Certified Child Life Specialists (CCLS) are healthcare professionals who help children, siblings, and families cope with the psychosocial effects of hospitalization and illness (Romito et al., 2021). They provide support for patients and families by planning and implementing interventions to help children and families better understand and manage the stresses of hospitalization. In general, healthcare workers have been found to be at increased risk for experiencing stress and trauma (Krisberg, 2018). Workplace stressors put healthcare professionals, including CCLS, at a greater risk for burnout (Holloway & Wallinga, 1990; Jacobs et al., 2012; Olson et al., 2015; Ptacek et al., 2013; Rodrigues et al., 2018). Burnout is a psychological condition resulting from extreme stress, often in the workplace, and professionals who are burned out feel apathy and indifference towards their work overall (Maslach & Jackson, 1982). CCLS may experience burnout due to a variety of factors related to their roles as both healthcare workers and psychosocial support professionals, including the hierarchical culture of the hospital, a required emotional investment in patients and families, and exposure to trauma and death (Fisackerly et al., 2015; Hoelscher & Ravert, 2021; Holloway & Wallinga, 1990; Shuck et al., 2013).

Studies have found medical professionals to be at risk for experiencing Impostor Phenomenon (IP), often referred to as “imposter syndrome” (Gottlieb et al., 2019; LaDonna et al., 2018; Leach et al., 2018; Legassie et al., 2008; Thomas & Bigatti, 2020). IP occurs in high-achieving individuals who, despite their accomplishments, feel like a fraud in their workplace environment (Clance & Imes, 1978). IP has been found to be a predictor of burnout in healthcare workers (Leach et al., 2019; Legassie et al., 2008; Ptacek et al., 2013; Villwock et al., 2016). Not only are IP and burnout experiences distressing when experienced individually, but the combination of these factors can be especially damaging to medical professionals’ overall well-being. Understanding how to combat IP and burnout can benefit the quality of life of CCLS.

Literature Review

Impostor Phenomenon

Clance and Imes (1978) originally coined the term “Impostor Phenomenon” (IP) after studying high-achieving professional women. IP is thought to occur when highly successful individuals cannot accept or internalize their accomplishments, live with consistent self-doubt and a fear of being exposed as a fraud, and believe their achievements are the result of luck or external factors (Clance, 1985, 1986). Individuals with IP are often thought of as externally successful but have an illusion of internal incompetence (Chrisman et al., 1995). IP experiences can be conceptualized as the most extreme end on a spectrum of personal doubt (LaDonna et al., 2018).

Clance’s original work focused on the female experience of IP, but this phenomenon has also been found to occur in different genders, races, and ethnic groups (Bravata et al., 2019; Levant et al., 2020). Clance and Imes (1978) found females to be at increased risk for IP as a result of the societal expectations of men to be successful in the workplace rather than women. These findings on the impact of gender and race on IP have implications for child life. The demographic makeup of the profession is vastly homogenous (ACLP, 2018). In a review of the demographics of child life, 91% of CCLS identified as White. In a setting where the vast majority of one’s coworkers are not of the same race or ethnicity, minoritized CCLS could be at increased risk of feeling ostracized and therefore could be at higher risk of experiencing IP. In the same review, 99% of CCLS reported identifying as female, another predictor of IP (ACLP, 2018). Therefore, high levels of IP could occur in the child life field, especially among minoritized CCLS, due to the demographics of the profession.


Burnout is a psychological phenomenon resulting from extensive and long-term work-related stress (Maslach, 1993; Maslach & Jackson, 1981, 1982). It has been historically conceptualized as a multifaceted experience comprised of three dimensions: emotional exhaustion, depersonalization, and personal accomplishment (Maslach, 1993; Maslach & Jackson, 1982). Those experiencing burnout are thought to have high levels of emotional exhaustion and depersonalization, but low levels of personal accomplishment. Emotional exhaustion is defined as feeling emotionally drained by one’s work. Depersonalization occurs when one feels cynical about their work and disconnected from those they work with or care for. Personal accomplishment relates to feelings of success and competence at work. Of note, burnout, like IP, is not a psychiatric diagnosis found in the DSM-V and is therefore not considered a syndrome on its own (Bravata et al., 2019; Nadon et al., 2022). However, burnout often co-occurs with other clinically significant mental health concerns such as depression, anxiety, and substance use disorders (Maslach et al., 2001).

