Examining an integrated path model of psychological and sociocultural predictors of camouflaging in autistic adults

Abstract

Camouflaging involves various strategies employed by autistic individuals to modulate the visibility of their autistic characteristics in social situations and is thought to be primarily motivated by psychosocial factors. Most studies to date have examined a limited number of psychosocial factors related to camouflaging. This study tested an integrated model encompassing several hypothesised individual psychological (i.e. fear of negative evaluation, self-esteem, autistic identity) and broader sociocultural predictors (i.e. perceived stigma, vulnerability events, cultural tightness-looseness, independent and interdependent self-construal). Participants were 225 autistic adults (18–77 years; 60.9% female), who completed self-report measures online. Path analysis partially supported the model, explaining about 25% of the variance in camouflaging. Several sociocultural factors – perceived stigma, cultural tightness and independent and interdependent self-construal – were indirectly associated with camouflaging through individual psychological factors. Notably, greater vulnerability to negative life events was the only sociocultural factor directly contributing to more camouflaging, without mediation by individual psychological factors. Fear of negative evaluation emerged as a strong predictor, mediating most relationships between broader sociocultural factors and camouflaging. Our findings highlight key psychosocial factors as crucial targets for social change, advocating a shift from stigmatisation to acceptance and inclusion to alleviate the pressure on autistic people to camouflage.

Lay abstract

Many autistic people use strategies known as ‘camouflaging’ to change how noticeable their autistic traits are in social situations. Previous research suggests that camouflaging is largely motivated by psychological and social factors. However, most studies so far have only looked at a few psychosocial factors related to camouflaging. In this study, we explored a model that included several individual psychological factors (such as fear of being negatively judged, self-esteem and autistic identity) and broader social and cultural factors (such as perceived stigma, negative life events, cultural emphasis on conformity and desire to fit in or stand out). We surveyed 225 autistic adults aged 18–77 years online. Our findings showed that several sociocultural factors were indirectly linked to camouflaging through individual psychological factors. Fear of being negatively judged emerged as a strong predictor of camouflaging. Specifically, autistic adults who perceived greater stigma, felt greater pressure to conform, had a lesser desire to stand out and a greater desire to fit in tended to experience a greater fear of being negatively judged and reported more camouflaging. In addition, those who experienced more negative life events were more likely to engage in camouflaging. Our study identifies key psychological and social factors as potential targets for social change. Our findings emphasise that our societies need to shift away from stigmatising attitudes towards accepting and including autistic people, which could reduce the pressure on autistic individuals to camouflage in social situations.

Keywords

autism camouflaging masking psychosocial factors social model of disability

Many autistic people experience a range of psychosocial challenges, including poorer mental health (Lai, 2023), difficulties in social participation (Mason et al., 2020) and an increased likelihood of victimisation (Gibbs et al., 2021; Griffiths et al., 2019) compared with non-autistic people. To navigate these challenges, some autistic people have developed coping strategies known as camouflaging. Camouflaging involves consciously or unconsciously modifying autistic characteristics to ‘pass as normal’ to fit into non-autistic social environments (Cage & Troxell-Whitman, 2019; Hull et al., 2017). These strategies include hiding or masking one’s autistic characteristics, actively compensating for social differences by imitating non-autistic social interaction styles and attempting to assimilate with others (Hull et al., 2019). While camouflaging can be helpful and necessary for social survival in a largely non-autistic world (Bradley et al., 2021), many autistic people have described it as detrimental to their well-being and have associated camouflaging with anxiety, depression and burnout (Chapman et al., 2022; Mantzalas et al., 2022).

Psychosocial predictors of camouflaging

Camouflaging occurs within a social context, and the existing literature highlights the role of psychosocial experiences in predicting camouflaging behaviours. Zhuang et al.’s (2023) mixed methods systematic review of 58 studies identified 3 themes relating to psychosocial correlates of camouflaging: (a) social norms and pressures of a largely non-autistic world, (b) social acceptance and rejection and (c) self-esteem and identity. In addition, Ai and colleagues (2022) have proposed a model conceptualising camouflaging as a transactional and context-dependent process motivated by psychosocial factors, such as self-esteem and stigma. Drawing from Zhuang et al. and Ai et al., we propose several psychological and sociocultural factors hypothesised to predict camouflaging, which are organised according to three levels of environmental influence (Bronfenbrenner, 1992): (a) individual psychological factors; (b) proximal sociocultural factors, encompassing direct influences from an individual’s immediate social environment and (c) distal sociocultural factors, encompassing indirect broader sociocultural influences.

Individual psychological factors

Fear of negative evaluation

Fear of negative evaluation (FNE) has been linked to social anxiety, with socially anxious individuals adopting safety and avoidance behaviours to conceal perceived flaws and avoid negative judgements (Moscovitch et al., 2013). Autistic people commonly experience social anxiety, with prevalence estimates ranging from 12% to 56%, significantly higher than the 7%–13% estimates for the non-autistic population (Spain et al., 2016, 2018). FNE may be implicated in camouflaging as autistic individuals often camouflage to avoid being perceived negatively, such as being labelled as ‘rude’ or ‘weird’ (Zhuang et al., 2023).

Self-esteem

Autistic people with lower self-esteem may perceive their autistic traits as undesirable and so experience a greater need to camouflage. Zhuang et al.’s (2023) review suggests that autistic people who internalise societal stigma may develop a negative self-image over time, increasing their tendency to camouflage out of shame. Consistent with this, a quantitative study found that lower self-esteem was associated with higher self-reported camouflaging among autistic adults (Evans et al., 2023).

Autistic identity

Autistic identity refers to a sense of affiliation with the autistic community and the integration of characteristics shared with other autistic individuals into their self-concept (Cooper et al., 2017). In 10 qualitative or mixed methods studies reviewed by Zhuang et al. (2023), participants described a trajectory in which receiving an autism diagnosis contributed to better self-understanding and acceptance of their autistic identity, resulting in less camouflaging over time. Consistent with this, one quantitative study found that autistic adults with a stronger autistic identity tended to disclose their autism diagnosis more frequently, which, in turn, was associated with reduced camouflaging (Cage, Troxell-Whitman, 2020).

Proximal sociocultural factors

Perceived stigma

Autistic people often experience stigmatisation across various life domains, including education (Gillespie-Lynch et al., 2019) and employment (Romualdez et al., 2021). Camouflaging can be understood as a stigma management strategy used by autistic people to conceal a stigmatised identity and protect against prejudice and discrimination (Ai et al., 2022; Botha et al., 2022; Pearson & Rose, 2021; Turnock et al., 2022). Supporting this notion, a quantitative study found that higher perceived autism stigma was associated with greater self-reported camouflaging among autistic adults (Perry et al., 2022).

Vulnerability events

Autistic adults are more vulnerable than non-autistic adults to various negative life experiences, including victimisation, unemployment and social isolation (Gibbs et al., 2021; Griffiths et al., 2019). In 17 qualitative or mixed methods studies reviewed by Zhuang et al. (2023), autistic individuals reported being victimised due to their autistic differences, which led to increased fear of re-victimisation and potential heightened FNE, compelling them to camouflage to safeguard against further adverse experiences. Using quantitative methods, Trundle and colleagues (2022) found that autistic people who experienced greater victimisation also camouflaged more.

Distal sociocultural factors

Independent and interdependent self-construal

Independent and interdependent self-construal reflect the extent to which individuals perceive themselves as separate from or connected with others (Markus & Kitayama, 1991). People with a more independent self-construal tend to prioritise independence and uniqueness, while individuals with a more interdependent self-construal emphasise fitting in and connecting with others (Markus & Kitayama, 1991). Individual differences in independent and interdependent self-construals are associated with cultural orientations of individualism (prioritising personal autonomy and independence) and collectivism (emphasising group cohesion and interdependence), which are more prominent in Western and non-Western cultures, respectively (Giacomin & Jordan, 2017; Kitayama & Salvador, 2024). People with a stronger interdependent self-construal may engage in more camouflaging, driven by a greater motivation to minimise autistic differences to fit in. Conversely, those with a stronger independent self-construal may engage in less camouflaging to preserve one’s unique autistic attributes and individual autonomy.

