Challenges Autistic Individuals Face at Work Systematic Review

J Autism Dev Disord. 2019; 49(8): 3387–3400.

A Systematic Review of What Barriers and Facilitators Prevent and Enable Physical Healthcare Services Admission for Autistic Adults

David Stonemason, ⁱ Barry Ingham,^ane, ² Anna Urbanowicz,ⁱⁱⁱ Cos Michael,^iv Heather Birtles,⁵ Marc Woodbury-Smith,^1, ⁱⁱ Toni Brown,² Ian James,⁶ Clare Scarlett,⁷ Christina Nicolaidis,⁸ and Jeremy R. Parr^1, ²

David Mason

ⁱInstitute of Neuroscience, Newcastle Academy, Sir James Spence Found level 3, Royal Victoria Infirmary, Newcastle upon Tyne, NE1 4LP Britain

Barry Ingham

¹Institute of Neuroscience, Newcastle University, Sir James Spence Institute level 3, Royal Victoria Infirmary, Newcastle upon Tyne, NE1 4LP Uk

²Northumberland, Tyne & Wear NHS Foundation Trust, Newcastle upon Tyne, Uk

Anna Urbanowicz

³Global, Urban and Social Studies, RMIT University, Melbourne, VIC Australia

Heather Birtles

⁵Newcastle University, Newcastle upon Tyne, Britain

Marc Woodbury-Smith

¹Institute of Neuroscience, Newcastle University, Sir James Spence Establish level 3, Imperial Victoria Hospital, Newcastle upon Tyne, NE1 4LP U.k.

^twoNorthumberland, Tyne & Article of clothing NHS Foundation Trust, Newcastle upon Tyne, UK

Toni Brown

²Northumberland, Tyne & Wear NHS Foundation Trust, Newcastle upon Tyne, Great britain

Ian James

^sixCampus for Ageing and Vitality, Newcastle General Hospital, Newcastle upon Tyne, UK

Clare Scarlett

^sevenNHS Due north Tyneside CCG, North Shields, United kingdom

Christina Nicolaidis

^viiiPortland State Academy, Portland, USA

Jeremy R. Parr

¹Constitute of Neuroscience, Newcastle University, Sir James Spence Institute level 3, Majestic Victoria Hospital, Newcastle upon Tyne, NE1 4LP United kingdom of great britain and northern ireland

²Northumberland, Tyne & Article of clothing NHS Foundation Trust, Newcastle upon Tyne, Great britain

Abstract

Autistic people are more likely to: be diagnosed with a range of physical wellness conditions (i.e. cardio-vascular disease); feel premature mortality (for about disease categories); and experience barriers to finer accessing healthcare. This systematic review sought to identify studies that report on barriers and facilitators to physical healthcare access for autistic people. A total of 3111 records were screened and half-dozen studies were included: two quantitative, two qualitative, and two mixed-methodology studies. Patient-provider communication, sensory sensitivities, and executive functioning/planning issues emerged as important barriers to healthcare. Recommendations for clinicians and those planning services are discussed.

Electronic supplementary fabric

The online version of this article (10.1007/s10803-019-04049-2) contains supplementary fabric, which is available to authorized users.

Keywords: Autism, Adult, Healthcare access, Physical health, Barriers, Sensory sensitivities

In that location is a growing enquiry literature regarding autistic adults, and their life experiences. I focus has been a range of health and healthcare challenges for autistic adults. Autism is associated with a wide range of co-occurring mental health atmospheric condition such as depression and feet (Lever and Geurts 2016). Whilst rates of diagnoses and full general population comparisons are difficult due to measurement and sampling problems (Howlin and Magiati 2017), autistic people are more probable than the full general population to experience elevated rates of co-occurring mental health weather (Croen et al. 2015; Howlin and Magiati 2017). In addition, in that location is an elevated rate of co-occurring physical health weather compared to the general population (Cashin et al. 2018). For instance, data propose that autistic adults compared to non-autistic people, are more likely to be diagnosed with epilepsy, cardiovascular disease (i.e. dyslipidaemia, hypertension,), and diabetes (Croen et al. 2015).

There is an elevated run a risk of premature mortality for autistic people compared to the general population. Using two nationwide population-based Swedish registers Hirvikoski et al. (2016) reported significantly elevated rates of bloodshed for autistic people compared to the general population (Hirvikoski et al. 2016). Further analysis of cause-specific mortality revealed that for all recorded categories of disease, except infection, autistic people were at a greater risk of mortality compared to the general population (i.e. OR = three.7 for endocrine, OR = one.5 for circulatory arrangement, or OR = iii.iii for digestive system diseases). These findings were similar to rates in Denmark, with comparable sample sizes (Schendel et al. 2016).

Regarding service utilise, autistic people are more likely to admission some healthcare services compared to the general population. Vohra et al. (2016) reported autistic people fabricated significantly more emergency department visits (for both physical and mental health reasons) compared to the general population (although fewer visits for booze and substance misuse disorders, and respiratory disease) (Vohra et al. 2016). Results from a recent study comparison health records for 1507 autistic people and xv,070 members of the general population indicated autistic people were 2.1 times more than likely to attend an outpatient healthcare visit (Zerbo et al. 2018). A separate study found that younger autistic adults were more likely to visit a general practitioner (OR = 1.27) or exist hospitalised (OR = 2.75) compared to historic period-matched general population controls (Weiss et al. 2018). Nonetheless, autistic adults are significantly more than likely to report unmet healthcare needs, and lower healthcare cocky-efficacy, compared to the general population (Nicolaidis et al. 2013) and there remain variabilities in which services are accessed: For instance, autistic people may be more likely than the general population to admission a screening service for diabetes but not prostate, cervical, or breast cancer screening (Zerbo et al. 2018). This elevated utilize of services may reflect autistic people trying to notice a healthcare provider with a expert level of noesis almost autism (Unigwe et al. 2017; Zerbo et al. 2015, 2018).