A wide variety of research shows burnout exists in helping professions, especially in healthcare (Jacobs et al., 2012; Olson et al., 2015; Ptacek et al., 2013; Rodrigues et al., 2018). Healthcare workers are thought to be at risk for burnout due to their increased interactions with the public requiring socioemotional investment (Hoelscher & Ravert, 2021; Holloway & Wallinga, 1990). Some literature has documented burnout specifically in CCLS (Fisackerly et al., 2015; Hoelscher & Ravert, 2021; Holloway & Wallinga, 1990; Shuck et al., 2013). Holloway and Wallinga’s (1990) preliminary research found burnout present in CCLS, and CCLS had similar levels of emotional exhaustion when compared to other medical professionals. This indicates CCLS are impacted by the stress of the healthcare environment much like other medical personnel.

The Relationship Between Impostor Phenomenon and Burnout

IP and burnout were originally studied individually in samples of medical professionals, but more recent literature has found a relationship between these constructs (Gottlieb et al., 2019; Leach et al., 2018; Villwock et al., 2016). One review of studies examining IP among physicians and physician trainees found IP to be related to higher levels of burnout in this population (Gottlieb et al., 2019). IP was also found to correlate with increased experiences of emotional exhaustion and depersonalization, both of which are defining features of burnout (Hutchins et al., 2017; Villwock et al., 2016). Burnout and IP have also been found to co-occur with the same psychological disorders, including depression and anxiety (Bravata et al., 2019; Ptacek et al., 2013).

The Influence of COVID-19 on Impostor Phenomenon and Burnout

A large-scale survey of American healthcare workers conducted at the height of the COVID-19 pandemic found that 76% of respondents felt exhausted and burnt out (Mental Health America, n.d.). The work environment caused by the COVID-19 outbreak was also inherently stressful and may have contributed to healthcare workers’ experiences of IP and burnout (Bravata et al., 2020; Jalili et al., 2021). Children have also been impacted by the pandemic in a variety of ways, primarily in the psychosocial domain (Ghosh et al., 2020). Children with preexisting conditions are also at greater risk for negative outcomes related to COVID-19 infections (Ghosh et al., 2020). As CCLS primarily work in hospital settings with children who are medically vulnerable, clinical child life practice has undoubtedly been shaped by this new need to support children and families coping with the added stress of medical vulnerability while living in a pandemic.

In a recent survey of CCLS, over 70% of respondents reported they were at moderate to high risk of experiencing burnout in the context of COVID-19 (ACLP, 2020). Over 70% of respondents indicated they noticed symptoms of burnout in their child life colleagues as well. While literature concerning experiences of CCLS and other healthcare workers during the pandemic is still forthcoming, there is no doubt COVID-19 negatively impacted the overall well-being of many hospital employees. The aim of the present study is to better understand how child life specialists experience IP, burnout, or a combination of the two, and what factors put them at risk for experiencing these phenomena.



Demographics of the study sample (N = 270) are presented in Table 1. Of the 335 responses collected, 270 were analyzed for the purpose of this study. The remaining 65 were excluded from analysis because respondents either did not complete the consent form, did not meet the eligibility criteria to participate in the study, or completed the consent form and screening questions, but not the actual survey questions. Participants were CCLS, currently working in the United States or Canada. Most participants identified as White and female which is representative of the overall demographic makeup of CCLS (ACLP, 2018). Most participants also had either a bachelor’s or master’s degree, had an average of 7.20 years working in the field, and worked in a hospital setting.

