Literature DB >> 30288823

The Baby Moves smartphone app for General Movements Assessment: Engagement amongst extremely preterm and term-born infants in a state-wide geographical study.

Amanda Kl Kwong1,2,3, Abbey L Eeles1,3, Joy E Olsen1,3, Jeanie Ly Cheong1,3,4, Lex W Doyle1,3,4,5, Alicia J Spittle1,2,3.   

Abstract

AIM: The Baby Moves smartphone application is designed for parents to video their infants' spontaneous movement for remote General Movements Assessment (GMA). We aimed to assess the engagement with Baby Moves amongst high- and low-risk infants' families and the socio-demographic variables related to engagement.
METHODS: Families of extremely preterm (EP; <28 weeks' gestational age) or extremely low-birthweight (ELBW; <1000 g) infants and term-born controls from a state-wide geographical cohort study were asked to download Baby Moves. Baby Moves provided reminders and instructions to capture videos of their infants' general movements. Parents were surveyed about Baby Moves' usability.
RESULTS: The parents of 451 infants (226 EP/ELBW; 225 control) were recruited; 416 (204 EP/ELBW; 212 control) downloaded Baby Moves, and 346 (158 EP/ELBW; 188 control) returned at least one scorable video for remote GMA. Fewer EP/ELBW families submitted a scorable video than controls (70 vs. 83%, respectively; odds ratio (OR) 0.48, 95% confidence interval (CI) 0.3-0.79, P = 0.003), but the difference diminished when adjusted for socio-demographic variables (OR 1.09, 95% CI 0.59-2.0, P = 0.79). Families who received government financial support (OR 0.28, 95% CI 0.1-0.78, P = 0.015), who spoke limited English at home (OR 0.39, 95% CI 0.22-0.69, P = 0.001) or with lower maternal education (OR 0.38, 95% CI 0.21-0.68, P = 0.001) were less likely to return a scorable video. Surveyed parents responded mostly positively to Baby Moves' usability.
CONCLUSIONS: Most parents in this study successfully used Baby Moves to capture infant movements for remote GMA. Families of lower socio-demographic status used Baby Moves less.
© 2018 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Entities:  

Keywords:  General Movements Assessment; cohort study; preterm infants; smartphone application; socio-demographic status

Year:  2018        PMID: 30288823     DOI: 10.1111/jpc.14240

Source DB:  PubMed          Journal:  J Paediatr Child Health        ISSN: 1034-4810            Impact factor:   1.954


  9 in total

1.  The AIMS home-video method: parental experiences and appraisal for use in neonatal follow-up clinics.

Authors:  I Suir; J Oosterhaven; M Boonzaaijer; J Nuysink; M Jongmans
Journal:  BMC Pediatr       Date:  2022-06-11       Impact factor: 2.567

2.  Early prediction of neurodevelopmental outcomes at 12 years in children born extremely preterm.

Authors:  Maria Örtqvist; Christa Einspieler; Ulrika Ådén
Journal:  Pediatr Res       Date:  2021-05-10       Impact factor: 3.953

3.  In-Motion-App for remote General Movement Assessment: a multi-site observational study.

Authors:  Lars Adde; Annemette Brown; Christine van den Broeck; Kris DeCoen; Beate Horsberg Eriksen; Toril Fjørtoft; Daniel Groos; Espen Alexander F Ihlen; Siril Osland; Aurelie Pascal; Henriette Paulsen; Ole Morten Skog; Wiebke Sivertsen; Ragnhild Støen
Journal:  BMJ Open       Date:  2021-03-04       Impact factor: 2.692

4.  Early Moves: a protocol for a population-based prospective cohort study to establish general movements as an early biomarker of cognitive impairment in infants.

Authors:  Catherine Elliott; Caroline Alexander; Alison Salt; Alicia J Spittle; Roslyn N Boyd; Nadia Badawi; Catherine Morgan; Desiree Silva; Elizabeth Geelhoed; Robert S Ware; Alishum Ali; Anne McKenzie; David Bloom; Mary Sharp; Roslyn Ward; Samudragupta Bora; Susan Prescott; Susan Woolfenden; Vuong Le; Sue-Anne Davidson; Ashleigh Thornton; Amy Finlay-Jones; Lynn Jensen; Natasha Amery; Jane Valentine
Journal:  BMJ Open       Date:  2021-04-09       Impact factor: 2.692

5.  Mobile applications for prematurity: a systematic review protocol.

Authors:  Malihe Sadeghi; Mehdi Kahouei; Shahrbanoo Pahlevanynejad; Ali Valinejadi; Marjan Momeni; Farzaneh Kermani; Hamed Seddighi
Journal:  BMJ Paediatr Open       Date:  2021-09-21

6.  Automated Movement Analysis to Predict Cerebral Palsy in Very Preterm Infants: An Ambispective Cohort Study.

Authors:  Kamini Raghuram; Silvia Orlandi; Paige Church; Maureen Luther; Alex Kiss; Vibhuti Shah
Journal:  Children (Basel)       Date:  2022-06-07

7.  A home-video method to assess infant gross motor development: parent perspectives on feasibility.

Authors:  M Boonzaaijer; F van Wesel; J Nuysink; M J M Volman; M J Jongmans
Journal:  BMC Pediatr       Date:  2019-10-29       Impact factor: 2.125

8.  Early Diagnosis and Classification of Cerebral Palsy: An Historical Perspective and Barriers to an Early Diagnosis.

Authors:  Anna te Velde; Catherine Morgan; Iona Novak; Esther Tantsis; Nadia Badawi
Journal:  J Clin Med       Date:  2019-10-03       Impact factor: 4.241

9.  Standardized Neurodevelopmental Surveillance of High-risk Infants Using Telehealth: Implementation Study during COVID-19.

Authors:  Nathalie L Maitre; Kristen L Benninger; Mary Lauren Neel; Jennifer A Haase; Lindsay Pietruszewski; Katelyn Levengood; Kathleen Adderley; Nancy Batterson; Kaleigh Hague; Megan Lightfoot; Sarah Weiss; Dennis J Lewandowski; Heather Larson
Journal:  Pediatr Qual Saf       Date:  2021-07-28
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.