Evidence map›Paper›PMID 37989758›Full record

ArticleScientific reports2023

Enhancing investigative interview training using a child avatar system: a comparative study of interactive environments.

Syed Zohaib Hassan, Saeed Shafiee Sabet, Michael Alexander Riegler, Gunn Astrid Baugerud, Hayley Ko, Pegah Salehi, Ragnhild Klingenberg Røed, Miriam Johnson, Pål Halvorsen

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 10% 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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  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

9 authors at 2 institutions in 1 country.

Syed Zohaib Hassan *Department of Holistic Systems, SimulaMet, 0167, Oslo, Norway. syed@simula.no.
Saeed Shafiee Sabet *Department of Holistic Systems, SimulaMet, 0167, Oslo, Norway.
Michael Alexander Riegler *Department of Holistic Systems, SimulaMet, 0167, Oslo, Norway.
Gunn Astrid Baugerud *Faculty of Social Sciences, OsloMet, 0167, Oslo, Norway.
Hayley Ko *Faculty of Social Sciences, OsloMet, 0167, Oslo, Norway.
Pegah Salehi *Department of Holistic Systems, SimulaMet, 0167, Oslo, Norway.
Ragnhild Klingenberg Røed *Faculty of Social Sciences, OsloMet, 0167, Oslo, Norway.
Miriam Johnson *Faculty of Health Sciences, OsloMet, 0167, Oslo, Norway.
Pål Halvorsen *Department of Holistic Systems, SimulaMet, 0167, Oslo, Norway.
Simula Metropolitan Center for Digital Engineering · NOUniversity of South-Eastern Norway · NO

Funding

Research Council of Norway 314690
6 · The paper itself

Abstract

The impact of investigative interviews by police and Child Protective Services (CPS) on abused children can be profound, making effective training vital. Quality in these interviews often falls short and current training programs are insufficient in enabling adherence to best practice. We present a system for simulating an interactive environment with alleged abuse victims using a child avatar. The purpose of the system is to improve the quality of investigative interviewing by providing a realistic and engaging training experience for police and CPS personnel. We conducted a user study to assess the efficacy of four interactive platforms: VR, 2D desktop, audio, and text chat. CPS workers and child welfare students rated the quality of experience (QoE), realism, responsiveness, immersion, and flow. We also evaluated perceived learning impact, engagement in learning, self-efficacy, and alignment with best practice guidelines. Our findings indicate VR as superior in four out of five quality aspects, with 66% participants favoring it for immersive, realistic training. Quality of questions posed is crucial to these interviews. Distinguishing between appropriate and inappropriate questions, we achieved 87% balanced accuracy in providing effective feedback using our question classification model. Furthermore, CPS professionals demonstrated superior interview quality compared to non-professionals, independent of the platform.

Indexed as

Child AbuseChildChild WelfareFeedbackHumansLearningStudents

Identifiers

PMID37989758
PMCPMC10663561
OpenAlexW4388852321

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.