This paper is in the following e-collection/theme issue:

Diagnostic Tools in Mental Health (224) Formative Evaluation of Digital Health Interventions (2226) Web-based and Mobile Health Interventions (3128) Technology in Psychiatry/Clinical Psychology Training and Education (26) Design and Usability of Websites for Special User Groups (133) Methods and New Tools in Mental Health Research (428) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (792)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50907, first published .
Developing and Implementing a Web-Based Branching Logic Survey to Support Psychiatric Crisis Evaluations of Individuals With Developmental Disabilities: Qualitative Study and Evaluation of Validity

Developing and Implementing a Web-Based Branching Logic Survey to Support Psychiatric Crisis Evaluations of Individuals With Developmental Disabilities: Qualitative Study and Evaluation of Validity

Developing and Implementing a Web-Based Branching Logic Survey to Support Psychiatric Crisis Evaluations of Individuals With Developmental Disabilities: Qualitative Study and Evaluation of Validity

Authors of this article:

Deborah A Bilder1 Author Orcid Image ;   Mariah Mthembu2 Author Orcid Image ;   Whitney Worsham2 Author Orcid Image ;   Patricia Aguayo1 Author Orcid Image ;   Jacob R Knight2 Author Orcid Image ;   Steven W Deng2 Author Orcid Image ;   Tejinder P Singh2 Author Orcid Image ;   John Davis3 Author Orcid Image
Article Authors Cited by Tweetations (2) Metrics

    Original Paper

    1University of Utah Huntsman Mental Health Institute, Salt Lake City, UT, United States

    2University of Utah School of Medicine, Salt Lake City, UT, United States

    3University of Utah, Salt Lake City, UT, United States

    Corresponding Author:

    Deborah A Bilder, MD

    University of Utah Huntsman Mental Health Institute

    383 Colorow Drive, Room 360

    Salt Lake City, UT, 84108

    United States

    Phone: 1 801 410 0852

    Email: deborah.bilder@hsc.utah.edu


    Background: Individuals with developmental disabilities (DD) experience increased rates of emotional and behavioral crises that necessitate assessment and intervention. Psychiatric disorders can contribute to crises; however, screening measures developed for the general population are inadequate for those with DD. Medical conditions can exacerbate crises and merit evaluation. Screening tools using checklist formats, even when designed for DD, are too limited in depth and scope for crisis assessments. The Sources of Distress survey implements a web-based branching logic format to screen for common psychiatric and medical conditions experienced by individuals with DD by querying caregiver knowledge and observations.

    Objective: This paper aims to (1) describe the initial survey development, (2) report on focus group and expert review processes and findings, and (3) present results from the survey’s clinical implementation and evaluation of validity.

    Methods: Sources of Distress was reviewed by focus groups and clinical experts; this feedback informed survey revisions. The survey was subsequently implemented in clinical settings to augment providers’ psychiatric and medical history taking. Informal and formal consults followed the completion of Sources of Distress for a subset of individuals. A records review was performed to identify working diagnoses established during these consults.

    Results: Focus group members (n=17) expressed positive feedback overall about the survey’s content and provided specific recommendations to add categories and items. The survey was completed for 231 individuals with DD in the clinical setting (n=161, 69.7% men and boys; mean age 17.7, SD 10.3; range 2-65 years). Consults were performed for 149 individuals (n=102, 68.5% men and boys; mean age 18.9, SD 10.9 years), generating working diagnoses to compare survey screening results. Sources of Distress accuracy rates were 91% (95% CI 85%-95%) for posttraumatic stress disorder, 87% (95% CI 81%-92%) for anxiety, 87% (95% CI 81%-92%) for episodic expansive mood and bipolar disorder, 82% (95% CI 75%-87%) for psychotic disorder, 79% (95% CI 71%-85%) for unipolar depression, and 76% (95% CI 69%-82%) for attention-deficit/hyperactivity disorder. While no specific survey items or screening algorithm existed for unspecified mood disorder and disruptive mood dysregulation disorder, these conditions were caregiver-reported and working diagnoses for 11.7% (27/231) and 16.8% (25/149) of individuals, respectively.

    Conclusions: Caregivers described Sources of Distress as an acceptable tool for sharing their knowledge and insights about individuals with DD who present in crisis. As a screening tool, this survey demonstrates good accuracy. However, better differentiation among mood disorders is needed, including the addition of items and screening algorithm for unspecified mood disorder and disruptive mood dysregulation disorder. Additional validation efforts are necessary to include a more geographically diverse population and reevaluate mood disorder differentiation. Future study is merited to investigate the survey’s impact on the psychiatric and medical management of distress in individuals with DD.

    JMIR Ment Health 2024;11:e50907

    doi:10.2196/50907

    Keywords

    developmental disabilities; disruptive behavior; psychiatric comorbidity; web-based; psychiatric crisis; disability; mental health; behavioral crises; intervention; general population; screening; accuracy; mood disorder; sources of distress; autism; intellectual disability 


    Background

    Individuals with developmental disabilities (DD) such as autism and intellectual disability (ID) experience mental health crises more frequently than the general population [1,2]. A broad range of psychiatric and medical conditions can contribute to the agitation, aggression, and self-injury that often characterize these crises [3-10]. Rates of anxiety (20%-77%), depression (10%-20%), expansive mood and bipolar disorder (5%-11%), and psychosis (5%-10%) among individuals with autism exceed those in neurotypical individuals [11-19]. Elevated rates of psychiatric disorders have also been identified in individuals with ID, notably for unspecified psychosis (4.8%), schizophrenia (3.9%), and bipolar disorder (8%) [20-22]. A history of trauma or abuse should also be considered in individuals with DD presenting in crisis [23].

    When psychiatric and medical conditions are recognized as factors contributing to a person’s mental health crisis, clear long-term treatment targets emerge. Nevertheless, for those with DD, co-occurring medical and psychiatric conditions are often unrecognized, leaving them vulnerable to experiencing diagnostic overshadowing. Diagnostic overshadowing occurs when disruptive behaviors in individuals with DD are attributed to their disability without consideration of other potential medical or psychiatric conditions that could contribute to their behavioral presentation [24].

    Self-, parent-, and caregiver-report mental health questionnaires provide an efficient means of screening for common psychiatric conditions in the neurotypical population. However, for those with DD, self-report questionnaires may be impeded by communication deficits or a limited capacity to reflect on internal experiences. Parent- and caregiver-report questionnaires normed in typically developing children may also provide inadequate mental health screening for those with ID because they often include items that are inapplicable to children with minimal language ability, exclude severe conditions that disproportionately affect children with DD (eg, mania and psychosis), and overlook the individualized manner in which psychiatric symptoms manifest in this population [20,25-27].

