Moving from Disorder to Difference: A Systematic Review of Recent Language Use in Autism Research

Abstract

Background:

The neurodiversity paradigm positions autism as a neurological difference that is disabling in the societal context, shifting away from the traditional medical view of a disorder. Several recent publications recommend use of alternative neuro-affirming language (ANL) instead of traditional medical language (TML) with the aim to increase acceptance of autistic people and reduce prejudice. Examining language use within recent autism literature, including by journal and study characteristics, may offer insight into the influence of these recommendations and current disability discourse.

Methods:

A systematic review was conducted using Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines in autism research from 2021 (n = 2322 articles; 394 journals). Articles were coded according to topic, participants, and use of self-report. Journals were coded by topic, geographic region, and language guidelines. Terminology use was extracted using QDA Miner software.

Results:

Many articles primarily used TML with a smaller subset primarily using ANL. There was a positive correlation between ANL use and publication date. More ANL was associated with articles on topics of autistic traits, diversity, equity, and inclusion (DEI), or lifespan and that included autistic adults or autistic self-report. More ANL was also found in journals from Australasia or Europe or those that had identify-first language (IFL) guidelines. Less ANL (more TML) was associated with articles on biology/causes or treatment and that included autistic or non-autistic parents, autistic youth, siblings, or other clinical groups, and were published in medical journals.

Conclusion:

TML continues to largely dominate language choices in autism research, with an emerging shift toward ANL in recent literature. Increased ANL may be facilitated by journal and article language recommendations. Neuro-affirming language was also more likely in articles on topics prioritized by the autistic community, that included autistic adults, and may also be driven by cultural differences. Researchers and practitioners should consider the potential for their language use to impact individual and societal views of autistic people.

Community brief

Why is this topic important?

Language use impacts how groups of people are viewed. Historically, autism was talked about as part of the medical model, which usually focuses on autism symptoms and deficits. The recent neurodiversity paradigm views autism as a difference that could be accepted and supported. Part of this acceptance is using words that describe autism as part of someone's identity and emphasizing individualized strengths or needs.

What is the purpose of this article?

Several recent papers recommend using alternative neuro-affirming language (ANL) instead of traditional medical language (TML) in autism research. This article summarizes autism language use and examines how certain parts of journals and articles may impact phrasing.

What did the authors do?

We used guidelines for the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) to gather autism research studies published in 2021. We found 2322 articles from 594 journals. We first summarized how much ANL was in the articles relative to TML. Then, we compared this language use based on the articles' topic and types of participants, and also the journals' field, geographic region, and whether they included guidelines for language use.

What were the results of the review?

We found that articles primarily used TML, but more recent articles had more ANL. Articles that had more ANL were studies published more recently, were about traits or lifespan experiences (e.g., parenting, work, aging), included autistic adults as participants, from journals with language guidelines specific to disabled or autistic people, or from journals from Australasia or Europe. Articles that had more TML were those about treatments for or biological explanations of autism, included siblings as participants, or were published in medical journals. This means that certain aspects of articles and journals are related to how researchers write about autism.

What do the authors recommend?

Clinicians and researchers should ask autistic people their preferences surrounding language. Common language when referring to autism may differ based on the topic and participants that are being studied. More research is needed to understand how different terms impact prejudice toward and societal views of autistic people. We should also consider cultural differences in autism views, which influence researchers' terminology use. Journals that wish to accelerate use of ANL should consider adopting explicit guidelines for language use.

How will these findings help autistic people now or in the future?

This article summarizes how researchers talk about autism, which likely impacts how autistic people are viewed by others. Increasing use of ANL may gradually impact conceptualizations of autism and prejudice regarding autistic people.

Background

Conceptualizations of autistic people have changed drastically over the past several decades,¹ and accordingly, terminology has adapted.² Early descriptions reflected a medicalized pathology focusing on deficits and impairments that would benefit from intervention.^3,4 More recently, the neurodiversity paradigm emerged, referring to the natural occurrence of neurobiological differences that can increase societal capacity for growth and success.^5–7

A neuro-affirming view of the autistic neurotype has broad implications for societal understanding of autistic people, and subsequently for shaping public and professional perceptions of stereotypes and stigma.^8–13 Recent publications offer recommendations for alternative terminology with the aim to be more precise and inclusive than traditional medical model language.^14–16 Despite growing attention to this topic, the language used to describe autism and autistic people in peer-reviewed literature is yet to be empirically examined.

The neurodiversity paradigm

The neurodiversity paradigm calls for acceptance of differences and consideration of autistic people's strengths and well-being, while criticizing efforts to minimize autistic characteristics or cure autism altogether.^5,17–19 In this vein, the autistic neurotype is viewed as inherent to and inseparable from an autistic person's identity.^8,9,20 Distinct from other models, this framework considers being autistic both a deficit or difference of neurobiology and a disability that is culturally composed by societal norms.^5,19,21,22

The neurodiversity paradigm incorporates Alternative Neuro-affirming Language (ANL) to describe autistic experiences without presuming incompetence or pathology. Perhaps the most visible example of this language shift is the use of identify-first language (IFL; e.g., “autistic person”) instead of person-first language (PFL; e.g., “person with autism”).