Cultural tightness-looseness

Different cultures vary in the strength of their social norms and the degree to which they tolerate deviation from norms (Gelfand et al., 2011). Tighter cultures tend to have stronger and clearer norms with lesser tolerance for deviation, whereas looser cultures tend to have weaker and less defined norms with greater tolerance for non-conformity (Gelfand et al., 2011). Cultural tightness-looseness is related to, but also somewhat distinct from, the concepts of individualism and collectivism, and it is possible for societies to be collectivistic and loose, or individualistic and tight (Kitayama & Salvador, 2024; Stamkou et al., 2018). Since certain autistic characteristics are often perceived as deviating from what society deems ‘normative’, autistic individuals may face stricter sanctions for their behaviours in tighter cultures. In Loo et al. (2023), one autistic interviewee described experiencing greater pressure to camouflage in Singapore compared with the United Kingdom and attributed this to Singapore’s emphasis on conformity. Thus, autistic individuals may camouflage more in culturally tighter contexts due to increased pressure to conform.

The present study

Zhuang et al.’s (2023) systematic review found that most studies exploring psychosocial correlates of camouflaging employed qualitative methods, with only a minority (18 of 58) involving quantitative approaches. Of the few quantitative studies, most focused on biologically determined or stable individual differences (e.g. age, sex, IQ), while only a few examined a small number of psychosocial correlates (e.g. Cage, Troxell-Whitman, 2020; Perry et al., 2022). To our knowledge, no quantitative study to date has investigated an integrated theoretically and empirically informed model of psychosocial predictors of camouflaging in autistic adults. Thus, this study tested a novel model of psychosocial predictors of camouflaging derived from Zhuang et al., Ai et al. (2022) and the broader sociocultural literature discussed earlier (Figure 1).

Figure 1.

Hypothesised model.

We hypothesised that greater FNE, lower self-esteem, weaker autistic identity, greater perceived stigma, greater vulnerability to negative life events, greater cultural tightness, lower independent self-construal and higher interdependent self-construal would be associated with more camouflaging in autistic adults. In addition, as Zhuang et al.’s (2023) findings suggested that sociocultural factors may indirectly impact camouflaging through individual psychological factors, we also examined whether the hypothesised psychological factors mediated relationships between sociocultural factors and camouflaging.

Method

Participants

Participants were autistic adults (a) aged 18+ years, (b) able to complete an online survey in English and (c) professionally diagnosed or self-identified as autistic. Self-identified autistic individuals were included to increase the representation of those facing barriers to professional diagnoses (Lai & Baron-Cohen, 2015; Lewis, 2017) or not formally identified due to camouflaging (Libsack et al., 2021). Moreover, research has shown no statistically significant differences between professionally diagnosed and self-identified autistic participants in self-reported autistic traits, autism identity, self-esteem and stigma experiences (English et al., 2021; McDonald, 2020).

Recruitment occurred between May and August 2021 through advertisements distributed via social media, autism associations and Prolific (https://prolific.co; a U.K.-based online research participation platform). Of the 259 respondents who accessed our survey, we excluded 32 who failed our screening checks (see Procedure). In addition, data from two respondents were identified as influential multivariate outliers and excluded from subsequent analyses. Our final sample comprised 225 autistic adults aged 18–77 years (M = 35.5, SD = 11.8).

Most participants were female, White, employed, university-educated and residing in Australia (Table 1). About 70% of participants reported having a mental health diagnosis in the last 5 years, most commonly anxiety and depression. Most were professionally diagnosed (n = 183; 81.3%), while 42 (18.7%) self-identified as autistic. In our study, there was no significant difference in Broad Autism Phenotype Questionnaire (BAPQ) total scores (Hurley et al., 2007) between participants with professional diagnoses (M = 4.3, SD = 0.6) and those self-identifying as autistic (M = 4.4, SD = 0.5; t(223) = 0.61, p = 0.546, d = 0.10). Most (n = 217; 96.4%)¹ scored above the BAPQ total cut-off score of 3.15, previously established as indicating a high likelihood of clinically significant levels of autistic traits (Hurley et al., 2007). Among professionally diagnosed participants, the mean age at autism diagnosis was 27.5 years (SD = 14.2, range 2–61).

Table 1.

Participant characteristics (N = 225).

Characteristics	N	%
Gender
Female	137	60.9
Male	64	28.4
Other genders^a	21	9.3
Preferred not to say	3	1.3
Ethnicity
White	193	85.8
Asian	13	5.8
Multiethnic	13	5.8
Black/African/Caribbean	4	1.8
Hispanic/Latino	2	0.9
Country of residence
Australia	125	55.6
United Kingdom	45	20.0
United States of America	30	13.3
New Zealand	8	3.6
Canada	7	3.1
Other European countries	7	3.1
Asian countries (Singapore, Hong Kong)	3	1.3
Highest educational level
Undergraduate degree	76	33.8
Postgraduate degree	58	25.8
Secondary school	50	22.2
Trade/technical certificate	34	15.1
Primary school	3	1.3
Other qualifications (e.g., diploma, A-level certificate)	4	1.8
Employment status
Employed full-time	63	28.0
Employed part-time	50	22.2
Unemployed	42	18.7
Student	36	16.0
Homemaker/caregiver	19	8.4
Unpaid work (e.g., volunteering, unpaid internship)	8	3.6
Retired	5	2.2
Preferred not to say	2	0.9
Living arrangements
Living with partner and/or child(ren)	103	45.8
Living with parents/relative(s)	59	26.2
Living alone	40	17.8
Living with friend(s)/housemate(s)	21	9.3
Other	2	0.9
Other neurodevelopmental diagnoses
Attention-deficit/hyperactivity disorder	55	24.4
Specific learning disorder	12	5.3
Intellectual disability	3	1.3
Other (e.g., cerebral palsy, developmental coordination disorder)	3	1.3
Preferred not to say	6	2.7
Mental health diagnoses (in the last five years)
Anxiety	127	56.4
Depression	113	50.2
Post-traumatic stress disorder	29	12.9
Obsessive-compulsive disorder	12	5.3
Personality disorders	7	3.1
Bipolar disorder	5	2.2
Eating disorders	5	2.2
Other (e.g., psychotic disorders, dissociative disorders)	10	4.4
Preferred not to say	6	2.7

Other genders included non-binary (n = 12), agender (n = 3), genderqueer (n = 2), gender neutral (n = 1), gender fluid (n = 1), gender curious (n = 1), and demifemale (n = 1).

Procedure

Ethical approval was granted by the University of Western Australia Human Research Ethics Committee (reference number: 2021/ET000065).

This study is part of a larger project exploring psychosocial factors associated with camouflaging, mental health and burnout in autistic adults across three time points. Participants completed demographic questions and self-report measures on a Qualtrics-hosted survey (https://www.qualtrics.com), taking approximately 45–60 min. All participants provided written informed consent and could choose ‘prefer not to say’ for all questions. Participants received AUD20 reimbursement for their time.

Given that this was an online survey, we employed several strategies to reduce invalid responses and enhance data quality. Initially, participants were invited to express their interest by completing a brief questionnaire. Eligible participants who achieved a reCAPTCHA score of ⩾ 0.70² received an individual survey link via email. Our study survey included two CAPTCHA questions and two attention check items. Upon completion, participants were asked to indicate whether their data was valid for research. We excluded the data of 32 participants for the following reasons: (a) incomplete or unsubmitted (n = 17), (b) ineligibility (n = 6), (c) a reCAPTCHA score of < .5 (n = 3), (d) indicated invalid data (n = 1), (e) chose ‘prefer not to say’ for over 20% of responses across all measures (n = 2) and (f) chose ‘prefer not to say’ for all items for at least one measure (n = 3).

Measures

Autistic traits

The 36-item BAPQ (Hurley et al., 2007) measures autism-related characteristics (rated from 1 = very rarely to 6 = very often; mean-item total score range 1–6) and demonstrates good sensitivity, specificity and excellent internal consistency in autistic and non-autistic groups (α = 0.95–0.96; Hull et al., 2019; Hurley et al., 2007; Sasson et al., 2013).

