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Extending the Minority Stress Model to Understand Mental Health Problems Experienced by the Autistic Population


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Research into autism and mental health has traditionally associated poor mental health and autism as inevitably linked. Other possible explanations for mental health problems among autistic populations have received little attention. As evidenced by the minority disability movement, autism is increasingly being considered part of the identities of autistic people. Autistic individuals thus constitute an identity-based minority and may be exposed to excess social stress as a result of disadvantaged and stigmatized social status. This study tests the utility of the minority stress model as an explanation for the experience of mental health problems within a sample of high-functioning autistic individuals (N=111). Minority stressors including everyday discrimination, internalised stigma, and concealment significantly predicted poorer mental health, despite controlling for general stress exposure. These results indicate the potential utility of minority stress in explaining increased mental health problems in autistic populations. Implications for research and clinical applications are discussed.
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Minority Stress in Autistic Populations - 1
Extending the Minority Stress Model to Understand Mental Health Problems Experienced by
the Autistic Population
Monique Botha* and David M. Frost
*Corresponding author
Monique Botha
University of Surrey
Botha, M. & Frost, D.M. (in press) Extending the Minority Stress Model to Understand
Mental Health Problems Experienced by the Autistic Population. Society and Mental Health
DOI: 10.1177/2156869318804297
Minority Stress in Autistic Populations - 2
Research into autism and mental health has traditionally associated poor mental health and
autism as inevitably linked. Other possible explanations for mental health problems among
autistic populations have received little attention. As evidenced by the minority disability
movement, autism is increasingly being considered part of the identities of autistic people.
Autistic individuals thus constitute an identity-based minority and may be exposed to excess
social stress as a result of disadvantaged and stigmatized social status. This study tests the
utility of the minority stress model as an explanation for the experience of mental health
problems within a sample of high-functioning autistic individuals (N=111). Minority
stressors including everyday discrimination, internalised stigma, and concealment
significantly predicted poorer mental health, despite controlling for general stress exposure.
These results indicate the potential utility of minority stress in explaining increased mental
health problems in autistic populations. Implications for research and clinical applications are
Minority Stress in Autistic Populations - 3
Extending the Minority Stress Model to Understand Mental Health Problems Experienced by
the Autistic Population
Over the last two decades, the meaning of the diagnosis of Asperger Syndrome (AS)
and High-functioning autism (HFA) has changed, with more autistic individuals considering
autism central to their identity as opposed to a disorder (Aylott 2000; Bagatell 2007; Elliman
2011). The vast majority of research into HFA/AS has tended towards researching the autism
spectrum through the biomedical model, specifically its aetiology and a possible cure
(Pellicano, Dinsmore, and Charman 2014) rather than recognizing HFA/AS as normal forms
of variation in human psychology. Less than 1% of autism research funding in both the
United States and the United Kingdom has gone into researching adults on the spectrum, nor
any social factors that may contribute to the high rates of mental health problems experienced
by people on the autism spectrum (Pellicano et al. 2014). Increasingly autistic people
themselves are beginning to consider AS and HFA a form of neurodiversity, and a key part of
their identity (Bagatell 2010; Kapp et al. 2013); as central as other social identities such as
their sexuality or race (Brown 2017). Under a minority model of disability, HFA and AS
represent a distinct socio-political experience as neurominorities with wide ranging diversity
(Altman 2001; Jaarsma and Welin 2012). ‘Neurominority’ is a relatively new term coined to
describe those who fall under the neurodiverse model (Walker 2012). This study will
examine how stress related to social stigma (e.g., Frost 2011) contributes to heightened rates
of mental health problems experienced by the autistic community. We highlight the utility of
social stress models (Meyer 2003; Meyer, Schwartz, & Frost, 2008) in understanding mental
health and wellbeing in autism.
Minority Stress in Autistic Populations - 4
Autism as identity
The biomedical model aims to cure disability (Rioux, Bach, and Roeher Institute 1994).
Understanding disease from this model is only logical considering the need to treat and cure
life threatening illness, however, it creates tension when considering disorders such as
autism, dyslexia, and dyspraxia (Ward and Meyer 1999). The biomedical model relies on
identifying disease and creating meaningful interventions to cure the person who is suffering
(Bagatell 2010; Rioux et al. 1994). The traditional idea of autism is one in which a person
does suffer (Kanner 1971). Viewing autism from a biomedical model has been opposed as it
leads to dehumanizing research and treatment of autism (Tyler Cowen 2009). For example, it
has been claimed that an autistic community cannot exist due to a central tenant of autism- a
lack theory of mind, meaning autistic individuals are too introspective to want to or be able to
form community connections (Barnbaum 2008). Similarly, it has resulted in work where they
are compared less favourably to brain damaged monkeys (Bainbridge 2008). The minority
model of disability formed partly as opposition to these notions.
The rise of the minority model of disability specifically challenged the medical model’s
notions of disability (Rioux et al. 1994; Smart 2006). The minority model of disability is
underpinned by the notion that one can have something the medical model considers a
disability, but in actuality, it is a society with restrictive notions of normal that creates
disability (Altman 2001; Smart 2006). The Deaf community is an example of a community
considered disabled by the medical model, and who reject that status, considering themselves
to be a cultural group defined by the use of sign language (Smart 2006). The Autism Network
International was the first self advocacy group created by and for autistic individuals, in part
to combat the biomedical view of autism (Ward and Meyer 1999). Narratives of autistic self-
advocacy are challenging the notions put forward from the biomedical model, and under the
banner of neurodiversity, claiming minority status (Kapp et al. 2013).
Minority Stress in Autistic Populations - 5
Individuals who are affected have come to consider autism an intrinsic part of an identity
(Bagatell 2010; Kapp et al. 2013). In fact, autism is sometimes as central to the identity of
autistic individuals as race, ethnicity, sexuality, gender or nationality (Brown 2017), a claim
often put forward by the Neurodiversity movement (Neurodiversity itself falling under a
minority model). Thus, the minority model of disabilities may provide a basis on which
autistic individuals can consider themselves within their own terms, and with dignity (Dunn
and Andrews 2015). It has even been proposed that those with AS and HFA form an ethno-
cultural minority akin to the Deaf community (Jaarsma and Welin 2012).
