Development and Validation of a Mobile Game for Culturally Sensitive Child Sexual Abuse Prevention Education in Tanzania: Mixed Methods Study

Engaging Parents in Child-Focused Child Sexual Abuse Prevention Education Strategies: A Systematic Review

Parents are their children's first teachers and there are long-standing calls for their involvement in child sexual abuse prevention. In this rapid systematic review, we asked the following questions: what rationales are used to justify parental involvement in child-focused child sexual abuse (CSA) prevention programs? what approaches are used for parental engagement in child-focused CSA prevention programs? and what are the facilitators and barriers to parental involvement in child-focused CSA prevention programs? We searched CINAHL, Cochrane, ERIC, Medline, PsycInfo, Scopus, and SocINDEX in May 2021. A total of 57 papers met our inclusion criteria, comprised of 50 empirical studies, and 7 program descriptions. Rationales for parental involvement included monitoring and shaping parental attitudes toward CSA program delivery in schools; reinforcing children's learning at home; promoting parent-child communication about CSA prevention; building parent capacity to respond to child disclosures; and supporting program delivery for preschoolers. Types of parental involvement included the following: communication, learning at home, volunteering, decision-making, and collaboration with the community. Barriers to parent involvement included ineffective program engagement modalities, and parental fears and misconceptions.

Exploring methods for creating or adapting knowledge mobilization products for culturally and linguistically diverse audiences: a scoping review

BACKGROUND

Connecting end-users to research evidence has the power to improve patient knowledge and inform health decision-making. Differences in the culture and language of the end users may shape the effectiveness of knowledge mobilization (KMb). This scoping review set out to understand current approaches and methods when creating or adapting KMb products for culturally and linguistically diverse (CALD) audiences.

METHODS

We searched 3 databases (Ovid Medline, CINAHL via EBSCOhost, PsychINFO) from 2011 until August 2023. We included any literature about KMb product creation or adaptation processes serving CALD communities. A primary reviewer screened all identified publications and a second reviewer screened publications excluded by the primary. Data were extracted using a standardized form by one reviewer and verified by a second reviewer. Studies were categorized by type of adaptations ('surface' and/or 'deep' structure) and mapped based on type of stakeholder engagement used in the research approach (i2S model), and end-user involvement (content, design, evaluation and dissemination) in KMb product creation or adaptation.

RESULTS

Ten thousand two hundred ninety-nine unique titles and abstracts were reviewed, 670 full-text studies were retrieved and reviewed, and 78 studies were included in final data extraction and mapping. Twenty-four studies (31%) created or adapted exclusively text-based KMb products such as leaflets and pamphlets and 49 (63%) produced digital products such as videos (n = 16, 33%), mobile applications (n = 14, 29%), and eHealth websites (n = 7, 14%). Twenty-five studies (32%) reported following a framework or theory for their creation or adaptation efforts. Twenty-eight studies (36%) engaged stakeholders in the research approach. Nearly all (96%) involved end-users in creating or adapting the KMb products through involvement in content development (n = 64), design features (n = 52), evaluation (n = 44) and dissemination (n = 20). Thirty-two (41%) studies included reflections from the research teams on the processes for creating or adapting KMb products for CALD communities.

CONCLUSION

Included studies cited a variety of methods to create or adapt KMb products for CALD communities. Successful uptake of created or adapted KMb products was often the result of collaboration and involvement with end-users for more applicable, accessible and meaningful products. Further research developing guidance and best practices is needed to support the creation or adaptation of KMb products with CALD communities.

REGISTRATION

Protocol submitted to Open Science Framework on August 16, 2022 ( https://osf.io/9jcw4/ ).

Digital games and virtual reality applications in child abuse: A scoping review and conceptual framework

Child abuse refers to any form of maltreatment, including physical abuse, sexual abuse, emotional abuse, and neglect that occurs to children under 18 years of age. Digital games and virtual reality (VR) can be used as beneficial solutions for dealing with child maltreatment concerns. This study aimed to present a conceptual framework for showing the applications of these technologies in managing child abuse. The framework is developed in two stages: (1) a scoping review to gather digital games and VR applications for child abuse issues through the search in PubMed, Ovid (APA PsycInfo), Scopus, Web of Science, ProQuest, Institute of Electrical and Electronics Engineers (IEEE), Cochrane Database of Systematic Reviews, and grey literature and (2) developing a conceptual framework based on the review results and validating it by 12 experts. The proposed conceptual framework shows that digital games and VR have been used for six main topics: (1) medical education, (2) prevention, (3) screening, (4) diagnosis, (5) treatment, and (6) forensic medicine in response to child abuse issues. Studies have more focused on child sexual abuse prevention, behavioral monitoring of sexual offenders in forensic medicine, and knowledge or performance assessment of students in medical education. Serious games (SGs), computer simulation, and immersive VR were common technologies for children, students, and forensic medicine, respectively. The experts believe the combination of immersive features of VR with SGs can further encourage user engagement. It appears that digital games and VR can play a positive role in child abuse management. Given the extensive capabilities of these technologies, further studies are needed to show all their potential applications for child abuse problems.

Artificial Intelligence-Driven Serious Games in Healthcare: A Scoping Review (Preprint).. [DOI: 10.2196/preprints.39840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

BACKGROUND

Artificial Intelligence (AI)-driven serious games have been used in healthcare to offer a customizable and immersive experience. Summarizing the features of the current AI-driven serious games is very important to explore how they have been developed and used and their current state in order to plan on how to leverage them in the current and future healthcare needs.

OBJECTIVE

The current study aimed to explore the features of AI-driven serious games in healthcare as reported by previous research.

METHODS

We carried out a scoping review to achieve the above-mentioned objective. The most popular databases in information technology and health fields (e.g., MEDLINE and IEEE Xplore) were searched using keywords related to serious games and AI. These terms were selected based on the target intervention (i.e., AI) and the target disease (i.e., COVID-19). Two reviewers independently performed the study selection process. Three reviewers independently used Microsoft Excel to extract data from the included studies. A narrative approach was used for data synthesis.

RESULTS

The search process returned 1470 records. Of these records, 46 met all eligibility criteria. 60 different serious games were found in the included studies. Motor impairment was the most common health condition targeted by these serious games. Serious games in most of the studies were used for rehabilitation. The serious games in the majority of the included studies can be played by only single player. Most serious games were played on standalone devices (offline games). The most common genres of serious games were role-playing games, puzzle games, and platformer games. Unity was the most prominent game engine used to develop serious games. Personal computers (PCs) were the most common platforms used to play serious games. The most common algorithms used in the included studies were Support Vector Machine (SVM), Convolutional Neural Network (CNN), Artificial Neural Networks (ANN), and Random Forest (RF). The most common purposes of AI were the detection of disease and the evaluation of user's performance. The dataset size ranged from 36 to 795,600, with an average of about 52,124. The most common validation techniques used in the included studies were K-fold cross-validation and training test split validation. Accuracy was the most commonly used metric to evaluate the performance of AI models.

CONCLUSIONS

The last decade witnessed an increase in the development of AI-driven serious games for healthcare purposes and targeting various health conditions and leveraging multiple AI algorithms; this rising trend is expected to continue for years to come. While the evidence uncovered in this study shows promising applications of AI-driven serious games, larger and more rigorous, diverse, and robust studies may be needed to examine the efficacy and effectiveness of AI-driven serious games in different populations with different health conditions.