PFL initially emerged from the disability rights movement with the goal to de-pathologize and focus on the person rather than their disability.^23–25 Yet, IFL has regained popularity as a means to reclaim labels integral to one's identity, similar to preferences in the Blind and Deaf communities.^26–29 Surveys of language preferences when referring to autistic people indicate that many (but not all) autistic people prefer IFL, whereas allistic stakeholders (e.g., non-autistic professionals and family members) have more varied opinions and many continue to prefer PFL.^5,9,30–34 The field would benefit from peer-reviewed studies that include the self-reported language preferences of autistic people who are non-speaking or with co-occurring intellectual disability.

ANL goes beyond identifiers for autistic people. Advocates also criticize broad functioning levels (e.g., “low/high functioning,” “severe/mild,” “profound”), as these may deny agency or support needs within the imprecise stereotype of a linear autistic experience.^22,33–37 Further, many autistic people describe being autistic as a “neurological difference” or “disability” rather than a “disease” or “disorder,” and contextualize autistic people's abilities using terms such as “challenges” and “difficulties” rather than “deficits” or “impairments.”^8,31,33,38

Given that autistic social communication may only be impaired when viewed through a neurotypical lens,^39–41 the neurodiversity paradigm rejects “treatments” that aim at reducing autistic characteristics; instead, “accommodations” are suggested that adjust allistic environments to be equitable across neurotypes while providing “services” or “supports” that facilitate autistic people meeting their own goals.^{17,21,42–44}

Finally, neuro-affirming language replaces terms that may presume incapability with more affirming alternatives. This includes using wording such as “non-speaking” or “non-vocal” instead of “minimally verbal” or “nonverbal,”^45,46 describing “likelihood” rather than “risk” of being autistic,⁴⁷ and other conditions being “co-occurring” versus “co-morbid.”^48,49

Rather than labeling behaviors as inherently odd or aberrant, this framework supports autistic people displaying stimming behaviors for self-regulation^50–52 or engaging with their preferred interests.⁵³ Similarly, specific behavior topography is described, rather than broadly labeling behavior as maladaptive or undesirable (e.g., “challenging” or “problem” behavior).^42,52,54

The traditional medical model

Terminology historically described autism as a common behavioral phenotype using diagnostic criteria.^5,17 Early monothetic prose increased the likelihood that a majority of people who met criteria for an autism diagnosis also had intellectual or early language delays.¹ In this context, and aligned with the medical model more broadly, terminology largely centered around deficits and pathology. Thus, traditional medical language (TML) may be considered clinically accurate in reflecting actual impairment or disabling co-occurring conditions common among this subset of autistic people.^55,56

For example, TML is often used to describe people on the autism spectrum with co-occurring profound intellectual disability and/or high sensory processing or emotion regulation support needs (e.g., self-injury that can cause significant permanent injury). Advocates of TML posit that these terms are needed to precisely describe the experiences and behaviors of, at least some, autistic people.⁵⁵

Parent advocates who support TML also describe a lack of adequate representation in determining appropriate terminology when referring to autism.^55,57 They express concern that views on this topic are dominated by autistic self-advocates without co-occurring intellectual disability and with intact language fluency (spoken or computer-mediated), which “crowds out” other voices with fewer skills or resources to advocate for their perspective.⁵⁷

Ongoing preferences for PFL and TML may be driven by parents of people on the autism spectrum with co-occurring intellectual disability or who are non-speaking.^57,58 Caregivers close with these people seek to express perspectives relevant to their experiences that they feel are not captured as part of the neurodiversity movement.⁵⁷

A final consideration is that language preferences remain mixed, even within the autistic community. Several surveys report that up to one-third of people on the autism spectrum use or prefer PFL, with estimates as high as two thirds of professionals.^31–34 Language preference may also vary by age such that older people on the autism spectrum prefer PFL.³⁰

Further, qualitative responses from people on the autism spectrum highlight a range of views, including describing autism as a pathology they would like to be rid of, taking pride in this identity, and other specific language preferences.^20,33,59 Taken together, these perspectives suggest that it may not be possible or appropriate to streamline language use across all contexts.

Language, stigma, and prejudice

Both perspectives described earlier seek to minimize harm to autistic people. Advocates of TML retain the position of earlier disability rights efforts to describe people as separate from their condition, within the premise that perceptions of cause and controllability underlie negative value judgments and can perpetuate stigma.^23,60 Within the stigma model, a person's individual characteristics are viewed as pathologizing or disordered.⁶¹

This perspective overlaps with efforts to de-stigmatize mental illness by focusing on neurobiological deficits (i.e., mental illness as a biological disposition rather than a choice). Separating a person from a diagnosis is incorporated within recommendations for terminology that minimizes blame and stigma^62,63 and is associated with reduced stigma associated with substance use disorder,^64–66 with replication related to depression but not autism.⁶⁷

Advocates of TML also express concern that eradicating medicalized terms may further stigmatize treatment seeking and exacerbate existing disparities in developing and accessing treatments.^55,68,69

Separately, advocates of ANL posit that medicalized language pathologizes autism as an abstract concept, whereas the neurodiversity paradigm promotes acceptance and positive outcomes by emphasizing that autistic people experience systemic prejudice rooted in structures of inequality.^61,70 This approach may subsequently reduce external harm toward autistic people as well as their own internalized ableism.