Thus, in the last two decades, what bio-medical researchers originally considered a
disorder, has come to be a central feature of identity to some. Therefore, it is important to
understand whether these minority identities leave autistic individuals vulnerable to the extra
social stresses suffered by other minority communities as a result of social stigma and
disadvantaged social status. Similarly,
Stigma as Stress Resulting from Labelling Processes
The process by which stigmatization occurs begins with the process of labelling. A
label is a definition, which categorizes a person by his or her characteristics (Link and Phelan
1999). Labelling in the case of AS/HFA involves a comparison of autistic individuals against
their non-autistic peers and the assignment of meaning to those differences (Bagatell 2010;
Elliman 2011; Hacking 2012). Most adults with HFA/AS will be aware of the differences
between themselves and those not on the autism spectrum (Aylott 2000). Being aware of
these differences is not an issue, until a value is assigned to them; whether it is perceived as a
positive, neutral or negative difference. Labels absorb the meaning society gives them and
thus, assigning value-based meanings to labels can often perpetuate stigma (Link and Phelan
1999); for example, a stereotype attached to autism is “loner” (Aylott 2000). In a study
investigating the stereotypes non-AS peers held towards autistic individuals, 9 of the top 10
Minority Stress in Autistic Populations - 6
terms used to describe AS individuals were negative (Wood and Freeth 2016). A separate
study found the behaviours central to autism were stigmatized (Butler and Gillis 2011).
The effects of stigma can be long lasting, and limit the quality of life available to the
stigmatized group (Markowitz 1998). A two year study on mental health and stigma showed
that exposure to stigma designated the self-worth individuals afforded to themselves
(Wright, Gronfein, and Owens 2000). Considering 9 out of 10 stereotypes afforded to autism
are negative, there is the possibility of high exposure to stigma. Similarly, that this exposure
has similar consequences.
The stigma afforded to autistic individuals likely explains why multiple studies have
found a high risk of victimisation in the HFA/AS community; including physical, verbal, and
sexual victimisation across the life-span from childhood (Little 2002), to adulthood
(Rosenblatt and National Autistic Society 2008). Similarly, autistic individuals are more
likely to face workplace discrimination in terms of unfair dismissal, workplace harassment,
underemployment, and unemployment (Baldwin, Costley, and Warren 2014; Barnard et al.
2001; National Autistic Society 2012). Social rejection can also be internalized and self-
perpetuating. For example, as a result of experiences of rejection, neurominorities may
become embroiled in a negative self-concept, built upon the foundation of social rejection
(Link et al. 1989). While the previously discussed research into victimisation and
discrimination documents high rates of exposure among autistic populations, researchers
have yet to focus on the impact of victimisation on the wellbeing of autistic individuals.
The Potential Utility of Minority Stress Theory
The primary aim of the minority stress model is to explain disparities in health
between majority and stigmatized minority groups (Meyer 2003). Social stress theory hinges
on the idea that social disadvantage can translate into health disparities (Schwartz and Meyer
2010). Researchers hypothesize that decreased social standing leads to stigmatized minority
Minority Stress in Autistic Populations - 7
groups being exposed to more stressful life situations, with simultaneously fewer resources to
cope with these events. Social structure facilitates this process through acts of discrimination
and social exclusion, which are added stress burdens that socially advantaged groups are not
equally exposed to.
The minority stress model has most frequently been used to explain both mental and
physical health disparities (Meyer 2003). Studies have consistently shown sexual minorities
to have higher stress burdens, while simultaneously experiencing higher rates of poorer
physical and mental health (Frost, Lehavot, and Meyer 2015; Herek, Gillis, and Cogan 1999;
Meyer 2003; Meyer and Dean 1998); Cochran and Mays 2000; Gilman et al. 2001; Herek et
al. 1999; Zietsch et al. 2011). To a lesser degree, the minority stress model has been used to
highlight disparities in added stress and negative health outcomes in African-American
populations (Feagin 1991; R. Williams and Williams-Morris 2000). Most pertinently for the
study at hand, minority stressors have also been shown to impact on the severity of
depressive symptoms experienced by those with physical disabilities (Brown 2017).
Four premises underpin the minority stress model. The first premise is that not all
differences are discrepancies; an increase, for example, of certain illnesses with age, is a
difference to be expected and is therefore not a discrepancy (Schwartz and Meyer 2010). The
second premise is that the theory is based on the law of averages, and average effects.
Although it is hypothesized that the social disadvantage influences the group in the entirety if
a subgroup remains unaffected it does not falsify the overall theory (Schwartz and Meyer
2010b). The third premise is that the social stress theory applies causally to overall health
rather than specific disorders. The fourth premise is that social stress theory is specifically
about the sociological category of disadvantage produced by exclusionary social hierarchies,
rather than anything specific about that group (Schwartz and Meyer 2010). In essence, the
social group is devalued based on societal norms, thus, being in keeping with the minority
Minority Stress in Autistic Populations - 8
model of disability, which posits that disability (and co-morbiding psychological outcomes)
stem from an inflexible society which has a preference for non-disabled individuals (Smart
2006). As shown in the paragraph above, support for this is shown by Brown (2017) who
demonstrates the utility of understanding perceived stigma and coping in populations with
physical disabilities, and how it may enhance our understanding of mental health outcomes.
Meyer and Schwartz discuss that it is unreasonable for any researcher to extend the
model where there is no existing documentation for disparities between populations
(Schwartz and Meyer 2010). A health disparity exists between autistic and non-autistic
individuals, with those on the spectrum regularly found to have higher rates of physical and
mental health problems (Baldwin and Costley 2016; Baldwin et al. 2014; Gillberg et al. 2016;
Hirvikoski et al. 2016; Kamio, Inada, and Koyama 2013; Locke et al. 2010; Shefcyk 2015).
A recent study showed an elevated risk of premature mortality for autistic individuals by on
average two decades compared to non-autistic peers (Hirvikoski et al. 2016). The
predominant cause of early death in HFA/AS was suicide (Hirvikoski et al. 2016). Rates of
depression, suicidality, PTSD, and poorer mental health are all higher in autistic populations
than non-autistic populations (Gillberg et al. 2016; Kerns, Newschaffer, and Berkowitz 2015;
McManus 2009; Mikami et al. 2009).
Current Study
Applying the minoity stress model to understaning social factors relevant to health in
the context of HFA/AS could begin to account for the additional stress burden faced by the
autistic community, and potentially redefine what is known about autism and psychological
wellbeing. The current study extended the minority stress model to examine the extent to
which stigma-related stressors are associated with diminished wellbeing experienced by the
HFA/AS population. We hypothesized that there would be a relationship between minority
stressors and poorer mental health outcomes, such that greater amounts of reported minority
Minority Stress in Autistic Populations - 9
stress would be associated with poorer mental health and wellbeing. In testing the potentially
unique contribution that minority stress makes to mental health among HFA/AS individuals,
we further hypothesized that associations between minority stress and mental health and
wellbeing outcomes would persist above and beyond the contribution of general stressful life
events known to impact the health of everyone, regardless of disadvantaged social status
(Frost et al, 2015).