Many factors potentially chronicle to effective wellness intendance for autistic people. Survey and interview data show many healthcare providers do not have sufficient skills or tools to finer treat autistic people (Zerbo et al. 2015); providers may not receive formal autism related grooming (Unigwe et al. 2017). A big survey recently found autistic people reported significantly lower satisfaction with patient-provider communication, and healthcare self-efficacy, and had significantly more unmet needs compared to the full general population (Nicolaidis et al. 2013). Communication is a two fashion process, and whilst social advice is a core difficulty for autistic people, professionals may non capeesh the demand to adapt their communication style to communicate effectively with autistic people—or be unable/unwilling to exercise so. For case, some healthcare providers are non amenable to the utilize of augmented advice; assuming the autistic patient cannot attend the appointment without a relative or carer (Nicolaidis et al. 2015).

Taken together, the research literature suggests autistic people have an increased prevalence of some wellness conditions; those contribute in part to the increased rates of premature bloodshed; and in that location are numerous barriers preventing autistic people from effectively engaging with the appropriate healthcare practitioners to increase the likelihood of their health needs being met. Recently a UK community priority setting exercise identified 'How should service delivery for autistic people be improved and adapted in order to encounter their needs?' as a research priority (James Lind Brotherhood 2016). In that context, understanding the barriers to healthcare access is central to implementing changes to services.

The objective of this review was to systematically review and synthesise the current inquiry into the barriers and facilitators to healthcare access experienced by autistic people. The specific question addressed by this review was: 'what barriers and facilitators forbid and enable physical healthcare services access for autistic adults?'

Review Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used throughout the review (Moher et al. 2009), which was registered on PROSPERO (the international prospective register of systematic reviews: www.crd.york.air conditioning.uk/prospero/). ID CRD42018110516.

Review Criteria

Peer-reviewed quantitative (i.due east. randomised command trials, observational studies), qualitative (i.e. interview or focus grouping) studies, and mixed methodology studies, published in English from whatever country of origin were eligible for inclusion in the review. The inclusion criteria were: Studies including or relating to autistic adults aged xvi years and over (primary sample/discrete sub-sample), or studies including a quantitative or qualitative description of barriers to physical healthcare access, or characteristics that promoted access to physical healthcare for autistic people. Studies that investigated which services autistic people access/are more probable to access were not eligible for inclusion. To decide whether a paper should be included, the first author, and HB, used a conclusion matrix. This matrix consisted of key questions to address the inclusion/exclusion criteria consistently (see Supplementary material Table S1).

Search Strategy

The authors designed and piloted the initial search strategy and search terms and consulted relevant experts to refine them further. The final list of search terms independent fundamental words taken from the literature and MeSH (Medical Field of study Headings) terms.

The showtime author searched the following databases: CINAHL, Web of Science, MEDLINE, Embase, and PsychINFO. Searches were limited to post 1994 to comprehend the DSM IV and DSM-v eras. Central search terms, in different permutations, were: autis*, Asperge*, developmental dis*, barrier, facilitator, booster, adjustment, accommodation, access*, utili*, healthcare, commitment of intendance, delivery of healthcare, health checks, wellness services, general practitioner, physician, primary healthcare. In parallel, experts in this surface area were contacted, and a search of Google Scholar and relevant policy and health reports was conducted to place additional citations.

The initial search, removal of duplicates, and full text read-throughs was completed by 31st October 2018. All searches were rerun from the 1st November 2018 up to the 24th of Jan 2019. No boosted papers were included.

Study Selection Process

Later on excluding duplicates, the showtime author screened articles by title and abstruse against the inclusion criteria. A 2nd reviewer, HB, checked a randomly selected 10% of the abstracts against the inclusion criteria to investigate agreement (99.6%). The showtime author then completed a full text read through of each study against the inclusion criteria. Several articles were thought to partially meet the inclusion criteria; the last determination was decided by group consensus by all authors.

Data extraction for the final sample of studies was completed using a information collection form to record study sample size, population, design, whatsoever intervention(s) and issue measures used, and the main findings. If farther information was required, corresponding authors were contacted for clarification.

Assessment of Methodological Quality

Studies included in the final information synthesis were evaluated for methodological quality. This was conducted independently past 2 reviewers (ii-way intraclass correlation coefficient = 0.97, p< 0.001 indicated excellent agreement of ratings). For all studies the methodological reliability and validity was evaluated using the Quality Cess Tool for Studies with Diverse Designs (QATSDD) (Sirriyeh et al. 2012). This is a 16-particular tool with 14 items relevant to quantitative or qualitative studies (all xvi items were scored for mixed-methodology studies). Each detail is scored from 0 to 3, thus quantitative or qualitative scores tin can range from 0 to 42, or 0–48 for mixed-methodology studies. This tool was selected as, a priori, information technology was expected that included studies would utilize a range of methodologies, and the QATSDD offers a numerical score for comparisons.

Information Synthesis

We chose a narrative approach to data synthesis because we expected, a priori, to find few quantitative studies and that any quantitative studies would include highly heterogeneous operationalisation of 'barriers'. Furthermore, it was expected that qualitative synthesis would represent the qualitative research well-nigh effectively.

Results

Study Selection

The search strategy yielded a total of 5192 records. After removing duplicates, a total of 3038 records were screened by championship and abstruse. A full of 3006 records were excluded at this phase. This left 32 studies for a total text review. Post review, six studies were included. The most common reason for exclusion was a lack of autistic participants. This is considering the search strategy immune for the inclusion of studies that included people with intellectual inability (who may or may not take included sub-samples of autistic participants). None of the studies describing intellectual disability participants met the inclusion criteria as they did not report the number of autistic people, or present the findings from autistic people. Come across Fig.one for a flowchart of the search process, and list of reasons for exclusions.

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PRISMA diagram showing the process used to identify studies, written report search and selection

Study Characteristics

Of the half-dozen papers selected, two were qualitative (Dern and Sappok 2016; Nicolaidis et al. 2015), two were quantitative (Raymaker et al. 2017; Vogan et al. 2017), and two used mixed-methods (Nicolaidis et al. 2016; Saqr et al. 2018). Sample sizes ranged from 10 (Saqr et al.'southward focus group; Saqr et al. 2018) to 209 (Raymaker et al. 2017). The combined sample size of autistic adults was 683; three studies (Nicolaidis et al. 2015, 2016; Raymaker et al. 2017) included 229 not-autistic supporters, clinicians, adults with disabilities, and adults without disabilities. 1 study did not provide sample size data (Dern and Sappok 2016). Table 1 describes the included studies.

