Evidence map›Paper›PMID 36532109›Full record

ArticleDigital health

A post-phenomenological analysis of using menstruation tracking apps for the management of premenstrual syndrome.

Sarah Riley, Klara Paskova

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sarah RileySchool of Psychology, Massey University, Wellington, New Zealand.ORCID https://orcid.org/0000-0001-6712-6976
Klara PaskovaSchool of Psychology, Massey University, Wellington, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Menstruation tracking digital applications (MTA) are a popular technology, yet there is a lacuna of research on how women use this technology for the management of PMS. Theoretical frameworks for understanding users' experiences are also underdeveloped in this nascent field. The objectives of the study were therefore twofold, to propose a theoretical framework for understanding women's use of MTA and apply it to the analysis of users' experiences in the management of PMS. Method: A novel theoretical framework was proposed, informed by post-phenomenology, postfeminist healthism, feminist new materialism and digital health technologies as public pedagogy. This framework focuses analytic attention on affective relationships between subjectivity, bodily sensations, digital technology, and discourse. It was used to structure the analysis of five in-depth timeline interviews with women in Aotearoa New Zealand who experienced benefits from using MTA to manage PMS symptoms. Results: Three pedagogical relationships were identified: a pedagogy of empowerment, where users learnt to control, predict and manage their PMS symptoms in line with healthism; a pedagogy of appreciation, where users learnt to understand their menstruating bodies as amazing, a valued part of them, and awe-inspiring that radically overturned past internalised stigma; and an 'untrustworthy teacher' who eroded this affirmative learning through inaccuracy, positioning users in dis-preferred categories, or being 'creepy'. Conclusions: MTA offers huge possibilities for challenging menstrual stigma that need to be nurtured, developed, and protected; and there are benefits for analysing MTA within wider scholarship on postfeminist healthism.

Indexed as

Digital healthhealthismmenstrual trackingperiod tracking appspersonal informaticspostfeminismpostfeminist healthismpost-phenomenologypremenstrual syndromeuser experience

Identifiers

PMID36532109
PMCPMC9756356

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.