    The American Psychiatric Association and the National Association for the Dually Diagnosed published the Diagnostic Manual–Intellectual Disability in 2007, and subsequently, in 2016, the second edition (Diagnostic Manual–Intellectual Disability–Second Edition; DM-ID-2) [28,29]. These texts adapt the Diagnostic and Statistical Manual of Mental Disorders criteria to reflect their presentation in individuals with ID. The Psychopathology Instrument for Mentally Retarded Adults and the Psychiatric Assessment Schedule for Adults with Developmental Disabilities (PAS-ADD) operationalize adapted diagnostic criteria into structured interviews to provide a framework through which to identify psychiatric conditions in this population [30,31]. These interviews are quite lengthy and require training to administer. Even as an abbreviated semistructured interview, the Mini PAS-ADD Clinical Interview takes approximately 45 minutes to complete [32]. Existing parent- and caregiver-report psychiatric screening tools for individuals with ID create a more efficient and practical means of collecting information [33-36]; yet, the checklist format of parent- and caregiver-report questionnaires limits depth and scope, both of which are necessary when evaluating crises in a population with complex medical and mental health needs. In addition, there is a great need for the inclusion of items that query symptoms of common medical conditions (eg, epilepsy, gastrointestinal disorders, and poor dentition) that manifest with agitation and aggression and occur more frequently in individuals with DD [3,37,38].

    Sources of Distress is a survey developed for parents and caregivers (hereinafter collectively referred to as caregivers) that uses a web-based branching logic format to screen for mental health and medical conditions among individuals with DD who present in crisis. This tool informs the care of individuals experiencing distress and is intended for use when the severity or persistence of disruptive behavior prompts the consideration of medication intervention. Screening information endorsed by caregivers is organized into relevant psychiatric and medical categories within a report. This report (Multimedia Appendix 1 [39]) is developed for the caregiver and can subsequently facilitate their shared decision-making process with health care providers as specific underlying conditions are evaluated. Sources of Distress aims to minimize diagnostic overshadowing and optimize the ability of the caregiver and the provider to recognize the presence of psychiatric and medical conditions that merit targeted intervention. The web-based branching logic format is adaptive in nature—optimizing caregiver and health care provider convenience and efficiency and minimizing caregiver burden for survey completion [40].

    Objectives

    This paper aims to (1) describe the initial development of Sources of Distress; (2) report on the findings from focus group evaluations and expert reviews and indicate how this feedback shaped the subsequent version of the survey; and (3) present the results from the evaluation of validity for Sources of Distress after its implementation in the clinical setting. The Methods and Results sections are divided into 3 subsections (apart from the Ethical Considerations section in Methods) corresponding to the development, initial evaluation, and clinical implementation phases of Sources of Distress.


    Ethical Considerations

    The University of Utah Institutional Review Board approved focus group activities for Sources of Distress content validation (IRB_00111975). Focus group participants provided informed consent and received compensation for their time in the form of an Amazon gift card worth US $50. The University of Utah Institutional Review Board approved with a waiver of consent for the retrospective records review, data collection, and subsequent deidentified data analysis for individuals for whom Sources of Distress was completed as part of their clinical care (IRB_00170868).

    Early Survey Development

    Funding for the development of Sources of Distress was provided by the Autism Council of Utah based in Murray, Utah, United States [41]. The development team comprised a triple board physician (pediatrics, general psychiatry, and child and adolescent psychiatry), an educational psychologist, a medical student, and a business consultant grandparent of a child with autism and ID. In the initial development phase, Sources of Distress was built in Qualtrics (Qualtrics International Inc) using a branching logic format to approximate the history-taking component of a DD psychiatric evaluation. This evaluation queries psychiatric symptom clusters, physical complaints, and psychiatric medical history to support the development of a diagnostic impression for which treatment recommendations could be made.

    Multiple expert opinion sources were reviewed to identify pertinent screening categories and corresponding items to include in Sources of Distress. The expert sources included published literature, the DM-ID-2, the Mini PAS-ADD Clinical Interview, and the screening interview for the Kiddie Schedule for Affective Disorders and Schizophrenia–Present and Lifetime (a semistructured psychiatric diagnostic interview for children and adolescents) [28,32,42]. As Sources of Distress is intended for use in the context of distress, the presence of at least 1 manifestation of a behavioral or emotional crisis must be endorsed to initiate survey questions.

    Initial Survey Evaluation

    Focus Group Evaluation

    In 2018 and early 2019, focus group participants were recruited from (1) a university-based outpatient program that provides medical and psychiatric care for individuals with DD across the lifespan and (2) the Autism Council of Utah (a community stakeholder organization for individuals and families affected by autism). Six focus groups were conducted that consisted collectively of parents (6/17, 35%), professional caregivers (6/17, 35%), and adults with both DD and the ability to provide verbal feedback (5/17, 29%). Participants completed Sources of Distress before attending the focus group and reported on specific items, missing items, item wording, and attribution of items to corresponding conditions. Interviews and discussions were transcribed and analyzed following the framework analysis of Ritchie and Spencer [43]. Inductive reasoning and the constant comparative method put forth by Strauss and Corbin [44] were used to compare statements by parents, professional caregivers, and individuals with disability within and across focus groups.

    Expert Review Evaluation

    Revisions were made to Sources of Distress based on focus group feedback. Experts reviewed the revised survey version, and additional changes were made. The experts included a pediatrician and 2 child psychiatrists, all with national recognition for their clinical and research work in DD.

    Clinical Implementation

    Overview

    Sources of Distress was implemented in various clinical settings to augment the clinical history-taking process—outpatient (primary care, neurology, developmental pediatrics, and psychiatry), emergency department, psychiatric inpatient, and residential care. Caregivers were given a link to the survey when their health care provider identified the need for expert support in managing severe agitation and aggression. All caregivers (231/231, 100%) completed the survey outside of the clinical setting. An informal or formal consult followed survey completion for a subset of individuals. In August 2020, the survey was transitioned from the Qualtrics platform to the REDCap (Research Electronic Data Capture; Vanderbilt University) platform to automate the Sources of Distress report generation using the custom template engine [45]. This external REDCap module was developed and has been maintained by the Integrated Research Informatics Services of British Columbia Children’s Hospital Research Institute [46].

    Survey Data Collection

    Sources of Distress responses were collected from its first use in a clinical setting from February 2019 through June 2022. The following information was obtained: respondent type, individual characteristics, caregiver-reported diagnoses, current medications, distress manifestations, psychiatric symptoms, and medical symptoms, conditions, or concerns. When multiple caregivers reported on the same individual, responses were used from the caregiver closest to where the individual lived (eg, parent for a child living at home and professional caregiver for an individual living in a residential setting). Psychotropic medications were organized within the following mutually exclusive categories: antipsychotics, antidepressants, non-antidepressant anxiolytics, anticonvulsants, lithium, alpha-2 agonists, stimulants, and atomoxetine.

    Consults

    A medical decision-making support consultation took place after survey completion as either an informal or a formal consult for a subset of individuals. This consult was conducted by a clinical team led by the triple board physician member of the survey’s development team. The consult team used DM-ID-2 criteria as the basis for establishing psychiatric diagnoses. At a minimum (as an informal consult), the consult involved a discussion between a DD clinical expert and the referring provider. This discussion resulted in a collective determination of working diagnoses and treatment plan. A formal consult included the additional components of medical records review, caregiver interview, and direct participant evaluation. Psychiatric diagnoses that were not reported in the survey but discussed by the provider or documented in the medical record were included among preexisting diagnoses.

    Working diagnoses were abstracted from formal and informal consult documentation and served as the standard to define true case status.

