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Record W3094349440 · doi:10.2196/24430

Psychological Effects of the COVID-19 Imposed Lockdown on Adults with Attention Deficit/Hyperactivity Disorder: Cross-Sectional Survey Study

2020· article· en· W3094349440 on OpenAlexvenueno aff
Marios Adamou, Tim Fullen, Nazmeen Galab, Isobel Mackintosh, Karl Abbott, Deborah A. Lowe, Claire Smith

Bibliographic record

VenueJMIR Formative Research · 2020
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyMental healthCross-sectional studyAttention deficit hyperactivity disorderPsychiatryPsychologyClinical psychologyPsychological interventionCoronavirus disease 2019 (COVID-19)PandemicPopulationDistressMedicineEnvironmental healthDisease

Abstract

fetched live from OpenAlex

BACKGROUND: The psychological effects of the COVID-19 government-imposed lockdown have been studied in several populations. These effects however have not been studied in adult populations with attention deficit/hyperactivity disorder (ADHD). OBJECTIVE: We wanted to investigate the psychological effects of the COVID-19 imposed lockdown on an adult population with ADHD. METHODS: We conducted a cross-sectional survey by administering the Patient Health Questionnaire-9, Generalized Anxiety Disorder Scale-7, Brief Adjustment Scale-6, Perceived Stress Scale, and Multidimensional Scale of Perceived Social Support to a pragmatic sample of adults with ADHD. RESULTS: In total, 24 individuals (male: n=18, 75%; female: n=6, 25%; age: mean 21.75 years, SD 1.85 years) were included in this study. The adults with ADHD we surveyed had significant levels of emotional distress during the COVID-19 pandemic period. However, there was no evidence of significant deterioration to the mental health of our sample during the COVID-19 pandemic. CONCLUSIONS: When treatment for ADHD is maintained, the effects of the COVID-19 pandemic on the mental health of adults with ADHD are mild. Targeted psychological interventions may be useful in such circumstances.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.122
GPT teacher head0.470
Teacher spread0.347 · 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 designObservational
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".

Quick stats

Citations21
Published2020
Admission routes1
Has abstractyes

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Same venueJMIR Formative ResearchSame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207