For example, viewing being autistic as part of one's positive self-identity is related to preference for IFL⁵ and lower depression symptoms.⁷¹ Lower depression and stress among autistic adults is also related to greater external acceptance (e.g., from society, family, friends) and less camouflaging of autistic behaviors.⁷¹ Beyond use of IFL, ANL and acceptance of autistic people may also increase autistic people's well-being and satisfaction via normalizing autistic people engaging with their areas of expertise⁷² and using their autistic strengths.⁷³ As such, advocates highlight that neuro-affirming language may facilitate shifting disability discourse to acceptance and flourishing.

Variables that may impact language use

Growth of the neurodiversity movement has prompted increasing consideration of the language used to talk about autism and autistic people over the past two decades. As such, passage of time may impact researcher descriptions as awareness of ANL increases. For example, there is evidence of shifts in language use or preference and increased interest in this topic across other mediums (e.g., media, surveys).^74–77 There have also been several published recommendations for language use, which may accelerate changes in how researchers describe autistic people.^14–16,36

Language in autism research may also differ by topic of study. Studies investigating biology/genetics or causes received 37%–71% of autism research funding over the past two decades and are based on a medical model. In contrast, a small but increasing portion (5%–15%) of funding supported research examining services/supports and lifespan issues for autistic people.^78–81 Evaluating terminology use across a range of topics, at both the individual article and journal levels, would enhance understanding of how autistic views and funding priorities interface with language recommendations.

Examining language use by participant group is another way to consider the impact of the neurodiversity movement. Autism was traditionally conceptualized as a childhood disorder, whereas the neurodiversity paradigm celebrates being autistic as a lifespan neurotype.^82,83 Thus, including autistic adult participants in published research may be more likely to use ANL.

In contrast, the medical model often positions autistic people within deficit conceptualizations relative to other groups,^17,47,84,85 suggesting that studies may use more TML if they include other clinical groups, siblings, or community peers. Finally, the importance of including autistic views within research is well outlined within guidelines informed by the neurodiversity paradigm,⁸⁶ so researchers who includes autistic self-report may also use more ANL.

In response to growing awareness of neurodiversity, some journals now include terminology guidelines within their instructions for authors. These include using IFL or referring to people “on the autism spectrum” as well as using strengths-based language and avoiding functioning labels.

Other journals recommend following professional guidelines, such as recommendations from the American Medical Association (AMA) to “put the person first”⁸⁷ or from the American Psychological Association (APA) to use either IFL or PFL.²⁹ It is not yet known how different types of language guidelines may impact terminology use across the full range of autism literature.

Last, geographical region may reflect cultural differences related to acceptance of autistic people.^88–91 There is also evidence of subtle differences in preferences across regions and of those speaking different languages.^30–34 These views may reflect cultural differences in conceptualizations of autism and disability and therefore impact common language used when describing autistic people in research.¹²

Present study

Researchers' language choices, such as use of TML and ANL, contribute to the construction of views about autistic people through not only empirical research findings but also by modeling communication. The purpose of the present study was to review the terminology used in recent autism research. We evaluated language frequency overall and change over time, as well as differences at the article level (research topic, participant group, self-report) and journal level (journal type, journal language guidelines, geographic region).

Methods

Search strategy

Searches were conducted in three databases (PsycInfo, ERIC, PubMed) in January 2022 using the keywords or subjects autism* OR autistic OR Asperger* OR Pervasive Development* Disorder* OR ASD, yielding 3532 articles. Several autism-specific journals were also searched directly if few or no articles from these sources were identified within the database search, which generated an additional 1117 articles. Inclusionary criteria were empirical articles (1) from a peer-reviewed journal, (2) written in English, (3) available online or in print in the calendar year 2021, (4) with human subjects, and (5) including autistic people or more broadly related to the field of autism research.

Articles were excluded if autistic participants were combined in a group of participants with other diagnoses (e.g., developmental disabilities) or if the topic of interest only described disabilities broadly (e.g., special education). A total of 2322 articles were retained (Supplementary Table S3) from 394 journals (Supplementary Table S4) following screening by the research team according to PRISMA guidelines (Fig. 1; online Supplementary Data S9). Included articles were published online between June 29, 2018 and December 31, 2021 and with print dates from January 1, 2021 and including several remaining advance online publications at the time of manuscript submission. “See Supplementary Table S8 for examples of excluded studies with rationale.”