    Mood Disorder Classification

    The presence of a mood disorder among preexisting and working diagnoses was classified into mutually exclusive categories such that there was no overlap among individuals across mood disorder categories to allow for direct comparisons across preexisting diagnoses, survey screening status results, and working diagnoses. The following mood disorder classification hierarchy was used from highest to lowest: (1) episodic expansive mood, hypomania, mania, and bipolar disorder, hereafter collectively referred to as bipolar disorder, (2) disruptive mood dysregulation disorder (DMDD) and unspecified mood disorder, and (3) unipolar depression. If an individual had a diagnosis of bipolar disorder, regardless of what other mood disorder diagnosis was reported or identified, their mood disorder classification would be bipolar disorder. An individual was only classified with unipolar depression if (1) they had a depression diagnosis and (2) they had no other mood disorder diagnosis.

    Statistical Analyses and Evaluation of Validity

    Descriptive statistics and chi-square tests were conducted in SPSS (version 28.0; IBM Corp) with an α of .05 selected to assess statistical significance. Differences between surveys with an accompanying consult and those without were measured. Positive predictive value (PPV), negative predictive value (NPV), and accuracy rates were calculated for (1) preexisting diagnoses and (2) survey screening results with working diagnoses used as the determinant of true case status. We calculated 95% CIs for the binomial distribution of accuracy rates.


    Early Survey Development

    Table 1 lists the modules and corresponding items initially selected as the categories, characteristics, and symptoms to be queried by Sources of Distress. The initial version of the survey included scoring algorithms to determine positive screen status for the following conditions: anxiety, unipolar depression, bipolar disorder, psychosis, and attention-deficit/hyperactivity disorder (ADHD).

    Table 1. Description of Sources of Distress and additions in response to focus group feedback.
    ModuleOriginal itemsAdded in response to feedback
    Introduction and demographics
    • Respondent’s relationship to the individual who is affected
    • Distress symptoms
    • Language ability
    • Age
    • Known diagnoses
    • Current medications
    • For professional caregivers: how long have you known the affected individual?
    • Added “increased fixation on certain things” and “changes in behavior such as increased isolation, social withdrawal” to distress symptoms
    • Is there a difference in language ability at the physician’s office? If so, is there something the provider can do to improve the individual’s ability to speak for themselves?
    Behavior patterns and triggers
    • Circumstances of disruptive behavior (recognized triggers, patterns, motivation and reinforcement, and location)
    • Query perceived function to behavior surrounding distress
    Sleep
    • Time of sleep onset and awakening
    • Middle-of-the-night interruptions
    • Naps
    • Activities interfering with sleep onset or returning to sleep
    • Intermittent periods of decreased need for sleep
    • Food seeking as an activity interfering with sleep
    • Sleep apnea diagnosis and symptoms
    • Discomfort precipitating sleep disturbance
    Anxiety
    • Leading to significant outbursts or discomfort: transitioning activities, getting stuck on certain topics or things, and minor changes in daily activities
    • Panic and nightmares
    • Sensory sensitivity that leads to discomfort
    • Repeated checking or rituals, which interferes with daily activities
    Depression
    • Less energy than usual, increased crying spells, sadness, irritability, isolative, loss of interest in activities typically enjoyed, and excess sleep
    • Injures self on purpose; if yes: location of injury and whether self-injury is causing discomfort?
    • Whether self-injury is concerning to parent or caregiver
    • Whether self-injury could be perpetuated by attention seeking or avoidance
    Mania
    • Establish baseline energy
    • Query discrete periods out of the blue lasting ≥2 days of increased energy compared to baseline, laughing or vocalizing for no clear reason, particularly happy or giddy, risk taking, sexually acting out, increased impulsivity, and decreased need for sleep
    • No changes made
    Psychosis
    • Appearing to be responding to internal auditory or visual stimuli
    • Yelling angrily in a room where no one else is present as if yelling at someone who is not there
    • No changes made
    ADHDa
    • Difficulty following through on instructions, avoiding task demands, easily distractible, fidgety or restless, high activity when expected to remain in 1 place, constantly moving, blurting into other people’s conversations, and demanding attention or desired items
    • Excessive talking
    General medical problems
    • Query history of headaches, seizures, injuries that can be causing discomfort, thyroid abnormalities, and tooth pain
    • Could any of these issues be contributing to distress?
    • Are there unusual ways of responding to physical discomfort?
    • Added joint pain; ear, nose, or throat pain; and seasonal allergies
    Traumab
    • N/Ac
    • History of trauma
    • Related to trauma: avoidance, flashbacks, and nightmares
    • Hypervigilance
    Gastrointestinal concernsb
    • N/A
    • Bowel movement frequency
    • Query history of constipation, stool accidents, frequent stomachaches, food allergies, and acid reflux. Could any of these issues contribute to distress?
    • Subsequent additions: changes in appetite, nausea, and variable bowel movements
    Menstrual concernsb (for female patients only)
    • N/A
    • Query presence of mood changes during menses, endometriosis, polycystic ovary syndrome, significant menstrual pain, excess bleeding during or between cycles, and anxiety surrounding periods. Could any of these conditions be leading to distress?
    • Birth control: oral contraceptives, hormonal IUDd, nonhormonal IUD, and Depo-Provera (a contraceptive injection).
    Dental concernsb
    • N/A
    • When was the last dental visit?
    • Query presence of changes in eating patterns: texture preference, sensitivity to hot or cold food or drink preference for eating on 1 side of the mouth, and reduced oral intake
    • Grinding teeth

    aADHD: attention-deficit/hyperactivity disorder.

    bModule added in response to focus group feedback.

    cN/A: not applicable.

    dIUD: intrauterine device.

    Initial Survey Evaluation

    Focus Group Feedback

    During the focus groups, 3 main themes emerged in this analysis.

    • Theme A: respondents gave overall positive feedback regarding existing content and specific feedback regarding areas where there was room to expand content. Table 1 describes the modules and items added in response to this feedback. Notably, a posttraumatic stress disorder (PTSD) module was added along with a PTSD scoring algorithm to determine positive screen status.
    • Theme B: most of the respondents (15/17, 88%) agreed that the symptoms queried matched their understanding of the psychiatric and medical conditions to which they are attributed.
    • Theme C: all participant groups reported positive acceptability of the branching logic format and time required to complete the measure.
    Expert Review

    Overall, the expert review supported the Sources of Distress categories and respective items attributed to each condition. One expert recommended adding items that query gender and replacing sex as the basis for pronoun selection within the tool and its report. This expert also suggested that the report include screening results for each psychiatric condition. The former recommendations were implemented when Sources of Distress was transitioned to the REDCap platform. The latter recommendation was deferred until after screening algorithms are validated in a clinical setting.

    Clinical Implementation

    Sample Characteristics

    Surveys (N=264) were completed by parents or guardians (n=200, 75.8%), professional caregivers (n=43, 16.3%), and other caregivers (n=21, 8%) of 231 individuals (n=161, 69.7% men and boys; n=69, 29.9% women and girls; and n=1, 0.4% other; mean age 17.7, SD 10.3; range 2-65 years). Informal (n=62, 41.6%) and formal (n=87, 58.4%) consults were performed for 149 individuals collectively. Table 2 presents sample characteristics, the manifestations of distress, and a comparison between individuals with a consult and those without.

