Background: Over the past decade, smartphone use has become widespread amongst today’s children and young people (CYP) which parallels increases in poor mental health in this group. Simultaneously, media concern abounds about the existence of ‘smartphone addiction’ or problematic smartphone use. There has been much recent research concerning the prevalence of problematic smartphone use is in children and young people who use smartphones, and how this syndrome relates to mental health outcomes, but this has not been synthesized and critically evaluated. Aims: To conduct a systematic review and meta-analysis to examine the prevalence of PSU and quantify the association with mental health harms. Methods: A search strategy using Medical Subject Headings was developed and adapted for eight databases between January 1, 1st 2011 to October 15th 2017. No language restriction was applied. Of 924 studies identified, 41 were included in this review, three of which were cohort studies and 38 were cross sectional studies. The mental health outcomes were self-reported: depression; anxiety; stress; poor sleep quality; and decreased educational attainment, which were synthesized according to an a priori protocol. Results: The studies included 41,871 CYP, and 55% were female. The median prevalence of PSU amongst CYP was 23.3% (14.0–31.2%). PSU was associated with an increased odds of depression (OR = 3.17;95%CI 2.30–4.37;I² = 78%); increased anxiety (OR = 3.05 95%CI 2.64–3.53;I² = 0%); higher perceived stress (OR = 1.86;95%CI 1.24–2.77;I² = 65%); and poorer sleep quality (OR = 2.60; 95%CI; 1.39–4.85, I² = 78%). Conclusions: PSU was reported in approximately one in every four CYP and accompanied by an increased odds of poorer mental health. PSU is an evolving public health concern that requires greater study to determine the boundary between helpful and harmful technology use. Policy guidance is needed to outline harm reduction strategies.

Sleep is crucial to the development of physically and psychologically healthy children. Sleep disturbance in childhood is known to lead to adverse physical and mental health consequences. Short- and long-term detrimental health outcomes include poor diet, sedentary behavior, obesity, reduced immunity, stunted growth, mental health issues (eg, depression and suicidal tendencies), and substance abuse.^1-3

OBJECTIVE: To investigate the effect of mobile phone applications (apps) on glycemic control (HbA1c) in the self-management of diabetes. RESEARCH DESIGN AND METHODS: Relevant studies that were published between 1 January 1996 and 1 June 2015 were searched from five databases: Medline, CINAHL, Cochrane Library, Web of Science, and Embase. Randomized controlled trials that evaluated diabetes apps were included. We conducted a systematic review with meta-analysis and GRADE (Grading of Recommendations Assessment, Development and Evaluation) of the evidence. RESULTS: Participants from 14 studies (n = 1,360) were included and quality assessed. Although there may have been clinical diversity, all type 2 diabetes studies reported a reduction in HbA1c. The mean reduction in participants using an app compared with control was 0.49% (95% Cl 0.30, 0.68; I2 = 10%), with a moderate GRADE of evidence. Subgroup analyses indicated that younger patients were more likely to benefit from the use of diabetes apps, and the effect size was enhanced with health care professional feedback. There was inadequate data to describe the effectiveness of apps for type 1 diabetes. CONCLUSIONS: Apps may be an effective component to help control HbA1c and could be considered as an adjuvant intervention to the standard self-management for patients with type 2 diabetes. Given the reported clinical effect, access, and nominal cost of this technology, it is likely to be effective at the population level. The functionality and use of this technology need to be standardized, but policy and guidance are anticipated to improve diabetes self-management care.

Hip fractures in the older person lead to an increased risk of mortality, poorer quality of life and increased morbidity. Benzodiazepine (BNZ) use is associated with increased hip fracture rate, consequently Z-drugs are fast becoming the physician’s hypnotic prescription of choice yet data on their use is limited. We compared the risk of hip fracture associated with Z-drugs and BNZ medications, respectively, and examined if this risk varied with longer-term use. We carried out a systematic review of the literature and meta-analysis. MEDLINE and SCOPUS were searched to identify studies involving BNZ or Z-drugs and the risk of hip fracture up to May 2015. Each included study was quality-assessed. A pooled relative risk of hip fracture was calculated using the generic inverse variance method, with a random effects model, with the length of hypnotic usage as a subgroup. Both BNZ, and Z-drug use respectively, were significantly associated with an increased risk of hip fracture (RR = 1.52, 95% CI 1.37–1.68; and RR = 1.90, 95% CI 1.68–2.13). Short-term use of BNZ and Z-drugs respectively, was also associated with the greatest risk of hip fracture (RR = 2.40, 95% CI 1.88–3.05 and RR = 2.39, 95% CI 1.74–3.29). There is strong evidence that both BNZ and Z-drugs are associated with an increased risk of hip fracture in the older person, and there is little difference between their respective risks. Patients newly prescribed these medicines are at the greatest risk of hip fracture. Clinicians and policy makers need to consider the increased risk of fallings and hip fracture particularly amongst new users of these medications.

Background:In a large UK study we investigated the relationship between smartphone addiction and sleep quality in a young adult population.Methods:We undertook a large UK cross-sectional observational study of 1,043 participants aged 18 to 30 between January 21st and February 30th 2019. Participants completed the Smartphone Addiction Scale Short Version, an adapted Pittsburgh Sleep Quality Score Index and reported smartphone use reduction strategies using both in-person (n= 968) and online (n= 75) questionnaires. A crude and adjusted logistic regression was fitted to assess risk factors for smartphone addiction, and the association between smartphone addiction and poor sleep.Results:One thousand seventy one questionnaires were returned, of which 1,043 participants were included, with median age 21.1 [interquartile range (IQR) 19–22]. Seven hundred and sixty three (73.2%) were female, and 406 reported smartphone addiction (38.9%). A large proportion of participants disclosed poor sleep (61.6%), and in those with smartphone addiction, 68.7% had poor sleep quality, compared to 57.1% of those without. Smartphone addiction was associated with poor sleep (aOR = 1.41, 95%CI: 1.06–1.87,p= 0.018).Conclusions:Using a validated instrument, 39% young adults reported smartphone addiction. Smartphone addiction was associated with poor sleep, independent of duration of usage, indicating that length of time should not be used as a proxy for harmful usage.