FIG. 1.

PRISMA 2020 flow diagram for new systematic reviews that included searches of databases, registers, and other sources. AIA, Autism in Adulthood; Autism Res., Autism Research; ETADD, Education and Training in Autism and Developmental Disabilities; Focus Autism, Focus on Autism and Other Developmental Disabilities; JADD, Journal of Autism and Developmental Disorders; JND, Journal of Neurodevelopmental Disorders; Mol. Autism, Molecular Autism; PRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses; RASD, Research in Autism Spectrum Disorders; Res. in DD, Research in Developmental Disabilities. From: Page et al.¹⁰⁴ For more information, visit: www.prisma-statement.org

Coding categories

Article level

Articles were coded according to topic, participant group, and use of autistic self-report. There were 11 topic codes: (1) treatment, (2) assessment and diagnosis, (3) co-occurring diagnoses, (4) biological explanations or mechanisms, (5) autistic traits, (6) lifespan experiences, (7) case studies, (8) associated features (e.g., social communication, executive functioning, motor skills), (9) family or provider experiences, (10) diversity, equity, and inclusion (DEI) experiences, and (11) other.

Article topic codes were developed through a combination of inductive and deductive approaches: an initial list of codes (and operational definitions) was first generated for each category based on the author's knowledge and existing literature,^79,92 which were tested via independent coding of 20 articles by each author. Codes were refined through group discussion to clarify disagreements and reflect the breadth of article content. Up to two topics were coded for each article based on the research question(s) studied.

Articles were also coded for including eight possible participant groups: (1) autistic youth, (2) autistic adults, (3) parents, (4) professionals, (5) siblings, (6) other clinical, (7) community, and (8) other. It is important to note that multiple groups were selected via dummy coding when applicable. For example, if the participants were autistic parents, both “autistic adults” and “parents” were selected. The autistic youth and autistic adult codes were only applied in cases where participants were explicitly described as autistic; groups without this descriptor were assumed to be allistic.

Finally, articles were coded according to a binary distinction of (1) including self-report from autistic participants or (0) only gathering information from other respondents. Articles that did not include autistic participants were coded as missing for this variable. Additional article coding details are provided in Supplementary Tables S1 (topics) and S2 (participants).

Journal level

Journals were coded according to their type or field of focus, having published language guidelines, and their geographic region. There were 16 journal types based on the stated aims/content of the journal website: (1) Speech/Verbal Behavior, (2) Neuroscience, (3) Child or Family Development, (4) Clinical or Counseling Psychology, (5) Health Psychology, (6) Education, (7) Autism, (8) Behavior Analysis, (9) Psychiatry, (10) Education or Educational Psychology, (11) Cognitive or Experimental Psychology, (12) Disability, (13) Neuropsychology, (14) Medicine, (15) Psychology (General), and (16) Other. To facilitate more parsimonious statistical analysis, these journal types were condensed to five superordinate categories based on the author's knowledge of theoretical similarities among the more distinct types: (1) autism, (2) practitioners, (3) psychology, (4) development/disability, and (5) medical. The “Other” type was also retained as a reference group.

In addition, journal language guidelines were coded if they described suggestions for (1) IFL; (2) PFL; (3) following APA guidelines (either IFL or PFL); (4) general avoidance of biased and stereotyped language (e.g., for age, gender, race, ethnicity); or (5) did not mention any language guidelines. Finally, journals were coded based on representing one of five geographic regions: (1) International (journal self-described as international, journal editors affiliated with countries across multiple regions, or journal editors affiliated with specific geographic region other than listed here), (2) Americas (North, Central, and South America), (3) Europe, (4) Asia, or (5) Australasia (Australia, New Zealand, and the Pacific Islands).

Journal language guidelines coding was conducted in January 2023 and reflects information available in the journal's instructions for authors or publishing guidelines at that time.

Language use

A list of 70 terms was created based on recently published guidelines from Bottema-Beutel et al.,¹⁴ Dwyer et al.,¹⁵ and Monk et al.¹⁶ Terms were included as Traditional Medical Language (TML; n = 36) or Alternative Neuro-affirming Language (ANL; n = 34) if they were listed within the example tables in any of these articles or referenced as such within the article(s) text.

Two members of the research team (H.E.M. and K.G.) independently generated an initial list of terms and resolved all discrepancies; the final term list was reviewed and approved by all authors. Coding queries were generated with contributions from each member of the research team and reviewed collectively and iteratively before and during terminology coding. See Supplementary Table S5 for full terminology list and coding queries.

Data analysis

Articles were coded using QDA Miner Lite qualitative analysis software. Text retrieval analysis was conducted to identify the frequency of each identified term at the sentence level within each article. Frequencies were exported and merged with author coding of articles and journals; subsequent analyses were conducted in StataBE.

