The (Linguistic) Profile of the Impostor Phenomenon
Implications for Job Application
Abstract
Abstract: This study examines the impostor phenomenon (IP) in the context of job applications. To this end, 70 candidates were surveyed. Furthermore, their job applications were assessed and analyzed, employing the Linguistic Inquiry and Word Count (LIWC; an often-used program for dictionary-based, automatic quantitative text analysis). With a higher IP expression, a differentiated picture emerges with regard to the application profile: The linguistic profile tends toward a more cautious, more specific and also justifying language. However, for many of the assumed LIWC variables, no correlations were found. It is thought that this might be attributed to the high level of standardization of application documents. Furthermore, this research showed that, at least to some extent, candidates with a higher IP level put more effort into their application and at the same time considered their chances of success to be lower. Conclusions regarding the use of language as a marker of IP expression and implications for the “imposter applicant” are discussed.
The impostor phenomenon (IP) describes highly successful individuals who do not internalize their accomplishments and attribute them to luck, complaisance, or special effort (Clance & Imes, 1978). Due to their achievements, they perceive increasing expectations from their professional and social environment and develop a fear of failure in the expectation of being exposed as a fraud (Noskeau et al., 2021). The IP is particularly prevalent among academics (Vaughn et al., 2020) and reduces the likelihood of taking on career challenges and consequently has a detrimental effect on employees and the organization. Neureiter and Traut-Mattausch (2016) showed that the IP “decreased career planning, career striving, and the motivation to lead” (p. 241). People with impostor syndrome show an internal-stable failure attribution and an external-instable success attribution (Ibrahim et al., 2021), resulting in low self-esteem (Schubert & Bowker, 2019).
As overcompensation, people with impostor syndrome demonstrate higher levels of maladaptive perfectionism (Cokley et al., 2018) and precrastination and procrastination tendencies (Sakulku & Alexander, 2011). They metaphorically experience the feeling of wearing a mask and show higher expression of impression management and self-handicapping (Ferrari & Thompson, 2006), as well as in situational variability (Ibrahim et al., 2021). This special concern regarding their public image could be particularly evident in connection with job applications. Despite the prevailing negative connotations regarding IP, notable positive features associated with this psychological construct exist. Clance and Imes (1978) noted that individuals experiencing IP may manifest traits such as adaptability, sensitivity, and charisma. Recent research by Tewfik (2022) has demonstrated that heightened sense of IP can lead to a perception of increased altruism and a stronger focus on the well-being of others among colleagues. Moreover, Grubb and McDowell (2012) found that those with IP tendencies are seen as possessing strong interpersonal skills and likable personalities. However, it is worth noting that these individuals also tend to show lower emotional engagement, resulting in lower organizational commitment and loyalty to their employers. Accordingly, a higher IP expression could manifest in the use of language and thus be characterized by certain linguistic features. In a study on the use of social network sites (SNS) by people with impostor syndrome, for example, IP proved to be a positive predictor of online self-presentation and preference for online communication (Ibrahim et al., 2023). Thus, a linguistic bias of IP SNS users could manifest in a greater expression in netspeak. It is this expected linguistic IP bias that we intend to explore in this study.
Computer-Based Language Analysis
To our current knowledge, the impostor phenomenon has not yet been investigated within the framework of a linguistic approach. A versatile approach for analyzing word use is the Linguistic Inquiry and Word Count (LIWC) which is one of the most widely used text analysis tools in psychology (Chung & Pennebaker, 2018). It has been used recently, for example, in the study of narcissism (Cutler et al., 2021), depression (Lyu et al., 2023), or also gender differences (Karlsson et al., 2019). We express ourselves through language, for this reason, we also express our personality through the words we choose. A meta-analysis has recently shown which language categories are related to the Big Five (Koutsoumpis et al., 2022). For example, those individuals who score low on emotional stability use more negative emotion words and also more words related to depressive attitudes “e.g., “I,” anxiety, sadness” (p. 857). The relevance of language in the occupational context could be demonstrated by LIWC studies as well: e.g., high and low status communicators differed in their word use (Markowitz, 2018) and even in standardized application documents, language differences could be found regarding e.g., age groups or the success of the application (Brandt & Herzberg, 2020, 2023).
Research Question and Hypotheses
One purpose of this study was to investigate whether the impostor phenomenon is reflected in the choice of language. A further aim is to derive consequences for job applications and careers through application in the context of recruitment.