    Table 2. Sample characteristics and distress manifestations.
    CharacteristicsWith consulta (n=149), n (%)Without consult (n=82), n (%)Total (N=231), n (%)Chi-square (df)P value
    Genderb2.3 (2).34

    		Man or boy102 (68.5)59 (72)161 (69.7)


    		Woman or girl47 (31.5)22 (25.5)69 (29.9)


    		Otherb0 (0)1 (1.2)1 (0.4)

    Caregiverc7.8 (2).02

    		Parent or guardian108 (72.5)71 (86.6)179 (77.5)


    		Professional caregiver32 (21.5)6 (7.3)38 (16.5)


    		Other9 (6)5 (6.1)14 (6.1)

    Age range (y)7.4 (2).03

    		<1346 (30.9)38 (46.3)84 (36.4)


    		13-2257 (38.3)30 (36.6)87 (37.7)


    		>2246 (30.9)14 (17.1)60 (26)

    Language ability0.0 (2).99

    		Full verbal ability76 (51)42 (51.2)118 (51.1)


    		Limited use of words46 (30.9)25 (30.5)71 (30.7)


    		Nonverbal27 (18.1)15 (18.3)42 (18.2)

    Manifestation of distress

    		Agitation130 (87.2)70 (85.4)200 (86.6)0.2 (1).69

    		Aggression97 (65.1)50 (61)147 (63.6)0.4 (1).53

    		Change in sleep86 (57.7)38 (46.3)124 (53.7)2.8 (1).10

    		Moodiness122 (81.9)65 (79.3)187 (81)0.2 (1).63

    		Increased fixation115 (77.2)57 (69.5)172 (74.5)1.6 (1).20

    		Change in eating patterns52 (34.9)19 (23.2)71 (30.7)3.4 (1).07

    		Change in personality99 (66.4)59 (72.0)158 (68.4)0.7 (1).39

    		Change in behavior96 (64.4)45 (54.9)141 (61)2.0 (1).15

    		Self-injurious behavior73 (49)39 (47.6)112 (48.5)0.0 (1).84
    Type of disability

    		Autism without IDd52 (34.9)47 (57.3)99 (42.9)10.9 (1)<.001

    		ID without autism15 (10.1)7 (8.5)22 (9.5)0.1 (1).71

    		ID and autism74 (49.7)18 (22.0)92 (39.8)17.0 (1)<.001

    		Genetic syndromee17 (11)17 (20.7)34 (14.7)3.7 (1).06

    aIncludes informal and formal consults.

    bOne participant reported other as gender: no participants reported non-binary as gender.

    cWhen multiple caregivers completed Sources of Distress, the report from the caregiver with whom the participant spends the most time was used in this table.

    dID: intellectual disability.

    eGenetic syndrome includes some individuals who also populate the autism or ID categories.

    Preexisting Psychiatric Diagnoses

    The presence of at least 1 preexisting psychiatric diagnosis was reported in 65.4% (151/231) of the individuals. Individuals who received a consult compared to those without a consult were more likely to have a caregiver-reported history of psychotic disorder (14/149, 9.4% vs 1/82, 1%; P=.02; Table 3).

    Table 3. Medical conditions, preexisting psychiatric diagnoses, and psychiatric screening results.
    CharacteristicsWith consulta (n=149), n (%)Without consult (n=82), n (%)Total (N=231), n (%)Chi-square (df)P value
    Medical conditionsb

    		Gastrointestinal concerns82 (55)37 (45.1)119 (51.5)2.0 (1).15

    		Dental concerns32 (21.5)25 (30.5)57 (24.7)2.3 (1).13

    		Menstrual concernsc16 (53.3)5 (27.8)21 (43.8)3.0 (1).13

    		General


    		Headache26 (17.4)8 (9.9)34 (14.7)2.5 (1).11


    		Ear, nose, and throat concerns17 (11.4)8 (9.9)25 (10.8)0.2 (1).70


    		Seasonal allergies34 (22.8)13 (15.9)47 (20.3)1.6 (1).21


    		Injury pain14 (9.4)9 (11)23 (10)0.2 (1).70


    		Thyroid abnormalities5 (3.4)6 (7.3)11 (4.8)1.8 (1).18


    		Joint pain9 (6)3 (3.7)12 (5.2)0.6 (1).44


    		Seizures29 (19.5)16 (19.5)45 (19.5)0.0 (1).99
    Seizure History40 (26.8)18 (22)58 (25.1)0.7 (1).41
    Sleep disturbance124 (83.2)68 (82.9)192 (83.1)0.0 (1).95
    Preexisting psychiatric diagnoses

    		Any psychiatric condition103 (69.1)48 (58.5)151 (65.4)2.6 (1).11

    		Depressiond20 (13.4)14 (17.1)34 (14.7)0.6 (1).46

    		Bipolar disorderd21 (14.1)9 (11)30 (13)0.5 (1).50

    		Unspecified mood disorder or DMDDd,e20 (13.4)7 (8.5)27 (11.7)1.2 (1).27

    		Anxietyf62 (41.6)31 (37.8)93 (40.3)0.3 (1).57

    		PTSDg11 (7.4)4 (4.9)15 (6.5)0.6 (1).46

    		Psychotic disorder14 (9.4)1 (1.2)15 (6.5)5.8 (1).02

    		ADHDh50 (33.6)26 (31.7)76 (32.9)0.1 (1).78
    Psychiatric screening status

    		Any psychiatric condition146 (98)80 (97.6)226 (97.8)0.1 (1).83

    		Unipolar depressiond61 (40.9)30 (36.6)91 (39.4)0.4 (1).52

    		Episodic expansive mood and bipolar disorderd60 (40.3)28 (34.1)88 (38.1)0.8 (1).36

    		Anxiety130 (87.2)71 (86.6)201 (87)0.0 (1).89

    		PTSD37 (24.8)15 (18.3)52 (22.5)1.3 (1).26

    		Psychosis52 (34.9)15 (18.3)67 (29)7.1 (1).008

    		ADHD102 (68.5)56 (68.3)158 (68.4)0.0 (1).98

    aIncludes informal and formal consults.

    bMedical conditions perceived by the caregiver as contributing to the current presentation of distress.

    cAnalysis for menstrual concerns restricted to female patients aged >12.

    dUnipolar depression, unspecified mood disorder and disruptive mood dysregulation disorder, and episodic expansive mood and bipolar disorder are mutually exclusive categories.

    eDMDD: disruptive mood dysregulation disorder.

    fPreexisting diagnosis of obsessive-compulsive disorder is included within the anxiety disorder category.

    gPTSD: posttraumatic stress disorder.

    hADHD: attention-deficit/hyperactivity disorder.

    Caregiver-Reported Medical Conditions

    Table 3 describes medical conditions reported by caregivers. Caregivers of 73.2% (169/231) of the individuals identified at least 1 physical concern that they perceived as contributing to distress. The most common conditions were gastrointestinal concerns (119/231, 51.5%), menstrual concerns (21/48, 44% of female patients aged >12 y), seasonal allergies (47/231, 20.3%), and seizures (45/231, 19.5%).

