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Enregistrement W4233690920 · doi:10.2196/preprints.25388

Investigation of Digital Technology Use in the Transition to Parenting: Qualitative Study (Preprint)

2020· preprint· en· W4233690920 sur OpenAlexaff
Lorie Donelle, Jodi Hall, Bradley Hiebert, Kimberley T. Jackson, Ewelina Stoyanovich, Jessica LaChance, Danica Facca

Notice bibliographique

Revuenon disponible
Typepreprint
Langueen
DomaineEnvironmental Science
ThématiqueSocioeconomic and Demographic Analysis
Établissements canadiensFanshawe CollegeWestern University
Organismes subventionnairesnon disponible
Mots-clésSnowball samplingFocus groupNonprobability samplingPsychologyQualitative researchDevelopmental psychologyTransition (genetics)Medical educationMedicineSociologyPopulationSocial science

Résumé

récupéré en direct d'OpenAlex

<sec> <title>BACKGROUND</title> The transition to parenting—that is, the journey from preconception through pregnancy and postpartum periods—is one of the most emotionally charged and information-intense times for individuals and families. While there is a developing body of literature on the use and impact of digital technology on the information behaviors of children, adolescents, and young adults, personal use of digital technology during the transition to parenting and in support of infants to 2 years of age is relatively understudied. </sec> <sec> <title>OBJECTIVE</title> The purpose of this study was to enhance our understanding of the ways digital technologies contribute to the experience of the transition to parenting, particularly the role these technologies play in organizing and structuring emerging pregnancy and early parenting practices. </sec> <sec> <title>METHODS</title> A qualitative descriptive study was conducted to understand new parents’ experiences with and uses of digital technology during 4 stages—prenatal, pregnancy, labor, and postpartum—of their transition to becoming a new parent. A purposive sampling strategy was implemented using snowball sampling techniques to recruit participants who had become a parent within the previous 24 months. Focus groups and follow-up interviews were conducted using semistructured interview guides that inquired about parents’ type and use of technologies for self and family health. Transcribed audio recordings were thematically analyzed. </sec> <sec> <title>RESULTS</title> A total of 10 focus groups and 3 individual interviews were completed with 26 participants. While recruitment efforts targeted parents of all genders and sexual orientations, all participants identified as heterosexual women. Participants reported prolific use of digital technologies to direct fertility (eg, ovulation timing), for information seeking regarding development of their fetus, to prepare for labor and delivery, and in searching for a sense of community during postpartum. Participants expressed their need for these technologies to assist them in the day-to-day demands of preparing for and undertaking parenting, yet expressed concerns about their personal patterns of use and the potential negative impacts of their use. The 3 themes generated from the data included: “Is this normal; is this happening to you?!”, “Am I having a heart attack; what is this?”, and “Anyone can put anything on Wikipedia”: Managing the Negative Impacts of Digital Information. </sec> <sec> <title>CONCLUSIONS</title> Digital technologies were used by mothers to track menstrual cycles during preconception; monitor, document, and announce a pregnancy during the prenatal stage; prepare for delivery during labor/birth stage; and to help babies sleep, document/announce their birth, and connect to parenting resources during the postpartum stage. Mothers used digital technologies to reassure themselves that their experiences were normal or to seek help when they were abnormal. Digital technologies provided mothers with convenient means to access health information from a range of sources, yet mothers were apprehensive about the credibility and trustworthiness of the information they retrieved. Further research should seek to understand how men and fathers use digital technologies during their transition to parenting. Additionally, further research should critically examine how constant access to information affects mothers’ perceived need to self-monitor and further understand the unintended health consequences of constant surveillance on new parents. </sec>

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,432
Score d'incertitude au seuil0,438

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,052
Tête enseignante GPT0,297
Écart entre enseignants0,245 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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