Camouflaging

The 25-item Camouflaging Autistic Traits Questionnaire (CAT-Q; Hull et al., 2019) measures camouflaging behaviours (rated from 1 = strongly disagree to 7 = strongly agree; total score range 25–175). It has been validated in autistic and non-autistic adults, demonstrating equivalence in factor structure across gender and diagnostic groups and high internal consistency (α = 0.91–0.94; Hannon et al., 2023; Hull et al., 2019).

Individual psychological factors

FNE

The eight-item Brief Fear of Negative Evaluation-II Scale (BFNE-II; Carleton et al., 2007) measures apprehension related to negative evaluation by others (rated from 0 = not at all characteristic of me to 4 = extremely characteristic of me; total score range 0–32). It demonstrates moderate convergent and discriminant validity and excellent internal consistency in clinical and nonclinical populations (α = 0.95–0.96; Carleton et al., 2007, 2011).

Self-esteem

The 10-item Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1965) measures global self-worth (rated from 1 = strongly disagree to 4 = strongly agree; total score 10–40). It demonstrates excellent internal consistency among autistic adults (α = 0.90–0.92; Cooper et al., 2017; Corden et al., 2021; Nguyen et al., 2020).

Autistic identity

The 14-item Multicomponent In-group Identification Scale (MIIS; Leach et al., 2008) measures in-group identification (rated from 1 = strongly disagree to 7 = strongly agree; mean-item total score range 1–7). It has been adapted to measure autism identification with good to excellent internal consistency (α = 0.84–0.91; Cooper et al., 2017, 2020, 2022; Maitland et al., 2021). Our adaptation used the terms ‘autistic individual/person/community’.

Proximal sociocultural factors

Perceived stigma

The original five-item Perceived Stigma Measure (PSM; Shtayermman, 2009) assesses perceived stigma related to having Asperger’s syndrome (a former autism diagnostic term). In this study, we replaced ‘having Asperger’s syndrome’ with ‘being autistic/on the autism spectrum’, to align with updated terminology and many autistic adults’ preferences (Bury et al., 2020; Kenny et al., 2016). To capture a broader range of responses, we modified the rating scale from the original ‘yes/no’ to a 5-point Likert-type scale (0 = never; 4 = very often; total score range 0–20). To our knowledge, the PSM is the only available measure directly assessing perceived autism stigma in the literature. Our adaptation demonstrated good internal consistency in our dataset (Table 2).

Table 2.

Descriptive statistics, reliabilities and correlations among study variables (N = 225).

	Camouflaging	FNE	Self-esteem	Autistic identity	Stigma	Vulnerability events	Cultural tightness	Indep SC	Interdep SC
FNE	0.40***
Self–esteem	–0.09	–0.47***
Autistic identity	0.21**	0.12	0.28***
Stigma	0.11	0.21**	–0.21**	–0.02
Vulnerability events	0.26***	0.12	–0.14*	0.03	0.32***
Cultural tightness	0.16*	0.16*	0.11	0.15*	0.05	0.05
Indep SC	–0.20**	–0.40***	0.58***	0.25***	–0.12	–0.01	0.09
Interdep SC	0.13	0.23***	–0.10	0.15*	–0.03	–0.08	0.19**	–0.09	–
M	132.72	22.48	24.14	4.73	13.37	22.32	4.79	4.32	4.43
SD	20.62	8.68	6.06	1.14	4.49	10.12	0.74	0.82	0.83
Range	73–175	0–32	10–40	1.50–7.00	0–20	3–48	2.60–6.00	1.92–6.67	2.35–6.83
Cronbach’s alpha (α)	0.89	0.95	0.89	0.91	0.84	0.91	0.65	0.71	0.72

FNE: fear of negative evaluation; indep SC: independent self-construal; interdep SC: interdependent self-construal; SD: standard deviation.

p < 0.05; **p < 0.01; ***p < 0.001; correlations ⩾ 0.3 in bold.

Vulnerability events

The 60-item Vulnerability Experiences Quotient (VEQ; Griffiths et al., 2019) assesses the frequency of negative experiences across multiple life domains. Participants scored 1 for presence and 0 for absence of each experience, except for three social support items, which are reverse scored (total score range 0–60). The VEQ demonstrates very good internal consistency among autistic adults (α = 0.89; Griffiths et al., 2019).

Distal sociocultural factors

Cultural tightness-looseness

The six-item Tightness-Looseness Scale (TLS; Gelfand et al., 2011) assesses the strength of social norms and tolerance for norm violations (rated from 1 = strongly disagree to 6 = strongly agree; mean-item total score range 1–6). It demonstrates good validity and internal consistency in large cross-national studies (α = 0.80–0.85; Aktas et al., 2016; Eriksson et al., 2021; Gelfand et al., 2011).

Independent and interdependent self-construal

The Self-Construal Scale (SCS; Singelis, 1994) comprises a 12-item independent subscale and a 12-item interdependent subscale (rated from 1 = strongly disagree to 7 = strongly agree; mean-item total subscale score range 1–7). Both subscales have acceptable internal consistency in ethnically diverse student populations (α = 0.69–0.81; Christopher & Skillman, 2009; Singelis, 1994; Singelis et al., 1995).

Data analyses

IBM SPSS Statistics version 29.0 and AMOS 29.0 were used.

Missing data

Responses indicating ‘prefer not to say’ were treated as missing data, which ranged from 0.1% to 3.3% across measures, with an overall 0.8% missing values. Little’s MCAR test indicated that data were missing completely at random for all measures, except for the CAT-Q, BFNE and TLS. Item-level missing data were addressed using multiple imputation (Woods et al., 2023). Twenty imputed datasets were combined into a single pooled dataset using the ‘bar procedure’ (Baranzini, 2018) for subsequent analyses.

Main analyses

To examine direct and indirect relationships between variables, path analysis was conducted in AMOS using maximum likelihood estimation and 10,000 bootstrap samples. Mediation was considered significant if the bootstrapped 95% bias-corrected confidence interval for the indirect effect excluded 0 (Hayes, 2009).

The hypothesised model (Figure 1) was assessed for goodness of fit. Modification indices were examined to consider the inclusion of additional, theoretically viable relationships. Model fit was assessed using multiple indices, with the following cut-off values indicating a good fit: comparative fit index (CFI) ⩾ 0.95, standardised root mean square residual (SRMR) ⩽ 0.08 and root mean square error of approximation (RMSEA) ⩽ 0.06 (Hu & Bentler, 1999). Model trimming was performed by removing non-significant paths to obtain the most parsimonious model.

Authors’ positionality

Our approach was influenced by our training in psychology, professional experiences as academics and lived experiences as autistic individuals. Our research team holds professional and personal values that align with a neurodiversity-affirming lens and the social model of disability.

Community involvement

The larger research project was developed in consultation with an autistic advisor who provided input on the conceptualisation, relevance of psychosocial factors and appropriateness of the survey. For this study, we engaged two additional autistic advisors who contributed to the model development, measure selection and interpretation of findings, ensuring alignment with their lived experiences and understanding of camouflaging within the autistic community. All advisors were reimbursed for their time and are co-authors.

Results

Descriptive statistics, internal consistencies and intercorrelations are presented in Table 2. FNE, vulnerability events, autistic identity and cultural tightness were significantly positively correlated with camouflaging, while independent self-construal was significantly negatively correlated with camouflaging, with small to medium correlations.³ Internal consistencies ranged from acceptable to excellent, except for TLS which had borderline reliability.⁴ Mardia’s (1970, 1974) normalised estimate of multivariate kurtosis was 1.43, lower than the recommended cut-off value of 5.0 (Bentler, 2006; Byrne, 2016), indicating multivariate normality.

