Evidence map›Paper›PMID 36415624›Full record

ArticleInternational journal of information management2023

The effect of fear and situational motivation on online information avoidance: The case of COVID-19.

Tahmina Sultana, Gurpreet Dhillon, Tiago Oliveira

Abstract read
In one paragraph

Article in International journal of information management, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Infodemic: Challenges and solutions in topic discovery and data process.Archives of public health = Archives belges de sante publique · 2023
    Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Tahmina SultanaInformation Systems and Supply Chain Management, University of North Carolina Greensboro, Greensboro, United States.
Gurpreet DhillonInformation Technology and Decision Sciences, University of North Texas, Denton, United States.
Tiago OliveiraNOVA Information Management School, Universidade NOVA de Lisboa, Lisbon, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the COVID-19 pandemic, a plethora of online sources for information and news dissemination have emerged. Extant research suggests that very quickly, individuals become disinterested and begin avoiding the information. In this study, we investigate how an individual's fear and situational motivation impact Online Information Avoidance. Using the self-determination theory and information avoidance theories, we argue that fear and external regulation are associated with increased Online Information Avoidance. We also argue that intrinsic motivation and identified regulation are associated with a decrease in Online Information Avoidance. Our findings suggest that fear, intrinsic motivation, and external regulation drive Online Information Avoidance, where intrinsic motivation is the most significant driver. We also found that identified regulation is a crucial inhibitor of Online Information Avoidance. While focusing on COVID-19, our study contributes to the broader information systems research literature and specifically to the information avoidance literature during a pandemic or a prolonged crisis. Our study's findings will be useful for governments, health organizations, and communities that utilize online platforms, forums, and related outlets to reach larger audiences for disseminating pertinent information and recommendations during a crisis.

Indexed as

COVID-19FearOnline information avoidanceSelf-determination theorySituational motivation

Identifiers

PMID36415624
PMCPMC9671792

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.