An online survey was used to test the current study’s hypothesis. Conducting the
study using the internet allowed for a method consistent with the way in which autistic
individuals communicate regularly; it has been noted that the internet allows for
communication unfettered by social interaction (Bagatell 2010; Benford and Standen 2009;
Hacking 2012; Jordan 2010). The survey, which is detailed below was circulated to autistic
individuals via the Qualtrics survey system. Inclusion criteria were a minimum age of 18 and
to consider oneself autistic. An official diagnosis was not necessary to participate. This
decision was made in order to ensure that those who have been unable to access a diagnosis
due to cost or personal circumstance, but still feel part of the autistic community, could
participate (as has been done in other studies e.g. Kapp et al. 2013).
A total of 142 participants completed the survey. All participants that had extensive
missing data (i.e., multiple variables were missing data) were removed (n= 31), resulting in a
final sample of N = 111 participants. Table 1 presents the demographic information for the
final analytic sample. Potential demographic limitations (e.g. gender) are discussed later.
A survey was developed using the measures described below to assess minority stress
experiences in the autistic community. Non-probability sampling techniques were used.
Minority Stress in Autistic Populations - 10
Recruitment was conducted within the following online groups: Aspergers Reality, Autistic
Women's Association, The Aspie Cloud, Asperger Safe Room, Adults with Asperger
Syndrome, Wrong Planet, Neurodiverse UK, Autism Action NZ, Autism Worldwide,
Autistics UK, and Heart for Autism. It was distributed to AS/HFA community pages with
permission from community moderators. Sampling evolved into a snowball technique as
participants referred other people from outside these groups to the survey. After each
participant had consented they completed a 14-minute survey, with the chance of winning a
£50 voucher to a popular online retailer. This research received a favourable ethical opinion
from the University of Surrey ethics committee prior to the commencement of data
Demographic information. Participants reported their gender, age, and ethnicity.
The options presented for gender were ‘male’, ‘female’, and ‘other. Where a participant
selected other, they were asked for a perscriptor of gender they felt comfortable with. Age
was reported by participants in a numerical entry box in the survey. Ethnicity was recorded in
line with British census categories (as the research was primarily based in Britain). If none of
the categories presented were relevant, participants could select the ‘other’ box, and were
consequently asked to provide a descriptor for their ethnicity and race. Diagnosis was self-
reported, with participants reporting if they had an official diagnosis, and, if so, providing the
details of it following the procedure used in Kapp et al. (2013).
General stressful life events. (Adapted from Slopen et al. 2011) The stressful life
events inventory was used to assess the impact of stressful life events on wellbeing. The
inventory is a ‘yes/no’ inventory. The measure is not related to minority stress, but rather
general life stress. The measure was coded in such a way that higher scores reflected more
Minority Stress in Autistic Populations - 11
stressful life events in the 12 months prior to taking the survey. Questions included items
such as ‘you recently ended a long-term relationship’.
Victimisation and discrimination events. (Cronbach’s alpha = 0.72, 8-items).
Victimisation and discrimination measured the extent to which participants have faced
discriminatory events in the last 12 months. The scale is on four points from never (0) to
three times or more (3). Scores were coded (summed) in a way that higher scores reflected
higher frequencies of victimisation and discrimination. Questions included items such as ‘you
were hit, beaten, physically attacked, or sexually assaulted.
Everyday discrimination. (Williams et al. 1997; Cronbach's alpha = .87, 8-items).
Experiences of everyday discrimination were measured with the everyday discrimination
scale, which specifically measures covert discrimination. The measure used a four-point scale
from often (3) to never (0) and asked questions such as ‘in your day-to-day life over the past
year, how often did any of the following things: People acted as if they thought you were not
smart’. The scale was coded (summed) in a way that higher scores reflected greater everyday
Expectation of rejection. (Meyer, Schwartz, & Frost 2008; Link 1987; 6 items,
Cronbach’s alpha = 0.90). Experiences of expecting rejection were measured using the
‘Expectation of Rejection’ scale. It asked you to consider your disability, gender race, and
then presented items such as employers will not hire a person like you’. Participants
responded on a scale that ranged from strongly agree (4) to strongly disagree (0). Scores were
coded (summed) so that higher scores reflected a higher expectation of rejection.
Outness. (Adapted from Meyer et al. 2002; Cronbach's alpha = 0.71; 4- items). The
outness scale measured the degree to which people on the spectrum disclosed to peers,
colleagues, non-autistic friends, healthcare providers or family. Responses scaled from out to
all (4), to out to none (1) The scale was coded (summed) so that higher scores reflected
Minority Stress in Autistic Populations - 12
higher outness. The wording of ‘outness’ was still used with regards to autism and disclosure
because it is a term the community has adopted to describe disclosure (Jones, n.d.).
Physical concealment. (Cronbach’s alpha = 0.83, 5 items). The physical concealment
scale was designed specifically to measure the extent to which participants physically conceal
behaviours associated with autism. It asked participants to recall whether they had had certain
experiences in the last 12 months. The measure contained questions such as ‘I have
purposefully avoided disclosing being autistic on official documents (job applications etc.)’.
Participants responded on a scale from never (0) to always (3) The measure was coded
(summed) in such a way that higher scores reflected higher behavioural concealment.
Internalized stigma. (Adapted from Meyer and Dean 1998; Cronbach’s alpha =0.84;
8 items). Used in an adapted format (specific to autism) to measure the extent to which
individuals reject their status on the autism spectrum. It had questions such as ‘you have felt
alienated from yourself because of being on the Autism Spectrum’. It contained adjusted
questions, of which the language was changed to relevant terms, but the concept remained the
same. It also added two novel questions addressing certain unique aspects of HFA/AS. It was
measured on a scale from strongly disagree (1) to strongly agree (5). It was coded (summed)
in a way in which higher scores reflect more intense feelings of internalized stigma with
regards to being autistic.
Wellbeing. (Keyes et al. 2008) The mental health continuum (MHC) was used in its
three subscales; social (5 items), emotional (3 items) and psychological (6 items) wellbeing,
with respective alpha ratings of .84, .91 and .87. The subscales were used individually to
capture quintessential aspects of various forms of wellbeing (social, emotional and
psychological) and examine how different forms of wellbeing inter-related to minority stress
variables. They were coded (summed) in a way that lower scores reflected poorer wellbeing.
Minority Stress in Autistic Populations - 13
Psychological distress. (Kessler, 2003; Cronbach’s alpha = 0.84) The psychological
distress scale (K6) was originally developed by the US department of national health
statistics. The K6 was designed to be sensitive around clinical thresholds for mental health
disorders, with the short form (6 item) being as sensitive as the ten-item survey (Wittchen
2010:10). Items on it included ‘how often during the past month did you feel… nervous?
…fidgety? …worthless?’. The response scale ranged on five points from all the time, to none
of the time. It was coded (summed) in such a way that higher scores reflected higher
psychological distress.
