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Record W2890842006 · doi:10.1002/smi.2833

Adult attention deficit hyperactivity disorder symptoms and passive leadership: The mediating role of daytime sleepiness

2018· article· en· W2890842006 on OpenAlexafffund
Erica Carleton, Julian Barling

Bibliographic record

VenueStress and Health · 2018
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsQueen's UniversityUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyAnxietyAttention deficit hyperactivity disorderDepression (economics)Ordinary least squaresClinical psychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Passive leadership is attracting empirical interest with the detrimental effects of this type of leadership on a broad array of individual and organizational outcomes becoming apparent. However, just why leaders would engage in this type of nonleadership has received less research attention. We investigate whether and how leaders' attention deficit hyperactivity disorder (ADHD) is associated with passive leadership. Using a framework specifying how the physiology of sleepiness impacts the workplace, we hypothesize that leaders' ADHD is associated with passive leadership indirectly through daytime sleepiness. After controlling for leaders' age, gender, and preclinical symptoms of depression and anxiety, standard ordinary least squares regression procedures were implemented through Hayes' PROCESS models. Multisource data from 98 leader-follower groups (M number of followers per leader = 4.38, SD = 1.78) showed that the effects of leaders' ADHD symptoms on passive leadership were mediated by daytime sleepiness. Conceptual, methodological, and practical implications are discussed.

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)0.000
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 score0.068
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.037
GPT teacher head0.323
Teacher spread0.286 · 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

Citations7
Published2018
Admission routes2
Has abstractyes

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