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Record W2626256952 · doi:10.1176/appi.pn.2017.5b22

Six-Question Screen for ADHD Developed for Adults

2017· article· en· W2626256952 on OpenAlexaboutno aff
Nick Zagorski

Bibliographic record

VenuePsychiatric News · 2017
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAttention deficit hyperactivity disorderImpulsivityPsychiatryAttention deficitHealth careClinical psychology

Abstract

fetched live from OpenAlex

Back to table of contents Previous article Next article Clinical and Research NewsFull AccessSix-Question Screen for ADHD Developed for AdultsNick ZagorskiNick ZagorskiSearch for more papers by this authorPublished Online:15 Jun 2017https://doi.org/10.1176/appi.pn.2017.5b22AbstractThis rapid assessment tool builds on the previously developed World Health Organization Adult ADHD Self-Report Scale and reflects DSM-5 diagnostic criteria.Making use of an advanced machine-learning algorithm, a team of physicians and researchers has developed a DSM-5-based tool to screen adults for attention-deficit/hyperactivity disorder (ADHD). The screen consists of just six questions, each with a numbered scale of severity (see sidebar). It is intended to offer health care providers a rapid, easily scored, and accurate diagnostic screen that can be used to refer someone for a more thorough evaluation.“We hope that this tool will do for ADHD screening what the PHQ [Patient Health Questionnaire] has done for depression screening of adults in primary care settings,” said study co-investigator Lenard Adler, M.D., a professor of psychiatry and child and adolescent psychiatry at NYU Langone Medical Center.Adler and his colleagues used the DSM-IV-based World Health Organization Adult ADHD Self-Report Scale (ASRS) as the template. The ASRS includes structured questions pertaining to each of the inattention and hyperactivity-impulsivity symptoms plus 11 questions related to problems in executive function that are associated with adult ADHD.DSM-5 Adult ADHD Self-Report ScaleHow often do you have difficulty concentrating on what people say to you, even when they are speaking to you directly? (DSM-5 A1c, scored 0-5)How often do you leave your seat in meetings or other situations in which you are expected to remain seated? (DSM-5 A2b, scored 0-5)How often do you have difficulty unwinding and relaxing when you have time to yourself? (DSM-5 A2d, scored 0-5)When you’re in a conversation, how often do you find yourself finishing the sentences of people you are talking to before they finish them themselves? (DSM-5 A2g, scored 0-2)How often do you put things off until the last minute? (Non-DSM, scored 0-4)How often do you depend on others to keep your life in order and attend to details? (Non-DSM, scored 0-3)Ronald Kessler, Ph.D., the McNeil Family Professor of Health Care Policy at Harvard Medical School, told Psychiatric News that updating the ASRS to comply with DSM-5 was not difficult; ADHD’s core symptoms were not changed in DSM-5, just the number needed to qualify for a diagnosis (down to five from six) and the age of onset (now 12 years of age instead of 7).The team analyzed data from hundreds of people who had taken the ASRS and then underwent a clinical interview to confirm an ADHD diagnosis. The samples used included two distinct groups: one consisting of 327 participants from the general community (in which ADHD prevalence is low) and one consisting of 300 people who attended NYU Langone’s ADHD program (in which prevalence is much higher). Adler said that including the Langone sample was important since it represents people whom primary care providers are most likely to encounter—adults who think they might have ADHD. As for including a general population sample, Kessler said that the screen could also be used in workplace settings as part of a wellness program. Doing so might provide data demonstrating how undiagnosed ADHD affects productivity, which might encourage employers to invest in mental health services.The screen has four questions that pertain to core ADHD symptoms and two that relate to deficits in executive function. The scale ranges from 0-24 points, with 14 or higher considered the most accurate cutoff for possible ADHD.The DSM-5 ASRS performed well in both general and clinical populations, identifying more than 91 percent of true ADHD positives in each group. However, in the clinical sample, the test had a higher false positive rate than in the general sample—26 percent versus 4 percent. This was expected since the Langone group had more people with subclinical inattentive and/or hyperactive traits.Timothy Bilkey, M.D., an Ontario psychiatrist who specializes in diagnosing and managing adults with ADHD, thinks that this screen will be valuable in identifying people for a fuller clinical evaluation. “These are much like the questions I would ask in the first few minutes of a clinical interview to distinguish ADHD from symptoms that are related to a mood disorder or a substance use problem,” he told Psychiatric News.One item not captured, though, was memory issues. “I call it PDF—procrastination, distractibility, and forgetfulness. These are three problems that need to be established in both adulthood and childhood” for a diagnosis of ADHD.“Another concern is that this scale will most likely capture people already aware that they might have a problem,” Bilkey added. “But many adults have managed to get by with ADHD for years or decades and can be somewhat oblivious.” That’s why Bilkey encourages clinicians to take a collateral history of a patient with family or friends to confirm the severity of problems.The DSM-5 ASRS Screening Scale was developed with support from Shire Pharmaceuticals. The details were published in the May 1 JAMA Psychiatry. ■“The World Health Organization Adult Attention-Deficit/Hyperactivity Disorder Self-Report Screening Scale for DSM-5” can be accessed here. The accompanying editorial, “Good News for Screening for Adult Attention-Deficit/Hyperactivity Disorder,” is available here. ISSUES NewArchived

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.390
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2017
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