The dependent variable was the ratio of alternative language to traditional language within each article, calculated as the frequency of neuro-affirming terms divided by total terms frequency: [ANL frequency/(ANL frequency + TML frequency)] × 100. We first present frequencies for terminology use and likelihood of using ANL (vs. TML) across the literature. To parallel prior studies, frequencies are also presented for use of IFL, PFL, and the potentially more neutral phrase “on the [autism] spectrum.”^14,45

Subsequently, changes in terminology use over time were examined (1) using Spearman's correlation due to significant kurtosis and outliers in the publication date variable, as well as t-tests adjusted for unequal variances as appropriate for the data and (2) dichotomously based on the online publication date (March 18, 2021) for the Bottema-Beutel et al.¹⁴ seminal language guidelines article.

Finally, ANL use was examined according to article and journal coding categories. A series of multilevel models were conducted to identify predictors of a greater ANL, while controlling for change over time and nested by journal. The amount of variance explained at the article and journal levels was calculated using the Snijders/Bosker R².^93,94

All dummy coded variables were initially entered into the respective univariate models omitting the “other” or “none” levels as the reference group. Dummy coded variables were then sequentially removed using backward deletion of the variable with the smallest |t value| until only significant predictors remained (p < 0.05). Significant predictors from each univariate model were then entered into a final model, again nested by journal, to identify variables that retain effects on language use within the multivariate environment.

Autistic self-report was not included within the final model due to this coding only being relevant for articles with autistic participants and the subsequent lack of conceptual relevance of a missing data approach. Across results, unstandardized effects are reported for direct interpretability of change in ANL percent according to model predictors.

Interrater agreement

Article screening

Two authors coded article eligibility across all phases. We calculated inter-rater agreement (IRA) as the number of articles wherein both coders agreed to include/exclude divided by the total number of articles assessed and multiplied by 100 (i.e., [agreements/(agreements + disagreements)] × 100). On average, IRA was high across phases (96%) and within each phase (title review: 36% assessed, IRA = 96%; abstract review: 36% assessed, IRA = 99%; full-text review: 6% assessed, IRA = 94%).

Coding categories

The IRA was calculated similarly for article and journal coding. Article coding was conducted by two authors (S.B.B. and K.G.) and all discrepancies resolved (article topic: 20.8% assessed; IRA = 87.5%; participant group: IRA = 97.1%; autistic self-report: IRA = 96.7%). Journal field coding was conducted in tandem by two authors (H.E.M. and K.A.B.) and disagreements resolved by all authors. Coding for journal language guidelines and geographic region was conducted by one author (H.E.M.). The IRA was conducted on 20.3% of journals by a second coder (K.G.; language guidelines: IRA = 93.8%; region: IRA = 96.3%).

Results

On average, articles contained 70.11% TML terms (median = 85.91%) versus 29.89% ANL terms (median = 14.09%). Almost two-thirds of the included articles (63.01%, n = 1463) included <25% ANL (primarily TML), 18.99% of articles (n = 441) had a combination of 25%–75% ANL/TML, and the remaining 18.00% of articles contained more than 75% ANL (primarily ANL; n = 418). Overall, traditional medical terms were 57% more likely to be used than alternative neuro-affirming terms (1.57:1, 95% confidence interval: 1.45–1.70). See Supplementary Table S3 for full terminology list and frequencies.

Almost all articles (99.44%; n = 2309) included at least one instance of referring to an autistic person using either PFL (i.e., “with autism,” “with ASD,” or “with autism spectrum condition”), IFL (i.e., “autistic” or “autist”), or in the context of the autism “spectrum” (i.e., “on the spectrum” or “on the autism spectrum”). Of these approaches, PFL was used an average of 22 times per article (median = 16, standard deviation [SD] = 21.32), IFL was used an average of 15 times per article (median = 1, SD = 29.30), and the potentially more neutral phrasing of “on the [autism] spectrum” was used an average of 1 time per article (median = 0, SD = 6.44).

Given low rates of describing autistic people as “on the [autism] spectrum,” this phrasing was subsequently combined with IFL, aligning with recommendations.¹⁴ Two-thirds of articles (66.83%; n = 1543) primarily referred to autistic people using PFL (<25% IFL), another 11.39% (n = 256) of articles used a combination of IFL and PFL, and 21.58% of articles primarily used IFL (>75%; n = 510) when referring to autistic people (Fig. 2).

FIG. 2.

Frequency of identify-first language versus person-first language.

Change over time

There was a small, positive correlation between ANL use and more recent online publication date (r_s = 0.128, p < 0.001). Further, articles published following online publication of Bottema-Beutel et al.¹⁴ were more likely to include at least one ANL term (n = 1226, M = 88.82%, standard error [SE] = 0.90%) compared with terms published before this seminal paper [n = 1096, M = 85.86%, SE = 1.05%; t(2220) = 2.14, p = 0.032]. Articles published after this cutoff also had significantly more ANL (M = 33.37%, SE = 0.98%) compared with articles before the cutoff [M = 26.00%, SE = 0.93%; t(2320) = 5.43, p < 0.001].

