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The relationship between smartphone use and smartphone addiction: An examination of logged and self-reported behavior in a pre-registered, two-wave sample

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The relationship between smartphone use and smartphone addiction: An examination of logged and self-reported behavior in a pre-registered, two-wave sample. / Lucy Hitcham; Dr Richard James.
In: Computers in Human Behavior, Vol. 146, 107822, 30.09.2023.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Lucy Hitcham, Dr Richard James. The relationship between smartphone use and smartphone addiction: An examination of logged and self-reported behavior in a pre-registered, two-wave sample. Computers in Human Behavior. 2023 Sept 30;146:107822. Epub 2023 Jun 3. doi: 10.1016/j.chb.2023.107822

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@article{33e11f3d61f84bf0ae385eab6c89c4a7,
title = "The relationship between smartphone use and smartphone addiction: An examination of logged and self-reported behavior in a pre-registered, two-wave sample",
abstract = "There has been a growing literature that has utilized logged behavior from smartphones to study the impacts of technology use on individuals. One of these proposed impacts has been that people become addicted to their smartphones. Measurements of smartphone addiction do not appear to strongly correlate with actual behavior logged from smartphones. Instead, smartphone addiction may be better explained by distress rather than disordered behavior, but this has not been adequately tested. This study examined the relative contributions of self-reported and actual smartphone behavior alongside key mental health and individual differences in a pre-registered, two-wave study with a two-week re-test. 511 smartphone users (391 at Time 2) completed measures of smartphone usage, attitudes towards smartphone usage, smartphone addiction, other behavioral addictions, mental health, and individual differences. The results suggest smartphone addiction is principally driven by perceived rather than actual usage, especially where these are discordant. Self-reported smartphone usage, other behavioral addictions, and the impulsivity facet of negative urgency are more predictive of smartphone addiction than logged behavior. These results suggest that volume of smartphone usage is insufficient in and of itself to explain problematic smartphone behavior and questions the criterion validity of smartphone addiction measurements.",
keywords = "Smartphone addiction, Screen time, Logged behavior, Smartphone, Impulsivity, Depression",
author = "{Lucy Hitcham} and Hannah Jackson and {Dr Richard James}",
year = "2023",
month = sep,
day = "30",
doi = "10.1016/j.chb.2023.107822",
language = "English",
volume = "146",
journal = "Computers in Human Behavior",
issn = "0747-5632",
publisher = "Elsevier Limited",

}

RIS

TY - JOUR

T1 - The relationship between smartphone use and smartphone addiction

T2 - An examination of logged and self-reported behavior in a pre-registered, two-wave sample

AU - Lucy Hitcham

AU - Jackson, Hannah

AU - Dr Richard James

PY - 2023/9/30

Y1 - 2023/9/30

N2 - There has been a growing literature that has utilized logged behavior from smartphones to study the impacts of technology use on individuals. One of these proposed impacts has been that people become addicted to their smartphones. Measurements of smartphone addiction do not appear to strongly correlate with actual behavior logged from smartphones. Instead, smartphone addiction may be better explained by distress rather than disordered behavior, but this has not been adequately tested. This study examined the relative contributions of self-reported and actual smartphone behavior alongside key mental health and individual differences in a pre-registered, two-wave study with a two-week re-test. 511 smartphone users (391 at Time 2) completed measures of smartphone usage, attitudes towards smartphone usage, smartphone addiction, other behavioral addictions, mental health, and individual differences. The results suggest smartphone addiction is principally driven by perceived rather than actual usage, especially where these are discordant. Self-reported smartphone usage, other behavioral addictions, and the impulsivity facet of negative urgency are more predictive of smartphone addiction than logged behavior. These results suggest that volume of smartphone usage is insufficient in and of itself to explain problematic smartphone behavior and questions the criterion validity of smartphone addiction measurements.

AB - There has been a growing literature that has utilized logged behavior from smartphones to study the impacts of technology use on individuals. One of these proposed impacts has been that people become addicted to their smartphones. Measurements of smartphone addiction do not appear to strongly correlate with actual behavior logged from smartphones. Instead, smartphone addiction may be better explained by distress rather than disordered behavior, but this has not been adequately tested. This study examined the relative contributions of self-reported and actual smartphone behavior alongside key mental health and individual differences in a pre-registered, two-wave study with a two-week re-test. 511 smartphone users (391 at Time 2) completed measures of smartphone usage, attitudes towards smartphone usage, smartphone addiction, other behavioral addictions, mental health, and individual differences. The results suggest smartphone addiction is principally driven by perceived rather than actual usage, especially where these are discordant. Self-reported smartphone usage, other behavioral addictions, and the impulsivity facet of negative urgency are more predictive of smartphone addiction than logged behavior. These results suggest that volume of smartphone usage is insufficient in and of itself to explain problematic smartphone behavior and questions the criterion validity of smartphone addiction measurements.

KW - Smartphone addiction

KW - Screen time

KW - Logged behavior

KW - Smartphone

KW - Impulsivity

KW - Depression

U2 - 10.1016/j.chb.2023.107822

DO - 10.1016/j.chb.2023.107822

M3 - Journal article

VL - 146

JO - Computers in Human Behavior

JF - Computers in Human Behavior

SN - 0747-5632

M1 - 107822

ER -