To answer the research question, whether there is a linguistic profile attributed to the IP expression, application documents shall be analyzed. Initial LIWC studies have shown different results for content (what is said) and function words (how it is said). In the often-cited cliché opening line “It was a dark and stormy night.” the words marked in italics are function words. In initial writing studies about, e.g., trauma processing or depression, surprisingly, it was the function words, such as articles, pronouns, prepositions, auxiliary verbs, or conjunctions, that showed significant correlations (Pennebaker, 2013). It should be noted that there are only a few function words, but they are used at very high rates—more than 99% of our vocabulary consists of content words, but half of the words we use are function words. Moreover function words are generated and processed unconscious, so they are also considered difficult to manipulate (Boyd, 2017; Tausczik & Pennebaker, 2010). For instance, words relating to the first person singular play an important role. On the one hand, studies describe that the lower the status of probands, the more first person singular pronouns are used (Kacewicz et al., 2014). On the other hand, volunteers who are very conscious of themselves and shift the attention to themselves use more of these pronouns as well (Pennebaker, 2013). In research on age differences, time words, future and past tense, or emotion words are discussed in connection with measures of neuroticism and affect (Pennebaker & Stone, 2003). Given the recruitment context, it makes sense to also examine some other LIWC categories such as performance, power, risk, or work. In summary, derived from the findings of insights into the impostor phenomenon on the one hand and LIWC studies on the other, the following hypotheses are proposed:
Individuals with high IP expression will use more words in the categories: first person singular, function words, negative emotion words, causation, discrepancy, insight, tentative, present focus, achievement, and power.
Individuals with high IP expression will use fewer words in the categories: past and future focus, time, netspeak, informal, positive emotions, and certainty. Based on the previous findings on the impostor phenomenon, the research question of whether an impostor manifestation is connected to expectations regarding a job application will be investigated. The hypotheses are:
Individuals with high impostor expression will invest more effort in presenting themselves more perfectly in their applications.
Individuals with high impostor expression will consider the success rate of their application to be less promising.
Method
Sample and Procedures
To test our hypotheses, we collected data at a personnel service agency with German and also international applicants. One advantage is that a recruitment agency handles a large number of applications. Second, we see an advantage in the fact that all applicants have applied for jobs in the same field, which allowed us to keep the external conditions constant. All probands applied for positions in education (e.g., teacher or lecturer). After submitting their application documents, 116 candidates were asked to take part in the research project. They were informed that their participation would not influence the further application process and that the results would be analyzed for scientific purposes only. Care was taken to ensure that the contact person for the study was clearly not the individual contact person involved in the application process. The final sample includes data of 70 applicants: 34 female (48.6%) and 36 male (51.4). The age of the participants ranged between 24 and 59 years (M = 38.35, SD = 9.60).
Analysis of the Application Documents
First, the participants’ application documents were examined. Most of the applications consist of two documents: a cover letter and a CV. Since these are very different regarding their structure, they were first analyzed separately and then together. Seven candidates provided only a CV and two only a cover letter. The candidates wrote 871 (SD = 321.03) words on average. The cover letters contained on average 241 (SD = 123.64), the CVs 606 (SD = 578.97) words. No document had to be excluded.
Computer-Based Text Analyses With LIWC (H1 and H2)
LIWC is a program that accesses predefined dictionaries. The software goes through the given text files and compares them word by word with the chosen dictionary. Words that are recognized as listed in the dictionary are categorized into belonging variables. After going through the words in the supplied text files, LIWC presents the percentage of how often words from a specific category were used. The dictionaries are the heart of the LIWC. They define words that belong to a particular category. By default, there are more than 80 categories that can be analyzed with LIWC. Some are straightforward, for example, the category 1st person singular contains only 12 words like “I,” “me,” or “mine.” Other categories are far more complex and had to be defined first; for example, the category of positive emotions (e.g., “love,” “nice,” “sweet”) contains 2,243 words. The dictionary development process and the psychometric evaluation are described in the manuals (Meier et al., 2018; Pennebaker et al., 2015).
There were 39 applications in German, 26 English documents, and in five applications a mix of both was used. Given the sample, we conducted the analysis with the German version DE-LIWC2015 of Meier et al. (2018) and also the original LIWC2015 (Pennebaker et al., 2015). 23 categories were selected for this study based on the research questions and the theoretical background of IP research. The relevant categories and example words are listed in Table 3.
For each candidate, we prepared three plain text files of their anonymized application documents: The cover letter, the CV, and also the two combined were analyzed by means of LIWC. By default, LIWC studies exclude text documents with less than a certain number of words (between 80 and 100). In our case, no application documents had to be excluded because of low word count.
