The Characteristics and Quality of Mobile Phone Apps Targeted at Men Who Have Sex With Men in China: A Window of Opportunity for Health Information Dissemination?
Bibliographic record
Abstract
BACKGROUND: A number of mobile phone apps has been developed specifically for men who have sex with men (MSM). We will call these mobile phone apps MSM apps for simplicity. At present, the characteristics and quality and purpose of these MSM apps are unclear. OBJECTIVE: The aim of this study was to objectively and comprehensively evaluate the characteristics and quality of the MSM apps to assess whether they disseminated health information among the MSM in China. METHODS: We searched 2 dominant mobile phone app stores (Apple Store and Android Market) to obtain MSM apps using the keywords MSM, gay, lesbian, gay, bisexual, and transgender (LGBT), ，，，，, and . Apps were excluded if they did not have a Chinese language interface or if their target population was not MSM. Basic information about the eligible apps for this study, such as app name, app store category, and date of last update was gathered from the specified app stores. The quality of apps was rated by 2 independent raters using Mobile App Rating Scale (MARS). The intraclass correlation coefficient (ICC) between raters was computed as a measure for interrater reliability of the MARS. All analyses were conducted using SPSS version 20.0 (SPSS Inc). RESULTS: A total of 575 apps were reviewed between September 15, 2018 and September 30, 2018, out of which, 532 apps were excluded. Finally, 43 apps were included. Of the 43 apps, 16 were from the Apple Store, 10 were from Android Market, and 17 were available in both app stores. In addition, 39 out of 43 apps were for social and sexual networking, whereas 10 contained sexual health information, for example, HIV/sexually transmitted diseases knowledge, HIV test, and condom use. The average rating was 4 stars. The number of downloads for 21 apps exceeded 10,000. A total of 31 apps had acceptable quality (as defined by a MARS score of >3), with functionality as the highest scoring domain, followed by information quality, esthetics, and engagement. Interrater reliability was excellent for the overall mean app quality scores (ICC=.946; 95% CI 0.904-0.970) and the subjective quality scores (ICC=.910; 95% CI 0.841-0.950). CONCLUSIONS: By reviewing the available apps, we found that MSM apps are popular. The majority of MSM apps are for dating, whereas few of them contain HIV prevention and health information. The overall quality of the apps is acceptable. The utilization of mobile phone technologies is a promising way for delivering HIV prevention messages to MSM. We recommend that researchers and app developers should work together to disseminate health information for MSM via mobile technologies.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".