Evidence map›Paper›PMID 30363738›Full record

ArticlemHealth2018

Differences in mobile phone affinity between demographic groups: implications for mobile phone delivered interventions and programs.

Marie A Sillice, Shira Dunsiger, Ernestine Jennings, Ryan Lantini, Beth C Bock

Open access · hybridAbstract read
In one paragraph

Article in mHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.6field-weighted citation impact, top 6% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
  2. Editors' Best of 2024.JAACAP open · 2025
    Article
  3. Article
  4. "Energy is a Finite Resource": Designing Technology to Support Individuals across Fluctuating Symptoms of Depression.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2020
    Article
  5. 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

5 authors at 2 institutions in 1 country.

Marie A SilliceDepartment of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA.
Shira DunsigerDepartment of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA.
Ernestine JenningsDepartment of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA.
Ryan LantiniCenters for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, USA.
Beth C BockDepartment of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA.
Miriam Hospital · USBrown University · US

Funding

Initiating and maintaining physical activity in depressed individualsR01HL127695 · NHLBI · BUTLER HOSPITAL (PROVIDENCE, RI) · PI ABRANTES, ANA M, UEBELACKER, LISA A · 2016 to 2019
$2.6M
Text Messaging as a Novel Alcohol Intervention for Community College StudentsR21AA021014 · NIAAA · MIRIAM HOSPITAL · PI BOCK, BETH C · 2012 to 2013
$377k
NHLBI NIH HHS R01 HL127695NIAAA NIH HHS R21 AA021014
6 · The paper itself

Abstract

backgroundThe impact of any intervention or program delivered through mobile phones (mHealth) may be influenced by the individual recipient's relationship with his or her mobile phone. However, few studies have assessed the attitudes and preferences of different demographic groups with respect to mobile phone use. This study assessed whether individuals' demographic characteristics [primary demographics (PD): race, ethnicity, gender and age] are influential factors in attitudes and behaviors associated with mobile use pattern, using the Mobile Phone Affinity Scale (MPAS). The MPAS examines six underlying constructs associated with mobile phone use: Connectedness, Productivity, Empowerment, Anxious Attachment, Addiction, and Continuous Use.

methodsU.S. adults (n=1,055, mean age 32.5 years, 10% Hispanic, 86.3% white) completed the MPAS and provided information about PD (e.g., race, ethnicity, age) and social demographic (SocD) characteristics (e.g., having children, employment). Chi-square analyses and multivariate analyses were used to assess the relationships among the PD and SocD variables, and MPAS constructs.

resultsSignificant differences were found between PD and SocD variables (all P<0.01). Specifically, whites were more likely than non-whites to be married and to be living with children, while non-Hispanics tended to report higher household income and education than Hispanics. Women were more likely to report living with children and less likely to have full-time employment than men (all P<0.01). There was a significant effect of PD characteristics on MPAS constructs in that whites and women tended to score higher on some MPAS constructs than non-whites and men (all P<0.01). Similarly, some SocD characteristics including employment status and living with children were differentially associated with some MPAS constructs (all P<0.01).

conclusionsResults indicate that there are differences in attitudes and use preferences to mobile phone use based on some of the primary and SocD demographic characteristics. These findings provide important insights into mHealth intervention components that will increase appeal to different subgroups.

Indexed as

demographic differencesMobile phone affinitymobile phone use patterns

Identifiers

PMID30363738
PMCPMC6182014
OpenAlexW2892248999

What OpenQuestion holds

Textmetadata
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.