ANL predictors

An empty mixed model predicting variance in ANL use nested by journal was a significant improvement over the linear model [χ²(1) = 235.70, p < 0.001], with journal level variance explaining 15.73% of variability in ANL use (Intraclass Correlation Coefficient = 0.1573). Thus, a nested model was appropriate for these data. Adding online publication date significantly improved this model [χ²(1) = 23.42, p < 0.001] such that a more recent article publication date was being associated with more ANL (B = 0.02, SE = 0.00, p < 0.001).

Subsequent analyses were conducted building on this model. See online Supplementary Data S6 for individual model-building results, with significant predictors retained from each of these models entered in the overall model. See Table 1 for descriptives by each predictor and online Supplementary Table S7 for descriptives by more specific journal types.

Table 1.

Article and Language Frequencies Overall and by Coding Categories

Predictor	Articles		ANL ratio ^a
Predictor	n	%	Mean (%)	Median (%)
Overall	2322	100.00	29.89	14.09
Article topic
Lifespan	112	4.82	60.76	83.68
Inclusion/DEI	142	6.12	57.68	77.30
Traits	208	8.96	49.71	54.86
Associated features	778	33.51	31.77	13.51
Co-occurring	141	6.07	29.99	18.37
Family/Provider	265	11.41	28.75	13.46
Diagnosis	185	7.97	24.70	16.67
Case study	41	1.77	24.20	17.86
Support	529	22.78	20.28	10.26
Biology/Cause	303	13.05	19.83	9.09
Other	78	3.36	29.35	14.29
Article participant group
AT Adult	662	28.51	41.68	25.00
Professional	202	8.70	35.10	19.41
Community	894	38.50	31.90	13.42
Parent	507	21.83	29.00	15.00
Sibling	97	4.18	22.15	12.00
AT Youth	1394	60.03	21.13	9.40
Clinical	281	12.10	20.92	12.07
Other	11	0.47	37.13	18.31
Article self-report (n = 1749 with AT participants)
Yes	423	24.19	53.58	67.44
No	1326	75.81	19.28	8.86
Journal type
Autism	1274	54.87	35.06	16.55
Psychology	222	9.56	29.24	14.75
Dev./Dis.	249	10.72	27.57	14.71
Medical	306	13.18	19.37	10.53
Practitioner	257	11.07	19.01	7.23
Other	14	0.60	41.42	46.71
Journal language guidelines
General	242	10.42	28.16	12.58
Mixed	58	2.50	26.84	10.42
PFL	50	2.15	15.70	11.51
IFL	906	39.02	39.05	22.55
None	1067	45.95	23.35	11.43
Journal geographic region
International	2005	86.35	30.56	14.29
Americas	222	9.56	23.67	13.57
Europe	66	2.84	32.77	17.82
Asia	21	0.90	14.38	11.76
Australasia	8	0.34	51.50	68.31

% TML is the reverse of ANL, for example 20% ANL indicates 80% TML is used within a given article.

ANL, alternative neuro-affirming language; AT, autistic; DEI, diversity, equity, and inclusion; Dev./Dis., development or disability; IFL, identify-first language; PFL, person-first language; TML, traditional medical language.

Overall model

The combined model was a significant improvement over the baseline model with online publication date [χ²(16) = 542.77, p < 0.001], explaining 27.35% of article-level variance and 30.34% of journal-level variance. By topic, articles contained more ANL if they were on Traits (B = 23.43, SE = 2.24, p < 0.001), DEI (B = 15.64, SE = 2.54, p < 0.001), or Lifespan (B = 14.20, SE = 2.82, p < 0.001); whereas less ANL was found in articles on Biology/Mechanisms (B = −8.23, SE = 1.93, p < 0.001) or Treatment (B = −4.77, SE = 1.58, p = 0.003).

Regarding participant group, articles had more neuro-affirming language if they included autistic adults (B = 9.09, SE = 1.41, p < 0.001) and more TML if they included siblings (B = −12.66, SE = 2.97, p < 0.001), autistic youth (B = −11.29, SE = 1.32, p < 0.001), other clinical groups (B = −10.18, SE = 1.84, p < 0.001), or parents (B = −3.67, SE = 1.48, p = 0.013).

Regarding journal predictors, articles contained more ANL if they were published in journals with IFL guidelines specific to disabled or autistic people (B = 20.19, SE = 4.26, p < 0.001) or journals from Australasia (B = 25.00, SE = 10.20, p = 0.014) or Europe (B = 10.18, SE = 3.93, p = 0.010), whereas less ANL was found in articles from medical journals (B = −7.75, SE = 2.34, p = 0.001) (Table 2).

Table 2.