The initial model demonstrated inadequate fit, χ²(13) = 90.85, p < 0.001, CFI = 0.76, SRMR = 0.09, RMSEA = 0.16 (90% CI (0.13, 0.20)). Guided by modification indices and previous literature on relationships between the variables, covariances were specified between stigma and vulnerability events,⁵ cultural tightness and interdependent self-construal⁶ as well as among the error terms of FNE, self-esteem and autistic identity.⁷

The revised model (Figure 2) exhibited excellent fit, χ²(8) = 11.29, p = 0.186, CFI = 0.99, SRMR = 0.04, RMSEA = 0.04 (90% CI (0.00, 0.10)), accounting for 26.5% of the variance in camouflaging. To derive the most parsimonious model, model trimming of the revised model was conducted by iteratively removing non-significant paths one by one, starting with the path with the largest p-value. The model was rerun to examine changes in model fit indices and to identify the next least significant path for removal until all remaining paths in the model were significant. In total, 10 paths were removed, including 3 direct paths from hypothesised predictors to camouflaging and 7 mediating paths between the predictors.

Figure 2.

Revised model with post-hoc modifications.

The final trimmed model (Figure 3) maintained excellent fit, χ²(18) = 22.98, p = 0.191, CFI = 0.98, SRMR = 0.05, RMSEA = 0.04 (90% CI (0.00, 0.07)), explaining 24.9% of the variance in camouflaging. Greater vulnerability events and lower levels of independent self-construal were directly associated with increased camouflaging. Perceived stigma, cultural tightness and both independent and interdependent self-construal were indirectly associated with camouflaging through individual psychological factors. As expected, greater FNE was associated with more camouflaging, but unexpectedly, higher self-esteem and a stronger autistic identity were linked to greater camouflaging. All statistically significant mediating paths before and after model trimming are presented in Table 3.

Table 3.

Statistically significant mediating paths (N = 225).

Mediating paths	Before model trimming					After model trimming
	b (SE)	95% CI		p	β^a	b (SE)	95% CI		p	β^a
	b (SE)	LL	UL	p	β^a	b (SE)	LL	UL	p	β^a
1. Stigma → FNE → Cam	0.22 (0.12)	0.03	0.51	0.024	0.05	0.26 (0.12)	0.07	0.54	0.006	0.06
2. Stigma → Self-esteem → Cam	–0.09 (0.07)	–0.29	–0.001	0.045	–0.02	–0.12 (0.08)	–0.33	–0.02	0.016	–0.03
3. Cultural tightness → FNE → Cam	1.40 (0.63)	0.42	2.99	0.006	0.05	1.60 (0.64)	0.57	3.19	0.002	0.06
4. Indep SC → FNE → Cam	–3.20 (0.93)	–5.21	–1.56	<0.001	–0.13	–3.41 (0.90)	–5.39	–1.83	<0.001	–0.14
5. Indep SC → Self–esteem → Cam	2.23 (1.06)	0.23	4.41	0.031	0.09	2.48 (1.09)	0.44	4.78	0.019	0.10
6. Indep SC → Autistic identity → Cam	0.93 (0.47)	0.20	2.08	0.011	0.04	1.02 (0.48)	0.27	2.20	0.007	0.04
7. Interdep SC → FNE → Cam	1.51 (0.64)	0.51	3.04	0.001	0.06	1.39 (0.58)	0.46	2.77	0.002	0.06
8. Interdep SC → Autistic identity → Cam	0.56 (0.38)	0.05	1.58	0.021	0.02	0.70 (0.41)	0.11	1.80	0.011	0.03

SE: standard error; CI: confidence interval; LL: lower limit; UL: upper limit; FNE: fear of negative evaluation; cam: camouflaging; indep SC: independent self–construal; interdep SC: interdependent self-construal.

As AMOS provides only unstandardised specific indirect effects, standardised specific indirect effects were manually calculated by multiplying the standardised path coefficients associated with each indirect effect (MacKinnon et al., 2007).

Figure 3.

Final trimmed model.

Discussion

To our knowledge, this is the first study to examine an integrated model of psychosocial predictors of camouflaging in autistic adults. Results partially supported the hypothesised model, which demonstrated excellent model fit after post hoc modifications. The final model accounted for about 25% of the variance in camouflaging, demonstrating a substantial contribution from psychosocial factors.

Several sociocultural factors – perceived stigma, cultural tightness and interdependent self-construal – were not directly associated with camouflaging; instead, they were indirectly associated with camouflaging through individual psychological factors, such as FNE, self-esteem and autistic identity. These findings align with the transactional model of camouflaging proposed by Ai and colleagues (2022) and empirically support conclusions from Zhuang et al.’s (2023) review, suggesting that sociocultural factors may indirectly influence camouflaging through autistic individuals’ internalisation of societal stigma and norms.

Notably, vulnerability to negative life events was the only sociocultural factor that was directly associated with camouflaging, without mediation by individual psychological factors. This could be attributed to camouflaging potentially being a conditioned trauma response driven by autistic people’s need for safety and social survival and directly impacted by negative life experiences, including victimisation, discrimination and abuse (Chapman et al., 2022; Pearson et al., 2022; Seers & Hogg, 2022). Given the cross-sectional nature of our data, it is also possible that the relationship between camouflaging and vulnerability to negative events may be bidirectional. While many autistic people camouflage to reduce or avoid victimisation and other negative life experiences, camouflaging may potentially increase one’s risk of being victimised through heightened compliance and a desire to please others (Pearson et al., 2022; Zhuang et al., 2023).

FNE emerged as a strong and important predictor of camouflaging, mediating most relationships between broader sociocultural factors and camouflaging. Autistic adults perceiving greater autism stigma and cultural tightness reported increased FNE, which, in turn, was associated with more camouflaging. These results extend Perry et al.’s (2022) findings by highlighting the mediating role of FNE in the relationship between autism stigma and camouflaging. They are also consistent with accounts of autistic individuals who camouflage to mitigate prejudicial biases (Zhuang et al., 2023). Moreover, our findings align with the literature indicating that tighter cultures are associated with a heightened sense of evaluation by others, promoting self-monitoring and behavioural mimicry (Baldwin & Mussweiler, 2018).

Given that FNE is a well-established mechanism of social anxiety (Rapee & Heimberg, 1997; Zhang et al., 2023), the statistically strong association between FNE and camouflaging may, to some extent, reflect a high degree of co-occurring social anxiety among our participants. Indeed, social anxiety is a common co-occurring mental health condition among autistic individuals (Spain et al., 2016, 2018). Furthermore, recent research has shown a strong positive association between camouflaging and social anxiety while also demonstrating construct overlap between camouflaging and social anxiety-related safety behaviours (Lei et al., 2024). Autistic people with greater FNE may, therefore, camouflage more to safeguard against potential adverse experiences and to cope with their social anxiety (Lei et al., 2024; Spain et al., 2020).

Consistent with our hypothesis, autistic adults with a stronger interdependent self-construal reported greater FNE and camouflaged more. In contrast, those with a stronger independent self-construal reported lower FNE and camouflaged less. Individuals with a stronger interdependent self-construal tend to value social harmony, likely increasing their FNE and motivation to camouflage to conform to social norms (Okawa et al., 2021; Tveleneva et al., 2023). Conversely, those with a stronger independent self-construal likely prioritise uniqueness and autonomy, likely reducing their FNE and motivation to conform (Okazaki, 1997; Torelli, 2006). Zhuang et al. (2023) discussed two potential trajectories involving continued camouflaging versus a shift from camouflaging towards disclosure and self-advocacy, which could be explained by self-construal differences. Autistic individuals with a stronger independent self-construal may be less concerned about social evaluations and have a greater desire to assert their individuality, thus being more inclined to utilise disclosure and self-advocacy instead of camouflaging. Conversely, those with a stronger interdependent self-construal may be more concerned with others’ judgements and motivated to camouflage to fit in. While disclosure and self-advocacy were not measured in this study, they are likely compatible with camouflaging and are not mutually exclusive pathways. Autistic individuals may select camouflaging, diagnostic disclosure and self-advocacy as goal-directed behaviours used in different contexts and settings to assert their agency in a non-autistic world (Zhuang et al., 2023).