Table i

Description of the focus, method and main findings from the included studies

Report	Population	Focus	Research type and study design	Findings
Nicolaidis et al. (2015)	39 autistic adults (who study an autism spectrum diagnosis); hateful age 35 years (19–64) xvi supporters of an autistic person(s); mean age 52 years (28–74)	To obtain an in-depth understanding of autistic adults' experiences with healthcare and their recommendations for improving care	Qualitative. Individual interviews (participants could reply to questions via phone, e-mail, or instant messenger); thematic analysis with an inductive approach at a semantic level	Identifies 3 clusters of barriers: Patient-level factors (e.1000. verbal communication skills, slow processing speed); provider-level factors (e.g. cognition nigh autism in adults, use of accessible language); and arrangement-level factors (e.g.. availability of formal/breezy support, stigma about autism)
Dern and Sappok (2016)	Autistic self-advocates and autism professionals (sample size and limerick are not described)	The available experiences of autism self-advocates and clinical experiences of practitioners	Qualitative. Summation of key meetings from a 5 yr (2006–2011) series of meetings between autism self-advocates and healthcare professionals	Identifies barriers to healthcare for autistic people (i.e. difficulties making phone calls, lack of fourth dimension to call up/respond or use written notes). Recommends how professionals can improves healthcare for autistic adults (i.due east. culling methods to make appointments, let patient to make notes/record discussions)
Nicolaidis et al. (2016)	259 autistic adults who took part in cognitive interviews (n = 30, mean historic period 37.half dozen years, twenty–64), test–retest reliability (n = 59, mean historic period 34.half-dozen, 18–64), pre- and post-intervention surveys (north = 170, mean historic period 36.5, eighteen-68); 51 primary care providers who took role in cognitive interviews (n = 10, mean age 41.half-dozen, 27–61), and a post-intervention survey (n = 41, hateful age 36.three, 28–62)	Using community-based participatory research to create and evaluate an online healthcare toolkit for autistic adults and their master care providers	Mixed methodology. Cognitive interviewing and test–retest studies. Toolkit evaluation was a single arm pre-/mail-test intervention comparing of surveys with closed- and open up-ended items	Most all autistic participants and supporters rated the Toolkit as piece of cake to use, important, and useful Most primary care providers rated the Toolkit equally moderately or very useful and indicated they would recommend it to their patients Over the course of the intervention the number of self-reported barriers to healthcare reduced significantly from a mean of 4.i to 2.eight (with healthcare self-efficacy scores likewise increasing significantly from 37.nine to 39.4 and satisfaction with patient-provider communication scores increasing significantly from 30.ix to 32.6)
Raymaker et al. (2017)	209 autistic adults (mean age 37 years, SD = 13); 55 adults in a disability grouping (mean age 45, SD = fourteen); 174 adults in a non-autistic non-disabled group (hateful historic period 38, SD = 12)	Identify and compare barriers to accessing healthcare experienced by autistic adults and adults with, and without other disabilities	Quantitative. Cross-sectional instrument development and validation (Long- and Short-Form Barriers to Healthcare Checklist)	Autistic adults and adults with other disabilities endorsed significantly more than barriers than the not-autistic adults without disabilities. Autistic adults selected a different pattern and a greater number of barriers that adults with other disabilities, peculiarly in areas related to emotional regulation, patient-provider communication, sensory sensitivity, and healthcare navigation
Vogan et al. (2017)	40 autistic adults (mean age 35.nine, SD = eleven.vii)	Autistic adults access of healthcare services, experiences of accessing healthcare services, barriers to service utilize, and reported unmet service needs	Quantitative. Longitudinal study over a 12-18 month time frame, with participants completing measures every ii months	The nearly commonly reported barriers by participants were not knowing where to detect help (65.viii%), overwhelming steps to seek help (52.6%), and negative experiences with professionals (47.four%). Over 75% endorsed three or more barriers to healthcare. Those with medical problems reported significantly more barriers to healthcare than those without (five.12, SD = ii.65; 3.20, SD = 2.25 respectively)
Saqr et al. (2018)	126 autistic adults who took part in a retrospective chart assay (mean historic period 21.2, SD = 5.6); ten autistic adults who took part in a focus group (ages xviii–30)	Ecology and process barriers to care access in a primary care setting and to examine medication use in the sample	Mixed methodology. Cross-sectional retrospective nautical chart assay; focus grouping	74 individualised plans were created for patients. The about common adjustment was taking the patient to the test room upon inflow and completing registration at that place (n = 16) Focus group data highlighted the nearly stressful parts of the healthcare visit: waiting (both in the waiting room and examination room, and the examination). Furthermore a negative feedback loop (fear of social interaction, heightens anxiety and overstimulation which makes social interaction difficult) was identified

Results of Individual Studies

Qualitative studies: Two qualitative studies (Dern and Sappok 2016; Nicolaidis et al. 2015) investigated the experiences of autistic adults when accessing healthcare. Nicolaidis et al. (2015) also recruited a sample of supporters of autistic adults as they may be the main communicators with healthcare professionals when the person they support accesses healthcare. Dern and Sappok (2016) collected data from an existing collaboration betwixt autistic self-advocates and healthcare professionals treating autistic people. Both studies identified an extensive list of barriers that impair or preclude autistic people from accessing health care, and recommendations for improving healthcare provision.