Descriptive and Bivariate Analyses
SPSS 24 was used to conduct all analysis. Chi-Square tests were carried out to
identify whether any differences of note (gender, ethnicity, autism type, age of diagnosis, age
of identifying as autistic, diagnosis status, autistic symptoms, and mental health outcome
variables) existed between those included and those excluded, however, none were detected;
(p ≥.082). Where there was a single missing value per case, the mode was computed and
input; there were only 25 values missing across all cases, and exclusion from the sample
based on one missing value would be extreme (all means and standard deviations can be
found in Table 2).
Data were examined to identify whether distributions met parametric standards. All
variables were normally distributed apart from victimisation and discrimination, which was
skewed. To correct for skewness, this variable was transformed into a binary variable
(Walters 2009). The variable was divided on the basis of exposure the specific items of the
inventory: no exposure = 0; any exposure = 1.
Bivariate analyses are presented in (Table 2). Correlations of variables raised some
concern regarding multicollinearity with independent variables having medium to high
Minority Stress in Autistic Populations - 14
correlation. Regression models with diagnostic information for multicollinearity were
performed to further examine multicollinearity. Variance inflation factor scores (VIF) were
all below 2, originally suggesting little to no multicollinearity. However, upon further
inspection multicollinearity was identified within eigen values (.01), condition indexes
(≥15), and variance proportion scores (≥.85). Theoretically, it is likely that minority stressors
may not be independent, but rather have a relation to each other, causing multicollinearity. In
order to address this issue, ridge regression (RR) was used to test the study hypotheses.
RR is an extension of linear regression. When there is a problem with multi-
collinearity, RR can be preferable to ordinary least squares (OLS) regression (Helwig 2017;
Jacobucci, Grimm, and McArdle 2016; McNeish 2015). This is because OLS regression
performs poorly with highly correlated variables, or where there are many predictor variables
as it causes large prediction intervals, making the model uninterruptable (Helwig 2017).
Ridge regression has been shown to be more effective at providing accurate results than other
forms of non-penalised regression (OLS, stepwise etc.) when multicollinearity is present
(Abram et al. 2016; Eledum 2016; Firinguetti, Kibria, and Araya 2017; Zhang and Ibrahim
2005). Introducing a small increase in bias can result in a large decrease in prediction error.
It is a process of trade-off between bias and variance (Marquaridt 1970). The small ‘penalty’
(λ) on the OLS estimators will reduce the variability of the estimators, making them more
stable, easier to interpret, and more likely to transfer to new samples (Helwig 2017).
Penalized regression has been highlighted as a good tool available to psychologists to
increase the replicability of their research (Helwig 2017). Thus RR was chosen as the
appropriate statistical method to approach the data with.
The penalty coefficient ranges from 0 (no penalty) to 1, on a .01 increment (Helwig
2017). The higher the penalty terms, the less variance, but also the smaller the beta
coefficients. As such, it is a process of balancing. SPSS uses an iterative approach, which
Minority Stress in Autistic Populations - 15
runs multiple versions of the model using different penalties to find that which best balances
bias, variance, and error. Using either cross validation or bootstrap .632 method of
resampling is standard practice when using RR (hence it is built into SPSS as part of the RR
algorithm) (a comprehensive explanation of the .632 method can be found in Efron and
Tibshirani 1997). This paper uses the .632 estimator bootstrap method, as research has shown
it to be more reliable (Efron and Tibshirani 1997; Linting et al. 2007). A randomised
selection of fifty different cases were included in each iteration (with 1000 iterations run),
and a mean standard error (MSE) computed from that. Similarly, the estimate of standard
error on the standardized coefficients was calculated using bootstrapping with 1000 samples.
This acts as a form of confidence intervals on the standardized beta coeeficients. No
unstandardized betas are calculated because standardization of all variables is undertaken
before RR is computed.
The demographics used in the analysis (ethnicity, gender, diagnosis status) were
included as binary variables. They were coded into majority/minority cases (as seen in
Meyer, Schwartz, and Frost 2008). Gender was coded as male 1, female and other 2.
Ethnicity was coded as White British, other White 1, mixed/multiple, Black British, Asian,
and other 2. Having a diagnosis was coded as 1, while no official diagnosis was coded as 2.
Codes used were 1 and 2 as the ridge regression function in SPSS reads 0 as missing data.
Similarly, due to this same issue, cases where a variable computed to a true 0 had to be
recoded, as advised by the software manual (IBM n.d), to a very small non-0 value (1×10-6).
This allowed it to be included in the analysis without adverse consequences on the result.
Results of Ridge Regression Analyses
The results of RR models predicting each of the mental health and wellbeing
outcomes are shown in Table 3.
Minority Stress in Autistic Populations - 16
The regularization penalty applied to the social wellbeing model was λ=.12. Social
wellbeing was significantly predicted by the behavioural concealment of autism, and
expectation of rejection. The model accounted for 58% of the variance in social wellbeing
F(38,72)=2.55, p<.001, R²=.58, MSE=.87. The significant standardized coefficients showed
that lower levels of social wellbeing were associated with higher levels of expectation of
rejection and behavioural concealment of autism. Gender was also associated with social
wellbeing; however, the sample size difference between men and women (and other), meant
this could not be explored further.
The regularization penalty applied to the emotional wellbeing was λ=.12. Emotional
wellbeing was significantly predicted by internalised stigma and diagnosis status. The model
accounted for 48% of the variance in emotional wellbeing, F(32, 78)=2.40, p=.001, R²=.48,
MSE=.89. The significant standardized coefficients indicated that lower levels of emotional
wellbeing were associated with higher levels of victimisation and discrimination, everyday
discrimination, expectation of rejection and internalised stigma.
The regularization penalty applied to the psychological wellbeing model was λ=.26.
Psychological wellbeing was significantly predicted by expectation of rejection, outness,
stressful life events and everyday discrimination. The model accounted for 58% of the
variance in psychological wellbeing F(32, 78)=3.57, p=.000, R²=.57, MSE=.85. The
significant standardized coefficients indicated that lower levels of psychological wellbeing
were associated with higher levels of victimisation and discrimination, everyday
discrimination, expectations of rejection, and outness. Psychological wellbeing was also
associated with ethnicity. The difference based on ethnicity could not be explored as the size
of the sample differed too extremely.
The regularization penalty applied to the psychological distress model was λ=.22.
Psychological distress was significantly predicted by everyday discrimination, expectation of
Minority Stress in Autistic Populations - 17
rejection, outness, internalised stigma, and diagnosis status, the model accounted for 72% of
the variance of psychological distress F(36, 74)=6.15, p<.001, R²=.72, MSE=.73. The
significant standardized coefficients indicated that higher levels of psychological distress
were associated with higher levels of everyday discrimination, expectation of rejection,
outness, and internalised stigma, and having a diagnosis status.