Contrary to our hypothesis, the final mediation model showed a positive association between self-esteem and camouflaging. Interestingly, the zero-order correlation between self-esteem and camouflaging was negative (Table 2), albeit non-significant, so the change in direction and significance in the model suggests the presence of a suppressor effect. Ai et al. (2022) proposed two routes to camouflaging: one seeking positive experiences (‘voluntary self-enhancement’) and another avoiding negative experiences (‘compelled social modification’, p. 3). The variance in camouflaging explained by negatively-valenced psychosocial predictors (e.g. FNE, stigma, vulnerability events) may be related to ‘compelled social modification’, where marginalised autistic people feel compelled to camouflage for safety. After accounting for this variance, the remaining variance in camouflaging may be related to ‘voluntary self-enhancement’, showing a positive association with self-esteem. As part of ‘voluntary self-enhancement’, autistic people with higher self-esteem may assert agency by camouflaging for pragmatic purposes, such as accessing opportunities (Ai et al., 2022; Zhuang et al., 2023). This dynamic could create a reinforcing loop where the positive outcomes of camouflaging contribute to higher self-esteem, motivating continued camouflaging. Conversely, autistic adults in our study who perceived greater autism stigma reported lower self-esteem and, in turn, reduced camouflaging. Greater awareness of public stigma may lead autistic individuals to internalise stigmatising attitudes, resulting in self-stigma, lowered self-esteem and the ‘why try’ effect (Corrigan et al., 2009, 2016) – a sense of futility and diminished motivation to pursue goals. Given that camouflaging can be a goal-directed behaviour that is effortful and exhausting (Zhuang et al., 2023), autistic individuals experiencing the ‘why try’ effect may be less motivated to engage in ‘voluntary self-enhancement’ and camouflage less. These findings highlight the complex and dynamic interplay between camouflaging and psychosocial factors, providing insight into the intricacies of camouflaging decisions as autistic individuals weigh up the benefits and costs of camouflaging versus not camouflaging across different contexts.

Finally, another unexpected finding was that a stronger autistic identity was associated with increased camouflaging, both as a zero-order association and in the final mediation model. This finding contradicts Zhuang et al.’s (2023) conclusions, which suggested that a stronger autistic identity may contribute to reduced camouflaging. However, they align with Cage and Troxell-Whitman’s (2020) study demonstrating a positive relationship between camouflaging and a stronger autistic identity. Individuals with a stronger autistic identity may have a greater awareness of their autistic traits and related stigma, potentially motivating them to camouflage (Cage et al., 2022).

Strengths, limitations and future directions

A notable strength of our study lies in the examination of an integrated, comprehensive model encompassing various psychological and sociocultural predictors of camouflaging. This approach revealed unexpected associations between some of the psychosocial factors examined and camouflaging, such as the positive correlation between camouflaging and self-esteem in the final model, which would not have been revealed in simple zero-order correlations. This study’s findings support our understanding of camouflaging as a complex phenomenon with context-dependent motivations and pathways. We encourage future research to similarly adopt an integrated model approach to understanding camouflaging, so that a more comprehensive, in-depth understanding of complex influences and interactions can be achieved.

Our study also has several limitations. Considering the exploratory nature of our model and the use of trimming procedures in a single sample, our findings should be considered tentative. Our participants were self-selected and recruited online, introducing sampling bias and limiting the generalisability of our findings to the wider autistic population (Rødgaard et al., 2022). Most participants were female, White, employed, university-educated, without intellectual disabilities and received late autism diagnoses; thus, future studies should test our model in independent cohorts with more diverse characteristics.

Furthermore, several psychosocial measures used have not been specifically validated or developed for the autistic population. Moreover, our study was cross-sectional, so we could not test directional paths among variables. While factors such as FNE, vulnerability events and self-esteem may influence camouflaging, it is plausible that camouflaging also reinforces these psychosocial experiences. Prospective longitudinal studies are needed to clarify the nature and direction of the relationships between psychosocial factors and camouflaging.

While our study demonstrated that the hypothesised psychosocial factors predicted a substantial amount of variance in camouflaging (25%), a large portion of variance remains unexplained. Future studies could explore additional predictors of camouflaging, including psychosocial factors not investigated in our study but considered relevant by Zhuang et al. (2023) and Ai et al. (2022), such as social motivation and internalised stigma. Finally, future research should explore whether specific psychosocial motivations for camouflaging are associated with more positive or negative mental health outcomes, which may provide insights into mitigating any adverse effects on mental well-being. Specifically, studies can explore the link between camouflaging, FNE and social anxiety, given that autistic people, driven by FNE, may engage in camouflaging as a safety behaviour to cope with social anxiety, potentially perpetuating social anxiety in the long run (Lei et al., 2024; Spain et al., 2020).

Implications

Our findings underscore the impact of social and contextual factors, including social stigma and norms, on how autistic individuals perceive themselves and relate to others, influencing their engagement in camouflaging. Drawing on Bronfenbrenner’s (1992) ecological systems theory, a nuanced understanding of camouflaging acknowledges that it is shaped by the interplay between autistic individuals and their social environment, rather than stemming solely from their intrinsic traits (Ai et al., 2022). Applying the minority stress model, autistic people can be seen as an identity-based minority facing stigma-related stressors, including everyday discrimination, internalised stigma and camouflaging, which negatively affect mental well-being (Botha & Frost, 2020). Given our finding that camouflaging is strongly influenced by FNE, interventions aimed at shifting societal attitudes away from stigmatisation and towards acceptance and inclusion of autistic people may be important in reducing psychosocial pressures to camouflage.

While social change is crucial to alleviate pressure on autistic people to camouflage, cultural and societal shifts in attitudes take time. Consequently, until such shifts occur, camouflaging serves as a sophisticated set of strategies employed by many autistic individuals to navigate and negotiate their social realities. Despite its consistent links with poorer mental health (e.g. Beck et al., 2020; Hull et al., 2019, 2021; Zhuang et al., 2023), autistic individuals who do not camouflage or are ‘unsuccessful’ in doing so may risk exposure to adverse psychosocial responses, negatively impacting well-being (Lai, 2023). Beyond serving as a defensive response to stigma and social pressures, our findings suggest that camouflaging may also be a goal-directed behaviour used by some autistic individuals with higher self-esteem to assert their agency in a non-autistic world. Considering the complexities surrounding camouflaging motivations, professionals working with autistic people should aim to understand and explore individual reasons, contexts and functions of camouflaging and prioritise the agency and autonomy of autistic individuals in decisions about when, where, with whom and how to camouflage. Rather than encouraging autistic people to simply ‘drop their mask’ and stop camouflaging, professionals should support them in weighing the benefits and costs of camouflaging against alternative strategies, such as disclosure and self-advocacy across various contexts. Relatedly, psychosocial interventions should address external social factors contributing to camouflaging, such as bullying or stigmatising narratives, while supporting autistic individuals in choosing environments that suit their needs and provide a better person-environment fit.

Footnotes

Acknowledgements

We thank Mohammadali Amini-Tehrani and Jack Brett for their statistical support in analysing the data for this study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: S.Z. is funded by the University of Western Australia International Fee Scholarship and University Postgraduate Award. D.W.T. is supported by a Macquarie University Research Fellowship (MQRF0001113). In addition, this work is supported by a start-up grant awarded to IM (PG10301041) by the University of Western Australia.

ORCID iDs

Sici Zhuang

Mackenzie Bougoure

Diana Weiting Tan

Notes

References

Cunningham

W. A.

Lai

M.-C.

