MétaCan
Menu
Back to cohort
Record W4405623270 · doi:10.2196/52651

Promoting Comprehensive Sexuality Education in Pakistan Using a Cocreated Social Media Intervention: Development and Pilot Testing Study

2024· article· en· W4405623270 on OpenAlexvenueno aff
Furqan Ahmed, Ghufran Ahmad, Katharina Eisinger, Muhammad Asad Khan, Tilman Brand

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
FundersLeibniz-GemeinschaftDeutscher Akademischer Austauschdienst
KeywordsSocial mediaCurriculumHuman sexualityFocus groupPsychologyIntervention (counseling)Medical educationMedicinePedagogySociologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Comprehensive sexuality education (CSE) is a curriculum-based approach to learning and teaching about sexuality that focuses on the cognitive, emotional, physical, and social domains. The United Nations Educational, Scientific, and Cultural Organization (UNESCO) CSE guideline emphasizes gender issues and is firmly rooted in a human rights-based approach to sexuality. A recent cross-sectional community readiness assessment in Islamabad, Pakistan, found that the community is at the denial or resistant stage when it comes to implementing school-based sexuality education. The reluctance was attributed to a lack of understanding and widespread misconceptions about CSE. OBJECTIVE: This study aims to use the cocreation process to develop, pilot, and evaluate an intervention based on community readiness level to respond to community resistance by introducing CSE content, its anticipated benefits, and addressing prevalent misconceptions through awareness and promotion content for digital social media platforms. METHODS: For the development of the intervention (audio-video content), focus group discussion sessions with key stakeholders were held. Two videos were created in partnership with social media influencers and subsequently shared on Facebook, YouTube, and Instagram. A comprehensive process and performance evaluation of the videos and intervention development phase was conducted to evaluate audience exposure, reach, engagement, demographics, retention, and in-depth insights. The videos were uploaded to social media platforms in June and July 2021, and the data used to assess their performance was obtained in February 2022. RESULTS: With a total reach (number of people who have contact with the videos) of 432,457 and 735,563 for the first and second videos, respectively, on all social media platforms, we concluded that social media platforms provide an opportunity to communicate, promote, and engage with important stakeholders to raise awareness and obtain support for CSE. According to the findings, the public is responsive to CSE promotion content developed for social media platforms, with a total engagement (the number of people who participate in creating, sharing, and using the content) of 11,578. The findings revealed that male viewers predominated across all social media platforms. Punjab province had the largest audience share on Instagram (51.9% for the first video, 52.7% for the second) and Facebook (44.3% for the first video and 48.4% for the second). YouTube had the highest audience retention, with viewers watching an average of 151 seconds (45%) of the first video and 163 seconds (38%) of the second. With a net sentiment score of 0.83 (minimum=-3, maximum=5), end-user participation was also positive, and audience feedback highlighted the reasons for positive and negative criticism. CONCLUSIONS: To promote sexuality education in Pakistan, it is vital to overcome opposition through sensitizing the society, and digital social media platforms offer a unique, though underused, chance to do so through reliable influencer marketing.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.466
GPT teacher head0.624
Teacher spread0.158 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Formative ResearchSame topicAdolescent Sexual and Reproductive HealthFrench-language works237,207