Multivariate Predictors of Alternative Neuro-Affirming Language Use

	B	SE	t	p
Online date	0.01	0.00	4.29	<0.001
Article topic
Trait	23.43	2.24	10.46	<0.001
Inclusion/DEI	15.64	2.54	6.17	<0.001
Lifespan	14.20	2.82	5.04	<0.001
Diagnosis	−3.03	2.26	−1.34	0.181
Treatment	−4.77	1.58	−3.02	0.003
Mechanism/Cause	−8.23	1.93	−4.26	<0.001
Participant group
AT adults	9.09	1.41	6.47	<0.001
Parents	−3.67	1.48	−2.49	0.013
Clinical	−10.18	1.84	−5.53	<0.001
AT youth	−11.29	1.32	−8.57	<0.001
Siblings	−12.66	2.97	−4.27	<0.001
Journal field
Medical	−7.75	2.34	3.31	0.001
Practitioner	−4.86	2.55	−1.91	0.056
Language guidelines
IFL	20.19	4.26	4.73	<0.001
Journal region
Australasia	25.00	10.20	2.45	0.014
Europe	10.18	3.93	2.59	0.010

SE, standard error.

Discussion

This systematic review examined terminology in recent peer-reviewed autism literature in accordance with guidelines for neuro-affirming language. Most studies included TML, consistent with literature that researchers' narratives are largely deficit based.⁹⁵ Yet, neuro-affirming language increased over time, including since the seminal publication of recommendations from Bottema-Beutel et al.¹⁴ Language use also differed according to article and journal characteristics.

More ANL was associated with articles on the topic of lifespan, DEI, and autistic traits, which largely align with autistic-reported priorities for research⁹⁶ and growing funding in these areas.^79,81 It is not surprising that researchers who prioritize autistic perspectives would be using more ANL. Similarly, more ANL was found in studies that included autistic adults or autistic self-report.

The neurodiversity paradigm emphasizes being autistic as a lifespan neurotype, thus ANL may help to expand the field's lexicon when describing autistic adults who have historically been under-studied in research.^82,83 These findings also highlight ANL as a useful tool to describe the self-reported autistic perspective.⁸⁶

In contrast, use of less ANL (more traditional language) was found in articles on biology or cause, intervention or treatment, and in journals from the medical field. This finding is consistent with views within these areas that being autistic is a disorder or pathology, and it may more closely align with the experiences of some caregivers for people on the autism spectrum with severe intellectual disability.^55,57

Relatedly, more TML was associated with studies that included autistic youth, parents, siblings, and other clinical groups. Autism research has a long history of focusing on childhood experiences and via informant report (e.g., parents), so researchers taking this approach likely adhere to TML common to this literature.⁸³

These results also suggest that comparing autistic people with their siblings or other clinical groups often positions autistic people within a deficit conceptualization that presumes inferiority.^17,47,84,85 This is not to say a strengths-perspective cannot include autistic youth or their family members, but these comparisons should be used to inform hypotheses of strengths and differences rather than (or in addition to) deficits.

Terminology use also differed based on journal language guidelines, with greater ANL in journals that included guidelines for affirming language when referring to disabled or autistic people. Journals that explicitly call for the use of neuro-affirming language may attract submissions from authors whose views already align with the neurodiversity paradigm, or use of ANL may increase through the review process. Yet, guidelines that were more general, or recommendations for mixed language (e.g., IFL or PFL per the APA), did not significantly impact language use.

Thus, journal editors who wish to encourage ANL should be explicit in their guidelines. Importantly, we also note that these findings are in contrast to a prior review by Arnhart et al.,⁹⁷ which found that journal guidelines did not impact autism language use. However, there are two methodological differences that offer important considerations.

First, Arnhart et al.⁹⁷ examined use of “Person Centered Language” (PCL), defined as the combined use of PFL (“person on the autism spectrum,” who “is autistic,” or who “has autism”) or IFL (“autistic person”), versus use of non-PCL labels (“disabled person” or other adjectives identified as stigmatizing). In addition, Arnhart et al. examined the impact of professional language guidelines (e.g., AMA/APA), publisher's guidelines, independent journal guidelines, or no guidelines.

Here, we find greater clarity when differentiating between ANL and TML (including IFL and PFL, respectively) in the context of both the outcome of interest as well as for journal language guidelines.

Finally, there were geographic differences in language use. Although most studies were published in international journals, those published in journals specific to Australasia or Europe had more ANL. These findings broadly align with literature purporting cultural differences in stigmatization of autistic and disabled people,¹² and more specifically with greater acceptance of autistic people in Europe or by White individuals.^90,91

Prior studies examining language preferences report differences by country,³³ or when surveying some non-English speakers.^29,30 The intersection of regional views on disability complicates definitive use of a prescribed lexicon for referring to autistic people in research. It will be crucial for ongoing examination of and recommendations for terminology within the field to consider regional and cultural preferences.

Implications for research and practice

Review of terminology use within autism research has many direct applications. First, findings indicate that language use varies according to both article and journal characteristics, emphasizing the impact of work from individual researchers and their teams as well as by journal editors and reviewers. Indeed, peer-reviewed literature is consumed within a position of privilege that sets the tone for other researchers, practitioners, and trainees.

