The purpose of this study was to carry out a review of observational studies that consider links between mobile phone use and mental health from a psychological or behavioral perspective. Systematic literature searches in PubMed and PsycINFO for articles published until 2017 were done. Exclusion criteria included: papers that considered radiofrequency fields, attention, safety, relational consequences, sexual behavior, cyberbullying, and reviews, qualitative, and case or experimental studies. A total of 4738 papers were screened by title and abstract, 404 were retrieved in full text, and 290 were included. Only 5% had any longitudinal design. Self-reporting was the dominating method of measurement. One third of the studies included children or youth. A majority of adult populations consisted of university students and/or self-selected participants. The main research results included associations between frequent mobile phone use and mental health outcomes, such as depressive symptoms and sleep problems. Mobile phone use at bedtime was associated with, e.g., shorter sleep duration and lower sleep quality. "Problematic use" (dependency) was associated with several negative outcomes. In conclusion, associations between mobile phone use and adverse mental health outcomes are found in studies that take a psychological or behavioral perspective on the exposure. However, more studies of high quality are needed in order to draw valid conclusions about the mechanisms and causal directions of associations.

Mobile Phone Use and Mental Health. A Review of the Research That Takes a Psychological Perspective on Exposure

Sleepless due to social media? Investigating problematic sleep due to social media and social media sleep hygiene

Mobile phone use is often blamed for adolescent sleeping difficulties in the popular and scientific literature, with correlations observed between adolescents’ mobile phone use and their bedtime. W...

Altering Adolescents' Pre-Bedtime Phone Use to Achieve Better Sleep Health.

Objectives This study compared subjective (questionnaire) and objective (actigraphy) sleep assessments, and examined agreement between these methods, in vulnerable older adults participating in a Veterans Administration Adult Day Health Care (ADHC) program. Methods 59 ADHC participants (95% male, mean age = 78 years) completed sleep questionnaires and 72 continuous hours of wrist actigraphy. Linear regression was used to examine agreement between methods and explore discrepancies in subjective/objective measures. Results Disturbed sleep was common, yet there was no agreement between subjective and objective sleep assessment methods. Compared with objective measures, one-half of participants reported worse sleep efficiency (SE) on questionnaires while one-quarter over-estimated SE. Participants reporting worse pain had a greater discrepancy between subjective and objective SE. Conclusions Vulnerable older adults demonstrated unique patterns of reporting sleep quality when comparing subjective and objective methods. Additional research is needed to better understand how vulnerable older adults evaluate sleep problems. Clinical implications Objective and subjective sleep measures may represent unique and equally important constructs in this population. Clinicians should consider utilizing both objective and subjective sleep measures to identify individuals who may benefit from behavioral sleep treatments, and future research is needed to develop and validate appropriate sleep assessments for vulnerable older adults.

Measuring Sleep in Vulnerable Older Adults: A Comparison of Subjective and Objective Sleep Measures.

In this chapter, two methods of examining the relationships among a set of variables will be examined. The first, principal components analysis (PCA), is essentially a method of data reduction that aims to reduce the dimensionality of multivariate data and, thus, aid in its understanding. The second technique to be discussed is exploratory factor analysis, which has somewhat similar aims to principal components analysis, but in addition tries to uncover something more fundamental about the data.

Principal Components and Factor Analysis

Adolescent Sleep and the Impact of Technology Use Before Sleep on Daytime Function.

Screening and evaluation tools for sleep disorders in older adults.

Background:Sleep disturbance is a frequent comorbidity in children with autism spectrum disorder (ASD), affecting an estimated 40–80% of cases. Previous reports have shown relationships between sev...

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Variations in Genes Related to Sleep Patterns in Children With Autism Spectrum Disorder.

Characteristics of sleep in children with autism spectrum disorders from the Simons Simplex Collection

BACKGROUND AND PURPOSE An estimated 40%-80% of children with autism spectrum disorders (ASD) have sleep problems. The Simons Simplex Collection Sleep Interview (SSCSI) is a parent-report questionnaire assessing bedtime and nighttime sleep problems and daytime function. The present study evaluated the factorial model of the SSCSI that best characterizes children aged 4-18 years with ASD. METHODS Exploratory factor analysis was performed using principal component analysis and promax rotation, beginning with 16 items and ending with 10 items. RESULTS Exploratory factor analysis concluded with ten dichotomous items, plus ageand regular sleep duration, in three factors: nighttime problems, daytime problems, andsleep duration problems. The analysis was performed on the full sample, and onprepubertal (4-8-years), pubertal (9-13-years), and postpubertal (14-18-years) subgroups. CONCLUSION Further refinement, including confirmatory factor analysis, test-retest reliability, and convergent validity testing, is needed.

Ann E.E. Johansson

Papers

Adolescent Sleep and the Impact of Technology Use Before Sleep on Daytime Function.

Screening and evaluation tools for sleep disorders in older adults.

Variations in Genes Related to Sleep Patterns in Children With Autism Spectrum Disorder.

Characteristics of sleep in children with autism spectrum disorders from the Simons Simplex Collection

Psychometric Properties of the Simons Simplex Collection Sleep Interview.