(2022). Reconsidering autistic ‘camouflaging’ as transactional impression management. Trends in Cognitive Sciences, 26(8), 631–645. https://doi.org/10.1016/j.tics.2022.05.002

Aktas

Gelfand

M. J.

Hanges

P. J.

(2016). Cultural tightness–looseness and perceptions of effective leadership. Journal of Cross-Cultural Psychology, 47(2), 294–309. https://doi.org/10.1177/0022022115606802

Baldwin

Mussweiler

(2018). The culture of social comparison. Proceedings of the National Academy of Sciences of the United States of America, 115(39), E9067–E9074. https://doi.org/10.1073/pnas.1721555115

Baranzini

(2018). The ‘bar procedure’: Single data-file compressing SPSS multiply imputed files. ResearchGate. https://www.researchgate net/profile/Daniele_Baranzini/publication/328887514_SPSS_Single_dataframe_aggregating_SPSS_Multiply_Imputed_split_ files/data/5be9a1cf299bf1124fce0d62/The-Bar-Procedure.docx

Beck

J. S.

Lundwall

R. A.

Gabrielsen

Cox

J. C.

South

(2020). Looking good but feeling bad: ‘Camouflaging’ behaviours and mental health in women with autistic traits. Autism, 24(4), 809–821. https://doi.org/10.1177/1362361320912147

Bentler

P. M.

(2006). EQS 6 structural equations program manual. Multivariate Software. https://www3.nd.edu/~kyuan/courses/sem/EQS-Manual6.pdf

Botha

Dibb

Frost

D. M.

(2022). ‘Autism is me’: An investigation of how autistic individuals make sense of autism and stigma. Disability & Society, 37(3), 427–453. https://doi.org/10.1080/09687599.2020.1822782

Botha

Frost

D. M.

(2020). Extending the minority stress model to understand mental health problems experienced by the autistic population. Society and Mental Health, 10(1), 20–34. https://doi.org/10.1177/2156869318804297

Bradley

Shaw

Baron-Cohen

Cassidy

(2021). Autistic adults’ experiences of camouflaging and its perceived impact on mental health. Autism in Adulthood, 3(4), 320–329. https://doi.org/10.1089/aut.2020.0071

10.

Bronfenbrenner

(1992). Ecological systems theory. In Vasta

(Ed.), Six theories of child development: Revised formulations and current issues (pp. 187–249). Jessica Kingsley.

11.

Bury

S. M.

Jellett

Spoor

J. R.

Hedley

(2020). ‘It defines who I am’ or ‘It’s something I have’: What language do [autistic] Australian adults [on the autism spectrum] prefer? Journal of Autism and Developmental Disorders, 53(2), 677–687. https://doi.org/10.1007/s10803-020-04425-3

12.

Byrne

B. M.

(2016). Structural equation modelling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge.

13.

Cage

Cranney

Botha

(2022). Brief report: Does autistic community connectedness moderate the relationship between masking and well-being? Autism in Adulthood, 4(3), 247–253. https://doi.org/10.1089/aut.2021.0096

14.

Cage

Troxell-Whitman

(2019). Understanding the reasons, contexts, and costs of camouflaging for autistic adults. Journal of Autism and Developmental Disorders, 49(5), 1899–1911. https://doi.org/10.1007/s10803-018-03878-x

15.

Cage

Troxell-Whitman

(2020). Understanding the relationships between autistic identity, disclosure, and camouflaging. Autism in Adulthood, 2(4), 334–338. https://doi.org/10.1089/aut.2020.0016

16.

Carleton

R. N.

Collimore

K. C.

Asmundson

G. J. G.

(2007). Social anxiety and fear of negative evaluation: Construct validity of the BFNE-II. Journal of Anxiety Disorders, 21(1), 131–141. https://doi.org/10.1016/j.janxdis.2006.03.010

17.

Carleton

R. N.

Collimore

K. C.

McCabe

R. E.

Antony

M. M.

(2011). Addressing revisions to the Brief Fear of Negative Evaluation scale: Measuring fear of negative evaluation across anxiety and mood disorders. Journal of Anxiety Disorders, 25(6), 822–828. https://doi.org/10.1016/j.janxdis.2011.04.002

18.

Carpenter

(2000). Effects of cultural tightness and collectivism on self-concept and causal attributions. Cross-Cultural Research, 34(1), 38–56. https://doi.org/10.1177/106939710003400103

19.

Chapman

Rose

Hull

Mandy

(2022). ‘I want to fit in. . . but I don’t want to change myself fundamentally’: A qualitative exploration of the relationship between masking and mental health for autistic teenagers. Research in Autism Spectrum Disorders, 99, Article 102069. https://doi.org/10.1016/j.rasd.2022.102069

20.

Cheng

Zhang

Ding

(2015). Self-esteem and fear of negative evaluation as mediators between family socioeconomic status and social anxiety in Chinese emerging adults. International Journal of Social Psychiatry, 61(6), 569–576. https://doi.org/10.1177/0020764014565405

21.

Christopher

M. S.

Skillman

G. D.

(2009). Exploring the link between self-construal and distress among African American and Asian American college students. Journal of College Counselling, 12(1), 44–56. https://doi.org/10.1002/j.2161-1882.2009.tb00039.x

22.

Cohen

(1988). Statistical power analysis for the behavioural sciences (2nd ed). Routledge. https://doi.org/10.4324/9780203771587

23.

Cohen

(1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155

24.

Cooper

Russell

A. J.

Lei

Smith

L. G.

(2022). The impact of a positive autism identity and autistic community solidarity on social anxiety and mental health in autistic young people. Autism, 27(3), 848–857. https://doi.org/10.1177/13623613221118351

25.

Cooper

Smith

L. G.

Russell

(2017). Social identity, self-esteem, and mental health in autism. European Journal of Social Psychology, 47(7), 844–854. https://doi.org/10.1002/ejsp.2297

26.

Cooper

Russell

A. J.

Smith

L. G.

(2020). ‘I’m proud to be a little bit different’: The effects of autistic individuals’ perceptions of autism and autism social identity on their collective self-esteem. Journal of Autism and Developmental Disorders, 51(2), 704–714. https://doi.org/10.1007/s10803-020-04575-4

27.

Corden

Brewer

Cage

(2021). Personal identity after an autism diagnosis: Relationships with self-esteem, mental well-being, and diagnostic timing. Frontiers in Psychology, 12, Article 699335. https://doi.org/10.3389/fpsyg.2021.699335

28.

Corrigan

P. W.

Bink

A. B.

Schmidt

Jones

Rüsch

(2016). What is the impact of self-stigma? Loss of self-respect and the ‘why try’ effect. Journal of Mental Health, 25(1), 10–15. https://doi.org/10.3109/09638237.2015.1021902

29.

Corrigan

P. W.

Larson

J. E.

Rüsch

(2009). Self-stigma and the ‘why try’ effect: Impact on life goals and evidence-based practices. World Psychiatry, 8(2), 75–81. https://doi.org/10.1002/j.2051-5545.2009.tb00218.x

30.

English

M. C. W.

Gignac

G. E.

Visser

T. A. W.

Whitehouse

A. J. O.

Enns

J. T.

Maybery

M. T.

(2021). The Comprehensive Autistic Trait Inventory (CATI): Development and validation of a new measure of autistic traits in the general population. Molecular Autism, 12(1), Article 37. https://doi.org/10.1186/s13229-021-00445-7

31.

Eriksson

Strimling

Gelfand

Abernathy

Akotia

C. S.

Aldashev

Andersson

P. A.

Andrighetto

Anum

Arikan

Aycan

Bagherian

Barrera

Batkeyev

Belaus

Berezina

Björnstjerna

Blumen

Van Lange

P. A.

(2021). Perceptions of the appropriate response to norm violation in 57 societies. Nature Communications, 12(1), Article 1481. https://doi.org/10.1038/s41467-021-21602-9

32.

Evans

J. A.

Krumrei-Mancuso

E. J.

Rouse

S. V.

(2023). What you are hiding could be hurting you: Autistic masking in relation to mental health, interpersonal trauma, authenticity, and self-esteem. Autism in Adulthood. https://doi.org/10.1089/aut.2022.0115

33.

Frost

D. M.

(2011). Social stigma and its consequences for the socially stigmatised. Social and Personality Psychology Compass, 5(11), 824–839. https://doi.org/10.1111/j.1751-9004.2011.00394.x

34.

Gelfand

M. J.

Raver

J. L.

Nishii

Leslie

L. M.

Lun

Lim

B. C.

Duan

Almaliach

Ang

Arnadottir

Aycan

Boehnke

Boski

Cabecinhas

Chan

Chhokar

D’Amato

Subirats

Fischlmayr

I. C.

Yamaguchi

(2011). Differences between tight and loose cultures: A 33-nation study. Science, 332(6033), 1100–1104. https://doi.org/10.1126/science.1197754

35.