Each study identified a set of barriers and a unique taxonomy of these barriers. Nicolaidis et al. (2015) identified patient-level factors (i.e. exact advice skills, sensory sensitivities, trunk awareness, slow processing speed, singular non-verbal communication, and challenges with organisation); provider-level factors (i.e. cognition nigh autism in adults, incorrect assumptions, flexibility in following the patient's preferred communication mode, use of adequate language, openness to proving accommodations, and skills in incorporating supporters); and systemic-level factors (i.e. bachelor formal or breezy supports, complexities and accessibility of the healthcare service, and stigma about autism). In comparing, Dern and Sappok (2016) identified v sets of barriers: making appointments (i.due east. telephone calls can be challenging); waiting area (i.due east. uncertain wait times, proximity of other patients, overly-stimulating noise level/lighting); examination (i.e. discomfort with unannounced impact, singular presentation and feel of pain); advice (i.due east. open-ended questions causing stress, patient cannot use written notes, idiosyncratic or hyper-specific language); hospital (i.due east. constantly irresolute staff, non being admitted due to rigid thinking about what is happening at home); and sensory difficulties (i.e. prosopagnosia, sensory overload through traveling to, or beingness at, appointments).

Quantitative: Ane quantitative study tracked the healthcare utilize, satisfaction with healthcare, and barriers to accessing healthcare by a sample of autistic adults (Vogan et al. 2017). A 2nd report described the evolution and validation of a measure of barriers to accessing healthcare (Raymaker et al. 2017). Each study addressed a different research question withal common barriers to healthcare were identified.

Raymaker et al. (2017) adapted an existing mensurate of barriers to healthcare used with disability populations. Using a community-based participatory research arroyo, the research team modified items for accessibility and added autism-specific barriers identified in previous research (Nicolaidis et al. 2013, 2015). The terminal version of the measure out showed acceptable content and construct validity (as established by the research team and the pattern of item endorsement respectively). The long-form of the measure consists of 41 items across nine domains: emotional (i.eastward. frustration/acrimony, lack of confidence); executive function (i.e. organising appointments, translating medical pedagogy in practicable steps); healthcare navigation (i.e. observe information technology too difficult to navigate managed care, bug with paperwork); provider attitudes (i.e. providers chronicle new symptoms to existing conditions, providers are unwilling to use the patient's preferred communication fashion); patient-provider communication (i.due east. difficulty communicating with providers, trouble post-obit spoken instructions); sensory (i.e. healthcare facilities cause sensory overload); socio-economic (i.e. concerns about costs, insurance does not cover atypical therapies); back up (i.east. socially isolated, lack of bachelor back up); and waiting (i.e. waiting rooms are hard to manage). The short course of the measure consists of 17 items. The short-form items cover the same nine domains as the long-form measure; items were created past collapsing conceptually similar items into 1 particular and removing more general items in favour of more than specific items (Raymaker et al. 2017).

Vogan et al. (2017) reported similar barriers, e.thou. non knowing where to find help, too many steps to finding help, and negative experiences with healthcare staff. Furthermore, Vogan and colleagues noted that around iii quarters of participants could non admission healthcare they needed, and over 3 quarters reported 3 or more barriers to healthcare admission. Moreover, those experiencing physical health conditions reported almost twice the corporeality of barriers to healthcare than those without medical conditions.

Mixed-methods: Ii studies (Nicolaidis et al. 2016; Saqr et al. 2018) sought to measure barriers to healthcare access, augmenting survey data with descriptive accounts (interviews and focus groups) from autistic people and, for Nicolaidis et al. (2016), master intendance providers. Saqr et al. (2018) conducted a retrospective medical record review of patients attending a chief care facility set up to facilitate transition for autistic people (Saqr et al. 2018); Nicolaidis et al. conducted a single arm pre-/post-intervention evaluation of an online toolkit, the Autism Healthcare Accommodations Toolkit (AHAT) using surveys of autistic patients and their providers (Nicolaidis et al. 2016). Saqr et al. nerveless qualitative information about the clinical experience of autistic people and Nicolaidis et al. also used cognitive interviews to assess the content validity of the AHAT.

One study, Saqr et al. (2018) used a standardised pre-visit assessment to identify possible barriers to a successful healthcare visit. An individualised plan was then made for patients who may experience such barriers. Saqr et al. reported that 23% of the patients in their sample (n = 17) had some class of individual plan. Qualitative data identified three sets of problems that interact with the healthcare visit. Participants suggested that sensory sensitivities made bank check-in and the waiting room a stressful feel. Feet from waiting fabricated the waiting in the examination room and talking with the healthcare provider challenging. Participants suggested that lack of mutual agreement, advice, and trust made both the examination and treatment chat more stressful. The authors then proposed that a negative feedback loop of social interaction developed during the healthcare visit. In brief, fear of social interaction drives anxiety and stress, which in turn heightens sensory sensitivity and overstimulation. This impacts concentration and makes social interaction more difficult, consequently increasing fear of social interaction. Nicolaidis et al. designed the AHAT to be completed by an autistic person or their supporter. The items were generated from previous inquiry into healthcare barriers (Nicolaidis et al. 2013, 2015). The patient completes the sections of the AHAT: How you communicate; Advice suggestions; Earlier the visit; During the visit; Later on the visit; Getting to know you; and Your supporters. The AHAT then generates an individualised report than can exist shared with the primary care provider. From the cognitive interviews, both autistic people and master care providers responded positively to the AHAT, rating it equally helpful and stating information technology included a comprehensive list of accommodations. Autistic people reported feeling more than validated in their experiences and more able to cocky-abet. Main intendance providers said they would recommend it to other autistic patients. The AHAT significantly reduced healthcare barriers over the course of the evaluation intervention, as measured by the Barriers to Healthcare Checklist—Short Form, and increased satisfaction with patient-provider communication. Open-ended questions suggested that the toolkit empowered patients' self-efficacy and that patients noted some changes in primary care providers' behaviour. Whilst some patients reported that their master care provider did not read the AHAT or did not change their practice after receiving information technology, most chief care providers in the evaluation rated the AHAT as moderately or very useful.

Synthesis of Results

Research investigating barriers to healthcare for autistic adults to appointment has used a various range of methodologies and measures. Qualitative studies have been used to elicit the lived experiences of autistic adults when accessing healthcare, providing recommendations for improving healthcare, and to posit tentative models of the healthcare visit. Furthermore, qualitative information has been integrated into validating measures of healthcare barriers. All studies included samples of autistic adults (aggregate age range approximately eighteen-64). One report compared autistic adults to the general population and to not-autistic people with other disabilities groups (Raymaker et al. 2017); ii studies but included autistic participants (Saqr et al. 2018; Vogan et al. 2017); three studies included groups of supporters (Nicolaidis et al. 2015) or healthcare professionals (Dern and Sappok 2016; Nicolaidis et al. 2016).

