Evidence map›Paper›PMID 40861136›Full record

ArticleIndustrial psychiatry journal

Excessive day time sleepiness, poor sleep quality, and their association to caffeine consumption among young Informational Technology professionals.

Aruna Raju, Madhavan Chandran, Jean Fredrick

Abstract read
In one paragraph

Article in Industrial psychiatry journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Aruna RajuDepartment of Physiology, All India Institute of Medical Science, Kalyani, West Bengal, India.
Madhavan ChandranDepartment of Physiology, All India Institute of Medical Science, Kalyani, West Bengal, India.
Jean FredrickDepartment of Physiology, All India Institute of Medical Science, Kalyani, West Bengal, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sleep is essential for promoting physical and mental wellbeing. Short sleep duration and poor sleep quality are becoming more common among Informational Technology (IT) professionals; many IT workers seem to be using caffeine as a coping mechanism to alleviate the negative effects of insufficient sleep. Caffeine reduces sleep quality, prolongs sleep latency, and shortens sleep duration. Information on the sleep quality of young IT professionals is required to determine whether there may be a link between sleep quality, excessive daytime sleep, and caffeine usage. Aim: This cross-sectional study examined sleep quality in IT professionals and the associations between sleep quality, excessive daytime sleep, and caffeine consumption. Materials and Methods: Caffeine Consumption, Epworth Sleepiness Scale, and Pittsburgh Sleep Quality Index questionnaires were administered to 200 IT professionals aged 23-40 years via the online survey. Results: The average daily caffeine intake was 156.2 (98.7-252.5) mg per day, with coffee and tea being the primary contributor. A high prevalence of poor sleep quality (70%) was observed in the study population. Daily caffeine consumption was associated with poor sleep quality (r = 0.510, Conclusion: These findings reveal that poor sleep quality is prevalent among IT professionals. More research is required to determine the methods to improve sleep issues. Additionally, health education should be provided regarding the quantity of caffeine in products to avoid excess caffeine consumption and to improve sleep quality.

Indexed as

Caffeineexcessive day time sleeppoor sleep quality

Identifiers

PMID40861136
PMCPMC12373328

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.