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Record W2904188093 · doi:10.2196/10814

Usability and Acceptability of a Text Message-Based Developmental Screening Tool for Young Children: Pilot Study

2018· article· en· W2904188093 on OpenAlexvenueno aff
Pamela R. Johnson, Jessica Bushar, Margaret C. Dunkle, Sharon Leyden, Elizabeth Jordan

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2018
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsUsabilityDevelopmental psychologyPsychologyMedicinePediatricsComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

BACKGROUND: Only 30% of parents of children aged 9-35 months report that their child received a developmental screening in the previous year. Screening rates are even lower in low-income households, where the rates of developmental delays are typically higher than those in high-income households. Seeking to evaluate ways to increase developmental screening, Text4baby, a national perinatal texting program, created an interactive text message-based version of a validated developmental screening tool for parents. OBJECTIVE: This study aimed to assess whether a text message-based developmental screening tool is usable and acceptable by low-income mothers. METHODS: Low-income mothers of infants aged 8-10 months were recruited from the Women, Infants and Children Program clinics in Prince George's County, MD. Once enrolled, participants used text messages to receive and respond to six developmental screening questions from the Parents' Evaluation of Developmental Status: Developmental Milestones. After confirming their responses, participants received the results and feedback. Project staff conducted a follow-up phone survey and invited a subset of survey respondents to attend focus groups. A representative of the County's Infants and Toddlers Program met with or called participants whose results indicated that their infants "may be behind." RESULTS: Eighty-one low-income mothers enrolled in the study, 93% of whom reported that their infants received Medicaid (75/81). In addition, 49% of the mothers were Hispanic/Latina (40/81) and 42% were African American (34/81). A total of 80% participated in follow-up surveys (65/81), and 14 mothers attended focus groups. All participants initiated the screening and responded to all six screening questions. Of the total, 79% immediately confirmed their responses (64/81), and 21% made one or more changes (17/81). Based on the final responses, 63% of participants received a text that the baby was "doing well" in all six developmental domains (51/81); furthermore, 37% received texts listing domains where their baby was "doing well" and one or more domains where their baby "may be behind" (30/81). All participants received a text with resources for follow-up. In a follow-up survey reaching 65 participants, all respondents said that they would like to answer screening questions again when their baby was older. All but one participant would recommend the tool to a friend and rated the experience of answering questions and receiving feedback by text as "very good" or "good." CONCLUSIONS: A mobile text version of a validated developmental screening tool was both usable and acceptable by low-income mothers, including those whose infants "may be behind." Our results may inform further research on the use of the tool at older ages and options for a scalable, text-based developmental screening tool such as that in Text4baby.

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.

How this classification was reachedexpand

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)0.001
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 score0.013
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.031
GPT teacher head0.295
Teacher spread0.264 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2018
Admission routes1
Has abstractyes

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