Giacomin

Jordan

(2017). Interdependent and independent self-construal. In Zeigler-Hill

Shackelford

T. K.

(Eds.), Encyclopedia of personality and individual differences. (pp. 1–7). Springer.

36.

Gibbs

Hudson

Hwang

Y. I.

Arnold

Trollor

Pellicano

(2021). Experiences of physical and sexual violence as reported by autistic adults without intellectual disability: Rate, gender patterns, and clinical correlates. Research in Autism Spectrum Disorders, 89, Article 101866. https://doi.org/10.1016/j.rasd.2021.101866

37.

Gillespie-Lynch

Daou

Sanchez-Ruiz

Kapp

S. K.

Obeid

Brooks

P. J.

Someki

Silton

Abi-Habib

(2019). Factors underlying cross-cultural differences in stigma toward autism among college students in Lebanon and the United States. Autism, 23(8), 1993–2006. https://doi.org/10.1177/1362361318823550

38.

Gök

B. G.

Yalçınkaya-Alkar

. (2023). Clarifying the association of social anxiety with cognitive variables: The role of self-esteem, self-perception, fears of positive and negative evaluation, and post-event processing. Scandinavian Journal of Psychology, 64(3), 278–287. https://doi.org/10.1111/sjop.12886

39.

Griffiths

Allison

Kenny

Holt

Smith

Baron-Cohen

(2019). The Vulnerability Experiences Quotient (VEQ): A study of vulnerability, mental health, and life satisfaction in autistic adults. Autism Research, 12(10), 1516–1528. https://doi.org/10.1002/aur.2162

40.

Hannon

Mandy

Hull

(2023). A comparison of methods for measuring camouflaging in autism. Autism Research, 16(1), 12–29. https://doi.org/10.1002/aur.2850

41.

Hayes

A. F.

(2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76(4), 408–420. https://doi.org/10.1080/03637750903310360

42.

Bentler

P. M.

(1999). Cut-off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modelling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

43.

Hull

Levy

Lai

Petrides

K. V.

Baron-Cohen

Allison

Smith

Mandy

(2021). Is social camouflaging associated with anxiety and depression in autistic adults? Molecular Autism, 12(1), Article 13. https://doi.org/10.1186/s13229-021-00421-1

44.

Hull

Mandy

Lai

M. C.

Baron-Cohen

Allison

Smith

Petrides

K. V.

(2019). Development and validation of the Camouflaging Autistic Traits Questionnaire (CAT-Q). Journal of Autism and Developmental Disorders, 49(3), 819–833. https://doi.org/10.1007/s10803-018-3792-6

45.

Hull

Petrides

K. V.

Allison

Smith

Baron-Cohen

Lai

M. C.

Mandy

(2017). ‘Putting on my best normal’: Social camouflaging in adults with autism spectrum conditions. Journal of Autism and Developmental Disorders, 47(8), 2519–2534. https://doi.org/10.1007/s10803-017-3166-5

46.

Hurley

R. S.

Losh

Parlier

Reznick

J. S.

Piven

(2007). The broad autism phenotype questionnaire. Journal of Autism and Developmental Disorders, 37(9), 1679–1690. https://doi.org/10.1007/s10803-006-0299-3

47.

Kenny

Hattersley

Molins

Buckley

Povey

Pellicano

(2016). Which terms should be used to describe autism? Perspectives from the UK autism community. Autism, 20(4), 442–462. https://doi.org/10.1177/1362361315588200

48.

Kitayama

Salvador

C. E.

(2024). Cultural psychology: Beyond east and west. Annual Review of Psychology, 75(1), 495–526. https://doi.org/10.1146/annurev-psych-021723-063333

49.

Lai

(2023). Mental health challenges faced by autistic people. Nature Human Behaviour, 7(10), 1620–1637. https://doi.org/10.1038/s41562-023-01718-2

50.

Lai

M.-C.

Baron-Cohen

(2015). Identifying the lost generation of adults with autism spectrum conditions. The Lancet Psychiatry, 2(11), 1013–1027. https://doi.org/10.1016/S2215-0366(15)00277-1

51.

Leach

C. W.

Van Zomeren

Zebel

Vliek

M. L.

Pennekamp

S. F.

Doosje

Ouwerkerk

J. W.

Spears

(2008). Group-level self-definition and self-investment: A hierarchical (multicomponent) model of in-group identification. Journal of Personality and Social Psychology, 95(1), 144–165. https://doi.org/10.1037/0022-3514.95.1.144

52.

Lei

Leigh

Charman

Russell

Hollocks

M. J.

(2024). Understanding the relationship between social camouflaging in autism and safety behaviours in social anxiety in autistic and non-autistic adolescents. Journal of Child Psychology and Psychiatry, 65(3), 285–297. https://doi.org/10.1111/jcpp.13884

53.

Lewis

L. F.

(2017). A mixed methods study of barriers to formal diagnosis of autism spectrum disorder in adults. Journal of Autism and Developmental Disorders, 47(8), 2410–2424. https://doi.org/10.1007/s10803-017-3168-3

54.

Libsack

E. J.

Keenan

E. G.

Freden

C. E.

Mirmina

Iskhakov

Krishnathasan

Lerner

M. D.

(2021). A systematic review of passing as non-autistic in autism spectrum disorder. Clinical Child and Family Psychology Review, 24(4), 783–812. https://doi.org/10.1007/s10567-021-00365-1

55.

Loo

B. R. Y.

Teo

T. J. Y.

Liang

M. J.

Leong

D.-J.

Tan

D. W.

Zhuang

Hull

Livingston

L. A.

Mandy

Happé

Magiati

(2023). Exploring autistic adults’ psychosocial experiences affecting beginnings, continuity and change in camouflaging over time: A qualitative study in Singapore. Autism, 28(3), 627–643. https://doi.org/10.1177/13623613231180075

56.

MacKinnon

D. P.

Fairchild

A. J.

Fritz

M. S.

(2007). Mediation analysis. Annual Review of Psychology, 58(1), 593–614. https://doi.org/10.1146/annurev.psych.58.110405.085542

57.

Maitland

C. A.

Rhodes

O’Hare

Stewart

M. E.

(2021). Social identities and mental well-being in autistic adults. Autism, 25(6), 1771–1783. https://doi.org/10.1177/13623613211004328

58.

Mantzalas

Richdale

A. L.

Adikari

Lowe

Dissanayake

(2022). What is autistic burnout? A thematic analysis of posts on two online platforms. Autism in Adulthood, 4(1), 52–65. https://doi.org/10.1089/aut.2021.0021

59.

Mardia

K. V.

(1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530. https://doi.org/10.1093/biomet/57.3.519

60.

Mardia

K. V.

(1974). Applications of some measures of multivariate skewness and kurtosis in testing normality and robustness studies. Sankhyā: The Indian Journal of Statistics, Series B 1960-2002, 36(2), 115–128. http://www.jstor.org/stable/25051892

61.

Markus

H. R.

Kitayama

(1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98(2), 224–253. https://doi.org/10.1037/0033-295x.98.2.224

62.

Mason

Capp

S. J.

Stewart

G. R.

Kempton

M. J.

Glaser

Howlin

Happé

(2020). A meta-analysis of outcome studies of autistic adults: Quantifying effect size, quality, and meta-regression. Journal of Autism and Developmental Disorders, 51(9), 3165–3179. https://doi.org/10.1007/s10803-020-04763-2

63.

McDonald

T. A. M.

(2020). Autism Identity and the ‘lost generation’: Structural validation of the Autism Spectrum Identity Scale and comparison of diagnosed and self-diagnosed adults on the autism spectrum. Autism in Adulthood, 2(1), 13–23. https://doi.org/10.1089/aut.2019.0069

64.

Moscovitch

D. A.

Rowa

Paulitzki

J. R.

Ierullo

M. D.

Chiang

Antony

M. M.

McCabe

R. E.

(2013). Self-portrayal concerns and their relation to safety behaviours and negative affect in social anxiety disorder. Behaviour Research and Therapy, 51(8), 476–486. https://doi.org/10.1016/j.brat.2013.05.002

65.

