecedents and consequences. The measure may also allow researchers and practitioners to identify ways to minimize the occurrence of USS and its associated consequences in the workplace.

Second, we provide further insight into the experience and effects of USS, in particular, as it occurs in everyday work life. While experimental research has demonstrated the consequences of USS for employees’ well-being, behavioral, and relational outcomes with between-person methodologies and simulated work (McIlroy et al., 2021b), the present research is the first to examine the within-person process of USS as it occurs in daily work life. Consistent with previous findings, in Study 2, we showed that, on days when employees experienced USS, they were more exhausted and had poorer perceptions of their supervisor’s leadership effectiveness, independent of their daily supervisor support. These findings demonstrate the value of examining USS as it fluctuates on a day-to-day basis, because these fluctuations have implications for employees’ well-being and the way they perceive their supervisor. Unexpectedly, we found that USS tended to result in greater helping behavior, although this finding should be interpreted with caution, as the effect was not robust across the analyses. Therefore, further research is needed to unpack the direct effects of USS on helping behavior. For example, employees may engage in helping to make a good impression with their supervisor to avoid their requests for support going unanswered in the future.

The present research also contributes to the SDT literature by answering the call to examine the effects of need frustration in combination with need satisfaction, particularly in diary research (Coxen et al., 2021; Van den Broeck et al., 2016). Although prior experimental research found that lower need satisfaction mediated the detrimental effects of USS (McIlroy et al., 2021b), prior research has not examined the relative effects of need frustration. In Study 2, we showed that, while USS was associated with both lower need satisfaction and higher need frustration on a daily basis, there was an indirect effect on emotional exhaustion via need frustration only. Sensitivity analyses showed that the frustration of the needs for competence and relatedness drove this indirect effect on emotional exhaustion. Further, on days when employees experienced USS, they indirectly perceived their supervisor to be a less effective leader via the frustration of their need for relatedness. Together, these results suggest that frustration of the needs for competence and relatedness, in particular, may be most important in explaining the effects of USS in employees’ daily work life. The results also suggest that it is the frustration of these needs, and not a lack of satisfaction, that drives the effects of USS. A potential explanation for this discrepancy is that USS is a negative experience, so, rather than merely having lower need satisfaction, employees may have had an aversive reaction, such that they doubted their own abilities and felt excluded, resulting in ill-being. Further, need satisfaction may not have mediated the effect of USS on emotional exhaustion because need satisfaction has been shown to be related to well-being, rather than ill-being (Chen et al., 2015). Thus, future research should continue to examine the indirect effects of USS via both need satisfaction and need frustration to further understand these processes. Moreover, it would be worthwhile to include outcome measures of well-being, such as job satisfaction or work engagement, in addition to measures of ill-being, like emotional exhaustion.

More generally, the present research also contributes to the literature examining supervisor support. In sensitivity analyses, the effects of USS remained the same after controlling for daily supervisor support, indicating that USS has unique effects, beyond being merely indicative of low levels of supervisor support. Further, USS predicted emotional exhaustion via need frustration, whereas supervisor support predicted both perceived leadership effectiveness and helping behavior via need satisfaction. These findings suggest that USS and supervisor support result in alternate pathways, with USS leading to detrimental outcomes via need frustration (the ‘dark’ pathway), and supervisor support leading to beneficial outcomes via need satisfaction (the ‘bright’ pathway; Coxen et al., 2023).

