Objective: To identify and rate reproductive endocrinology and infertility (REI) mobile applications (apps) targeted toward REI providers.
Design: A list of REI apps was found in both the Apple iTunes and Google Play stores using the following seven MeSH terms: reproductive endocrinology, REI, infertility, fertility, In Vitro Fertilization, IVF, and embryology. Patient-centered apps were excluded. The remaining apps were then evaluated for accuracy using reliable references.
Setting: Mobile technology.
Patients/interventions: None.
Main Outcome Measures: Accurate apps were evaluated for comprehensiveness (the extent of the ability to aid in clinical decision-making) and rated with objective and subjective components using the APPLICATIONS scoring system.
Results: Using the seven REI-related MeSH terms, 985 apps and 1,194 apps were identified in the Apple iTunes and Google Play stores, respectively. Of these unique apps, only 20 remained after excluding patient-centered apps. Upon further review for applicability to REI specifically and content accuracy, only seven apps remained. These seven apps were then rated using the APPLICATIONS scoring system.
Conclusion: Only 0.32% of 2,179 apps reviewed for this study were useful to REI providers. There is potential for further mobile resource development in the area of REI, given the limited number and varying comprehensiveness and quality of available apps.
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http://dx.doi.org/10.1089/tmj.2016.0079 | DOI Listing |
BMC Med Res Methodol
January 2025
Biostatistics Research Group, Department of Population Health Sciences, University of Leicester, Leicester, UK.
Background: Since 2015, the Complex Reviews Synthesis Unit (CRSU) has developed a suite of web-based applications (apps) that conduct complex evidence synthesis meta-analyses through point-and-click interfaces. This has been achieved in the R programming language by combining existing R packages that conduct meta-analysis with the shiny web-application package. The CRSU apps have evolved from two short-term student projects into a suite of eight apps that are used for more than 3,000 h per month.
View Article and Find Full Text PDFSci Rep
January 2025
Computer Science Department, Faculty of Computers and Information, South Valley University, Qena, 83523, Egypt.
Adversarial attacks were commonly considered in computer vision (CV), but their effect on network security apps rests in the field of open investigation. As IoT, AI, and 5G endure to unite and understand the potential of Industry 4.0, security events and incidents on IoT systems have been enlarged.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Early Intervention in Psychosis Advisory Unit for South-East Norway, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
Background: Shared decision-making between clinicians and service users is crucial in mental health care. One significant barrier to achieving this goal is the lack of user-centered services. Integrating digital tools into mental health services holds promise for addressing some of these challenges.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China.
Background: Tinnitus is a major health issue, but currently no tinnitus elimination treatments exist for chronic subjective tinnitus. Acoustic therapy, especially personalized acoustic therapy, plays an increasingly important role in tinnitus treatment. With the application of smartphones, personalized acoustic stimulation combined with smartphone apps will be more conducive to the individualized treatment and management of patients with tinnitus.
View Article and Find Full Text PDFAm J Audiol
January 2025
Department of Communication Sciences and Disorders, University of Wisconsin-Madison.
Purpose: Prior work estimating sound exposure dose from earphone use has typically measured earphone use time with retrospective questionnaires or device-based tracking, both of which have limitations. This research note presents an exploratory analysis of sound exposure dose from earphone use among college-aged adults using real-ear measures to estimate exposure level and ecological momentary assessment (EMA) to estimate use time.
Method: Earphone levels were measured at the ear drum of 53 college students using their own devices, earphones, and preferred music and speech stimuli at their normal listening volume.
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