    Psychiatric Screening Results

    Table 3 lists the frequency of positive psychiatric screening results. All but 2% (5/231) of the individuals screened positive for a psychiatric condition, with a mean of 2.8 (SD 1.1; range 0-5) conditions per individual. Of those who were classified as having bipolar disorder, 89% (78/88) screened positive for a recent depressive episode. Positive screen status for psychiatric conditions were similar between those with a consult and those without, except in the case of psychosis (52/149, 34.9% vs 15/82, 18%; P=.008).

    Psychotropic Medication Use

    Table 4 reports on the frequency of medication use. Most of the individuals (194/231, 84%) were taking psychotropic medication, and the majority were receiving antipsychotics (142/231, 61.5%) and antidepressants (129/231, 55.8%).

    Table 4. Medication use reported in Sources of Distress.
    MedicationWith consult (n=149), n (%)Without consult (n=82), n (%)Total (N=231), n (%)Chi-square (df)P value
    Any medication146 (98)68 (82.9)214 (92.6)17.6 (1)<.001
    Any psychotropic medication136 (91.3)58 (70.7)194 (84)16.6 (1)<.001

    		Antipsychotic102 (68.5)40 (48.8)142 (61.5)8.7 (1).003

    		Antidepressanta87 (58.4)42 (51.2)129 (55.8)1.1 (1).29

    		Anxiolyticb66 (44.3)23 (28.0)89 (38.5)5.9 (1).02

    		Anticonvulsantc45 (30.2)12 (14.6)57 (24.7)6.9 (1).009

    		Lithium10 (6.7)7 (8.5)17 (7.4)0.3 (1).61

    		Alpha-2 agonist72 (48.3)27 (32.9)100 (43.3)5.1 (1).02

    		Stimulant and atomoxetine30 (20.1)14 (17.1)44 (19)0.3 (1).57

    aSelective serotonin reuptake inhibitors, duloxetine, tricyclics, mirtazapine, and trazodone were included exclusively within the antidepressant category.

    bBenzodiazapines, buspirone, hydroxyzine, beta-blockers, and prazosin were included exclusively within the anxiolytic category.

    cAnticonvulsant medication use in the absence of a reported seizure history.

    Working Psychiatric Diagnoses

    Of the 149 individuals who received a consult, 148 (99.3%) were diagnosed with at least 1 psychiatric condition with a mean of 2.7 (SD 1.0; range 0-5) diagnoses per individual. The conditions identified were anxiety (129/149, 86.6%), ADHD (84/149, 56.4%), bipolar disorder (67/149, 45%), unipolar depression (33/149, 22.1%), PTSD (35/149, 23.5%), and psychosis (31/149, 20.8%). Furthermore, 25 (16.8%) of the 149 individuals were diagnosed with either unspecified mood disorder or DMDD. Nearly all individuals identified with psychosis (29/31, 94%) had a co-occurring mood disorder diagnosis: bipolar disorder (22/31, 71%), unipolar depression (5/31, 16%), and unspecified mood disorder or DMDD (2/31, 6%).

    Evaluation of Validity

    Sources of Distress accuracy rates ranged from 76% (95% CI 69%-82%) for ADHD to 91% (95% CI 85%-95%) for PTSD and exceeded those of preexisting diagnoses, except in the case of psychosis, for which the accuracy rates were equivocal (82%, 95% CI 75%-87%; Table 5). The survey demonstrated higher NPVs (81%-98%) than PPVs (51%-78%) for all conditions, with the exceptions of anxiety (53% and 92%, respectively) and episodic expansive mood bipolar disorder (85% and 90%, respectively). Low PPVs were notable for depression (51%) and psychosis (54%).

    Table 5. Association between consult diagnoses after completing Sources of Distress with preexisting psychiatric diagnoses and Sources of Distress screening status (n=149).
    Working diagnosisPreexisting psychiatric diagnosisaSources of Distress screening status

    		Case negative, nCase positive, nPPVb (%)NPVc (%)Accuracy rated, % (95% CI)Screen negative, nScreen positive, nPPV (%)bNPV (%)cAccuracy rated, % (95% CI)
    Unipolar depressione,f508278 (71-84)

    		519879 (71-85)

    		Case negative10610


    		8630



    		Case positive2310


    		231


    Episodic expansive mood and bipolar disordere,f766062 (55-70)

    		908587 (81-92)

    		Case negative775


    		766



    		Case positive5116


    		1354


    DMDDg and unspecified mood disordere458882 (75-88)

    		N/AhN/AN/A

    		Case negative11311


    		N/AN/A



    		Case positive169


    		N/AN/A


    Anxiety disorderi972052 (44-60)

    		925387 (81-92)

    		Case negative182


    		1010



    		Case positive6960


    		9120


    Posttraumatic stress disorder1008384 (77-89)

    		789591 (85-95)

    		Case negative1140


    		1068



    		Case positive2411


    		629


    Psychotic disorderj648482 (75-87)

    		549782 (75-87)

    		Case negative1135


    		9424



    		Case positive229


    		328


    Attention-deficit/hyperactivity disorder845866 (59-74)

    		748176 (69-82)

    		Case negative578


    		3827



    		Case positive4242


    		975


    aPreexisting diagnoses included caregiver-reported diagnoses in Sources of Distress and diagnoses in the medical record before survey completion.

    bPPV: positive predictive value =

    cNPV: negative predictive value =

    dAccuracy rate =

    eDepression, episodic expansive mood and bipolar disorder, and disruptive mood dysregulation disorder and unspecified mood disorder are mutually exclusive categories. There is no Sources of Distress screening algorithm for disruptive mood dysregulation disorder or unspecified mood disorder.

    fPreexisting and working diagnoses included schizoaffective disorder when hypomanic, manic, or mixed episode was specified.

    gDMDD: disruptive mood dysregulation disorder.

    hN/A: not applicable.

    iPreexisting and working diagnoses of anxiety disorder and obsessive-compulsive disorder are combined to coincide with anxiety disorder screening status.

    jPreexisting and working diagnoses were schizophrenia, schizoaffective disorder, unspecified psychotic disorder, and psychotic features associated with a mood disorder.

    Exploration of Mood Disorder Categories

    Figure 1 demonstrates the distribution of mood disorder diagnoses among individuals based on (1) preexisting mood disorder diagnosis and (2) Sources of Distress mood disorder screening status. The majority of the individuals (18/25, 72%) who received a working diagnosis of unspecified mood disorder and DMDD screened positive for either unipolar depression or bipolar disorder.

    ‎
    Figure 1. Comparison of mood disorder categorization between working diagnosis established during consultation and (A) preexisting diagnosis and (B) Sources of Distress positive screen. DMDD: disruptive mood dysregulation disorder.

