Evidence map›Paper›PMID 27979792›Full record

ArticleJMIR mHealth and uHealth2016

The Mobile Phone Affinity Scale: Enhancement and Refinement.

Beth C Bock, Ryan Lantini, Herpreet Thind, Kristen Walaska, Rochelle K Rosen, Joseph L Fava, Nancy P Barnett, Lori Aj Scott-Sheldon

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Mapping of Crowdsourcing in Health: Systematic Review.Journal of medical Internet research · 2018
    Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Mobile Device Usage before and during the COVID-19 Pandemic among Rural and Urban Adults.International journal of environmental research and public health · 2022
    Article
  8. The Validity and Reliability of the Serbian Version of the Smartphone Addiction Scale-Short Version.International journal of environmental research and public health · 2022
    Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. 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

8 authors.

Beth C BockCenters for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, United States.ORCID http://orcid.org/0000-0002-4530-7618
Ryan LantiniCenters for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, United States.ORCID http://orcid.org/0000-0003-2436-5664
Herpreet ThindDepartment of Public Health, University of Massachusetts Lowell, Lowell, MA, United States.ORCID http://orcid.org/0000-0001-8878-4927
Kristen WalaskaCenters for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, United States.ORCID http://orcid.org/0000-0003-1315-5370
Rochelle K RosenCenters for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, United States.ORCID http://orcid.org/0000-0003-1598-667X
Joseph L FavaCenters for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, United States.ORCID http://orcid.org/0000-0001-7129-7903
Nancy P BarnettDepartment of Behavioral and Social Sciences, Center for Alcohol and Addiction Studies, School of Public Health, Brown University, Providence, RI, United States.ORCID http://orcid.org/0000-0001-9634-8287
Lori Aj Scott-SheldonCenters for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, United States.ORCID http://orcid.org/0000-0003-1524-3374

Funding

Examining a Text Message Intervention for Smoking CessationR21DA027142 · NIDA · MIRIAM HOSPITAL · PI BOCK, BETH C · 2009 to 2010
$361k
NIDA NIH HHS R21 DA027142
6 · The paper itself

Abstract

backgroundExisting instruments that assess individuals' relationships with mobile phones tend to focus on negative constructs such as addiction or dependence, and appear to assume that high mobile phone use reflects pathology. Mobile phones can be beneficial for health behavior change, disease management, work productivity, and social connections, so there is a need for an instrument that provides a more balanced assessment of the various aspects of individuals' relationships with mobile phones.

objectiveThe purpose of this research was to develop, revise, and validate the Mobile Phone Affinity Scale, a multi-scale instrument designed to assess key factors associated with mobile phone use.

methodsParticipants (N=1058, mean age 33) were recruited from Amazon Mechanical Turk between March and April of 2016 to complete a survey that assessed participants' mobile phone attitudes and use, anxious and depressive symptoms, and resilience.

resultsConfirmatory factor analysis supported a 6-factor model. The final measure consisted of 24 items, with 4 items on each of 6 factors: Connectedness, Productivity, Empowerment, Anxious Attachment, Addiction, and Continuous Use. The subscales demonstrated strong internal consistency (Cronbach alpha range=0.76-0.88, mean 0.83), and high item factor loadings (range=0.57-0.87, mean 0.75). Tests for validity further demonstrated support for the individual subscales.

conclusionsMobile phone affinity may have an important impact in the development and effectiveness of mobile health interventions, and continued research is needed to assess its predictive ability in health behavior change interventions delivered via mobile phones.

Indexed as

assessmentmeasuremobile phonepsychometrics

Identifiers

PMID27979792
PMCPMC5200845

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Registered trials

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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.