scholarly journals The impact of mobile phone distraction on the braking behaviour of young drivers: A hazard-based duration model

2015 ◽  
Vol 50 ◽  
pp. 13-27 ◽  
Author(s):  
Md. Mazharul Haque ◽  
Simon Washington
Keyword(s):  
Mobile Phone ◽  
Duration Model ◽  
Young Drivers ◽  
The Impact

The Impact of Mobile Phone Technology in Bridging the Gaps in The Health Care Service Delivery in Kenya: A Case of Nairobi County. (Preprint)

2019 ◽  
Author(s):  
Alice Ndwiga
Keyword(s):  
Service Delivery ◽  
Mobile Phone ◽  
Care Service ◽  
Health Care Service ◽  
Informal Settlements ◽  
Healthcare Services ◽  
P Value ◽  
Delivery Of Healthcare ◽  
Mobile Phone Technology ◽  
The Impact

BACKGROUND INTRODUCTION: The Kenyan constitution seeks to guarantee every citizen the right to quality healthcare services. Quite often this delivery is hampered by geographical location, socio-economic statuses among other factors. The country has a high mobile phone penetration rate. Digitalization of the healthcare sector is a vital aspect that contributes to effective delivery of care services. This study set out to assess the impact of mobile technology in closing the gaps within the health care service delivery. The objective of the study was to investigate the impact of mobile phone technology in bridging the gap in healthcare service delivery in Kenya with a focus on Nairobi, Kibera informal settlements. Hypothesis testing using P-value of 0.05 also showed that use of mobile phone technology positively impacted the delivery of healthcare services. OBJECTIVE The objective of the study was to investigate the impact of mobile phone technology in bridging the gap in healthcare service delivery in Kenya with a focus on Nairobi, Kibera informal settlements. Hypothesis testing using P-value of 0.05 also showed that use of mobile phone technology positively impacted the delivery of healthcare services. METHODS The target population were patients visiting Médecins Sans Frontières (MSF) clinic in Kibera informal settlements. A cross-sectional study design was employed. Purposive and simple random sampling method was used to select the study sample of 210 participants and 3 healthcare providers. Data were collected using survey questionnaire that was provider-administered and Data were analyzed using SPSS version. RESULTS The characteristics of the respondents were general (mean age, education level, social economic status) to only patients who visited the clinics for HIV tests and other related services such as going for ARVs. The main findings showed that 66.12% of the respondents (14.29% strongly agreed + 55.24% agreed) that the use of mobile phone technology improved their access to healthcare services. Using chi square, there was a statistical difference due to the positive impact of mobile technology on healthcare delivery (p=0.05). CONCLUSIONS The study findings showed that 66.12% of the respondents agreed that the use of mobile phone technology and SMS improved their access to healthcare services. The results hypothesis also proved that use of mobile phone technology positively impacts the delivery of healthcare services.

scholarly journals National movement patterns during the COVID-19 pandemic in New Zealand: the unexplored role of neighbourhood deprivation

2021 ◽  
pp. jech-2020-216108 ◽  
Author(s):  
Malcolm Campbell ◽  
Lukas Marek ◽  
Jesse Wiki ◽  
Matthew Hobbs ◽  
Clive E Sabel ◽  
...  
Keyword(s):  
New Zealand ◽  
Mobile Phone ◽  
Well Being ◽  
Policy Debate ◽  
Population Mobility ◽  
Neighbourhood Deprivation ◽  
Movement Data ◽  
Spatial Inequalities ◽  
The Impact

BackgroundThe COVID-19 pandemic has asked unprecedented questions of governments around the world. Policy responses have disrupted usual patterns of movement in society, locally and globally, with resultant impacts on national economies and human well-being. These interventions have primarily centred on enforcing lockdowns and introducing social distancing recommendations, leading to questions of trust and competency around the role of institutions and the administrative apparatus of state. This study demonstrates the unequal societal impacts in population movement during a national ‘lockdown’.MethodsWe use nationwide mobile phone movement data to quantify the effect of an enforced lockdown on population mobility by neighbourhood deprivation using an ecological study design. We then derive a mobility index using anonymised aggregated population counts for each neighbourhood (2253 Census Statistical Areas; mean population n=2086) of national hourly mobile phone location data (7.45 million records, 1 March 2020–20 July 2020) for New Zealand (NZ).ResultsCurtailing movement has highlighted and exacerbated underlying social and spatial inequalities. Our analysis reveals the unequal movements during ‘lockdown’ by neighbourhood socioeconomic status in NZ.ConclusionIn understanding inequalities in neighbourhood movements, we are contributing critical new evidence to the policy debate about the impact(s) and efficacy of national, regional or local lockdowns which have sparked such controversy.