    Principal Findings

    The focus group feedback indicates that Sources of Distress provides an acceptable means for caregivers to share their knowledge and insights about individuals with DD who present in crisis. As a screening tool, this survey demonstrates good accuracy, although additional work is needed to differentiate among mood disorders. The purpose of this survey is to screen individuals with DD for mental health and common medical concerns in health care settings when they present in crisis. By querying what symptom clusters and physical conditions coincide with their patient’s crisis, providers can direct their evaluation toward specific psychiatric and medical conditions that have established treatment protocols in the general population. This approach aims to reduce diagnostic overshadowing and improve medical decision-making surrounding the management of agitation and aggression in individuals with DD. Focus group participants validated the survey content and provided recommendations that prompted the inclusion of additional modules and items. Despite its length (ie, 15-20 min), participants reported positive acceptability of the survey’s format and duration. This feedback may reflect the convenience of completing a web-based survey at home versus in the medical setting and highlights caregivers’ motivation toward understanding potential factors contributing to the person’s distress. After incorporating caregiver recommendations, Sources of Distress content was also reviewed and supported by clinical and research experts.

    Caregivers of most of the individuals (200/231, 86.6%) identified agitation as a presenting concern. The Food and Drug Administration has approved short-term antipsychotic medication for treating irritability in individuals with autism [47]; 61.5% (142/231) of the individuals were taking antipsychotics at the time of presenting in crisis. This frequency exceeds previously reported estimates of antipsychotic use in the population with DD (ie, 10%-48%) and reflects the high acuity and potentially treatment-resistant nature of individuals for whom the survey was completed [48,49]. This study group’s acuity is further supported by the high frequency in which severe mental health conditions were diagnosed in those receiving a consultation (eg, bipolar disorder and psychosis).

    Anxiety was the most common condition to screen positive (201/231, 87%) and be established as a working diagnosis (129/149, 86.6%). These rates exceeded measured anxiety prevalence rates in the population with DD (ie, 20%-77%), indicating a higher propensity toward experiencing anxiety among those presenting in crisis [12,15,16]. As a precipitant of distress, prior studies have identified aggression, disruptive behavior, sleep disturbance, and self-injurious behavior as symptoms of anxiety among individuals with DD [4,8,50]. To reduce overclassification among individuals whose autism core features overlap with some anxiety symptoms [51], the Sources of Distress anxiety scoring algorithm was set at a higher threshold than the generalized anxiety disorder criteria described in DM-ID-2. The survey’s low NPV (53%) and high PPV (92%) for anxiety likely reflect this adaption.

    Sources of Distress captured well the presence of a mood disturbance; however, the type of mood disorder was not. Study results report a diagnosis frequency of 16.8% (25/149) for unspecified mood disorder and DMDD and indicate the need to add items and a screening algorithm for this condition. The low PPV (51%) for depression primarily resulted from individuals screening positive for depression who were subsequently diagnosed with unspecified mood disorder and DMDD. The DM-ID-2, survey data, and records review will inform new items and algorithm development as well as revisions for the depression screening algorithm. In the interim, the Sources of Distress report will replace the “depression” category label with “depression and unspecified mood disorder” to broaden the range of conditions which it currently captures.

    Caregivers of the majority of the individuals (169/231, 73.2%) identified at least 1 physical concern that they perceived as contributing to distress. As agitation may be one of the few visible indicators of pain in an individual with limited expressive language ability and DD, sources of pain should be considered when unexplained agitation is present [3,9,52]. Limited access to medical care by the population with DD further reduces the likelihood that pain and other underlying physical causes of agitation are recognized [53]. Through Sources of Distress, caregivers demonstrated their ability to provide meaningful insight into the potential presence of physical discomfort. This attention was directed most frequently to gastrointestinal, menstrual, dental, and seizure concerns.

    Limitations

    The generalizability of study results is limited to the geographic, racial, and ethnic diversity of Utah. While survey access requires internet or smartphone access, it has been completed by parents without this access through the assistance of state-sponsored support coordinators and medical assistants. Sources of Distress has a Spanish translation available (Causas de Aflicción); however, these data were not included because its content has not yet been validated by Spanish-speaking caregivers and individuals who are affected. The expert leading the consult team was a member of the survey’s development team, which introduces the inherent bias of evaluating for the presence of mental health conditions through the lens of DM-ID-2 criteria on which survey components were also based. While the DM-ID-2 is well recognized and accepted in the ID provider community, few autism specialty providers are familiar with its use.

    Future Directions

    Edits and additions to mood disorder items and scoring algorithms are being made to improve differentiation across mood disorders. Branching logic that incorporates the individual’s language ability has recently been added to the psychosis module to improve question clarity and scoring algorithm accuracy. The most updated version of the Sources of Distress can be accessed through the Utah Department of Health and Human Services Autism Systems Development Program webpage [39]. Reevaluation of the survey’s PPVs, NPVs, and accuracy will follow the completion of these changes. Additional studies of this survey are needed to measure its acceptability and validity in clinical settings outside of Utah and by other DD specialty providers. REDCap has also demonstrated capacity to integrate digital mental health screening results into electronic medical records, significantly improving provider adoption of the screening tools [54]. The integration of Sources of Distress into electronic medical records could further enhance its impact on provider efficiency. This survey has already been used during medical evaluations to facilitate the consideration of potential discordance between medications prescribed and conditions present [55]. Prospective studies are merited to determine the survey’s impact on treatment approaches, hospital and emergency department use, and outcomes for individuals with DD who experience crisis.

    Conclusions

    Individuals with DD presenting in crisis experience high rates of psychiatric disorders and medical concerns that may contribute to, or manifest as, distress. Sources of Distress is a valuable screening tool for psychiatric and medical conditions that commonly accompany treatment-resistant agitation in individuals with DD. When systematically queried, caregivers’ knowledge provides essential information to minimize diagnostic overshadowing and support an evaluation focused on the individual rather than their disability when persistent agitation is assessed in the population with DD.

    Acknowledgments

    The authors thank the individuals with developmental disabilities and their parents and caregivers whose support and participation shaped the development, validation, and piloting of the Sources of Distress. In particular, the authors appreciate the insight and assistance provided by Jaye Olafson. The Autism Council of Utah funded the development of this survey, and access to REDCap (Research Electronic Data Capture) is supported through UM1TR004409 NCATS/NIH.

    Conflicts of Interest

    The Sources of Distress survey is copyrighted by the University of Utah; DAB, JD, and WW are listed as inventors. DAB consults for BioMarin Pharmaceutical Inc, Encoded Therapeutics, Taysha Gene Therapies, and Synlogic Therapeutics and attended an advisory board meeting for Sanofi. All other authors declare no other conflicts of interest.

    Multimedia Appendix 1

    A sample of the Sources of Distress report.

