Evidence map›Paper›PMID 36781356›Full record

ArticleSleep health2023

Feasibility and acceptability of mobile methods to assess home and neighborhood environments related to adolescent sleep.

Stephanie L Mayne, Gabrielle DiFiore, Chloe Hannan, Uchenna Nwokeji, Vicky Tam, Corinne Filograna, Tyler Martin, Eugenia South, Jonathan A Mitchell, Karen Glanz and 1 more

Abstract read
In one paragraph

Article in Sleep health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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

11 authors.

Stephanie L MayneCenter for Pediatric Effectiveness, PolicyLab, and the Possibilities Project, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA; Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Leonard Davis Institute for Healthcare Economics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address: maynes@chop.edu.
Gabrielle DiFioreCenter for Pediatric Effectiveness, PolicyLab, and the Possibilities Project, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Chloe HannanCenter for Pediatric Effectiveness, PolicyLab, and the Possibilities Project, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Uchenna NwokejiCenter for Pediatric Effectiveness, PolicyLab, and the Possibilities Project, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Vicky TamData Science and Biostatistical Unit, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Corinne FilogranaCenter for Pediatric Effectiveness, PolicyLab, and the Possibilities Project, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Tyler MartinCenter for Healthcare Innovation, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Eugenia SouthLeonard Davis Institute for Healthcare Economics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Urban Health Lab, Department of Emergency Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Jonathan A MitchellDepartment of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Division of Gastroenterology, Hepatology, and Nutrition, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Karen GlanzDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA; School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Alexander G FiksCenter for Pediatric Effectiveness, PolicyLab, and the Possibilities Project, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA; Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Leonard Davis Institute for Healthcare Economics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Funding

Integrating GPS, GIS, and Ecological Momentary Assessment to Determine the Effect of Home and Neighborhood Context on Adolescent SleepK01HL155860 · NHLBI · CHILDREN'S HOSP OF PHILADELPHIA · PI MAYNE, STEPHANIE · 2021 to 2025
$810k
NHLBI NIH HHS K01 HL155860
6 · The paper itself

Abstract

objectiveA growing evidence base suggests home and neighborhood environmental exposures may influence adolescent sleep, but few studies have assessed these relationships using methods that account for time-varying, location-specific exposures, or multiple neighborhood contexts. This study aimed to assess the feasibility and acceptability of using smartphone global positioning system (GPS) tracking and ecological momentary assessment (EMA) to assess time-varying home and neighborhood environmental exposures hypothesized to be associated with adolescent sleep.

methodsAdolescents aged 15-17 years in Philadelphia completed 7 days of continuous smartphone GPS tracking, which was used to identify daily levels of exposure to geocoded neighborhood factors (eg, crime, green space). Four daily EMA surveys assessed home sleep environment (eg, noise, light), stress, health behaviors, and neighborhood perceptions. Feasibility and acceptability of GPS tracking and EMA were assessed, and distributions of daily environmental exposures were examined.

resultsAmong 25 teens (mean age 16, 56% male), there was a high level of GPS location data captured (median daily follow-up: 24 hours). Seventy-eight percent of EMA surveys were completed overall. Most participants (96%) reported no privacy concerns related to GPS tracking and minimal burden from EMA surveys. Exposures differed between participants' home neighborhoods and locations visited outside the home neighborhood (eg, higher crime away from home). Sleep environment disruptions were present on 29% of nights (most common: uncomfortable temperature) and were reported by 52% of adolescents.

conclusionsResults demonstrate the feasibility and acceptability of mobile methods for assessing time-varying home and neighborhood exposures relevant to adolescent sleep for up to 1 week.

Indexed as

Geographic Information SystemsSmartphoneAdolescentFeasibility StudiesFemaleHumansMaleNeighborhood CharacteristicsNoiseActivity spaceAdolescentsNeighborhood environmentSleep environment

Identifiers

PMID36781356
PMCPMC10293018

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.