Table 1.Study Demographics (N = 270)
Participant Characteristics N (%)
Country of Residence
      United States
263 (97.40)
7 (2.60)
      60 or over
0 (0)
145 (53.70)
88 (32.60)
22 (8.10)
11 (4.10)
      Prefer not to answer
2 (0.70)
263 (97.40)
1 (0.40)
4 (1.50)
      Black or African American
      Native Hawaiian or Other Pacific Islander

3 (1.10)
3 (1.10)
1 (0.40)
253 (94.40)
8 (3.0)

19 (7.00)
251 (93.00)
      Bachelor’s degree (e.g. BA, BS)
      Master’s degree (e.g. MA, MS, MEd)
      Professional degree (e.g. MD, DDS, DVM)
      Doctorate (e.g. PhD, EdD)
91 (33.70)
174 (64.40)
1 (0.40)
3 (1.10)
1 (0.40)
Work Setting
      In-patient hospital setting
      Out-patient hospital setting
      Private practice
      Community setting
      Academic setting
154 (57.00)
86 (31.90)
1 (0.40)
9 (3.30)
2 (0.70)
18 (6.7 0)


Clance Impostor Phenomenon Scale

Levels of IP were measured using the Clance Impostor Phenomenon Scale (CIPS; Clance, 1986). This is a 20-item measure with a variety of literature supporting its validity (Chrisman et al., 1995; French et al., 2008; Holmes et al., 1993). Items on the CIPS utilize success-oriented language rather than negative rhetoric to reduce self-report bias due to respondents striving to appear socially desirable (Chrisman et al., 1995). Participants rank how true each item is on a five-point Likert scale ranging from not at all true to very true. Scores for the CIPS are calculated by totaling the number correlating with each item response. Scores of 40 or less are indicative of few impostor characteristics, scores between 41 to 60 of moderate characteristics, between 61 to 80 of frequent characteristics, and scores higher than 80 show intense impostor characteristics. Chronbach’s alpha scores for the CIPS range from α = .92 to α =.96, showing strong internal consistency (Chrisman et al., 1995; Holmes et al., 1993). For this study, the 20-item CIPS was found to be a highly reliable measure (α =.93).

Oldenburg Burnout Inventory

Level of burnout was measured using the Oldenburg Burnout Inventory (OLBI), a validated measure with Cronbach’s alpha scores of α =.84 (Demerouti et al., 2003; Demerouti & Bakker, 2008). Although this scale was originally created for German-speaking individuals, the English translation of the OLBI has been found to be reliable among English-speaking samples (Halbesleben & Demerouti, 2005). This 16-item scale asks respondents to indicate the degree of their agreement with each statement on a 4-point Likert scale ranging from strongly agree to strongly disagree. Higher scores indicate higher levels of burnout. There are two subscales on the OLBI, disengagement and exhaustion. Disengagement refers to distancing oneself from work and experiencing negative attitudes surrounding work (Demerouti et al., 2003). Exhaustion refers to both physical and mental strain one’s work has on a professional. Cronbach’s alpha scores for the disengagement subscale range from α = .74 to α = .85 and from α = .73 to α = .85 for the exhaustion subscale (Demerouti et al., 2003; Halbesleben & Demerouti, 2005). For this study, the 16-item OLBI overall was found to be highly reliable (α = .83) as were the disengagement (8 items; α = .79) and exhaustion subscales (8 items; α = .84).

COVID-19 and Burnout Question

A single multiple-choice item was included on the survey to assess the impact of the COVID-19 pandemic on child life specialists’ level of burnout. Participants were asked “to what extent has working during the COVID-19 pandemic affected your level of burnout?” Responses were measured on a five-point Likert-type scale, ranging from none to severe. This self-report measure of burnout was included to provide additional insight into the impact of the pandemic on CCLS.