    PDF File (Adobe PDF File), 80 KB
    1. Durbin A, Balogh R, Lin E, Wilton AS, Selick A, Dobranowski KM, et al. Repeat emergency department visits for individuals with intellectual and developmental disabilities and psychiatric disorders. Am J Intellect Dev Disabil. May 2019;124(3):206-219. [CrossRef] [Medline]
    2. Lunsky Y, Lin E, Balogh R, Klein-Geltink J, Wilton AS, Kurdyak P. Emergency department visits and use of outpatient physician services by adults with developmental disability and psychiatric disorder. Can J Psychiatry. Oct 01, 2012;57(10):601-607. [CrossRef] [Medline]
    3. Antonacci DJ, Manuel C, Davis E. Diagnosis and treatment of aggression in individuals with developmental disabilities. Psychiatr Q. Sep 23, 2008;79(3):225-247. [CrossRef] [Medline]
    4. Kim JA, Szatmari P, Bryson SE, Streiner DL, Wilson FJ. The prevalence of anxiety and mood problems among children with Autism and Asperger syndrome. Autism. Jun 30, 2016;4(2):117-132. [CrossRef]
    5. Kishore MT, Nizamie SH, Nizamie A. The behavioural profile of psychiatric disorders in persons with intellectual disability. J Intellect Disabil Res. Nov 06, 2005;49(Pt 11):852-857. [CrossRef] [Medline]
    6. Lowe K, Allen D, Jones E, Brophy S, Moore K, James W. Challenging behaviours: prevalence and topographies. J Intellect Disabil Res. Aug 09, 2007;51(Pt 8):625-636. [CrossRef] [Medline]
    7. McGuire K, Fung LK, Hagopian L, Vasa RA, Mahajan R, Bernal P, et al. Irritability and problem behavior in autism spectrum disorder: a practice pathway for pediatric primary care. Pediatrics. Feb 2016;137 Suppl 2:S136-S148. [CrossRef] [Medline]
    8. Oliver C, Licence L, Richards C. Self-injurious behaviour in people with intellectual disability and autism spectrum disorder. Curr Opin Psychiatry. Mar 2017;30(2):97-101. [FREE Full text] [CrossRef] [Medline]
    9. Regnard C, Reynolds J, Watson B, Matthews D, Gibson L, Clarke C. Understanding distress in people with severe communication difficulties: developing and assessing the Disability Distress Assessment Tool (DisDAT). J Intellect Disabil Res. Apr 29, 2007;51(Pt 4):277-292. [CrossRef] [Medline]
    10. Rojahn J, Matson JL, Naglieri JA, Mayville E. Relationships between psychiatric conditions and behavior problems among adults with mental retardation. Am J Ment Retard. Jan 2004;109(1):21-33. [CrossRef] [Medline]
    11. Brookman-Frazee L, Stadnick N, Chlebowski C, Baker-Ericzén M, Ganger W. Characterizing psychiatric comorbidity in children with autism spectrum disorder receiving publicly funded mental health services. Autism. Nov 15, 2018;22(8):938-952. [FREE Full text] [CrossRef] [Medline]
    12. Buck TR, Viskochil J, Farley M, Coon H, McMahon WM, Morgan J, et al. Psychiatric comorbidity and medication use in adults with autism spectrum disorder. J Autism Dev Disord. Dec 24, 2014;44(12):3063-3071. [FREE Full text] [CrossRef] [Medline]
    13. Eaves LC, Ho HH. Young adult outcome of autism spectrum disorders. J Autism Dev Disord. Apr 1, 2008;38(4):739-747. [CrossRef] [Medline]
    14. Leyfer OT, Folstein SE, Bacalman S, Davis NO, Dinh E, Morgan J, et al. Comorbid psychiatric disorders in children with autism: interview development and rates of disorders. J Autism Dev Disord. Oct 15, 2006;36(7):849-861. [CrossRef] [Medline]
    15. Lai MC, Kassee C, Besney R, Bonato S, Hull L, Mandy W, et al. Prevalence of co-occurring mental health diagnoses in the autism population: a systematic review and meta-analysis. Lancet Psychiatry. Oct 2019;6(10):819-829. [CrossRef] [Medline]
    16. Lecavalier L, McCracken CE, Aman MG, McDougle CJ, McCracken JT, Tierney E, et al. An exploration of concomitant psychiatric disorders in children with autism spectrum disorder. Compr Psychiatry. Jan 2019;88:57-64. [FREE Full text] [CrossRef] [Medline]
    17. Morgan CN, Roy M, Chance P. Psychiatric comorbidity and medication use in autism: a community survey. Psychiatr Bull. Jan 02, 2018;27(10):378-381. [CrossRef]
    18. Simonoff E, Pickles A, Charman T, Chandler S, Loucas T, Baird G. Psychiatric disorders in children with autism spectrum disorders: prevalence, comorbidity, and associated factors in a population-derived sample. J Am Acad Child Adolesc Psychiatry. Aug 2008;47(8):921-929. [CrossRef] [Medline]
    19. Varcin KJ, Herniman SE, Lin A, Chen Y, Perry Y, Pugh C, et al. Occurrence of psychosis and bipolar disorder in adults with autism: a systematic review and meta-analysis. Neurosci Biobehav Rev. Mar 2022;134:104543. [CrossRef] [Medline]
    20. Mazza MG, Rossetti A, Crespi G, Clerici M. Prevalence of co-occurring psychiatric disorders in adults and adolescents with intellectual disability: a systematic review and meta-analysis. J Appl Res Intellect Disabil. Mar 2020;33(2):126-138. [CrossRef] [Medline]
    21. Platt JM, Keyes KM, McLaughlin KA, Kaufman AS. Intellectual disability and mental disorders in a US population representative sample of adolescents. Psychol Med. Apr 2019;49(6):952-961. [FREE Full text] [CrossRef] [Medline]
    22. Munir KM. The co-occurrence of mental disorders in children and adolescents with intellectual disability/intellectual developmental disorder. Curr Opin Psychiatry. Mar 2016;29(2):95-102. [FREE Full text] [CrossRef] [Medline]
    23. Smit MJ, Scheffers M, Emck C, van Busschbach JT, Beek PJ. Clinical characteristics of individuals with intellectual disability who have experienced sexual abuse. An overview of the literature. Res Dev Disabil. Dec 2019;95:103513. [CrossRef] [Medline]
    24. Jamieson D, Mason J. Investigating the existence of the diagnostic overshadowing bias in Australia. J Ment Health Res Intellect Disabil. Apr 22, 2019;12(1-2):58-70. [CrossRef]
    25. Joshi G, Biederman J, Petty C, Goldin RL, Furtak SL, Wozniak J. Examining the comorbidity of bipolar disorder and autism spectrum disorders: a large controlled analysis of phenotypic and familial correlates in a referred population of youth with bipolar I disorder with and without autism spectrum disorders. J Clin Psychiatry. Jun 2013;74(6):578-586. [CrossRef] [Medline]
    26. Rapoport J, Chavez A, Greenstein D, Addington A, Gogtay N. Autism spectrum disorders and childhood-onset schizophrenia: clinical and biological contributions to a relation revisited. J Am Acad Child Adolesc Psychiatry. Jan 2009;48(1):10-18. [FREE Full text] [CrossRef] [Medline]
    27. Bertelli M, Scuticchio D, Ferrandi A, Lassi S, Mango F, Ciavatta C, et al. Reliability and validity of the SPAID-G checklist for detecting psychiatric disorders in adults with intellectual disability. Res Dev Disabil. 2012;33(2):382-390. [CrossRef] [Medline]
    28. Fletcher RJ, Barnhill J, Cooper SA. Diagnostic Manual—Intellectual Disability 2 (DM-ID): A Textbook of Diagnosis of Mental Disorders in Persons with Intellectual Disability. Washington, DC. NADD Press; 2016.