scholarly journals Quantifying the Impact of Accessibility on Preventive Healthcare in Sub-Saharan Africa Using Mobile Phone Data

Epidemiology ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 223-228 ◽  
Author(s):  
Amy Wesolowski ◽  
Wendy Prudhomme O’Meara ◽  
Andrew J. Tatem ◽  
Samson Ndege ◽  
Nathan Eagle ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Sub Saharan Africa ◽  
Mobile Phone Data ◽  
Preventive Healthcare ◽  
Sub Saharan ◽  
The Impact

The effect of a mobile health app on adherence to physical health treatment. (Preprint)

2021 ◽  
Author(s):  
Jay Greenstein ◽  
Robert Topp ◽  
Jena Etnoyer-Slaski ◽  
Michael Staelgraeve ◽  
John McNulty ◽  
...  
Keyword(s):  
Physical Health ◽  
Mobile Phone ◽  
Usual Care ◽  
Usual Care Group ◽  
Clinic Visit ◽  
Care Group ◽  
Health Treatment ◽  
Rehabilitation Clinic ◽  
The Impact ◽  
Clinic Visits

BACKGROUND Adhering to prescribed medical interventions predicts the efficacy of the treatment. In the physical health clinics, not adhering to prescribed therapy can take the form of not attending a scheduled clinic visit (no-show appointment) or prematurely terminating treatment against the advice of the provider (self-discharge). A variety of interventions, including mobile phone apps have been introduced with patients to increase their adherence with attending scheduled clinic visits. Limited research has examined the impact of a mobile phone app among patients attending a chiropractic and rehabilitation clinic visits. OBJECTIVE The purpose of this study was to compare adherence with prescribed physical health treatment among patients attending a chiropractic and rehabilitation clinic who did and did not choose to adopt a phone-based app to complement their treatment. METHODS The medical records of new patients who presented for care during 2019 and 2020 at five community-based chiropractic and rehabilitation clinics were reviewed for the number of kept and no-show appointments and if the patient was provider discharged or self-discharged. During this 24-month study 36.3% of the 4,126 patients seen in the targeted clinics had downloaded the Kanvas App to their mobile phone while the remaining patients chose not to download the app (Usual Care Group). The gamification component of the Kanvas app provided the patient with a point every time they attended their visits which could be redeemed for an incentive. RESULTS During both 2019 and 2020 respectively the Kanvas App Group (50%-38%) were provider discharged at a greater rate than the Usual-Care group (47-31%). The Kanvas App Group kept a similar number of appointments compared to the Usual-Care Group in 2019 (10.20 vs. 8.68) but kept significantly more appointments than the Usual-Care Group in 2020 (11.63 vs. 7.67). During 2019 both groups exhibited a similar number of no-show appointments (1.89 vs 1.96) but in 2020 the Kanvas App Group demonstrated more no-show appointments (2.89 vs 2.14) than the Usual Care. When collapsed across years and self discharged the Kanvas App group had a greater number of kept appointments (7.79) compared to the Usual Care group (4.58). When provider discharged both groups exhibited a similar number of kept appointments (15.25 vs 13.82). The Kanvas App group (1.38) and the Usual Care group (1.34) were similar in the number of no-show appointments when provider discharged and when self-discharged the Kanvas App Group had more no-show appointments (3.37) compared to the Usual Care Group (2.44). CONCLUSIONS When patients were provider discharged, they exhibited a similar number of kept appointments and no-show appointment. When subjects were self-discharged and received the Kanvas App they exhibited 3.2 more kept appointments and .94 more no-show appointments than self-discharged Usual Care group.

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