Evidence map›Paper›PMID 36141741›Full record

ArticleInternational journal of environmental research and public health2022

A Creative Approach to Knowledge Translation: The Use of Short Animated Film to Share Stories of Refugees and Mental Health.

Katherine M Boydell, Joseph Croguennec

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

2 authors.

Katherine M BoydellBlack Dog Institute, Sydney 2034, Australia.ORCID 0000-0002-1464-8532
Joseph CroguennecBlack Dog Institute, Sydney 2034, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study used animated film to translate narratives of refugees and mental health into accessible material aimed at enhancing empathy and understanding. It focuses on the use of short animated films in series one and two of the Woven Threads catalogue. Series one shared moments of hope in a refugee's journey, whilst series two focused on people living with mental health challenges. This research was designed to understand the responses to viewing for people who watch these animations. A mixed-method design was used via an online Qualtrics platform that asked respondents to view two short animated films, one from the refugee series and one from the mental health series. 364 members of the general public viewed and responded to the refugee film and 275 responded to the mental health film. The platform collected both quantitative and qualitative data. Survey responses indicated that the majority of viewers found the films challenged public misconceptions about refugees and individuals with mental health challenges and left them with a feeling of hopefulness. Qualitative narratives were organised into one superordinate theme: the power of film as a knowledge translation strategy, with four subthemes: (i) changing perceptions and inspiring empathy, (ii) enhancing literacy, (iii) highlighting the power of storytelling, and (iv) encouraging hope and a sense of belonging. The use of short animated film as a knowledge translation strategy can enhance our understanding, promote deep reflection, increase empathy and has the potential to lead to social change.

Indexed as

RefugeesHumansMental HealthSurveys and Questionnairesanimationarts-based methodsfilmknowledge translationmental healthrefugee

Identifiers

PMID36141741
PMCPMC9517506

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.