Smartphone apps for child sexual abuse education: gaps and design considerations
Bibliographic record
Abstract
The objectives of this study are understanding the requirements of a child sexual abuse (CSA) education app, identifying the limitations of existing apps, and providing guidelines for better app design. An electronic search across three major app stores was conducted and the selected apps were rated by a devised app rating scale. Our rating scale evaluates essential features, functionalities, and software quality characteristics that are necessary for CSA education apps, and determined their effectiveness for potential use as CSA education programs for children. User comments from the app stores are collected and analysed to understand their expectations and views. After analysing the feasibility of the reviewed apps, CSA app design considerations are proposed that highlight game-based teaching approaches. The evaluation results show that most of the reviewed apps are not suitable for being used as CSA education programs. Moreover, all the apps need to be improved in terms of their software qualities and CSA-specific features to be considered as potential CSA education programs. This study provides the necessary knowledge to developers and individuals regarding the essential features and software quality characteristics for designing and developing CSA education apps.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".