Open-Ended Questions

Two open-ended response questions were included to collect qualitative information on CCLS’s experiences of IP and burnout. These items were added to provide a deeper understanding of the child life experience. To give space for participants to elaborate on their experience of IP as a CCLS, respondents were asked, “Are there any times you have felt like you are not as knowledgeable about the psychosocial care of children as others think you are?” To gain more information on CCLS’s experiences of burnout, the short answer question, “Do you have any other comments surrounding child life and burnout?” was included.


Data were collected online using a survey format created in Qualtrics survey software and participants were recruited to complete the survey via various professional online platforms. All contact with participants took place online. No identifying information concerning participants’ locations or specific workplace was recorded to protect privacy. Participants completed a consent statement and answered two questions to establish eligibility before completing the survey.

Data Analysis

Quantitative Analyses

Quantitative analyses were conducted using IBM SPSS Statistics Version 27.0. First, descriptive statistics for each study variable were calculated along with correlations between variables. Then, a hierarchical regression analysis was conducted for variables predicting burnout. Model 1 included only demographic predictors. Models 2 and 3 also included IP and then IP and COVID-19 impact as predictors, respectively.

Qualitative Analyses

Qualitative analyses were conducted using a thematic analysis (Braun & Clarke, 2006). The six phases of thematic analysis identified by Braun & Clarke (2006) were followed. Data analysis, including coding and theme identification and organizing, were discussed during various meetings with several members of the research team. Participant responses to the two open-ended questions were coded for commonalities. Codes were then grouped into a series of themes for each question. Some main themes also had subthemes identified. Finally, descriptive statistics, including number of responses and percentages of responses in each theme, were examined.


Quantitative Results

Correlations and Descriptive Statistics

On average, participants reported a mean of 56.91 (SD = 14.10) on the CIPS, indicating moderate levels of IP (Clance, 1985). Scores on the CIPS can range from 20 to 100, and the range of scores for this sample was from 22 to 90. The average total burnout score on the OLBI was 36.62 (SD = 6.66). Scores on the OLBI can range from 16 to 64, and the range of scores for this sample was from 20 to 55. The average exhaustion subscale score on the OLBI was 20.03 (SD = 3.92), and the average disengagement subscale score was 18.57 (SD = 3.84). Overall OLBI scores were positively correlated with IP (r = .48, p < .01). Exhaustion subscores (r = .49, p <. 01) and disengagement subscores (r = .38, p <. 01) on the OLBI were also positively correlated with IP. Number of years in the field was negatively correlated with IP (r = -.24, p < .01) and overall burnout on the OLBI (r = -.16, p < .05). Years in the field was negatively correlated with both OLBI exhaustion (r = -.16, p <. 05) and disengagement subscores (r = -.13, p <. 05). All descriptive statistics and correlations are reported in Table 2.

Table 2.Correlations and Descriptive Statistics
Variable 1 2 3 4 5 6 7
1 Burnout - OBLI Total Score 1.00**
2 OLBI Disengagement Subscore .90** 1.00
3 OLBI Exhaustion Subscore .92** .67** 1.00
4 Burnout - Single Item .70** .66** .64** 1.00**
5 Impostor Phenomenon .48** .38** .49** .35** 1.00**
6 Years in Field -.16* -.13* -.16* -.15* -.24** 1.00**
7 Impact of COVID-19 .40** .31* .41** .39** .23** -.074 1.00**
Standard Deviation

Note. * p < 0.05 ** p < 0.01.

Impact of COVID-19

On a scale of none (1) to severe (5), participants reported the extent to which working during the COVID-19 pandemic impacted their perceived level of burnout. Participants reported a mean of 3.48 (SD = 1.06). The level of impact COVID-19 had on a CCLS also positively correlated with IP (r = .28, p < .01) and overall burnout on the OLBI (r = .40, p < .01). COVID-19 impact was also positively correlated with exhaustion (r = .41, p < .01) and disengagement (r = .31, p < .05) subscores on the OLBI. However, there was no significant association between the impact of COVID-19 and the number of years in the field (r = .07, p = .23).