Despite diverse measures of barriers (for quantitative studies) and interview guides (qualitative studies), a consistent prepare of obstacles emerged across studies (see Table2). Communication with healthcare providers was reported across five studies every bit a barrier to healthcare (Dern and Sappok 2016; Nicolaidis et al. 2015, 2016; Raymaker et al. 2017; Saqr et al. 2018). Advice difficulties included: checking into a healthcare visit (Saqr et al. 2018), communicating with the primary intendance provider (Dern and Sappok 2016; Nicolaidis et al. 2015; Saqr et al. 2018), or providers not respecting the autistic person's preferred advice method (Dern and Sappok 2016; Nicolaidis et al. 2015). Negative experiences with healthcare providers was also a prominent barrier (Nicolaidis et al. 2015). Vogan et al. plant that 47.four% of their sample reported such experiences (Vogan et al. 2017).

Table 2

Barriers to healthcare admission reported across studies (listed in society of consistency of findings across studies)

Barrier(due south)	Studies
Barrier(due south)	Nicolaidis et al. (2015)	Dern and Sappok (2016)	Nicolaidis et al. (2016)	Raymaker et al. (2017)	Vogan et al. (2017)	Saqr et al. (2018)
Communication (i.e. singular advice, literal interpretation, making appointments)	+	+	+	+		+
Sensory Sensitivities (including the waiting room, physical examination)	+	+	+	+		+
Challenges with bodily awareness (i.e. difficulty describing pain or symptoms)	+	+	+	+	+
Providers' degree of flexibility (i.e. allowing written communication, using accessible linguistic communication, making needed accommodations)	+	+	+	+		+
Slow processing speed (i.e. during social interaction) or executive functioning (i.e. cocky-regulating medication, missing appointments)	+	+	+	+
Providers' negative attitudes (i.e. misinterpreting behaviours, advice is non taken seriously)	+		+	+	+
Availability of supports (both formal and informal; fearfulness of social isolation)	+		+	+	+
Healthcare system is besides complex or inaccessible (including not knowing where to discover help)	+		+	+	+
Emotional (i.e. anxiety or embarrassment)*			+	+	+	+
Challenges with organization (i.east. remembering to take medication, making or attend appointments)	+	+	+	+
Need for consistency (i.e. seeing the same staff)	+	+	+
Providers' (lack of) knowledge most autism in adults (including making assumptions about behaviour, or defective confidence in treating autistic patients)	+		+	+
Negative experiences with healthcare (including lack of trust in professional person help, not including the autistic patient in healthcare discussions)	+			+	+
Stigma about autism	+		+		+
Other societal issues that impact health (including socio-economic factors)	+			+
Highly variable needs of autistic people			+			+
Distance too far to become assist				+	+
The problem did not seem so serious					+
Want to handle the problem ourselves [the autistic person]					+
Likewise busy/other priorities					+
Problem was considered temporary					+
Other people did not want the family to seek help					+

+ Barrier is reported by this study

Nicolaidis et al.'due south qualitative study provided rich data regarding barriers to healthcare. This study reported that healthcare providers' knowledge about autism can act as a bulwark to healthcare. For example, qualitative reports from autistic adults advise that many healthcare providers do not know what autism entails and hence how treatment may need to be adapted (Nicolaidis et al. 2015). One key finding, relevant to clinicians, is that assumptions made by healthcare providers based on the presentation of the autistic patient (Nicolaidis et al. 2015). For example, if the autistic patient requests that healthcare providers utilize an alternative communication device and so they may assume the patient lacks the ability to comprehend what is said. Culling advice preferences have been reported in several studies. For case, written notes may be preferred due to challenges with verbal and non-exact communication (Dern and Sappok 2016).

Sensory sensitivities were a prominent barrier across v studies (Dern and Sappok 2016; Nicolaidis et al. 2015, 2016; Raymaker et al. 2017; Saqr et al. 2018). Unlike aspects of the healthcare visit are associated with sensory sensitivities. For case, the waiting room (Dern and Sappok 2016; Nicolaidis et al. 2016; Saqr et al. 2018), unpredictable waiting times (Nicolaidis et al. 2016; Saqr et al. 2018), travelling to appointments (Dern and Sappok 2016; Saqr et al. 2018), lighting and environmental factors (Nicolaidis et al. 2015; Saqr et al. 2018) tin can all contribute to sensory overload. Interestingly, Saqr et al.'s qualitative data suggest that the stress and anxiety almost a healthcare visit begins prior to the visit (i.e. at home, or when travelling to the healthcare venue) (Saqr et al. 2018).

Finally, a prepare of intra-person factors were reported across several studies as barriers to accessing healthcare. These included a slower processing speed when talking with providers (Nicolaidis et al. 2015) which could hamper 'real-time' interactions during an appointment (Raymaker et al. 2017). Less oftentimes mentioned, but important none the less, were problems of information processing and retentiveness. Raymaker et al.'s Barriers to Healthcare Checklist included a domain about executive functioning (i.due east. remembering to attend appointments or take medication) and difficulties with completing paper piece of work were noted (Nicolaidis et al. 2015; Raymaker et al. 2017).

Methodological Quality of Included Studies

Many studies relied on self-reported diagnoses of beingness on the autism spectrum. For instance, Nicolaidis et al. (2015, 2016) required that participants report a formal or medical diagnosis of autism, Asperger's syndrome, pervasive developmental disorder not otherwise specified, or autism spectrum disorder. Nicolaidis et al. (2015) too allocated a portion of their sample to those who self-identified every bit being on the autism spectrum, with the autism quotient (AQ; Businesswoman-Cohen et al. 2001) used as a screen to indicate autistic traits. Raymaker et al. (2017) also recruited participants who identified equally being on the autism spectrum (Raymaker et al. 2017). For their retrospective chart analysis Saqr et al. (2018) identified all patients who attended a specific healthcare provider between April 2014 and April 2015, and autism diagnosis was confirmed by a review of medical records and psychological evaluation (Saqr et al. 2018). Finally one study did not provide whatsoever participant information (Dern and Sappok 2016).

