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Record W4387009381 · doi:10.32920/24194727

Problematic Smartphone Use, Separation from the Phone, and Stress and Anxiety

2023· preprint· en· W4387009381 on OpenAlexaff
Zahra Vahedi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAnxietyPhonePsychologyStress (linguistics)Separation (statistics)Association (psychology)Clinical psychologyMobile phoneEveryday lifePsychiatryComputer sciencePsychotherapist

Abstract

fetched live from OpenAlex

Although smartphones have become a ubiquitous part of everyday life, their use – especially excessive or compulsive use – is thought to be associated with detrimental effects, such as increased stress and anxiety. Whilst some research has been devoted to exploring these effects, the purpose of this dissertation was to: a) quantify the strength of this relationship within the existing cross-sectional literature, and b) extend the experimental literature. Across a series of three studies – including a meta-analytic review and two experiments – the possible associations between the severity of problematic smartphone use, separation from the phone, and stress and anxiety were explored. Study One was a meta-analytic review of 39 independent samples (N = 21 736), which examined the cross-sectional relationships between smartphone use, stress, and/or anxiety. The summary effect size of r = .22, p < .001, CI [.17–.28], indicated a small‐to medium association between smartphone use and stress and anxiety. Studies that assessed the severity of problematic phone use (use that is compulsive, excessive, or addictive) had stronger effect sizes than those that assessed non-problematic use. To follow-up these results, two experiments, which were based on a study by Cheever, Rosen, Carrier, and Chavez (2014) were conducted, to examine one possible source of smartphone-induced stress and anxiety – temporary separation from the phone. Smartphone separation has been hypothesized to result in “Fear of Missing Out” (FoMO) and (phone) separation anxiety, especially among those high in problematic phone use. In Study Two, participants (N = 181) were randomly assigned to three conditions: (1) Smartphone Separation, (2) Wallet Separation, and (3) No Separation, and had their levels of self-reported anxiety and stress, as well as their heart rate and skin conductance response measured. The results did not support the notion that smartphone separation results in detrimental effects on participants’ physiological or self-reported stress and anxiety, or that individuals with the highest levels of problematic phone use experience more detrimental effects from smartphone separation than those with lower levels. Study Three explored the possibility that previous studies that found significant effects of smartphone separation on anxiety may have been confounded by participant boredom during the separation period. This study involved manipulating participants’ levels of boredom across three conditions – two of which involved smartphone restriction – and examined their effects on self-reported stress and anxiety. Participants (N = 224) were randomly assigned to sit for an hour either: (1) without their phones and in complete silence, (2) without their phones while watching a documentary, or (3) using their phones. Participants’ boredom levels better explained participants’ anxiety in Study Three than did smartphone restriction. Taken as a whole, the results of this dissertation suggest that, while there is a significant association between smartphone use – especially higher levels of problematic use – and stress and anxiety, temporary periods of separation from the phone are not likely in themselves to be part of the explanation of this association. The implications of these findings for both previous and future research are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.333
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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