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Record W4400429597 · doi:10.2196/48453

Evaluating the Impact of a Dutch Sexual Health Intervention for Adolescents: Think-Aloud and Semistructured Interview Study

2024· article· en· W4400429597 on OpenAlexvenueno aff
Gido Metz, Rosa Ricarda Leni Charlotte Thielmann, Hanneke Roosjen, Rik Crutzen

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsnot available
FundersZonMw
KeywordsIntervention (counseling)PsychologyThink aloud protocolReproductive healthRead aloudSemi-structured interviewDevelopmental psychologyClinical psychologyQualitative researchMedicinePsychiatrySociologyPolitical scienceEnvironmental healthComputer scienceAnthropologyReading (process)

Abstract

fetched live from OpenAlex

BACKGROUND: Engagement with and the potential impact of web-based interventions is often studied by tracking user behavior with web analytics. These metrics do provide insights into how users behave, but not why they behave as such. OBJECTIVE: This paper demonstrates how a mixed methods approach consisting of (1) a theoretical analysis of intended use, (2) a subsequent analysis of actual use, and (3) an exploration of user perceptions can provide insights into engagement with and potential impact of web-based interventions. This paper focuses on the exploration of user perceptions, using the chlamydia page of the Dutch sexual health intervention, Sense.info, as a demonstration case. This prevention-focused platform serves as the main source of sexual and reproductive health information (and care if needed) for young people aged 12-25 years in the Netherlands. METHODS: First, acyclic behavior change diagrams were used to theoretically analyze the intended use of the chlamydia page. Acyclic behavior change diagrams display how behavior change principles are applied in an intervention and which subbehaviors and target behaviors are (aimed to be) influenced. This analysis indicated that one of the main aims of the page is to motivate sexually transmitted infection (STI) testing. Second, the actual use of the chlamydia page was analyzed with the web analytics tool Matomo. Despite the page's aim of promoting STI testing, a relatively small percentage (n=4948, 14%) of the 35,347 transfers from this page were to the STI testing page. Based on these two phases, preliminary assumptions about use and impact were formulated. Third, to further explore these assumptions, a study combining the think-aloud method and semistructured interviews was executed with 15 young individuals aged 16-25 (mean 20, SD 2.5) years. Template analysis was used to analyze interview transcripts. RESULTS: Participants found the information on the Sense.info chlamydia page reliable and would visit it mostly for self-diagnosis purposes if they experienced potential STI symptoms. A perceived facilitator for STI testing was the possibility to learn about the symptoms and consequences of chlamydia through the page. Barriers included an easily overlooked link to the STI testing page and the use of language not meeting the needs of participants. Participants offered suggestions for lowering the threshold for STI testing. CONCLUSIONS: The mixed methods approach used provided detailed insights into the engagement with and potential impact of the Sense.info chlamydia page, as well as strategies to further engage end users and increase the potential impact of the page. We conclude that this approach, which triangulates findings from theoretical analysis with web analytics and a think-aloud study combined with semistructured interviews, may also have potential for the evaluation of web-based interventions in general.

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)0.014
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.172
GPT teacher head0.553
Teacher spread0.382 · 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 designQualitative
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

Citations4
Published2024
Admission routes1
Has abstractyes

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