| Literature DB >> 36121804 |
Brandon G Smith1,2, Charlotte J Whiffin2,3, Ignatius N Esene4, Claire Karekezi5, Tom Bashford2, Muhammad Mukhtar Khan2,6, Davi J Fontoura Solla2,7, Bhagavatula Indira Devi2,8, Wellingson S Paiva2,7, Franco Servadei9, Peter J Hutchinson1,2, Angelos G Kolias1,2, Anthony Figaji2,10, Andres M Rubiano2,11.
Abstract
BACKGROUND: Traumatic brain injury (TBI) is a major global health issue, but low- and middle-income countries (LMICs) face the greatest burden. Significant differences in neurotrauma outcomes are recognised between LMICs and high-income countries. However, outcome data is not consistently nor reliably recorded in either setting, thus the true burden of TBI cannot be accurately quantified.Entities:
Mesh:
Year: 2022 PMID: 36121804 PMCID: PMC9484678 DOI: 10.1371/journal.pone.0274922
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.752
Inclusion criteria.
| Inclusion criteria |
|---|
| • Practising physician within a country identified as an LMIC by the World Bank |
| • At least 2 years’ experience of managing neurotrauma |
| • Some experience in the research process and/or long-term follow-up |
| • Self-declared fluency in written or spoken English |
| • Access to electronic communication platform (e-mail, videoconferencing, telephone) |
| • Able to provide informed consent |
Application of reflexive thematic analysis [47, 49, 50].
| Phase | Description | Product of framework |
|---|---|---|
|
| Transcription of data, reading and re-reading data, taking note of initial ideas and keeping a reflexive diary. | Preliminary codes. |
|
| Systemically coding interesting features of the data across the dataset, collating data relevant to each code, and creating relevant memos as to the meaning behind each code. | Comprehensive coding. |
|
| Collating codes into potential early categories and exploring hierarchies and possible relationships between these, with critical discussion with second author. | Raw, potential ‘precursor themes’. |
|
| Checking if the themes work with relation to the coded extracts, and further with the entire dataset, followed by generating a thematic map of the analysis, with further critical discussion with second author. | Themes and an early map of the potential relationships and flow between themes. |
|
| Ongoing analysis and revisiting and refining specifics of each theme, the overall narrative being portrayed from the analysis, and generating firm names and definitions for each theme with second author. | Refined themes and a uniting narrative. |
|
| Selection of vivid, compelling extract examples and a final opportunity for analysis, relating the analysis to the initial research question and literature in the production of a first report. | Comprehensive report of all themes, interpretations, and accompanying narrative supported by quotes. |
| Respondent validation and co-author feedback advanced and finalised the final report. |
Participant demographics.
|
|
| ||
| 30–39 | 11 | Low | 4 |
| 40–49 | 2 | Lower-middle | 10 |
| 50–59 | 5 | Middle | 4 |
|
|
| ||
| Male | 15 | East Asia & Pacific | 1 |
| Female | 3 | Europe & Central Asia | 0 |
|
| Latin America & the Caribbean | 2 | |
| Public | 15 | Middle East & North Africa | 2 |
| Private | 8 | South Asia | 6 |
| Urban | 9 | Sub-Saharan Africa | 7 |
| Rural | 1 |
| |
| Large national reference centre | 9 | Brazil | 1 |
| Small regional centre | 3 | Colombia | 1 |
|
| Egypt (Arab Rep.) | 1 | |
| 2 to 5 | 9 | Ethiopia | 2 |
| 6 to 10 | 2 | India | 3 |
| 11 to 15 | 2 | Malaysia | 1 |
| 15 + | 5 | Morocco | 1 |
|
| Nepal | 1 | |
| 2 to 5 | 5 | Nigeria | 2 |
| 6 to 10 | 5 | Pakistan | 2 |
| 11 to 15 | 1 | Rwanda | 1 |
| 15 + | 7 | South Africa | 1 |
| Uganda | 1 | ||