Evidence map›Paper›PMID 35409967›Full record

ReviewInternational journal of environmental research and public health2022

Technology-Based Mental Health Interventions for Domestic Violence Victims Amid COVID-19.

Zhaohui Su, Ali Cheshmehzangi, Dean McDonnell, Hengcai Chen, Junaid Ahmad, Sabina Šegalo, Claudimar Pereira da Veiga

Open access · goldAbstract readReview
In one paragraph

Review 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 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 11% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Learn to Live Again: A Pilot Study to Support Women Experiencing Domestic Violence.International journal of environmental research and public health · 2025
    Article
  6. Article
  7. Article
  8. 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

7 authors at 6 institutions in 5 countries.

Zhaohui SuSchool of Public Health, Southeast University, Nanjing 210009, China.ORCID 0000-0003-2005-9504
Ali CheshmehzangiFaculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China.ORCID 0000-0003-2657-4865
Dean McDonnellDepartment of Humanities, Institute of Technology Carlow, R93 V960 Carlow, Ireland.
Hengcai ChenFaculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China.
Junaid AhmadPrime Institute of Public Health, Peshawar Medical College, Warsak Road, Peshawar 25160, Pakistan.ORCID 0000-0002-8580-7529
Sabina ŠegaloFaculty of Health Studies, University of Sarajevo, 71000 Sarajevo, Bosnia and Herzegovina.ORCID 0000-0002-9280-3278
Claudimar Pereira da VeigaSchool of Management-PPGOLD, Federal University of Parana-UFPR, Curitiba 80210-170, PR, Brazil.ORCID 0000-0002-4960-5954
Hiroshima University · JPInstitute of Technology Carlow · IESoutheast University · CNUniversidade Federal do Paraná · BRUniversity of Nottingham Ningbo China · CNUniversity of Sarajevo · BA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDomestic violence is a threat to human dignity and public health. Mounting evidence shows that domestic violence erodes personal and public health, spawning issues such as lifelong mental health challenges. To further compound the situation, COVID-19 and societies' poor response to the pandemic have not only worsened the domestic violence crisis but also disrupted mental health services for domestic violence victims. While technology-based health solutions can overcome physical constraints posed by the pandemic and offer timely support to address domestic violence victims' mental health issues, there is a dearth of research in the literature. To bridge the research gap, in this study, we aim to examine technology-based mental health solutions for domestic violence victims amid COVID-19.

methodsA literature review was conducted to examine solutions that domestic violence victims can utilize to safeguard and improve their mental health amid COVID-19. Databases including PubMed, PsycINFO, and Scopus were utilized for the literature search. The search was focused on four themes: domestic violence, mental health, technology-based interventions, and COVID-19. A reverse search of pertinent references was conducted in Google Scholar. The social ecological model was utilized to systematically structure the review findings.

resultsThe findings show that a wide array of technology-based solutions has been proposed to address mental health challenges faced by domestic violence victims amid COVID-19. However, none of these proposals is based on empirical evidence amid COVID-19. In terms of social and ecological levels of influence, most of the interventions were developed on the individual level, as opposed to the community level or social level, effectively placing the healthcare responsibility on the victims rather than government and health officials. Furthermore, most of the articles failed to address risks associated with utilizing technology-based interventions (e.g., privacy issues) or navigating the online environment (e.g., cyberstalking).

conclusionOverall, our findings highlight the need for greater research endeavors on the research topic. Although technology-based interventions have great potential in resolving domestic violence victims' mental health issues, risks associated with these health solutions should be comprehensively acknowledged and addressed.

Indexed as

COVID-19Domestic ViolenceHumansMental HealthPandemicsTechnologyCOVID-19domestic violencemental healthsocial ecological modeltechnology-based interventions

Identifiers

PMID35409967
PMCPMC8998837
OpenAlexW4223616740

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.