The aim of this study was to investigate the utility of the minority stress model in
understanding how stigma-related stressors contribute to mental health and wellbeing
problems in the autistic population. Originally designed to investigate sexual minorities and
ethnic minorities; the minority stress model (Meyer 2003) has provided a novel way to
consider the experience of being HFA/AS. The findings suggest that autistic individuals
experience an added stress burden in the form of minority stress. This stress burden is a
potentially preventable factor in the mental health and wellbeing disparity seen in the autistic
population. Minority stressors such as victimisation and discrimination, everyday
discrimination, expectation of rejection, outness, internalised stigma, and physical
concealment of autism consistently predicted diminished wellbeing and heightened
psychological distress.
Thus, these findings provide the first, albeit preliminary, support that the minority
stress model can be usefully extended to understand mental health and wellbeing problems
faced by the HFA/AS population in that greater exposure to minority stressors are associated
with poor mental health and wellbeing. Even further, it is important to note that these
associations between minority stressors and mental health indicators persisted above and
beyond the effect of general life stress and other demographic factors known to be associated
with health and wellbeing (e.g., gender, race/ethnicity). Thus, these findings support previous
Minority Stress in Autistic Populations - 18
research indicating that minority stress has a unique and additive negative effect on health,
which is not reducible to general stress alone (Frost et al. 2015).
Everyday discrimination was highly positively correlated with the expectation of
rejection, which is something that should be investigated further. With each small act of
discrimination it would, theoretically, make sense that expectations of rejection would
increase. This association between smaller events of discrimination and the expectation for
rejection is a sentiment that previous papers have expressed (Link and Phelan 1999; Stucky et
al. 2011).
Outness, in the case of HFA/AS, was associated with poorer mental health in the form
of lower psychological wellbeing and higher psychological distress. These findings run
contrary to some findings from research on outness and wellbeing among sexual minorities,
which indicate outness is beneficial for wellbeing (Daley 2010; Legate, Ryan, and Rogge
2017). A potential explanation for this discrepancy is that when HFA/AS individuals
disclose their status on the spectrum it opens them up to more acts of discrimination. Within
the minority stress literature the safeness of the environment is taken into account; in one
situation outness may be therapeutic and in another, outness could be considered a risk (di
Bartolo 2013). Such situational differences are highlighted by the ‘Don’t Ask, Don’t Tell’
(DADT) policy that was for a time implemented in the US armed forces (Davis 2010), where
outness of LGBT status threatened one’s career and safety within the army. The DADT
policy affected the mental health of soldiers whether or not they disclosed, but more so when
they did (Barber 2012). The potential wellbeing detriment of disclosure in autism could
represent the effect of social punishment for being outside of the expected norm of
neurotypicality. As previously discussed, the rate of unfair dismissal and bullying in the
workplace is high for HFA/AS individuals (Baldwin et al. 2014). As tolerance and
acceptence for neurodiversity and the autistic population increases, the direction of the
Minority Stress in Autistic Populations - 19
relationship between outness and mental health may change. While others have postulated
that openness may reduce stigma (Corrigan, Kosyluk, and Rüsch 2013) the present results
indicate that it can also be a factor in reduced wellbeing for the person ‘coming out’.
Eventually it may also represent a therapeutic process that will correlate with lower
internalised stigma and better mental health as it does currently with LGBT communities in
most Western situations (di Bartolo 2013).
Similarly, labelling theory (Link & Phelan 1987) may also explain why outness
decreases mental health and wellbeing; post diagnosis, certain labels are attached to the
individual and stereotypes often attached to autism are rarely positive, with 9 of 10 being
derogatory (Wood and Freeth 2016). However, there was a significant negative relationship
between psychological distress and diagnosis, with higher distress experienced among those
with a diagnosis. Increased expectation of rejection in the diagnosed group may reflect the
stigma that comes from having a proper diagnosis, or the stress of then having to hide this
aspect of the self.
Clinical Implications
In light of the results, the findings of this study, if upheld in further research, could
mark a change in the way we consider mental health and wellbeing in the autistic community.
Previously, poor quality of life (Barnbaum 2008; Kamio et al. 2013) has been intrinsically
linked with autism, without the consideration that negative social factors (i.e., minority
stress) may play a part in the wellbeing disparity experienced by autistic individuals. In
Kamio et al. researchers investigating suicidal ideation in those on the spectrum found that
three-quarters of their sample had suffered from bullying, yet still attributed suicidal ideation
to the characteristics of autism (2011). This research has expanded the focus to include the
wider implications of discrimination on members of the autistic community. These findings
may shed light on the experience of autistic individuals in society and highlight the
Minority Stress in Autistic Populations - 20
consequences of the discrimination and victimisation highlighted in other research; for
example, increased employment discrimination, sexual victimisation, bullying, isolation and
homelessness (Baldwin and Costley 2016; Brown-Lavoie, Viecili, and Weiss 2014; Carter
2009; Heinrichs and Myles 2003; Homeless link 2014). This reframing of perspectives on
autism can reflect a movement in which mental health problems such as depression, anxiety,
and suicidal ideation are no longer considered inherent to autism (as in Kamio et al. 2013).
Limitations and Directions for Future Research
A possible limitation of the study is the translation of the measures from one minority
community to another. While some of the measures were created for use with all minorities
(expectation of rejection and everyday discrimination), others were originally designed for
use with sexual minority communities and needed to be translated specifically for this study
(outness and internalised stigma). The unique aspects of the autistic community may not have
been reflected in these measures, and, rather than changing the language of existing
measures, attempts need to be made to design new assessments of the unique qualities of the
autistic experience ‘from the ground up.
Women were disproportionately represented in the study, which may decrease the
generalizability of these findings. However, this is something that frequently happens in
reverse, with males being overrepresented in autism research. The present sample could
reflect the frustration that autistic females feel at the usual exclusion from research
(Rynkiewicz et al. 2016; Shefcyk 2015). It is important to note that gender was controlled
for in all analyses in order to partially account for this limitation. Future research needs to
investigate the potential additive effects of multiple minority identities, such as being both
autistic and an ethnic minority to see whether there are effects related to ‘double
discrimination’ (as suggested by Grollman) (Grollman 2014). Similarly, other research
(Brown 2014) has found a gender difference in the effects of perceived social devaluation on
Minority Stress in Autistic Populations - 21
mental health (albeit of physical disability), which might explain gender affecting social
wellbeing in these results. A more in-depth analysis of that effect in a sample balanced for
gender is needed.
It may be important to understand the relationship that everyday discrimination has on
expectations of rejection and the place of labelling theory within the experiences of
discrimination and expectation of rejection. This would require longitudinal research to
understand the causal and cyclical relationships between these aspects of the minority stress
experience. Such research has the potential to provide a better understanding of minority
stress as the dynamic and situational model that it is theorized to be. Similarly, more research
could be done on the meaning of diagnosis to unpick the relationship it has with the autistic
person being labelled, and the societal context and perception of that label.
