Evidence map›Paper›PMID 37917601›Full record

ArticlePloS one2023

Decision making among residents in training of obstetrics and gynecology: A qualitative exploration in Pakistani context.

Sana Younas, Saeeda Khanum, Azher Hameed Qamar

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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 at 2 institutions in 2 countries.

Sana YounasDepartment of Behavioral Sciences, School of Social Sciences and Humanities, National University of Sciences and Technology, Islamabad, Pakistan.ORCID 0000-0003-1893-3039
Saeeda KhanumDepartment of Behavioral Sciences, School of Social Sciences and Humanities, National University of Sciences and Technology, Islamabad, Pakistan.ORCID 0000-0002-4335-1623
Azher Hameed QamarDepartment of Behavioral Sciences, School of Social Sciences and Humanities, National University of Sciences and Technology, Islamabad, Pakistan.
National University of Sciences and Technology · PKLund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical decision-making is critical and the decisions are made under uncertain, complex, and dynamic conditions. In this regard, practitioners' experiences and perceptions may provide a bottom-up knowledge of the issues, as well as a corresponding support system that assists them in learning to make decisions in critical situations. The current study aimed to examine these experiences in the Pakistani context. We interviewed 14 trainee residents (aged 26 to 34 years) from tertiary care hospitals. Using inductive thematic analysis, we explored a participant-centered perspective on the support system and decision-making process. Findings reveal that the major challenges to decision-making include uncertain and complex situations, hospital-related constraints, and sociocultural context. Both non-critical and critical case management are used in individual and group decision-making processes. The residents use knowledge-based, emotional, and instrumental support to make decisions. The study gave practitioners and academics a transdisciplinary platform to explore the cognitive, social, and behavioral aspects of decision-making in the healthcare industry.

Indexed as

GynecologyObstetricsDecision MakingFemaleHumansPakistanPregnancyQualitative Research

Identifiers

PMID37917601
PMCPMC10621809
OpenAlexW4388215418

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.