    29. Fletcher R, Loschen E, Stavrakiki C, Kingston MF. Diagnostic Manual - Intellectual Disability: A Textbook of Diagnosis of Mental Disorders in Persons With Intellectual Disability. New York, NY. NADD Press; 2007.
    30. Moss S, Patel P, Prosser H, Goldberg D, Simpson N, Rowe S, et al. Psychiatric morbidity in older people with moderate and severe learning disability. I: development and reliability of the patient interview (PAS-ADD). Br J Psychiatry. Oct 1993;163:471-480. [CrossRef] [Medline]
    31. Matson JL, Kazdin AE, Senatore V. Psychometric properties of the psychopathology instrument for mentally retarded adults. Appl Res Ment Retard. 1984;5(1):81-89. [CrossRef] [Medline]
    32. Devine M, Taggart L, McLornian P. Screening for mental health problems in adults with learning disabilities using the Mini PAS‐ADD Interview. Br J Learn Disabil. Nov 04, 2010;38(4):252-258. [CrossRef]
    33. Moss S, Prosser H, Costello H, Simpson N, Patel P, Rowe S, et al. Reliability and validity of the PAS-ADD Checklist for detecting psychiatric disorders in adults with intellectual disability. J Intellect Disabil Res. Apr 1998;42 ( Pt 2):173-183. [CrossRef] [Medline]
    34. Sevin JA, Matson JL, Williams D, Kirkpatrick-Sanchez S. Reliability of emotional problems with the diagnostic assessment for the Severely Handicapped (DASH). Br J Clin Psychol. Feb 1995;34(1):93-94. [CrossRef] [Medline]
    35. Myrbakk E, von Tetzchner S. Screening individuals with intellectual disability for psychiatric disorders: comparison of four measures. Am J Ment Retard. Jan 2008;113(1):54-70. [CrossRef] [Medline]
    36. Taylor JL, Hatton C, Dixon L, Douglas C. Screening for psychiatric symptoms: PAS-ADD Checklist norms for adults with intellectual disabilities. J Intellect Disabil Res. Jan 2004;48(1):37-41. [CrossRef] [Medline]
    37. Marcangelo MJ, Ovsiew F. Psychiatric aspects of epilepsy. Psychiatr Clin North Am. Dec 2007;30(4):781-802. [CrossRef] [Medline]
    38. Périsse D, Amiet C, Consoli A, Thorel MV, Gourfinkel-An I, Bodeau N, et al. Risk factors of acute behavioral regression in psychiatrically hospitalized adolescents with autism. J Can Acad Child Adolesc Psychiatry. May 2010;19(2):100-108. [FREE Full text] [Medline]
    39. Bilder DA. Sources of distress - Autism Systems Development. Utah Department of Health and Human Services. URL: https://familyhealth.utah.gov/cshcn/asd/# [accessed 2024-03-11]
    40. Martin-Key NA, Spadaro B, Funnell E, Barker EJ, Schei TS, Tomasik J, et al. The current state and validity of digital assessment tools for psychiatry: systematic review. JMIR Ment Health. Mar 30, 2022;9(3):e32824. [FREE Full text] [CrossRef] [Medline]
    41. Home page. Autism Council of Utah. URL: https://www.autismcouncilofutah.org/ [accessed 2024-02-11]
    42. Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, et al. Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry. Jul 1997;36(7):980-988. [FREE Full text] [CrossRef] [Medline]
    43. Ritchie J, Spencer L. Qualitative data analysis for applied policy research. In: Bryman A, Burgess B, editors. Analyzing Qualitative Data. London, UK. Routledge; 1994.
    44. Strauss A, Corbin J. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. 2nd edition. Thousand Oaks, CA. Sage Publications; 1998.
    45. Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O'Neal L, et al. REDCap Consortium. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. Jul 2019;95:103208. [FREE Full text] [CrossRef] [Medline]
    46. Custom template engine. GitHub. URL: https://github.com/BCCHR-IT/custom-template-engine, [accessed 2024-02-18]
    47. LeClerc S, Easley D. Pharmacological therapies for autism spectrum disorder: a review. P T. Jun 2015;40(6):389-397. [FREE Full text] [Medline]
    48. Downs J, Hotopf M, Ford T, Simonoff E, Jackson RG, Shetty H, et al. Clinical predictors of antipsychotic use in children and adolescents with autism spectrum disorders: a historical open cohort study using electronic health records. Eur Child Adolesc Psychiatry. Jun 15, 2016;25(6):649-658. [FREE Full text] [CrossRef] [Medline]
    49. Esbensen AJ, Greenberg JS, Seltzer MM, Aman MG. A longitudinal investigation of psychotropic and non-psychotropic medication use among adolescents and adults with autism spectrum disorders. J Autism Dev Disord. Sep 12, 2009;39(9):1339-1349. [FREE Full text] [CrossRef] [Medline]
    50. Shui AM, Katz T, Malow BA, Mazurek MO. Predicting sleep problems in children with autism spectrum disorders. Res Dev Disabil. Dec 2018;83:270-279. [CrossRef] [Medline]
    51. Wood JJ, Gadow KD. Exploring the nature and function of anxiety in youth with autism spectrum disorders. Clin Psychol Sci Pract. Dec 2010;17(4):281-292. [CrossRef]
    52. Gössler A, Schalamon J, Huber-Zeyringer A, Höllwarth ME. Gastroesophageal reflux and behavior in neurologically impaired children. J Pediatr Surg. Sep 2007;42(9):1486-1490. [CrossRef] [Medline]
    53. Matson JL, Rivet TT. Characteristics of challenging behaviours in adults with autistic disorder, PDD-NOS, and intellectual disability. J Intellect Dev Disabil. Dec 2008;33(4):323-329. [FREE Full text] [CrossRef] [Medline]
    54. Hawley S, Yu J, Bogetic N, Potapova N, Wakefield C, Thompson M, et al. Digitization of measurement-based care pathways in mental health through REDCap and electronic health record integration: development and usability study. J Med Internet Res. May 20, 2021;23(5):e25656. [FREE Full text] [CrossRef] [Medline]
    55. Bartel RL, Knight JR, Worsham W, Bilder D. Discordance between psychiatric diagnoses and medication use in children and adults with autism presenting in crisis. Focus (forthcoming). 2024;22 [CrossRef]

    ‎
    ADHD: attention-deficit/hyperactivity disorder
    DD: developmental disabilities
    DMDD: disruptive mood dysregulation disorder
    DM-ID-2: Diagnostic Manual–Intellectual Disability–Second Edition
    ID: intellectual disability
    NPV: negative predictive value
    PAS-ADD: Psychiatric Assessment Schedule for Adults with Developmental Disabilities
    PPV: positive predictive value
    PTSD: posttraumatic stress disorder
    REDCap: Research Electronic Data Capture

    Edited by J Torous; submitted 17.07.23; peer-reviewed by H Onyeaka, A AL-Asadi; comments to author 04.02.24; revised version received 18.02.24; accepted 20.02.24; published 29.03.24.

    Copyright

    ©Deborah A Bilder, Mariah Mthembu, Whitney Worsham, Patricia Aguayo, Jacob R Knight, Steven W Deng, Tejinder P Singh, John Davis. Originally published in JMIR Mental Health (https://mental.jmir.org), 29.03.2024.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included.