Evidence map›Paper›PMID 40866858›Full record

ArticleBMC medical informatics and decision making2025

Development and evaluation of an Instagram version (prototype) of decision-making aid for women on the methods of pharmacological and non-pharmacological pain relief during childbirth.

Eri Shishido, Anna Hayashi, Risa Takahashi, Shigeko Horiuchi

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Eri ShishidoSt. Luke's International University, 10-1 Akashi-cho, Chuo-ku, Tokyo, 104-0044, Japan. eri-shishido@slcn.ac.jp.
Anna HayashiAiiku Hospital, 1-16-10 Shibaura, Minato-ku, Tokyo, 105-0023, Japan.
Risa TakahashiAiiku Hospital, 1-16-10 Shibaura, Minato-ku, Tokyo, 105-0023, Japan.
Shigeko HoriuchiSt. Luke's International University, 10-1 Akashi-cho, Chuo-ku, Tokyo, 104-0044, Japan.

Funding

Japan Society for the Promotion of Science 21K17401/24K20352
6 · The paper itself

Abstract

backgroundPregnant women need sufficient information and explanations from midwives to create a birth plan that includes pain relief options during labor. This study aimed to create an Instagram version prototype of the decision aid, “Aids of What You Can Do During Labor”, which supports the choice of various pharmacological and non-pharmacological pain relief methods. Additionally, the study evaluated the usefulness of this prototype among pregnant women planning vaginal deliveries after 28 weeks of gestation.

methodsThis was a descriptive study. First, the Instagram prototype was developed on the basis of the “Aids of What You Can Do During Labor”, created by Takahashi (2023). The prototype consisted of explanations of the aid, definitions of key terms, and four steps; Step 1: “Learning how to make an informed decision”, Step 2: “Learning the pros and cons of each option”, Step 3: “Setting clear priorities for decision-making”, and Step 4: “Deciding how to spend time during labor”. A total of 17 posts containing information from Step 1 to Step 4 were created. Next, the usefulness of the prototype was assessed through a questionnaire survey conducted with 20 women with singleton pregnancies planning vaginal deliveries after 28 weeks of gestation. The usefulness data, such as whether pregnant women have found a method of labor pain relief that they would like to try were descriptively analyzed and qualitative including free-text data were analyzed via the KJ. The ethics committee approved the study.

resultsThe study participants included 12 primiparas and 8 multiparas (a total of 20). More than 80% of the participants provided positive feedback regarding the usefulness of the Instagram prototype, particularly in terms of the following: “I was able to learn what I wanted to know compared to before reading the aid,” “I found a pain relief method that interested me or that I wanted to try,” and “I think reading the aid helped in creating a birth plan.” On the basis of the participants’ feedback, a revised version of the Instagram aid was created, increasing the total number of posts to 18.

conclusionThe usefulness of the Instagram version prototype was confirmed, through this study. Future studies should evaluate the impact of using the Instagram aid on the creation of birth plans. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Decision Support TechniquesLabor PainPain ManagementParturitionSocial MediaAdultFemaleHumansPregnancySurveys and QuestionnairesBirth planDecision aidInstagramLabor and childbirthPain relief

Identifiers

PMID40866858
PMCPMC12382101

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.