A cross-sectional study of the association between mobile phone use and symptoms of ill health

Abstract

ObjectivesThis study analyzed the associations between mobile phone call frequency and duration with non-specific symptoms.MethodsThis study was conducted with a population group including 532 non-patient adults established by the Korean Genome and Epidemiology Study. The pattern of phone call using a mobile phone was investigated through face-to-face interview. Structured methods applied to quantitatively assess health effects are Headache Impact Test-6 (HIT-6), Psychosocial Well-being Index-Short Form, Beck Depression Inventory, Korean-Instrumental Activities of Daily Living, Perceived Stress Scale (PSS), Pittsburgh Sleep Quality Index, and 12-item Short Form Health Survey where a higher score represents a higher greater health effect.ResultsThe average daily phone call frequency showed a significant correlation with the PSS score in female subjects. Increases in the average duration of one phone call were significantly correlated with increases in the severity of headaches in both sexes. The mean (standard deviation) HIT-6 score in the subgroup of subjects whose average duration of one phone call was five minutes or longer was 45.98 (8.15), as compared with 42.48 (7.20) in those whose average duration of one phone call was <5 minutes. The severity of headaches was divided into three levels according to the HIT-6 score (little or no impact/moderate impact/substantial or severe impact), and a logistic regression analysis was performed to investigate the association between an increased phone call duration and the headache severity. When the average duration of one phone call was five minutes or longer, the odds ratio (ORs) and the 95% confidence intervals (CIs) for the moderate impact group were 2.22 and 1.18 to 4.19, respectively. The OR and 95% CI for the substantial or severe impact group were 4.44 and 2.11 to 8.90, respectively.ConclusionsMobile phone call duration was not significantly associated with stress, sleep, cognitive function, or depression, but was associated with the severity of headaches.

Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review

“…We did not find any research article that explains how social patterns change with depression, but the review article by Baker et al [27] on online social networks suggests a complex relation involving factors that mediate or moderate the correlation and increase the variability in the findings. Furthermore, Cho et al [44] found a direct opposite correlation between genders (male negative, female positive) in the call duration and call frequency features. This suggests that social-based features should be treated as a highly personalized feature that should be assessed in a within-subject analysis.…”

“…In a cross-cultural study with people from Switzerland and Turkey, Hernández et al [29] found different correlation directions between the two groups in screen active frequency and number of running apps . Furthermore, several device-based features such as browser app usage and reading app usage have different correlation directions between genders (male positive, female negative) [33], and the two social features call duration and call frequency also exhibit different correlation directions between genders (male negative, female positive) [44]. …”

Correlations between objective behavioral features collected from mobile and wearable devices, and depressive mood symptoms in affective disorders: A systematic review (Preprint)

“…In a cross-cultural study with people from Switzerland and Turkey, Hernández et al [31] found different correlation directions between the two groups in screen active frequency and number of running apps. Furthermore, several device-based features such as browser app usage and reading app usage have different correlation directions between genders (male positive, female negative) [35], and the two social features call duration and call frequency also exhibit different correlation directions between genders (male negative, female positive) [45]. Transition time is currently only investigated by the research group of Saeb et al [7,51] where they did a study to replicate previous findings of the same features.…”

“…Faurholt-Jepsen et al [6] presented a new feature; missed calls which is statistically significantly correlated with the HDRS-17 (β = 0.05, p = .006). The result was presented in 2016, but not replicated in any of the later studies such as the comprehensive study on phone records with 532 subjects [45].…”

“…No research articles were found that tried to explain how social patterns changes with depression but the review article by Baker et al [26] on online social networks suggest a complex relation involving factors that mediate or moderate the correlation and increase the variability in the findings. Furthermore, Cho et al [45] found a direct opposite correlation between genders (male negative, female positive) in the call duration and call frequency features. This suggests that socialbased features should be treated as a highly personalized feature that should be assessed in a within-subject analysis.…”