Loneliness, Risk-Taking, and Attention Deficit Hyperactivity Disorder During the COVID-19 Pandemic
Notice bibliographique
Résumé
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder, commonly associated with impulsivity, risk-taking, and greater reported loneliness. Risk-taking can manifest in various ways, including reduced regard for health-conscious practices. Recent research indicates that individuals with ADHD may be less likely to follow pandemic safety instruction. (e.g., not following social distancing recommendations). Given that individuals with ADHD tend to discount the value of delayed reward in favour of immediate gratification, it can be presumed that individuals with greater ADHD symptomology may be more likely to not follow social distancing guidelines in an attempt to relieve acute feelings of loneliness. The present project is comprised of two studies that sought to better understand the relation between ADHD, loneliness, and risk-taking during the COVID-19 pandemic. Study 1 tested and validated a measure of COVID-related risk-taking (CrRT) that was developed for the main analysis in Phase I of Study 2. We investigated CrRT in 318 undergraduate students recruited from a Canadian university. With exploratory factor analysis, we identified a two-factor structure of COVID-related risk-taking: social non-avoidance and personal protection non-compliance, which is consistent with other related studies. Our scale was validated with results from multiple regression analysis showing that younger age, lower risk perception, lower stress, non-planning, and greater risk-tolerance significantly predicted public health risk-taking behaviours, also validated by previous work. Study 2 was divided into two phases. Phase I explored ADHD-related problems and health-risk behaviours in emerging adults within the context of the pandemic. Using multiple regression analysis, we investigated predictors of COVID-related risk-taking (i.e., reduced adherence to public health and safety measures) in 456 young adults. It was hypothesized that: (1) Participants with more ADHD-related symptoms would report greater loneliness, emotional dysregulation, and negative emotional states during the COVID-19 pandemic than non-ADHD individuals; and (2) Greater ADHD symptomology, loneliness, and substance use would predict risk-taking behaviours. Findings supported the first hypothesis and partially supported the second hypotheses. Participants with more ADHD symptoms reported higher ratings of psychological distress, emotional dysregulation, loneliness, and cannabis use compared to participants with low ADHD symptoms. More severe ADHD symptoms were predictive of COVID-related risk-taking, including non-adherence to pandemic health measures. Phase II used qualitative analysis to answer the following questions: (1) What are the overlapping themes in relation to resilience, emotion regulation, and successful coping?; and (2) What role does ADHD symptomology play in coping with pandemic-related difficulties? Results indicated that external-avoidance strategies (e.g., distraction) were the most frequently used, however, respondents rated internal-approach strategies (e.g., cognitive restructuring, acceptance, exercise) to be the most effective overall. Results suggest that psychological well-being is associated with strategies designed to engage with or move through distressing experiences, greater self-compassion, and emotional regulation. These studies provide an initial overview of coping and risk-taking behaviours during a global health crisis. Findings are consistent with similar research, which suggests that individuals with more severe ADHD symptoms are more vulnerable to distressing situations and, as a result, may engage in high-risk behaviours. The current dissertation’s findings highlight clear targets for intervention tailored for individuals with ADHD during times of heightened distress. Specifically, interventions may include skills-based training that facilitates emotion regulation strategies (e.g., distress tolerance, emotion recognition), self-compassion, problem solving, and attentive awareness. This research provides meaningful insights that may be used to guide intervention planning for individuals with ADHD symptomology in clinical and academic settings.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».