Quantitative measures used in the included studies were highly heterogeneous, and in some cases not validated for use with this population (or authors did not comment on the measures' validities). Four studies used quantitative data drove methods in their designs. Two of these studies sought to validate a measure or tool for use with autistic adults accessing healthcare (Nicolaidis et al. 2016; Raymaker et al. 2017). The initial validation findings were promising, suggesting that each tool is appropriate for utilize with autistic participants in future studies or interventions. One study looked at retrospective chart analyses for every patient attending a specific healthcare provider over a 12 month menstruation (Saqr et al. 2018). The complexity of each patient's medication regimen was analysed. The authors do state the mensurate of complication is valid for use with chronic illness, but the mensurate of medication regimen complexity has not nevertheless been validated for use with autistic people. Finally, Vogan et al. used several measures including the Kessler Psychological Distress Scale-6 and the Demand for Aid Questionnaire (Vogan et al. 2017). One measure out of service utilise was created by the research squad ('service utilize'). Neither the Kessler Psychological Distress Scale-6 nor the Need for Help Questionnaire have been validated for the autistic population.

Discussion

We identified vi papers investigating the barriers and facilitators to healthcare as reported past autistic adults. Despite the limited literature, there are similar barriers and facilitators reported beyond the six studies; efforts to devise interventions and measurement tools are underway, and initial steps towards evaluating the effectiveness of implementing change have been evidenced (Nicolaidis et al. 2016; Dern and Sappok 2016; Saqr et al. 2018; Vogan et al. 2017; Nicolaidis et al. 2015; Raymaker et al. 2017).

Nicolaidis et al. reported that exact communication skills were an autism-related cistron affecting healthcare access (Nicolaidis et al. 2015). Social or communicative atypicalities are part of the diagnostic criteria for autism spectrum conditions (McPartland et al. 2012), all the same, autistic people brandish highly heterogeneous profiles of social and communicative power (Frazier et al. 2012). Thus, social advice accommodations required by autistic patients are probable to exist highly heterogeneous and unique to each patient. General difficulties in exact and not-verbal advice can human action as a barrier to healthcare, or a lack of initiative in reporting medical conditions (Dern and Sappok 2016). Past way of instance, literal interpretation of language was reported to impair some autistic people's ability to answer questions near, for instance, quantifying pain (Nicolaidis et al. 2015). These findings suggest that healthcare practitioners should be sensitive to the communication atypicalities associated with autism spectrum weather. A 'one size fits all' arroyo to patient interaction is unlikely to work for autistic people; hence efforts to create individualised reports tailored to the autistic patient's needs (Nicolaidis et al. 2016; Hislop et al. 2016). Given autistic patients are more than likely to report barriers to healthcare compared to both adults with disabilities (vision/hearing, mobility, learning/remembering, activities of daily living, leaving home alone, working at a chore) and non-autistic adults without disabilities (Raymaker et al. 2017), such attending to individual needs may reduce barriers to healthcare (Nicolaidis et al. 2016). For example, negative experiences with healthcare providers (Vogan et al. 2017) and 'agin events' that might affect medical procedures (i.due east. measuring vital signs) or increase feet nearly attending healthcare appointments (Saqr et al. 2018).

Chiefly, these communication difficulties only stand for 1 aspect of barriers to healthcare. Several studies reported different barriers related to stigma or stereotyping, healthcare providers' lack of autism knowledge, healthcare providers' openness to different modes of advice, and trust in professionals. Almost 1 quarter of autistic people in Vogan et al.'south study reported a fear of stigmatisation or labelling (Vogan et al. 2017); although the sample size was small (Northward = 40) this does repeat the findings of other studies that used qualitative methods. For instance, some autistic people who use culling communication devices reported that their healthcare professional doubted the autistic patient's competence (Nicolaidis et al. 2015). Provider attitudes towards autistic patients was discussed in qualitative studies (Dern and Sappok 2016; Nicolaidis et al. 2015) and was a discrete factor in the 'Barriers to Healthcare Checklist- Long Course' (Raymaker et al. 2017). For instance, healthcare providers were reported to make assumptions almost autistic patients from their initial presentation (Nicolaidis et al. 2015), not have into account rigid thinking (Dern and Sappok 2016), or presume behaviours expressing symptoms (i.e. pain) were behaviours more than directly related to autism (Dern and Sappok 2016). These findings are in line with healthcare professionals' self-reporting. For example, 79% of adult medicine, 88% of obstetrics/gynaecology, and 70% of mental wellness professionals in the The states rated their power to provide healthcare to autistic patients as poor or fair (Zerbo et al. 2015). Furthermore, in the United Kingdom 39.5% of general practitioners (due north = 120 out of 304) reported having no formal training in autism, and limited conviction in their ability to offering healthcare to autistic patients (despite having a skilful knowledge of the key features of autism) (Unigwe et al. 2017). Over again, these findings have important implications for healthcare professionals. It is important that healthcare professionals with autistic patients accept the fourth dimension to acquire about autism spectrum atmospheric condition, and the individual needs of autistic patients. Nicolaidis et al. reported that the AHAT was rated positively past master care providers (82% rated it as moderately or very useful) (Nicolaidis et al. 2016).

