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Record W2977662316 · doi:10.21037/mhealth.2019.08.10

Parenting apps review: in search of good quality apps

2019· article· en· W2977662316 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuemHealth · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of Calgary
FundersUniversity of Alberta
KeywordsApp storeMobile appsInternet privacyQuality (philosophy)World Wide WebPsychologySmartphone appComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Parenting can be challenging, and in this digital age, first-time parents actively access mobile applications or "apps" to adjust to their new roles. Apps are now technologically-savvy parents' go-to tool for accessing information, tracking their babies' development, editing and sharing photos, and much more. While apps have the potential to make parenting easier, the abundance of low-quality apps makes the process of finding a reliable one arduous for parents. Therefore, the objective of this app review paper was to provide a list of quality parenting apps that parents can use. METHODS: The Google Play Store was searched on June 1st, 2018 for available parenting apps using 18 search terms: mum, mom, mommy, mama, mother, father, dad, daddy, papa, newborn, baby, infant, kid, child, children, family, parent, and parenting. The eligible apps (n=16) were evaluated on engagement, functionality, aesthetics, and information domains using Mobile App Rating Scale (MARS). RESULTS: The authors identified 4,300 free apps on the initial search, of which n=16 apps were included in the review. All 16 apps were freely available to the public on Google Play Store. Most apps (n=13) were also available on the iOS platform. All eligible apps had a privacy policy, and half of the apps contained advertisements. Most apps (n=12) were updated within the last year and received 4.5 or above ratings from users. Babybrains app, developed by a neuroscientist, had the lowest number of downloads (one thousand) whereas, BabyCenter, a commercial app, had the highest number of downloads (ten million). A majority of apps (n=11) received MARS scores between 4.2 and 4.4/5, with four apps received highest MARS score of 4.5/5, and one app received the lowest MARS rating of 4/5. CONCLUSIONS: Apps play an increasingly important role in supporting new parents in their first year of parenthood due to convenience and ease of accessibility. Health care professionals are in an ideal position to support technologically savvy parents in locating good quality apps; therefore, they should support the evaluation of existing parenting apps to ensure that the parents are presented with the up to date and best options.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.071
GPT teacher head0.410
Teacher spread0.339 · 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