Self-Presentation (H3)
In addition to the analysis of the application documents with LIWC, we evaluated the application, particularly in specific the candidate's resume about their self-presentation. First, we monitored the scope of the application, e.g., number of words, of words per sentence, and of big words. Furthermore, we screened the CVs for listed details, e.g., the indication of references, prizes, scholarships, awards, or publications and, based on the findings, created the variable “listings” (0 = nothing reported to 5 = mentioning of five of the specific details). Finally, along these lines, we also used matched LIWC analyses to see how candidates presented themselves with content word categories such as “reward,” “work,” or “achievement.”
Data Collected as Self-Reports
In addition to the analysis of the application documents, the second part of the study data involved a questionnaire. After giving consent for data processing, the questions were presented digitally to the participants and the candidates could choose the language themselves. 52.9% chose English; 47.1% decided to answer in German.
Demographic Data and Control Variables
We requested information on age, gender, country of origin and of residence, qualification/degrees, and also the language skills level of German and English. 37.1% of the candidates were located in Germany at the time of application. The remainder was located all over the world, with a minor regional focus on Turkey (7 applicants). Because this study is about language, we monitored all variables related to language. Table 1 shows the candidates' self-evaluation of language skills for German (on average B2 level) and English (on average between B2 and C1 level). Around 50% of the candidates reported near-native proficiency (above C2) in German or English. All participants had a university degree. Table 2 provides an overview of the qualifications. As a whole, this was a highly qualified group of applicants which is representative for applicants in this field.
Anticipation of the Future (H4)
To assess the future expectations, we ask for an evaluation of the items “The future holds a lot of good in store for me” and “I expect my application to be successful.” The possible answers ranged from 1 (strongly disagree) to 6 (strongly agree). Data were missing for 7 participants. The LIWC variables “positive emotion” and “future focus” were of additional interest but had already been covered by the previous analysis. The “risk” category was also included for exploratory purposes.
Impostor Profile
To assess the impostor expression, we used the Impostor Profile 30 (IPP30 Ibrahim et al., 2022) in English or German. The questionnaire measures the impostor phenomenon facets across six subscales (Competence Doubt, Working-Styles, Alienation, Other-Self Divergence, Ambition, and Need for Sympathy) and provides a total score. The instrument is presented as visual scale ranging from 1 (= does not apply in any aspect) to 100 (= applies completely). Internal consistency was assessed with Cronbach’s α = .85, the subscales ranged from .65 to .82. For 6 participants, no IP data were available. Figure 1 shows the distribution of IP scores.
Regarding the evaluation of the distribution, prevalence of IP is still subjected to research, as it depends on the instrument, cut-off scores, and the sample. Nevertheless, Gravois (2007) concluded that the lifetime prevalence of IP is about 70 %. It has also been shown that high performers such as physicians (Thomas & Bigatti, 2020) and academic researchers (Jaremka et al., 2020) similar to our sample are particularly affected.
Results
The underlying question of this study was to test whether differences in the IP characteristics of a person were associated with their job application. We used simple correlation and their 95% CI to answer this question. First, we calculated correlations between IP and LIWC variables. These are shown in Table 3, divided according to cover letter, CV, and both documents combined. Since we were testing multiple bivariate correlation, with a small sample size, it is important to consider the trade-off between controlling Type I errors and the risk of Type II errors. Correcting for multiple comparisons (e.g., using methods like Holm's method or false discovery rate correction) increase the threshold for declaring statistical significance. This reduces the likelihood of finding false positives but may also make it harder to detect true effects, particularly with a small sample size (Rice et al., 2008). As our study was exploratory and we were interested in investigating the relationships between IP and language use, we did not correct the p-values for multiple testing. Instead, we reported the 95% CIs for the correlations and approached the interpretation cautiously.
Regarding the first set of hypotheses, the LIWC variable causation was statistically significant (p’s < .05) associated with IP across all three application documents. Furthermore, discrepancy was statistically significant (p < .05) associated with IP, but only in the CVs. With regard to another LIWC variable, there was only one positive correlation in the cover letters: tentative. None of the other correlations met statistical significance (p’s > .05).
Regarding the second hypothesis, none of the assumed associations were confirmed, all correlations were statistically not significant (p’s > .05).