The prospects for future research stemming from this article are numerous. This
study found increased exposure to minority stress was associated with poorer wellbeing
within an autistic sample. By carrying out within-group analysis we can understand the
impact of the actual social stress (Schwartz & Meyer 2010a). It provides an opportunity to
understand the effect of exposure to minority stress on wellbeing in the autistic population.
Every individual within the group may experience the process of social stress to different
degrees. A between group study is also needed however, to fully test the full minority stress
Finally, although the present study contributes to the intergration of disability and
stress literature (by demonstrating a clear relationship between minority stress and mental
health in the autistic population), further work is needed to examine resilience factors that
potentially buffer the negative effects of minority stress. Indeed, the minority stress model
points to the potential buffering effect community connectedness may have and stress, stigma
and disability literatures have been poorly integrated thus far (Brown 2010). Given the
Minority Stress in Autistic Populations - 22
increasing community identity emerging in members of the HFA/AS population, theorizing
and empirically testing the stress-ameliorating function of community connectedness for
autistic people will likely prove useful.
Summary and Conclusions
Although preliminary, this study represents the first to examine the applicability of
the minority stress model to the autistic community, demonstrating the unique and additive
impact of minority stress on mental health and wellbeing for members of the HFA/AS
population. More research is needed to replicate these findings and address questions of
causality in the association between minority stress and mental health for autistic individuals,
along with stress-ameliorating factors in the autistic population.
Minority Stress in Autistic Populations - 23
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Minority Stress in Autistic Populations - 35
Table 1: Sample demographics (N=111)
Characteristics Percent
British White
Other White
Mixed multiple
Official Diagnosis
Autism type
Asperger Syndrome
Classic Autism
Pervasive Development Disorder
Age in years
72.1 82
21.7 22
6.2 7
45.0 50
39.6 44
7.2 8
1.8 2
6.3 7
70.3 78
29.7 33
82.9 92
10.8 12
6.3 7
M = 35.8 SD =11.
Minority Stress in Autistic Populations - 36
1 Ethnicity
2 Gender
3 Diagnosis status
4 Stressful life events
5 Victimisation and
6 Everyday
7 Expectation of rejection
8 Outness scale
9 Behaviour concealment
of autism
10 Internalised stigma
11 Social wellbeing
12 Emotional wellbeing
13 Psychological
14 Psychological distress
Standard deviation
c ** significant at <.001, **significant at <.01, *significant at <.05 (N=111)
Minority Stress in Autistic Populations - 37
Table 3. Minority stress predictors of mental health and wellbeing outcomes
βESE df FβESE df FβESE df FβESE df F
0.01 0.06 1 0.04 0.10 0.06 1 2.60 0.08* 0.04 1 4.18 0.03 0.05 1 0.51
0.20* 0.09 1 4.76 0.03 0.08 1 0.17 0.06 0.07 1 0.87 0.02 0.05 1 0.28
0.07 0.06 1 1.45 0.19 0.10 1 4.01 0.04 0.05 1 0.67 0.14* 0.07 1 4.14
0.18 0.13 4 2.06 -0.12 0.17 2 0.46 0.06 0.13 3 0.18 0.08 0.09 2 0.80
0.19 0.18 3 1.09 -0.20* 0.12 3 3.05 -.14* 0.07 2 3.93 -0.10 0.09 2 1.44
-0.22 0.21 5 1.12 -.24* 0.13 3 3.34 -.16* 0.10 4 2.56 0.23** 0.12 5 3.58
-.44*** 0.10 6 19.81 -.35*** 0.15 7 5.21 -.50*** 0.13 7 13.65 0.48*** 0.17 5 8.30
-.20 0.14 5 1.98 -0.16 0.18 4 0.81 -.15* 0.09 6 2.63 0.15** 0.08 7 3.86
-.22* 0.15 8 2.24 0.19 0.17 6 1.15 0.02 0.17 2 0.02 -0.06 0.10 6 0.38
0.15 0.18 4 0.71 -.26* 0.16 3 2.77 -0.15 0.16 4 0.88 0.26** 0.13 6 4.09
Psychological Well-Being
Psychological Distress (K6)
Note: * p ≤0.05, ** p ≤0.01, *** p ≤0.001. Estimated standard error (ESE) calculated using bootstrap (1000). Lower scores in well-being reflect poorer well-being, higher distress scores reflect higher distress (N=111).
Internalised stigma
Physical concealment
Outness scale
Expectation of rejection
Everyday discrimination
Victimisation and Discrimination
Stressful life events
Diagnosis status
Social Well-Being
Emotional Well-Being
Minority Stress in Autistic Populations - 38
... The National Federation for the Blind [44], which is a national advocacy organization representing blind and low-vision (BLV) people, elected to use IFL to refer to BLV individuals in its 1993 resolution [46], stating that person-frst language "implies shame instead of true equality" [16,17]. Similarly, the autistic community is a strong proponent of using IFL for autistic people [8,10,34,35,50], expressing that IFL encourages society to acknowledge and celebrate them as autistic individuals [35,50,52]. Additionally, IFL can help increase public visibility into the stigma disabled people experience as an underrepresented minority group and assist in reducing that stigma to build a more inclusive society [8]. ...
... Similarly, the autistic community is a strong proponent of using IFL for autistic people [8,10,34,35,50], expressing that IFL encourages society to acknowledge and celebrate them as autistic individuals [35,50,52]. Additionally, IFL can help increase public visibility into the stigma disabled people experience as an underrepresented minority group and assist in reducing that stigma to build a more inclusive society [8]. ...
... Participants did not limit their descriptions to social strategies or the camouflaging of autistic traits; masking included the suppression of emotion, reactions, sensory sensitivities, opinions and other aspects of identity such as class and gender. This reflects a growing awareness of the intersecting impact of multiple stigmatised identities for many autistic people (Botha & Frost, 2018). ...
Background Previous research has identified an association between masking and mental health for autistic people. However, the direction of causality and mechanisms involved in this relationship are not well understood. This qualitative study aimed to investigate autistic teenagers’ experiences of masking, mental health and how the two develop and interact. Methods Twenty autistic teenagers took part in a semi-structured interview. The interviews were analysed using Reflexive Thematic Analysis. Results From the analysis, one theme was identified to conceptualise masking as described by participants. Five more inter-related themes were identified, each involved both in the relationship between masking and mental health and conversely in the relationship between authenticity and mental health. Participants described how masking and mental health both influence each other, and both are influenced by social and environmental factors. Conclusions The findings are consistent with previous research indicating that masking is associated with mental health difficulties. Our analysis presents a broader conceptualisation of masking than previously defined in the literature, placing social oppression of autistic people at the heart of the relationship between masking and mental health. The findings have implications for diagnostic services, post-diagnostic support and therapeutic interventions, highlighting the need to challenge deficit-based narratives of autism.
