Add to Cart: Problematic Shopping and Behavioral Addictions in a Canadian Sample During the COVID-19 Pandemic
Bibliographic record
Abstract
ABSTRACT Objective: Problematic shopping can include uncontrollable and frequent urges to shop. The coronavirus disease 2019 (COVID-19) pandemic may have influenced these behaviors in several ways, such as through increased online shopping opportunities and pandemic-related stress. The purpose of this exploratory study was to examine shopping and other behavioral addictions in the context of COVID-19. Methods: Canadian participants (n=546) reported on shopping, gambling, and gaming behaviors, using an online questionnaire. Results: Many participants reported that they shopped more overall (42%), shopped more online (57%), and shopped more for nonessential goods (38%) during the pandemic. Online shoppers also demonstrated greater scores on 2 measures of problem shopping behavior: the Bergen Shopping Addiction Scale, and the Richmond Compulsive Buying Scale. Further, female participants were more likely to report problematic shopping behaviors, whereas male participants were more likely to report problematic gaming behaviors. However, both problematic gambling and gaming were associated with problematic shopping. Conclusions: The present findings may shed light on how individuals are faring in relation to behavioral addictions and consumerism during COVID-19. The clinical implications are that a number of individuals may be struggling with problematic shopping, which may overlap with other behavioral addictions (ie, gambling, gaming), and which could be exacerbated by the current economic pressures of the pandemic. Objectif: Le magasinage problématique peut comprendre des envies incontrôlables et fréquentes de faire des achats. La pandémie de la COVID-19 peut avoir influencé ces comportements de plusieurs manières, notamment par le biais de l’augmentation des possibilités d’achat en ligne et le stress lié à la pandémie. L’objectif de cette étude exploratoire était d’examiner le magasinage et d’autres dépendances comportementales dans le contexte du COVID-19. Méthodes: Les participants canadiens (N=546) ont déclaré leurs comportements de magasinage, de paris d’argent et de jeux vidéo, à l’aide d’un questionnaire en ligne. Résultats: De nombreux participants ont déclaré avoir fait plus d’achats dans l’ensemble (42%), plus d’achat en ligne (57%) et ont acheté davantage de biens non essentiels (38%) pendant la pandémie. Les acheteurs en ligne ont également obtenu des résultats plus élevés sur deux mesures de comportement d’achat problématique : l'échelle de Bergen sur la dépendance au magasinage et l'échelle de Richmond sur les achats compulsifs. En outre, les femmes étaient plus susceptibles de signaler des comportements de magasinage problématique, tandis que les hommes étaient plus susceptibles de signaler des comportements de jeu problématiques. Cependant, les paris d’argent et les jeux vidéo étaient associés à des achats compulsifs. Conclusions: Les présents résultats peuvent éclairer la façon dont les individus se comportent par rapport aux dépendances comportementales et à la consommation pendant la COVID-19. Les implications cliniques constatées sont qu’un certain nombre de personnes peuvent être aux prises avec des problèmes de magasinage compulsif, qui peuvent se chevaucher avec d’autres dépendances comportementales (p.ex. les paris d’argent et les jeux vidéo), et qui pourraient être exacerbées par les pressions économiques actuelles de la pandémie.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".