Predictors of Burnout Among CCLS

A hierarchical regression analysis was conducted to examine whether demographic characteristics, IP, and COVID-19 impact predicted burnout as measured by the OLBI. First, demographic characteristics including gender, race, education, hospital setting, other child life setting, and years in the field were analyzed. Second, IP was entered into the model. Last, COVID-19 impact was entered into the model. The results of this analysis are presented in Table 3. In Model 1, three predictors explained 7.1% of the variance in burnout (R2 =.071, F(6, 254)= 3.25, p < .01). Race significantly predicted burnout (β = .164, p < .05) such that minoritized CCLS had higher levels of burnout than White child life specialists. Higher levels of education (β = -.12, p < .05) and more years in the field (β = -.15, p < .05) were associated with lower levels of burnout. In Model 2, the addition of IP resulted in 28.0% of the variance in burnout (R2 =.28, F(7, 253)= 14.06, p < .01). Higher levels of IP were associated with higher levels of burnout (β = .47, p < .01). Among demographic characteristics, only race remained a significant predictor of burnout (β = .17, p < .01). Finally, in Model 3, with the addition of the COVID-19 impact measurement, the predictors explained 36.3% of the variance in burnout (R2 =.36, F(8, 252)= 17.95, p < .01). Higher levels of reported impact of COVID-19 were associated with higher levels of burnout (β = .23, p < .01). Both race and IP remained significant predictors of burnout (β = .15, p < .01, β = .41, p < .01, respectively) in the final model. The results of this hierarchical regression analysis are presented in Table 3.

Table 3.Summary of Hierarchical Regression Analysis for Variables Predicting Burnout (N = 261)
Model 1 Model 2 Model 3
Variable B SE B β B SE B β B SE B β
Gender -.92 2.86 -.02 .54 2.53 .01 .95 2.39 .02
Race 3.42 1.33 .16* 3.54 1.17 .17** .95 1.11 .15**
Education -1.72 .87 -.12* -1.31 .77 -.09 -1.34 .72 -.10
Hospital Setting -.77 .90 -.05 -.864 .79 -.06 -.63 .75 -.04
Other Child Life Setting -2.03 1.35 -.10 -1.57 1.19 -.07 -1.48 1.12 -.07
Years in Field -.15 .06 -.15* -.05 .06 -.05 -.04 .054 -.04
Impostor Phenomenon .22 .03 .47** .19 .03 .41**
Impact of COVID-19 1.89 .33 .30**
R2 .07 .28 .36
F for change in R2 3.25* 73.37* 32.76*

Note. * p < .05. **p < .01.

Qualitative Results

Open-Ended IP Question

A total of 152 participants responded to the open-ended IP question. However, 77 of these participants provided simple, close-ended responses such as “yes” (n = 40, 51.95%), “no” (n = 28, 36.36%), and “sometimes” (n = 9, 11.69%) displayed in Table 4. The remaining 75 responses were included in thematic analysis. A total of five themes, two of which had subthemes, were identified and are displayed in Table 5. Many aspects of participant responses fell into the general insecurities subtheme of self-doubt (n = 42, 56.0%). The knowledge and professional development theme encapsulated a majority of the data (n = 63, 80.0%). See Table 5 for listed themes, subthemes, and example quotations.

