Evidence map›Paper›PMID 34113286›Full record

ArticleFrontiers in psychology2021

Techno Trend Awareness and Its Attitude Towards Social Connectedness and Mitigating Factors of COVID-19.

Vijyendra Pandey, Neelam Misra, Rajgopal Greeshma, Arora Astha, Sundaramoorthy Jeyavel, Govindappa Lakshmana, Eslavath Rajkumar, G Prabhu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Vijyendra PandeyDepartment of Psychology, Central University of Karnataka, Gulbarga, India.
Neelam MisraDepartment of Microbiology, Gulbarga University, Gulbarga, India.
Rajgopal GreeshmaDepartment of Psychology, Central University of Karnataka, Gulbarga, India.
Arora AsthaDepartment of Psychology, Central University of Karnataka, Gulbarga, India.
Sundaramoorthy JeyavelDepartment of Psychology, Central University of Karnataka, Gulbarga, India.
Govindappa LakshmanaDepartment of Social Work, Central University of Karnataka, Gulbarga, India.
Eslavath RajkumarDepartment of Psychology, Central University of Karnataka, Gulbarga, India.
G PrabhuDepartment of Psychology, Central University of Karnataka, Gulbarga, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While COVID-19 has taken a toll on many professions and livelihood of all walks of lives, technology has amplified its intrusion to ease the necessities. Innovative technology, therefore, has improved the glitches and provided the software to adhere to these new normal. However, individuals' awareness and attitude toward the advancements of these technological trends need to be addressed. Although the government has taken measures to prevent and curb the growing cases for COVID-19 with the help of technology, the support from the individuals would depend mostly on their level of awareness and the attitude toward those measures. The present qualitative study explored the techno trend awareness, perception and attitudes of techno experts and technical professionals toward social connectedness and mitigating factors of COVID-19. Besides, it also explained individuals' shift toward virtual interaction to maintain social connections during the pandemic. The thematic analysis generated four prominent themes. Social Connectedness, emphasized on the emotional connections that created a positive feeling of belongingness. Technological Advancement provided three sub-themes highlighting perception, techno trend awareness and desirable attitudes toward the mitigation of COVID-19. The categories under Treatment and Preventive Measures indicated the enhanced self-care of individuals and also the tendencies to minimize the spread of diseases. The emergence of the theme Inclination toward Indigenous Knowledge, which is an important finding, indicated the techno-experts inclination toward the indigenous knowledge amid vague scientific shreds of evidence.

Indexed as

belongingnessCOVID-19Indian cultureindigenous knowledgesocial connectednesstechnological trend awareness

Identifiers

PMID34113286
PMCPMC8185047

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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.