Next, we analysed the self-presentations of the candidates (H 3). As indicators we employed the LIWC variables word count, big words and also words per sentence, reward, and work. The last three of these were statistically significantly (p’s < .05) associated with IP: reward and work in the cover letter and in the case of words per sentence also for the complete application (p < .05). Furthermore, we found a positive significant correlation between IP and the listing of promotions (Table 4).
Regarding the last hypothesis (H4), we tested the association between the LIWC variables risk and future expectations and the expression of IP. Risk was not statistically correlated with IP (p > .05). The correlation of anticipation for the future and IP is shown in Table 4.
Discussion
Given the limitations of multiple testing with small sample sizes, our results should be interpreted with caution. The aim of this study was to examine the association between the expression of IP and job application behavior. Overall, the assumption that individuals who perceive themselves as impostors tend to attribute successes as external-unstable and failures as internal-stable differ in their use of the written expressions, especially in a job application context. With regard to hypothesis 1, some linguistic differences emerged, whereas no findings could be established for the linguistic pattern of hypothesis 2. In this sample, applicants with a higher IP level were not more self-focused, however, they tended to use a more specific, justifying, and careful language.
To a great extent it could be confirmed that candidates with a high impostor expression make more effort to present themselves well in the applications (H3). As assumed a high IP expression is connected with giving more detailed information about, e.g., references, publications, or scholarships. Also, it can be concluded that a more complex language is used since, e.g., sentences are significantly longer. The fact that more words from the reward category were used in the cover letter also supports our presumption. Surprisingly this pattern did not show regarding the use of words related to work topics, which were in fact reduced. One reason for this could be that candidates with a higher IP profile may also tend to include other topics, apart from work-related subjects, to a greater extent in their cover letters.
Finally, the hypothesis that individuals with a high impostor expression will consider their application to be less promising has been supported (H4). Their way of anticipating the future turned out to be more negative. There was no association for the LIWC category risk, but words of this category were used quite rarely in general.
Looking at the results, from a linguistic point of view, the most significant correlations can be found in the cover letters. This makes sense insofar as CVs are even more standardized than cover letters and contain even less free flow of language. In the following, we will take a more detailed look at the language variables for which an effect was found:
The results indicate that individuals with impostor tendencies tend to exhibit an increased usage of words falling into the category of causation (e.g., because). These findings align with prior personality psychology associations of IP with self-esteem (Schubert & Bowker, 2019) and a more negative self-evaluation (Lee et al., 2022), as impostors may not readily engage in positive self-presentation. Providing more solid justifications for their overall job suitability and positive self-presentation necessitates a more elaborate argumentative structure and biographical indicators. Additionally, the diminished self-assessment within the Honesty-Humility dimension (Ibrahim et al., 2021) could potentially explain why individuals with impostor tendencies strive to be transparent in job applications, thus offering more comprehensive explanations of relationships and causal links.
The increased usage of the word category tentative (e.g., maybe) is also consistent with the construct of the IP. On one hand, it can be interpreted as qualifying positive self-assessments and indicators of suitability, reflecting a certain level of uncertainty. However, on the other hand, it can also serve as an indicator of an interpersonal strategy of humility (Leary et al., 2000), given that individuals with impostor tendencies exhibit a higher need for sympathy (Ibrahim et al., 2022). They may implicitly believe they must compensate for perceived competence deficits by eliciting sympathy.
Interestingly, individuals with higher levels of IP exhibit an increased frequency of words falling into the reward category. Initially, one might assume that individuals with lower self-esteem and higher neuroticism would use fewer positively connoted terms. Nevertheless, this finding can also be understood as a typical overcompensation for their insecurities, symptomatical of impostors. The optimistic tone of the cover letter and overall job applications aligns with the typical mechanism of impostors masking their insecurities behind a facade of positivity and confidence. Thus, on closer examination, this initially paradoxical finding appears consistent with the IP. Impostors tend to display situational variability, heightened attention to social comparison (Ibrahim et al., 2021), and an overall reduced authenticity, where their external presentation reflects neutrality and contradicts their internal experiences, which is a central aspect of the construct.
Further investigation of written expression, particularly a comparison of public and private settings, would be of interest, especially to differentiate between strategic and true impostors (Leonhardt et al., 2017) and to identify characteristic language use. It is possible that strategic impostors, in public settings, may exhibit more tentative (maybe/possibly) words, actively expressing humility and demonstrating impostor tendencies as an interpersonal strategy. Identifying a linguistic pattern that is explicitly used in job application letters or job interviews but potentially also implicitly, such as in anonymous diaries, could serve as a categorization criterion for distinguishing true impostors from strategic impostors.