Table 4.Close-Ended Participant Responses to Impostor Phenomenon Question
Response N (%)
Yes 40 (51.95)
No 28 (36.36)
Sometimes 9 (11.69)
Table 5.Thematic Analysis: Open-Ended Participant Responses to Impostor Phenomenon Question
Theme Subthemes Description N (%) Example quote
1. Self-Doubt 1.1. General insecurities Responses including discussion of feeling like they aren’t an expert, fears of appearing incompetent, self-doubt, second guessing oneself, and more 42 (56.0) “I am afraid I will forget, say the wrong thing, or assess incorrectly. I hesitant to share my assessments immediately without double checking them in case I messed up.”
1.2. Failures reinforce self-doubt Responses including discussion of working during difficult cases, when interventions don’t work, repeated failures, and more 6 (8.0) “Sometimes if I have multiple procedures or even multiple shifts in a row where my patients cope poorly or things don’t go according to plan I can get frustrated and start to doubt my knowledge/abilities.”
2. Effects of Social Comparison Responses including discussion of comparison to other child life staff, comparison to non-child life staff members, and more 13 (17.33) “I work within a fairly large program and often feel like other child life specialists do a much better job than I do and feel like no matter what I do it does not compare to my coworkers.”
3. Assuming the Role Regardless of Insecurities Responses including discussion of social support, using a “fake it ‘till you make it” mentality, gaining confidence, and more 12 (16.0) “… since changing to my current position, I have started to gain more confidence in my abilities due to staff support.”
4. Knowledge and Professional Development 4.1. Lack of knowledge with specific content areas Responses including discussion of working with certain patient populations, certain developmental age groups, certain diagnoses, certain hospital units, and more 30 (40.0) “Working with patients with sensory considerations, trauma victims, and bereaved families.”
4.2. Experience over education Responses including discussion of education not being adequate, using intuition primarily, struggling to use theory, and more 21 (28.0) “Though I present myself as very confident, I often times question how knowledgeable I really am, even though I received a comprehensive bachelors and masters education.”
4.3. Timeline of professional development Responses including discussion of being new to the field or experiencing IP even after years in the field 12 (16.0) “I question myself daily partially because I am new to the field”
5. IP increases when the child life role & scope is misunderstood Responses including discussion of frustration when other staff don’t understand the child life role and explaining child life to others 7 (9.33) “I find that medical staff wants child life to always have the answer or the "magic pill" to fix something and that this is an unrealistic expectation.”

Open-Ended Burnout Question

A total of 99 participants opted to respond to the open-ended burnout question. Six themes were identified, two of which had subthemes, and are displayed in Table 6. Most pieces of participant responses were coded and grouped under the employment and hospital context theme (n = 69, 69.70%). See Table 6 for listed themes, subthemes, and example quotations.

Table 6.Thematic Analysis: Open-Ended Burnout Question
Theme Subthemes Description # (%) Example quote
1. Employment and hospital context Responses including discussion of toxic workplace environments, administration-level issues, pay rate, the impact of hospital-level factors versus the emotional burden of the job, and more 69 (69.70%) “Though the emotional nature of child life work can be incredibly draining, I would argue that a major contributor to the high burnout rate in the field is the typical salary of a CCLS.”
2. Child life specific factors 2.1. Relationships with child life staff and leadership Responses including discussion of support from leadership, support from child life co-workers, child life department dynamics, and more 43 (43.43%) “Leaders in Child Life are not equipped to recognize and assist in the alleviation of burnout.”
2.2. Factors unique to child life, especially as a helping profession in healthcare Responses including discussion of an excess of non-clinical tasks, the emotional nature of the job, experiencing compassion fatigue, unrealistic expectations, and more 33 (33.33%) “Keeping up with emails, donors, meetings, committees, etc. all while trying to provide the best care and interventions for my patients can be draining.”
3. Interactions with non-child life medical staff Responses including discussion of advocating for child life to other staff members, a lack of understanding of child life by others, experiencing staff pushback, feeling unappreciated by staff, and more 30 (30.30%) “The regular act of advocating for child life within the medical team can be frustrating and more tiring than the emotional toll of child life work itself.”
4. Emotional demands impact well-being 4.1. Self-care, boundaries, and mental health are difficult, yet important, for child life specialists Responses including discussion of self-care, work/life balance, boundaries, mental health, and more 29 (29.29%) “I think the key to avoiding burnout in the field of child life is having a healthy work-life balance. When I leave for the day, I don’t think about work.”
4.2. Various sentiments impact burnout Responses including discussion of feeling overworked, feeling underappreciated, feeling exhausted, and more 33 (34.33%) “I feel like my burnout has come from workload and overall hospital staff morale. Although I can manage my workload, it’s exhausting.”
5. Challenge of recognizing burnout and its complexity Responses including discussion of burnout coming in waves, burnout being caused by a variety of factors, the difficulty of recognizing burnout signs, the need to educate students on burnout, and more 27 (27.27%) “I find that burnout comes and go. I will go through months of feeling great about coming to work, and then other times I feel bored and exhausted.”
6. Effects of COVID-19 Pandemic Responses including discussion stressors due to the COVID-19 pandemic 18 (18.18%) “Because of COVID-19, my hospital lost a lot of money and cut half of the child life team. Stressors of patients and families became higher during the pandemic but we had half the amount of CCLS to support them.”