... Działania takie mogą prowadzić do nawiązywania i podtrzymywania oczekiwanych interakcji (Goffman, 1959;Leary, 1995). Jednostki posiadające zaburzenia ze spektrum autyzmu częściej jednak niż osoby o normatywnym rozwoju posiadają potrzebę korzystania z kamuflażu, gdyż są one w większym stopniu narażone na stygmatyzację lub dyskryminację z powodu nie w pełni normatywnego rozwoju (Lai, Baron-Cohen, 2015;Mandy, 2019;Botha, Frost, 2020;Perry i in., 2021). ...
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Zaburzenia ze spektrum autyzmu (ASD) to zaburzenia neurorozwojowe. U osób z ASD występują trudności w społecznym funkcjonowaniu oraz werbalnej i niewerbalnej komunikacji. Ponadto osoby z ASD często posiadają wąskie i specyficzne zainteresowania oraz realizują dość ograniczony repertuar zachowań. Kamuflaż jest strategią, która służy osobom z ASD do maskowania lub kompensowania charakterystycznych cech zaburzeń, a także do asymilacji pożądanych społecznie zachowań poprzez naukę określonych schematów, a następnie adekwatne wykorzystywanie ich w konkretnej sytuacji społecznej. Prezentowany artykuł stanowi próbę opisu zjawiska kamuflażu na podstawie współczesnych doniesień naukowych. Wychodząc od definicji słownikowej, opisano funkcje oraz powody wykorzystywania kamuflażu przez osoby z ASD, a także omówiono wybrane czynniki różnicujące stosowanie strategii kamuflażu, takie jak diagnoza i/lub poziom prezentowanych cech charakterystycznych dla tych zaburzeń, płeć, tożsamość płciowa oraz wiek. Ponadto zwrócono uwagę na skutki, jakie osobom z ASD przynosi korzystanie z technik kamuflażu. W podsumowaniu ukazane zostały główne kierunki dalszych badań, na podstawie których możliwe będzie uzyskanie pełniejszej wiedzy dotyczącej przybliżonego w artykule zjawiska, dzięki czemu pojawi się szansa na wypracowanie bardziej trafnych działań pomocowych ukierunkowanych na osoby szczególnie ich potrzebujące.
... It also queries autism traits without making comparisons with an implicit neurotypical standard whenever possible and includes items that capture experiences of prejudice and misunderstanding. 62 The inclusion of these experiences recognizes the role that communities can play in discriminating against autistic people, intentionally or unintentionally. 12 This potentially makes the measure more acceptable to autistic people and enables the SAAT to more accurately capture the complexity of the autistic experience by framing autistic traits through an autistic lens (e.g., describing intense interests as deep passions, rather than allconsuming interests that eclipse all other interests). ...
... Qualitative and quantitative methods are no longer divided into scientific versus non-scientific, and instead generalised versus particular methods (Langhout, 2003). Quantitative methods thus become a tool for general research which can produce enlightenment on important regularities such as mental and physical health disparities that exist between minority and majority communitiesincluding in racial, sexual, and neuro-minorities (see Williams et al., 1997;Matlin, Molock and Tebes, 2011;Hirvikoski et al., 2016;Botha and Frost, 2018;Timmins, Rimes and Rahman, 2019). Yet numbers are limited in their scope to provide platforms for substantial "voice" to relatively powerless groups, and are general in scope, whereas qualitative methods provide narrative, intimate experiential data, and particular detail, which may not be accessed (Bond, García de Serrano and Keys, 2017). ...
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Introduction While not all autism research is ableism, autism researchers can be ableist, including by talking about autistic people in sub-human terms (dehumanization), treating autistic people like objects (objectification), and making othering statements which set autistic people apart from non-autistic people, and below in status (stigmatization). Method This mixed-method study aimed to investigate how autism researchers construct autistic people and autism research, and to investigate whether including autistic people more in research relates to lower ableism in narratives about autistic people. We used a survey with autism researchers ( N = 195) asking five open-ended questions about autism and autism research, as well as demographics, career length, contact with autistic people (familial and non-familial) and degree to which researchers involve autistic people in their research. We used content analysis to categorize narratives used by autism researchers and cues for ableism (dehumanization, objectification, and stigmatization). We then used binary-logistic regression to identify whether narrative or higher inclusion of autistic people predicted fewer ableist cues, controlling for career length and connections to autistic people. Results and discussion Using medicalized narratives of autism predicted higher odds of ableist cues compared to employing social model or neutral embodiment narratives. Greater inclusion of autistic people in research predicted significantly lower odds of ableist cues, while controlling for other contact with autistic people and career length. Next, we used reflexive thematic analysis to analyze researcher’s perceptions of autistic people and autism research. Narratives reflected core ideological disagreements of the field, such as whether researchers consider autism to be an intrinsic barrier to a good life, and whether researchers prioritize research which tackles “autism” versus barriers to societal inclusion for autistic people. Instrumentality (a form of objectification) was key to whether researchers considered a person to have social value with emphasis revolving around intellectual ability and independence. Lastly, language seemed to act as a tool of normalization of violence. Researchers relied on an amorphous idea of “autism” when talking about prevention or eradication, potentially because it sounds more palatable than talking about preventing “autistic people,” despite autism only existing within the context of autistic people.
Background The positive psychology and neurodiversity movements both aim to promote and improve wellbeing through strengths-based approaches. However, little is known about how positive psychology can support the wellbeing of autistic people. The present study investigated character strengths profiles as a potential tool to identify strengths-based interventions that could enhance wellbeing outcomes for autistic adults. To our knowledge, this is first study to use this method as a possible way of improving the wellbeing of autistic adults in the community in the UK. Method Forty-seven self-reported formally diagnosed (83%) and self-identifying (17%) autistic adults completed online self-rated standardised questionnaires about their character strengths and life satisfaction. Descriptive statistics and correlational analyses were used to evaluate the profile of character strengths and their relationship to overall life satisfaction. Results Character strengths most frequently reported by autistic adults were Honesty, Appreciation of Beauty and Excellence, Love of Learning, Fairness, and Kindness. Higher levels of life satisfaction were associated with character strengths of Gratitude, Hope, and Honesty. Conclusions The most frequent character strengths were consistent with autistic traits reported in the wider body of autism literature, such as intense interests and strong attention to detail. The present study provides preliminary findings and recommendations for potential future strengths-based interventions that could enhance life satisfaction of autistic adults in a community setting. Further investigation with larger samples is needed to replicate the emerging findings on this topic.