Finally, our findings are supposed to help to derive practical help for those affected by impostor feelings. With the knowledge that an application is approached in a different way, for example, specific interventions can be used in career counseling. In addition to common counseling strategies, interventions that have been examined with regard to IP could be used specifically in the job application context. Zanchetta et al. (2020) evaluated the impact of a coaching and a training intervention which could be adapted for application purposes. They promote a mindset shift by reducing the fear of negative evaluations and proved that by doing so expression of the IP could be reduced. In the study, the “intervention effect is not just sustainable but even increases over time” (p. 11) which provides a promising starting point for further dealing with our results (Zanchetta et al., 2020).
Finally, for a further study, it will be intriguing to examine how the shown effects unfold further along the application and recruiting chain. Real implications for personnel selection arise mainly from the perception and processing of linguistic differences by other individuals like recruiters. In addition to exploring the perception threshold, the self-representation in job interviews of different IP characteristics would also be of great interest.
Strength and Limitations
A major limitation comes with the generalizability of the findings. We considered keeping a lot of the external factors constant an advantage. The flip side of the coin is that on the basis of the current data, it is not reasonable to draw conclusions for different recruiting sectors and industries. Furthermore, the effect sizes described in this study are generally relatively small. It should be noted that this issue has already been described as a typical occurrence in studies using language analysis the way we did, and it weighs against the consistency with which findings are shown (Newman et al., 2008). Many LIWC studies also use much larger samples. Advantageously, our sample is not based on social media or student data but on real-life data. To consolidate the results discussed, replication studies are necessary and have also recently been called for regarding other LIWC studies (Bierstetel et al., 2020). This study is not a validation of LIWC being used as a tool for diagnostic purposes nor does it justify conclusions or predictions with regard to an individual’s behavior.
Next to the question why some of the associations shown turned out to be small, we ask ourselves why did some of the hypotheses not hold up. As mentioned above, language analyses of highly standardized texts such as application documents present specific challenges compared to analyses of, e.g., essays or blog entries. Moreover, some LIWC categories were neglected due to their rare occurrences in application documents. In a job application context, it seems only natural that word categories like anxiety are rarely, if ever, used. For future studies, it might be interesting to investigate if categories of personal concerns, psychological or social processes show effects in other text types. Applications contain little natural language fluency. It also needs to be considered that half of the test subjects were non-native speakers. In some studies, an attenuating character of the so-called foreign language hypothesis has been discussed. For example, the use of a foreign language might reduce intuition or increase cognitive load which could have an effect on the magnitude of our results (Geipel et al., 2016). Furthermore, application documents may be affected, for example, by the use of templates, autocorrections, the use of software like ChatGPT or other forms of support. In the light of these external influences, it seems unsurprising that some hypotheses proved to be unfounded and the effects that could be shown seem even more relevant. Taking all the limitations and constraints into account, the results found are all the more impressive.
Taken the heading limitations more broadly, critical voices about the popular descriptive kind of research with LIWC must be addressed. Recent critical reviews have been addressing restrictions of a mere correlational approach: emotion, trait, or behavior X is associated with LIWC category Y. Researchers have expressed concerns about the depth of these kinds of studies (Boyd & Schwartz, 2021). Some even regard a dictionary-based approach in language studies as outdated. The authors of a study aiming to identify sentiment in psychotherapy discuss the advantages of a natural language processing model (NLP) named BERT (Tanana et al., 2021). A comparison of different methods, including BERT, regarding prediction of positive and negative communication behavioral codes of couples showed a 4% accuracy performance improvement using BERT (Biggiogera et al., 2021). Therefore, the use of other models, specifically more advanced and more comprehensive language tools, including AI-based approaches like ChatGPT, present an exciting new opportunity for follow-up studies. LIWC scores for a first examination with simplicity; it seems transparent and comprehensible. Another aspect to discuss is the local processing of LIWC, which makes it possible to analyze sensitive data, common recruiting contexts, in compliance with the data protection regulations applicable in the EU. With respect to our study, it was possible to show that there are linguistic differences in applications depending on the degree of IP. Since no one has approached this topic in this way before, we consider it a good starting point to shed new light on known phenomena, to now ask for and to discuss underlying processes and implications, and to discover new angles for further research. After all, in language analysis with methods like LIWC, it is argued that verbal behavior mainly reflects attention.
Electronic Supplementary Materials
The electronic supplementary material is available with the online version of the article at https://doi.org/10.1027/2151-2604/a000562
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