Importantly, language used in research likely also transfers to public discourse (e.g., news outlets), having a broader reach of impact and further highlighting researchers and editors as possible gatekeepers of shifting appropriate dialogue surrounding autistic people.^77,92

Professionals in all fields have a responsibility to use affirming language, inclusive of disability and other minority identities and experiences. Recognizing that preferences differ, researchers and practitioners should make every effort to ascertain and use an autistic person's preferred language while retaining clinical accuracy.

The importance of following terminology preferences from those with lived experience is repeatedly emphasized related to gender and sexual orientation,^98,99 as well as race and ethnicity,^100,101 and must now extend to autistic and otherwise neurodivergent people.^49,102

Although it may not be possible to gather views from autistic people with profound communication support needs or intellectual disability, researchers are encouraged to incorporate majority preferences on language use and avoid using potentially harmful or pathologizing language.¹⁴ Additional research is needed that examines the impact of language choices on community perceptions, clinical decisions, and the experiences of autistic people. The present study may serve as a guide for common terms to assess in future studies.

Consideration of language preferences and views about autistic people should also incorporate the intersectionality of the autistic neurotype with other minoritized identities or disabilities, including those with profound intellectual disability. The present review reflects the likely impact of intersecting cultural identity and neurotype on autism-related terminology.

More nuanced work in this area is needed, particularly examining the impact of intersecting identities at the individual level, which may be most relevant in practical application. Beyond specific language use, future research should also examine the utility and social validity of ways that being autistic is conceptualized within other aspects of the field, including diagnostic assessment methodologies and intervention approaches across settings as well as community advocacy efforts.

Limitations

There are several limitations of the present study. First, terminology was coded using software and so it was not possible to consider context, which certainly impacts interpretation. Due to this methodology, we did not include terms from published recommendations if it was necessary to interpret their context (e.g., “neurotypical” should only be used if other forms of neurodivergence are screened out^14,15).

Relatedly, certain terminology was too broad to be adequately documented within this approach (e.g., “difference” has myriad meanings, including related to the autistic phenotype and statistical findings). In addition, our examination is limited by the information available for each article and journal, including article data and current journal guidelines.

The online publication date for each article is only a proxy for manuscript writing timeframe. Similarly, coding for journal guidelines was conducted in January 2023 and it is not known when these guidelines were adopted by each journal. We also note that the final model captured 30% or less of variance explained at each of the article- and journal levels, suggesting there are additional variables that impact the language used to refer to autistic people that we did not capture within the present coding scheme. These could include whether researchers incorporated autistic co-creation or advisement within any aspects of the study, as well as the principal investigator's prior training and background, as well as the influence of co-investigators.

Finally, autism-related terminology is situated within a broader discourse of acceptance and autonomy for autistic people. There is growing perception of opposition between autistic advocates and allistic parents of autistic people with co-occurring profound intellectual disability within the premise that being autistic exists solely within a deficit-based model or as a socially contrived disability.⁵⁷

Bridging this dichotomy, the neurodiversity paradigm clarifies that the autistic neurotype can be both a deficit and a difference.⁵ About one-third of autism researchers hold this more neutral view, although they may still use medicalized language or evince ableist cues within writing.⁹⁵ The language coding herein was based on published guidelines for shifting terminology about autistic people to be more affirming, but does not encompass all possible phrases or represent confirmed delineation of terms.

Rather than focusing on the specific prevalence of ANL or TML, we present the relative use of these terms across the autism literature. We encourage autistic and allistic stakeholders to explore more nuanced views of autism than those afforded by the broad findings in this review, such as by reading perspectives of those in different roles¹⁰³ or through more fine-grained analysis of language preferences or existing literature.

Conclusion

This systematic review of language use in autism research revealed that traditional, medicalized language continues to be the dominant discourse; however, there is a recent increase in the use of alternative terminology, likely stemming from the burgeoning neurodiversity movement. This shift is most apparent in literature on topics that align with autistic preferences, that include self-report and autistic adults, and are published in journals with specific language guidelines.

ANL, preferred by many self-advocates, may offer an expanded semantic toolbox when describing autistic people and likely impacts societal prejudice and views about autistic and disabled people. It is crucial for researchers and practitioners to consider the implications of their language and content choices, and within the context of culture and identity.

Data Availability Statement

Data for all analyses and analytic code are available via open science sharing at https://osf.io/dt48p.

Footnotes

Authorship Confirmation Statement

S.B.B. and H.E.M. contributed equally to this paper as co-first authors. S.B.B. initially conceptualized the idea; S.B.B. and H.E.M. expanded the conceptualization together, and both engaged in literature review and initial study methodology. H.E.M. led implementation of the search strategy and analytic efforts, including software selection, statistical analyses, and data visualization. K.A.B. managed PRISMA guideline tracking and reporting and data extraction agreement. All authors contributed to data extraction (see the section) and writing the original draft, and also edited and approved the final version for publication. The article has been submitted solely to Autism in Adulthood and is not published, in press, or submitted elsewhere.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this study.

Supplementary Material

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