Interestingly, the results showed that neither co-worker support nor workload moderated the indirect effects of USS. This was observed with both daily measures of these potential moderators as well as with baseline measures (i.e., general levels) collected before the study observation period. The finding that co-worker support has no influence on the effects of USS is inconsistent with research showing that co-worker support can act as a substitute for supervisor support (Eby et al., 2015), as well as research showing that co-worker support can buffer against the negative effects of stressful supervisor interactions (Pradhan & Jena, 2018; Rasheed et al., 2021; Sloan, 2012; Xu et al., 2018). This suggests that being supported by co-workers is not enough to mitigate the consequences of USS, which is similar to previous research showing that supervisor support is more beneficial for employee well-being compared to co-worker support (Dormann & Zapf, 1999; Hämmig, 2017). A potential explanation for this finding is that co-workers may be unable to provide the necessary support because they lack the relevant information or resources to help the employee. Likewise, it is possible that in contexts where an employee seeks support from their supervisor, the supervisor is the only person able to provide the specific support that is requested. To further unpack this finding, a future line of research could examine the relative importance of the type of support requested. For example, if an employee does not receive emotional support from a supervisor after requesting it, co-workers may be able to offer a sympathetic ear to the employee, thus buffering the effects of USS. However, if the desired support is instrumental in nature, co-workers may be limited in their ability to help, in which case co-worker support is less likely to influence the effects of USS. Similarly, workload did not moderate the effects of USS, which is inconsistent with research on the JDR model (e.g., Bakker et al., 2005; Goh et al., 2015). This finding suggests that USS has negative consequences for employees, regardless of their daily workload levels. Thus, even when employees have a manageable workload, they are still likely to be stressed and less motivated when their request for support goes unanswered.

Overall, the moderators did not play out as hypothesized. When combined with previous research that also failed to find a moderating effect of attributions (McIlroy et al., 2021b), it suggests that the effects of USS are fairly robust and not easily influenced by viable moderators. Thus, future research could be conducted to identify other potential moderators, such as the employee’s coping mechanisms, or whether they receive support from friends and family, to help inform strategies to prevent the consequences of USS. Another avenue for future research is to examine the supervisor’s role in the USS process. For example, exploratory analyses suggested that, on days when employees experienced USS, they tended to view their supervisor as a less effective leader that day if they had a general perception that their supervisor was supportive overall. A potential explanation for this finding is that, when the supervisor’s daily behavior contradicts their usual behavior, the employee may view this daily behavior more negatively because it is not normative. Thus, future research should continue to explore the dynamics of the employee-supervisor relationship and how this influences employees’ daily experiences of USS. Similarly, the way the supervisor responds may be an important consideration. For example, the consequences of USS may be minimized if the supervisor explains to the employee that they will be able to help at a future time, compared to a supervisor who fails to reply at all. Thus, future research could develop a more nuanced measure of USS to assess the different types or dimensions of USS, including denied requests, no response, inadequate support, or empty promises described by McIlroy et al. (2021b), to examine whether the supervisor’s response moderates the effects.

Finally, examining the day-to-day experiences of USS allowed us to control for the effects of USS and the outcomes from the previous day. The findings remained the same after controlling for these variables, suggesting that daily changes in the variables did not affect the observed within-day effects. Further, the effects of USS did not carry over onto the next workday, suggesting that USS is more of a momentary, within-day phenomenon. Interestingly, we also found that employees who experienced USS on the previous day were less likely to experience USS the next day. A potential explanation for this finding is that employees who asked for support on the previous day may have only received a response from their supervisor the following day. Thus, on the previous day, their request went unanswered, but on the following day, it may have then been answered.

Limitations and Future Directions

While the present research makes several important contributions, there are some limitations that should be noted. First, all measures were completed once per day at the same time, so causation cannot be inferred. Future research should seek to better understand the temporal order of the relationships between variables by having participants complete multiple measures within the workday. For instance, research could use event-contingent sampling to examine USS as it unfolds in the moment (Reis & Gable, 2000). This method would also allow researchers to examine the cumulative effects of experiencing repeated instances of USS throughout the workday, and to identify alternative mechanisms and outcomes. For example, event-based theories, such as affective events theory (Weiss & Cropanzano, 1996), could be used as a guiding framework to study the relationship between USS and employees’ more discrete affective reactions (e.g., Chan et al., 2023; Dimotakis et al., 2011). However, such research would need to consider time constraints placed on employees (e.g., limited ability to complete frequent surveys), and also select an appropriate timeframe over which USS and its consequences occur (i.e., identifying at what point a request for support is considered to be unanswered, and how much time is needed for this to affect the outcomes). Further, to better understand the causal effects of USS on the outcomes via need frustration, future research could conduct work simulations and manipulate USS (see McIlroy et al., 2021b).