This study indicates CCLS experience IP and burnout, and a relationship exists between these two constructs. When other covariates are considered, levels of IP can help predict levels of burnout in CCLS samples. The impact of the COVID-19 pandemic has influenced CCLS’s experiences of both IP and burnout. Broad, systemic issues are most likely to be influential causes of IP and burnout in CCLS.

This study found the newer a professional is to child life, the more likely they are to experience both IP and burnout. This is consistent with previous literature concerning IP that found the newer a professional is to their field, the more likely they are to experience this phenomenon (Urwin, 2017). However, this finding is not consistent with previous burnout literature that found older professionals to be at higher risk for burnout (Maslach et al., 2001; Masterson-Allen et al., 1985). Heightened levels of burnout in newer CCLS may be an artifact of COVID-19. It is possible CCLS entering the field closer to the start of the COVID-19 pandemic were at higher risk for burnout because a greater percentage of their overall time in the field occurred during the pandemic. As indicated in the qualitative themes, being new to the field is challenging enough on its own. On top of transitioning from student to professional, recently hired CCLS spent a greater proportion of their career dealing with the stress of working in healthcare during a pandemic. These newer specialists experienced a combination of challenges as they are both finding their footing in a new profession and experiencing burnout intensified by the COVID-19 pandemic.

This study shows IP, along with other covariates, can predict burnout rates in CCLS. When considering demographic variables alone, race, education level, and fewer years in the field help predict a CCLS’s level of burnout while workplace setting does not. However, when considering the impact of IP and COVID-19 on burnout rates, education and years working in the profession were no longer significant predictors, while race remained significant. This finding indicates that race is strongly related to IP and burnout experiences, especially when compared to other demographic variables. When working to alleviate the negative effects of burnout in CCLS, targeting causes of IP experiences could be an effective, tangible technique. One way to accomplish this could be targeting racial discrimination in the workplace, as previous literature has found racial discrimination to predict levels of IP (Bernard et al., 2018). While previous research on burnout experiences of minoritized racial groups is mixed, this study found that CCLS of minoritized racial groups reported higher levels of burnout on the OLBI than White CCLS (Lawrence et al., 2021). Because race remains a significant predictor of burnout even when accounting for the impact of IP and COVID-19, the unique lived experiences of CCLS of minoritized racial groups should be considered. As one participant in the study indicated, “as a child life specialist of color, more emphasis on equity in child life would be immensely helpful for my mental health and hope for the advancement of this field.”

The qualitative findings provide more insight into factors influencing CCLS’s experiences of IP and burnout. Causes of IP were primarily identified as being due to general insecurities and self-doubt, both of which help define IP as a construct (Clance, 1985, 1986). Several CCLS also identified heightened IP experiences when working with populations or developmental ages they are not comfortable with despite being trained with a transferable skillset. As the qualitative data indicated several factors contribute to IP experiences, it is probable one factor alone does not impact a CCLS’s self-doubt; rather, a culmination of variables leads to these professional insecurities which is consistent with the current theoretical understanding of IP (Clance & Imes, 1978).