Nguyen

Ownsworth

Nicol

Zimmerman

(2020). How I see and feel about myself: Domain-specific self-concept and self-esteem in autistic adults. Frontiers in Psychology, 11, Article 913. https://doi.org/10.3389/fpsyg.2020.00913

66.

Okawa

Arai

Sasagawa

Ishikawa

Norberg

M. M.

Schmidt

N. B.

Kwon

J.-H.

Rapee

R. M.

Shimizu

(2021). A cross-cultural comparison of the bivalent fear of evaluation model for social anxiety. Journal of Behavioural and Cognitive Therapy, 31(3), 205–213. https://doi.org/10.1016/j.jbct.2021.01.003

67.

Okazaki

(1997). Sources of ethnic differences between Asian American and White American college students on measures of depression and social anxiety. Journal of Abnormal Psychology, 106(1), 52–60. https://doi.org/10.1037/0021-843x.106.1.52

68.

Pearson

Rose

(2021). A conceptual analysis of autistic masking: Understanding the narrative of stigma and the illusion of choice. Autism in Adulthood, 3(1), 52–60. https://doi.org/10.1089/aut.2020.0043

69.

Pearson

Rose

Rees

(2022). ‘I felt like I deserved it because I was autistic’: Understanding the impact of interpersonal victimisation in the lives of autistic people. Autism, 27(2), 500–511. https://doi.org/10.1177/13623613221104546

70.

Perry

Mandy

Hull

Cage

(2022). Understanding camouflaging as a response to autism-related stigma: A social identity theory approach. Journal of Autism and Developmental Disorders, 52(2), 800–810. https://doi.org/10.1007/s10803-021-04987-w

71.

Qualtrics

X. M.

(n.d.). Fraud detection. https://www.qualtrics.com/support/survey-platform/survey-module/survey-checker/fraud-detection/#BotDetection

72.

Rødgaard

Jensen

Miskowiak

K. W.

Mottron

(2022). Representativeness of autistic samples in studies recruiting through social media. Autism Research, 15(8), 1447–1456. https://doi.org/10.1002/aur.2777

73.

Rapee

R. M.

Heimberg

R. G.

(1997). A cognitive-behavioral model of anxiety in social phobia. Behaviour Research and Therapy, 35(8), 741–756. https://doi.org/10.1016/s0005-7967(97)00022-3

74.

Romualdez

A. M.

Heasman

Walker

Davies

Remington

(2021). ‘People might understand me better’: Diagnostic disclosure experiences of autistic individuals in the workplace. Autism in Adulthood, 3(2), 157–167. https://doi.org/10.1089/aut.2020.0063

75.

Rosenberg

(1965). Society and the adolescent self-image. Princeton University Press. https://doi.org/10.1515/9781400876136

76.

Sasson

N. J.

Lam

K. S.

Childress

Parlier

Daniels

J. L.

Piven

(2013). The broad autism phenotype questionnaire: Prevalence and diagnostic classification. Autism Research, 6(2), 134–143. https://doi.org/10.1002/aur.1272

77.

Seers

Hogg

(2022). ‘Fake it ‘till you make it’: Authenticity and well-being in late diagnosed autistic women. Feminism & Psychology, 33(1), 23–41. https://doi.org/10.1177/09593535221101455

78.

Shtayermman

(2009). An exploratory study of the stigma associated with a diagnosis of Asperger’s syndrome: The mental health impact on the adolescents and young adults diagnosed with a disability with a social nature. Journal of Human Behaviour in the Social Environment, 19(3), 298–313. https://doi.org/10.1080/10911350902790720

79.

Singelis

T. M.

(1994). The measurement of independent and interdependent self-construals. Personality and Social Psychology Bulletin, 20(5), 580–591. https://doi.org/10.1177/0146167294205014

80.

Singelis

T. M.

Triandis

H. C.

Bhawuk

D. P.

Gelfand

M. J.

(1995). Horizontal and vertical dimensions of individualism and collectivism: A theoretical and measurement refinement. Cross-Cultural Research, 29(3), 240–275. https://doi.org/10.1177/106939719502900302

81.

Spain

Happé

Johnston

Campbell

Sin

Daly

Ecker

Anson

Chaplin

Glaser

Mendez

Lovell

Murphy

D. G.

(2016). Social anxiety in adult males with autism spectrum disorders. Research in Autism Spectrum Disorders, 32, 13–23. https://doi.org/10.1016/j.rasd.2016.08.002

82.

Spain

Happé

Johnston

Campbell

Sin

Daly

Ecker

Anson

Chaplin

Glaser

Mendez

Lovell

Murphy

D. G.

(2016). Social anxiety in adult males with autism spectrum disorders. Research in Autism Spectrum Disorders, 32, 13–23. https://doi.org/10.1016/j.rasd.2016.08.002

83.

Spain

Sin

Linder

K. B.

McMahon

Happé

(2018). Social anxiety in autism spectrum disorder: A systematic review. Research in Autism Spectrum Disorders, 52, 51–68. https://doi.org/10.1016/j.rasd.2018.04.007

84.

Spain

Zıvralı Yarar

Happé

(2020). Social anxiety in adults with autism: A qualitative study. International Journal of Qualitative Studies on Health and Well-being, 15(1), Article 1803669. https://doi.org/10.1080/17482631.2020.1803669

85.

Stamkou

van Kleef

G. A.

Homan

A. C.

Gelfand

M. J.

van de Vijver

F. J.

van Egmond

M. C.

Boer

Phiri

Ayub

Kinias

Cantarero

Efrat Treister

Figueiredo

Hashimoto

Hofmann

E. B.

Lima

R. P.

Lee

(2018). Cultural collectivism and tightness moderate responses to norm violators: Effects on power perception, moral emotions, and leader support. Personality and Social Psychology Bulletin, 45(6), 947–964. https://doi.org/10.1177/0146167218802832

86.

Torelli

C. J.

(2006). Individuality or conformity? The effect of independent and interdependent self-concepts on public judgements. Journal of Consumer Psychology, 16(3), 240–248. https://doi.org/10.1207/s15327663jcp1603_6

87.

Triandis

H. C.

(1989). The self and social behaviour in differing cultural contexts. Psychological Review, 96(3), 506–520. https://doi.org/10.1037/0033-295x.96.3.506

88.

Trundle

Jones

K. A.

Ropar

Egan

(2022). The forensic implications of camouflaging: A study into victimisation and offending associated with autism and pathological demand avoidance. Advances in Autism, 9(2), 116–131. https://doi.org/10.1108/aia-02-2022-0006

89.

Turnock

Langley

Jones

C. R. G.

(2022). Understanding stigma in autism: A narrative review and theoretical model. Autism in Adulthood, 4(1), 76–91. https://doi.org/10.1089/aut.2021.0005

90.

Tveleneva

Scholz

Yoon

Lieberman

M. D.

Cooper

O’Donnell

M. B.

Falk

E. B.

Cascio

C. N.

(2023). The relationship between agency, communion, and neural processes associated with conforming to social influence. Personality and Individual Differences, 213, Article 112299. https://doi.org/10.1016/j.paid.2023.112299

91.

Woods

A. D.

Gerasimova

Van Dusen

Nissen

Bainter

Uzdavines

Davis-Kean

P. E.

Halvorson

King

K. M.

Logan

J. A. R.

Vasilev

M. R.

Clay

J. M.

Moreau

Joyal-Desmarais

Cruz

R. A.

Brown

D. M. Y.

Schmidt

Elsherif

M. M.

(2023). Best practices for addressing missing data through multiple imputation. Infant and Child Development, 33(1), Article e2407. https://doi.org/10.1002/icd.2407

92.

Zhang

Mai

(2023). Fear of negative evaluation modulates the processing of social evaluative feedback with different valence and contexts. Cerebral Cortex, 33(8), 4927–4938. https://doi.org/10.1093/cercor/bhac390

93.

Zhuang

Tan

D. W.

Reddrop

Dean

Maybery

Magiati

(2023). Psychosocial factors associated with camouflaging in autistic people and its relationship with mental health and well-being: A mixed methods systematic review. Clinical Psychology Review, 105, Article 102335. https://doi.org/10.1016/j.cpr.2023.102335