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Finding new ways of supporting the well-being of autistic adults is an essential goal for research and practice. We tested the predictive value of attitudes towards autism (as neurodiversity or as a disorder) and identification with other autistic people, on the psychological distress and self-esteem of autistic adults ( n = 109). Adopting a neurodiversity attitude not only predicted higher self-esteem but also served as a protective factor against the negative impact of identification with other autistic people on psychological distress. These findings show that clinicians should be sensitive to the way autistic people understand autism and the extent to which they identify with the autism community, as these factors relate to their well-being. Lay abstract Autistic adults experience a high level of distress. Finding new ways to support their well-being is an important goal for researchers and clinicians. We assessed the way autistic adults view their autism, as a disorder or as a type of mind (neurodiversity), and the level they integrate with other autistic people, and we checked how those factors contribute to their well-being. People who see autism rather as a type of mind than as a disorder had higher self-esteem. People who view themselves as more similar to other autistic people felt more stressed, but this result was not accurate for people who view autism as a type of mind. Clinicians should be sensitive to the way autistic people understand autism and to what extent they identify with the autism community, because it may relate to their well-being.
In this paper, I explore how autistic behaviors are rendered Othered transgressive acts in general research and in the figured world of occupation. I assess how the normalization agenda, which aims to condition autistic people into appearing abled, is associated with endemic disparities. I contend that occupational science has often countered anti-autistic stigma. However, I analyze how the field has perpetuated ableism by replicating normalization ideology and through its silence on the occupational significance of autistic behaviors. To contrast dominant assumptions, I examine autistic ways of being within occupational frameworks. I propose that the field can foster inclusion, rethink its figured worlds, and recognize autistic behaviors to promote social responsiveness. I argue these steps are ethically imperative as evidence on the harms of normalization accumulates.
Autistic girls’ social motivation and associated desire to fit in, suggests that feeling a sense of belonging is important for the girls. This may be particularly relevant during adolescence, as this period is marked by uncertainty and loneliness due to increasing independence and development of identity. There is evidence that feeling a sense of belonging provides pupils social acceptance and is a protective factor against harmful psychological outcomes. Despite this, limited research has considered autistic girls belonging experiences in mainstream schools and what needs to change to facilitate belonging. Further, the historical underdiagnoses of autistic girls has entailed that their personal stories are mostly absent from autism research. This research prioritises autistic girls’ voices by exploring the girls’ constructs of belonging, including the facilitators of and barriers to feeling a sense of belonging, and the impact on wellbeing. This study included the autistic community in the research process in various ways. An autism advisory group provided consultation on pre-study considerations, data collection and data analysis. Personal constructs and lived experiences of school belonging were explored using semi-structured interviews and personalised activities (e.g. drawings and poetry) with eighteen adolescent autistic girls. Participants were involved in the data analysis process as they commented on emerging codes and themes. Data were analysed using thematic analysis and five themes were identified: (I) autistic girl’s want to be seen and heard, (II) the joys and pains of mutuality, (III) losing myself under the mask, (IV) marginalisation links with invalidation, (V) sensory fatigue. The autistic girls defined belonging from a relational perspective, as they want to be externally valued, heard, and involved in the school community. However, aspects of masking, stigma and sensory experiences limit the girls belonging in school. Implications for schools and Educational Psychologists are discussed using an experience sensitive framework of wellbeing.
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Using a daily diary methodology, we examined how social environments support or fail to support sexual identity disclosure, and associated mental and physical health outcomes. Results showed that variability in disclosure across the diary period related to greater psychological well-being and fewer physical symptoms, suggesting potential adaptive benefits to selectively disclosing. A multilevel path model indicated that perceiving autonomy support in conversations predicted more disclosure, which in turn predicted more need satisfaction, greater well-being, and fewer physical symptoms that day. Finally, mediation analyses revealed that disclosure and need satisfaction explained why perceiving autonomy support in a conversation predicted greater well-being and fewer physical symptoms. That is, perceiving autonomy support in conversations indirectly predicted greater wellness through sexual orientation disclosure, along with feeling authentic and connected in daily interactions with others. Discussion highlights the role of supportive social contexts and everyday opportunities to disclose in affecting sexual minority mental and physical health.
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This paper considers both Partial Least Squares (PLS) and Ridge Regression (RR) methods to combat multicollinearity problem. A simulation study has been conducted to compare their performances with respect to Ordinary Least Squares (OLS). With varying degrees of multicollinearity, it is found that both, PLS and RR, estimators produce significant reductions in the Mean Square Error (MSE) and Prediction Mean Square Error (PMSE) over OLS. However, from simulation study it is evident that the RR performs better when the error variance is large and the PLS estimator achieves its best results when the model includes more variables. However, the advantage of ridge regression method over PLS is that it can provide the 95% confidence interval for the regression coefficients while PLS can't.
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Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks.
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The purpose of this paper is to discuss the multicollinearity problem in regression models and presents some typical ways of handling the collinearity problem. In Addition, the paper attempts to compare RR , and PCR and LS methods using minimum squared error MSE and the accuracy of the prediction. The results of this paper showed that, RR method performs better than PCR and LS methods , because RR had minimum MSE and a higher predicted accuracy than other methods. The results of this paper showed that, based on the criteria of model accuracy PCR performs better than RR, whereas, according to mean squares errors criterion MSE , RR performs slightly better. In general, the two biased estimator RR and PCR perform better than LS.
p>This research aimed to ascertain the contents (Study 1) and valence (Study 2) of the stereotype associated with Autism Spectrum Conditions (ASC) in university students. Study 1 used a free-response methodology where participants listed the characteristics that they thought society associates with individuals with ASC. This study revealed that the stereotypic traits most frequently reported by students without personal experience of ASC were poor social skills, being introverted and withdrawn, poor communication and difficult personality or behaviour. Study 2 had participants rate the valence of the 10 most frequently mentioned stereotypic traits identified in Study 1, along with additional traits frequently used to describe disabled and non-disabled people. This study found that eight of the ten most frequently listed stereotypic traits from Study 1 were seen as negative, and were rated significantly more negatively than traits used to describe non-disabled people. The knowledge of the contents and valence of the stereotype of ASC gained from this research can be used to tackle negative aspects of this stereotype.</p
A new method is proposed that extends the use of regularization in both lasso and ridge regression to structural equation models. The method is termed regularized structural equation modeling (RegSEM). RegSEM penalizes specific parameters in structural equation models, with the goal of creating easier to understand and simpler models. Although regularization has gained wide adoption in regression, very little has transferred to models with latent variables. By adding penalties to specific parameters in a structural equation model, researchers have a high level of flexibility in reducing model complexity, overcoming poor fitting models, and the creation of models that are more likely to generalize to new samples. The proposed method was evaluated through a simulation study, two illustrative examples involving a measurement model, and one empirical example involving the structural part of the model to demonstrate RegSEM’s utility.