The last 'global' barrier reported was sensory sensitivities. Autistic people written report elevated sensory processing sensitivity compared to the general population (Crane et al. 2009; Tavassoli et al. 2014). This over-sensitivity is across a range of sensory modalities (sight, sense of taste, touch, sound, smell) and tin can therefore have a pregnant touch on on daily living (Tavassoli et al. 2014). The studies in this review hold with these findings. Compared to both non-autistic adults without inability (vision/hearing, mobility, learning/remembering, activities of daily living, leaving home alone, working at a task) and adults with inability, autistic people endorsed significantly more sensory items (e.g., lights/smells/sounds brand visits uncomfortable or communicate well in healthcare settings) (Raymaker et al. 2017). Lighting (likewise harsh or bright), crowded waiting rooms (noise, smell, proximity of others), and unpredictable waiting times were also reported to be sources of sensory overload (Nicolaidis et al. 2015). Saqr et al. describe a 'feedback' model in which sensory overload reinforces feelings of anxiety, exacerbating communication difficulties when accessing healthcare (Saqr et al. 2018). These findings are important for ensuring the healthcare visit goes well. Healthcare settings should seek to minimise sensory sensitivities where possible. This could include having quiet waiting areas for autistic patients or assuasive autistic patients to wait outside the healthcare building and being brought directly into their healthcare appointment.

The intra-person cerebral factors of processing speed, system, and memory were not extensively mentioned just accept of import implications for healthcare settings. The Barriers to Healthcare Checklist includes items virtually processing speed affecting healthcare discussions and finding it difficult to follow spoken instructions (Raymaker et al. 2017). It is well documented that autistic children struggle to integrate multi-modal sensory information (Marco et al. 2011), or take difficulty processing quickly presented information (Gepner and Mestre 2002). Evidence suggests that autistic adults are amend than the general population at identifying parts of faces, but are poorer at identifying a confront holistically (Lahaie et al. 2006). This is of import every bit healthcare appointments with detailed conversations involve processing three streams of information: verbal (listening to the information), visual (looking at the healthcare provider, which some autistic people detect aversive, Hurlbutt and Chalmers 2002), and processing (thinking nearly the data beingness presented and preparing a exact response). Thus, an autistic developed may be overwhelmed by the demands of maintaining a social chat and thinking through the implications of what they are existence told. Furthermore, prospective retentivity (planning ahead for an event, and remembering to carry it out) may be impaired for autistic people. For example, there are documented problems with timing-based prospective retention (i.eastward. do event x at time y) in both autistic children (Williams et al. 2013, 2014) and autistic adults (Altgassen et al. 2012). Whilst these are experimental data and may not be entirely valid for healthcare settings, the findings do agree with the anecdotal accounts (Nicolaidis et al. 2015) and mensurate development (Raymaker et al. 2017) that was identified by this review. Therefore, information technology is essential that healthcare providers account for these private differences when interacting with autistic patients. Patients may need more support during healthcare appointments with how health information is disseminated, and more support with making and attending healthcare appointments. The AHAT for chief care providers has data nigh communication issues for autistic people, and allows the autistic patient to inform their care provider if they take processing speed issues (Nicolaidis et al. 2016). As the AHAT was shown to significantly subtract barriers to healthcare over time (Nicolaidis et al. 2016), accommodating these differences may improve the delivery of healthcare to, and consequently the wellness of, autistic adults.

Although the age range of participants in the included studies was good (18-64 years) some questions remain well-nigh differences in healthcare access needs beyond the lifespan for autistic people. Currently there is a dearth of research about the characteristics and needs of older autistic adults (Mukaetova-Ladinska et al. 2012; Herrema et al. 2017; Rodgers et al. 2018). Yet, autistic people take many questions virtually how they will experience the ageing procedure and the additional support that will be required. For instance, what is the future like for an older autistic person cared for by elderly relatives? (Michael 2016). There is a wealth of literature about the transition experiences of young autistic people (Adreon and Durocher 2007; Hendricks and Wehman 2009; Taylor and Seltzer 2011). Yet, footling is known almost transitions for older autistic people (Mukaetova-Ladinska et al. 2012; Rodgers et al. 2018). A recent study with autistic adults (hateful age 36 years) identified several factors important to autistic people as they contemplate the time to come (Rodgers et al. 2018). The overarching theme was incertitude near the future, and specifically, worry about support needs and relationships, living circumstances, and health (Rodgers et al. 2018). These findings concord with a contempo survey of 45 individuals who were either autistic individuals or carers of autistic individuals. The survey identified long-term management and sensation of ageing in autism as key research priorities (Mukaetova-Ladinska and Stuart-Hamilton 2015). Taken together, this research highlights the dearth of evidence that could inform healthcare practice for older autistic people. Exploring other literatures could provide a starting indicate for investigation. For instance, dementia research has looked at promoting a positive hospital experience for patients with cognitive impairment (Prato et al. 2018). Prato and colleagues identified themes that determined the quality of the infirmary experience: valuing the person, activities to promote empowerment, and creating a suitable environment to support well-existence (Prato et al. 2018).

None of the included studies included samples of autistic people with intellectual disability (ID). It is feasible that some of the excluded studies did in fact have participants with ID who were as well on the autism spectrum. Even so, this review took the position to just include papers that had reported details about samples (or subsamples) of autistic people. Hence, there could be some strategies to improve healthcare access for autistic people with ID that were not included hither. For instance, toolkits designed to improve healthcare self-efficacy in ID populations (Lennox et al. 2012) could be tested with both autistic people, and autistic people with co-occurring ID.

A last observation is that overarching healthcare 'systems' may affect on healthcare. For instance, Nicolaidis et al. identified organisation level factors affecting access to healthcare (Nicolaidis et al. 2015). These factors included availability of formal or informal supports and the complexities of the healthcare system (for instance the number of 'authoritative hoops' patients have to navigate). Indeed, some autistic people reported they felt that they could not navigate the healthcare system without help (Nicolaidis et al. 2015). This is supported past Vogan et al.'south findings whereby only over 50% of participants reported that the steps to seeking help and about lxx% reported that not knowing where to find assist were barriers to accessing health (Vogan et al. 2017). These findings do suggest that healthcare professionals could alleviate some difficulties for their autistic patients by providing accurate and concise signposting to healthcare services. Signposting to advisable services (i.e. towards services the autistic person needs) has been reported to improve access to a range of services (i.e. education and support) and overall well-being in a non-funded community group (Southby and Robinson 2018). This does suggest that directing autistic people to advisable services does non entail extra costs, and the result could amend effective access to intendance for autistic people.