The qualitative data demonstrated causes of burnout to be primarily due to systemic and administrative level issues. For example, facing staff pushback, not feeling respected by hospital administration, and low pay rates were commonly identified as contributing to feelings of burnout. Sentiments surrounding low pay have been identified as contributors to burnout experiences in other helping professions, including education (Podolsky et al., 2016; Tickle et al., 2011). Advocating for respect of the child life profession and pay raises are tangible ways healthcare leaders can increase the mental well-being of CCLS.

While participants were asked to comment on their experiences with IP and burnout separately, there was still some crossover between the responses to the IP and burnout open-ended questions. This crossover supports the quantitative findings that these constructs are indeed related to each other. For example, mention of the impact of negative interactions with non-child life staff was present in both sets of qualitative data. This also supports the findings in the quantitative data since IP and burnout were found to be significantly correlated and IP predicted burnout experiences.

Table 7.Common Themes Between IP and Burnout Data
Common Theme
or Subtheme
Description N (%) Example IP Quote Example Burnout Quote
Interactions with non-child life staff Burnout and IP are impacted by various interactions with non-child life members of the medical team, including through staff pushback and not respecting or understanding the child life scope of practice 37 (14.74) “Most of the time it is not that I don't feel knowledgeable but that I don't feel others understand the full value of the knowledge I have. This can then make it difficult to feel confident and competent when trying to advocate for the child life role.” “I feel that needing to repeatedly advocate for your role to the interdisciplinary team increases burnout.”
Interactions with child life staff Burnout and IP are heightened/impacted by various interactions with members of the child life team, primarily child life co-workers, but also child life managers and leadership 56 (22.31) “I feel this way when I compare myself to other child life specialists.” “The work dynamic with coworkers has led to my burnout and I am only 7 months into the field…I’m finding issues within the department and that is what is burning me out already.”


This study has several limitations. All psychometrics utilized were self-report measures and participants evaluated their own levels of IP and burnout. The nature of self-report measures could inherently result in bias. Due to time constraints and feasibility, the study design used convenience sampling. The current sample may not be fully representative of the entirety of the CCLS population.

Implications and Future Directions

The present study has several implications for the child life profession. These results indicate CCLS who are new to the field are at greater risk for experiencing IP and burnout. Therefore, education and interventions are needed to support these specialists as they transition from student to professional. For example, a mentorship program for new CCLS could be beneficial as social support was indicated to alleviate the impacts of IP and burnout in the qualitative data. Previous literature has indicated formal mentorship programs can help alleviate burnout in healthcare workers (Leung et al., 2021). Because many participants noted that child life leadership impacted their experience of burnout, educating child life managers on ways to alleviate burnout could improve the mental well-being of CCLS. As indicated by several participants, education on IP and burnout can also start at the student level. Directors of child life academic programs can improve the mental well-being of students preparing to become CCLS by starting conversations on IP and burnout in the classroom.

Future research, especially longitudinal work, is needed to learn more about how and why CCLS experience burnout, IP, and a combination of both. As shown in the qualitative data, burnout is a cycle and often comes in waves. Analyzing the experiences of CCLS over time would provide more insight into how to best support long term well-being. Research is also needed to better understand how IP and burnout experiences show up for minoritized groups in the profession. In-depth qualitative studies on the experiences of various minoritized groups would provide insight into how the profession can best alleviate burnout and IP.


The experiences of IP and burnout by CCLS are closely related. Steps need to be taken to reduce the effects of IP and burnout overall in child life, beginning by increasing awareness of the scope and role of child life practice in healthcare settings, training leadership to support their staff through these experiences, and educating CCLS on how to recognize signs and symptoms of these constructs at the student level. Future work is needed to support the mental well-being and professional quality of life of CCLS, such as creating mentorship programs for new CCLS. These interventions would be especially relevant in light of the negative effects of COVID-19.