Second, this research relied on self-reported data, which may have been susceptible to socially desirable responding and common method bias (Donaldson & Grant-Vallone, 2002; Podsakoff et al., 2012). We did adopt several strategies to try and minimize common method bias, including using an experience sampling design, randomizing items within blocks, using a mix of positively and negatively worded items, and using different scale points for some measures (i.e., ‘strongly agree’ to ‘strongly disagree’ and ‘not at all’ to ‘all the time’; Beal, 2015; Jordan & Troth, 2020). Nevertheless, future research could include other sources of data, such as objective measures of well-being, ill-being, and helping behavior, or observer-rated measures.

Third, some of the CFI and TLI indices in the CFA measurement models in Study 2 did not quite reach Hu and Bentler's (1999) cutoff criteria for good fit. This was due to the need satisfaction and need frustration items used. Like many other researchers (e.g., Aldrup et al., 2017; Wang et al., 2020), we made the decision to use a smaller number of items to lessen the burden on participants, which is considered acceptable in diary research with employees (Ohly et al., 2010). Importantly, both the need satisfaction and need frustration scales had acceptable reliability, and there were no serious factor loading or factor correlation issues. Nevertheless, future diary research could use a validated shortened measure of need satisfaction and need frustration that has been published since the data collection for this project (e.g., Coxen et al., 2023).

A final limitation is that we focused only on unanswered support from supervisors, and did not examine unanswered support from other sources, such as co-workers. This is an important consideration given that some organizations are tending to move away from hierarchical structures (e.g., Lee & Edmondson, 2017), so employees may ask their co-workers for support instead of their supervisors. Although we looked at whether having access to co-worker support can buffer the effects of USS, future research would benefit from examining unanswered support from co-workers alongside USS. This would allow researchers to determine whether the source can influence the effects of unanswered support. For example, the consequences may not be as detrimental when an employee seeks support from a co-worker as opposed to a supervisor. Therefore, research could examine the relative effects or the possible additive effects of unanswered support from different sources.

More generally, future research could investigate the magnitude of the employee’s request. For example, a larger request may require more time for the supervisor to respond, so the employee may be more forgiving of a delayed response compared to a smaller request that could be addressed more quickly. Indeed, future research could employ dyadic designs to understand both the employee and the supervisor perspective on the USS process. Additionally, future research could examine other factors that might influence the experience of USS, such as work experience, age, and level of task interdependence. It is possible that older, more experienced workers may require less support than younger, less experienced workers. Likewise, people with lower task interdependence may require less support from their supervisor, compared to people whose work is more dependent on the work of others. Finally, future research could examine unanswered employee support from the supervisor’s perspective – that is, supervisors may also seek support from their employees but not receive it. Research could identify discrepancies or commonalities between USS and unanswered employee support, including how these two groups perceive and interpret unanswered support, and whether there is an interaction or compensatory mechanism operating between supervisor support and employee support.

Practical Implications and Conclusion

Our findings demonstrate that there is within-person, day-to-day variation in the experience of USS, which has implications for employees’ well-being and the perceptions they have of their supervisor. As such, supervisors and organizations need to be aware of such instances and how to prevent them in a timely manner, given the immediate consequences that can occur. For example, the findings could be applied to leadership development programs to highlight to supervisors the importance of providing timely support to employees, particularly when requested. However, there may be situations where it is not feasible for supervisors to respond to such requests in a timely manner, for example, if the supervisor themselves has a particularly high workload. In such instances, it is important to identify ways in which employees can still receive the support they need. Our findings suggest that support from co-workers may not be enough to substitute the lack of support from the supervisor, so, rather than simply referring employees to another colleague for support, it is important to ensure employees have other avenues they can turn to. For example, employees could be provided with appropriate information, guides, or resources that they are able to access themselves. Organizational interventions could also be implemented to reduce the likelihood of USS, such as redesigning the work of supervisors to reduce their workload, or reducing their number of direct reports, so they are able to provide adequate and timely supervision.

In summary, this research developed and validated a new measure of USS and examined the consequences of daily fluctuations in USS. The findings demonstrate that daily experiences of USS frustrate employees’ psychological needs, leading them to be more emotionally exhausted and to perceive their supervisor as a less effective leader. These findings contribute to the current understanding of USS by examining fluctuations at the within-person level, and demonstrate that need frustration is important in driving the consequences of USS as it occurs in daily work life. The findings can also be applied to the workplace by informing policies and procedures to prevent instances of USS.