Development of and Experiences With an Informational Website on Early Labor: Qualitative User Involvement Study
Bibliographic record
Abstract
BACKGROUND: The period of regular contractions before 4 cm of cervical dilatation is often referred to as the latent phase or early labor. Women find it challenging to prepare for and cope with this phase of labor, and easily accessed web-based information from reliable sources may be useful in this preparation. OBJECTIVE: The aim of this study is to describe the development of a Norwegian website, Latens.no, for people seeking information on early labor and to explore users' experiences with the website to increase its user-friendliness. METHODS: We developed a website using an iterative process involving a multidisciplinary research team, health personnel, users, a graphic designer, and an expert in software development. We explored the website's user-friendliness using semistructured individual interviews and the think-aloud method. All interviews were audio recorded and transcribed. We then analyzed the participants' feedback on the website. RESULTS: Participants included women who had recently given birth to their first baby (n=2), women who were pregnant with their first baby (n=4), and their partners (n=2). Results from participants' experiences completing tasks included positive feedback related to the content of Latens.no, positive feedback related to the website's design, and suggestions for improvement. Participants wanted to find information on early labor on the internet. Moreover, they found the information on the website relevant, trustworthy, and easy to read, and the design was attractive and easy to use. Overall, the participants performed the tasks easily, with few clicks and minimal effort. CONCLUSIONS: The think-aloud method, while performing tasks, allowed for detailed feedback. The participants confirmed the user-friendliness of the website but at the same time provided information enabling improvement. We expect that changes made based on this user-centered design study will further increase the usability and acceptability of Latens.no.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".