Evidence map›Paper›PMID 38315187›Full record

ArticleEuropean journal of cardiovascular nursing2024

Transcribing in the digital age: qualitative research practice utilizing intelligent speech recognition technology.

Helen Eftekhari

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European journal of cardiovascular nursing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Trial
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  8. Canadian oncology nursing journal = Revue canadienne de nursing oncologique · 2026
    Article
  9. Identifying Barriers to Fertility Preservation in Adolescent and Young Adult Cancer Patients.Canadian oncology nursing journal = Revue canadienne de nursing oncologique · 2026
    Article
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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

1 author.

Helen EftekhariDepartment of Health Sciences, University of Warwick, UK.ORCID 0000-0001-7140-7180

Funding

British Heart Foundation FS/20/1/34946
6 · The paper itself

Abstract

The digital revolution provides many opportunities for researchers to develop and evolve data collection methods. A key process in qualitative research data collection is the transcription of interviews, focus groups or fieldwork notes. Transcription is the process of converting audio, video or notes into accessible written format for qualitative data analysis. Transcribing can be time intensive, costly and laborious with decisions and methods of transcribing requiring transparency. The development of intelligent speech recognition technology can change how qualitative data is transcribed. This methods paper describes audio data transcribing, current challenges, opportunities and implications in using intelligent speech recognition technology for transcribing. An application of this methodology is presented.

Indexed as

Qualitative ResearchSpeech Recognition SoftwareData CollectionHumansDigital ageQualitative methodsSimultaneous speech recognition technologyTranscribing

Identifiers

PMID38315187
PMCPMC11334016

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.