Overall, the quality of the six included studies was acceptable to adept (60–80%, with one study scoring xx%); even so, they addressed different questions with an array of methods and some observations can be made. Starting time, the total sample size for each written report tended to exist small (i.e. number of participants between 40 and 259), and participants from diverse demographic groups were included (or case, a range of educational attainment and ethnicity, Nicolaidis et al. 2015, 2016; Raymaker et al. 2017); ane study did include participants who were from high-income areas, Vogan et al. 2017). Two studies included people with autism cocky-diagnosis (Nicolaidis et al. 2015; Raymaker et al. 2017); many adults may exist autistic, yet lack a formal diagnosis because electric current adults were less likely to accept received a diagnosis in babyhood (Stuart-Hamilton and Morgan 2011; Lewis 2016). It is possible that those with a cocky-diagnosis face comparable barriers to those with a formal diagnosis, however further inquiry is required to determine this. Every bit such, clinicians should be sensitive, or receptive, to those who self-identify as existence on the autism spectrum. Second, 3 studies used a co-designed approach whereby autistic people were involved in choosing research questions, designing the studies, recruitment, consent process, data collection and analysis (Nicolaidis et al. 2015, 2016; Raymaker et al. 2017). Two of these studies evaluated a new tool. One, to help healthcare providers by creating a argument of individualised healthcare adjustments that could help improve the healthcare date for the autistic patient (Nicolaidis et al. 2016) and the other a checklist to measure barriers to healthcare access (Raymaker et al. 2017). Both of these tools were reported to accept loftier face validity and acceptable measurement properties. It is reasonable to advise that this co-design process was a key component in the success of developing these measures (also, these three studies obtained the highest ratings in the quality assessment). Future studies could emulate this arroyo to make research more accessible for autistic people. Third, there is now a validated checklist that healthcare providers and researchers tin employ to tackle futurity inquiry questions about healthcare barriers with the autism population (Raymaker et al. 2017). 4th, there is not nonetheless a consensus on how to identify and group barriers to healthcare admission. For instance, the Barriers to Healthcare Checklist has eight domains (i.e. emotional, executive performance, support, transportation) (Raymaker et al. 2017). The model proposed by Nicolaidis et al. does encapsulate many, but not all, of these domains (Nicolaidis et al. 2015). This conceptualisation is of import to guide future research coherently, to ensure that a full business relationship of barriers to healthcare is given, and to specify hypotheses for studies. As the research into this area is very contempo (i.eastward. all studies are within the past iii years) more than comprehensive studies are likely to follow.

This review had several strengths. First, the agreement betwixt the two authors who screened papers for the 10% sample of included studies (over 99%) suggests that both the selection criteria and initial screening process were valid. Second, the two authors who independently conducted the quality assessment had a very high caste of understanding. These two points propose the papers included in the final review are likely exhaustive of the bachelor literature and that each newspaper has been evaluated reliably. The search strategy was developed in an iterative way, and so that search terms were refined. Experts in this inquiry area were also included in the evolution of the search strategy. This study utilise the QATSDD to appraise the quality of the included studies. This was selected a priori as a range of study methodologies was anticipated. This measure out allows for a comparison betwixt qualitative, quantitative, and mixed-methodology studies. However, it should be noted that a range of tools for different study types are available and that future studies could employ multiple measures as per study blazon. Because the limitations of this review, first, our review simply identified a small number of papers meeting inclusion criteria. Thus, the barriers and facilitators identified in this review should non be considered definitive. It remains to be seen whether a broader fix of barriers will consistently emerge when further inquiry is conducted. Second, the exclusion criteria set for this written report mean that our review may not have not accept identified some facilitators of healthcare admission used in clinical services. Thus, studies about clinicians' perspectives on healthcare access for autistic people were not included. In the future, studies should explore the perspectives of autistic people, relatives/carers of autistic people, and clinicians about barriers and facilitators to healthcare admission.

Conclusions

This review identified six studies that investigated the barriers to healthcare admission faced by autistic people and ways of addressing those barriers. Although the studies varied in their methodologies, 3 consistent findings emerged. Start, autistic people find inter-personal communication with healthcare providers challenging. This can be due to literal thinking, or other advice atypicalities idiosyncratic to autistic people. Nevertheless, healthcare providers may exist unwilling to empower autistic people to communicate using their preferred communication mode. 2nd, healthcare providers' cognition of autism may be lacking. Autistic people depict stigma and assumptions made about their abilities by healthcare providers. Yet, providers report feeling unable to provide adequate care to autistic patients, and some report a lack of formal training. Tertiary, sensory sensitivities make accessing healthcare difficult for autistic people. This begins in the waiting/reception surface area, and continues through the appointment in a dispensary room. Alleviating these sensitivities for autistic patients is likely to meliorate their healthcare admission. Future research should focus on specifying a robust framework of health care barriers (for case, operationalising what a barrier is, and creating a taxonomy of barriers), and creating tools/environments that can be used in services to reduce barriers in a way that is tailored to the person. In the Britain, the NHS England 10 yr plan recently announced the design and trial of an autism specific health check that volition aim to improve the health care experience of autistic people (National Wellness Service 2019). In the US, the AASPIRE Healthcare Toolkit (www.autismandhealth.org) is being used to address barriers. If these interventions are effective, implementation across health intendance in a range of wellness settings will likely ensure improved admission to usual healthcare for autistic people, and improvements in wellness, quality of life, and life expectancy may follow.

Electronic Supplementary Textile

Beneath is the link to the electronic supplementary material.

Acknowledgments

The review was supported by funding from the Inge Wakehurst Foundation, and the UK autism enquiry charity Autistica.

Author Contributions

All authors designed the search strategy. DM ran the initial searches, screened all titles and abstracts, conducted full-text read through of each article, and conducted the quality assessment. HB carried out a second check of ten% of the manufactures, agreed the content of tabular array 1, and updated the searches. All authors were responsible for drafting the paper and approving the final manuscript.

Compliance with Upstanding Standards

Conflict of interest

The authors accept no conflicts of involvement to declare.

Ethical Blessing

This article does non comprise any studies with human being participants or animals performed by any of the authors.

Footnotes

Publisher's Annotation

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6647496/