BACKGROUND
Disease screening identifies a disease in an individual/community at an early stage to prevent or treat the condition effectively. The current COVID-19 pandemic has restricted hospital visits for screening and other healthcare services resulting in the disruption of screening for diseases such as cancer, diabetes and CVD. Smartphone technologies, coupled with built-in sensors and wireless technologies, enable the smartphone to function as a device for disease screening and monitoring with negligible additional costs.
OBJECTIVE
This review aimed to evaluate the use of smartphone applications (apps) in the disease screening and acceptability of this technology in the medical and healthcare sectors.
METHODS
We followed a systematic review process to assess the scope for the app in the disease screening process. Four databases (Medline complete, Web of Science, Embase, and Proquest) were searched. Articles published in English and examining the use of the app in disease screening were included. Primary outcomes for the research articles and their statistically significant Results showed that app-based screening group had significant (OR:1.7, 95% CI: 1.2–2.4) eye care utilisation compared to their traditional screening counterparts. A good correlation between clinical Snellen and smartphone visual acuity measurements (ρ=.91) is observed. For depression screening, the ROC curve is .8012, indicating that mental-health ratings are comparable to Patient Health Questionnaire-9 (PHQ-9) results, and could be used as a depression screening tool in practice. Although the findings of cognitive impairment suggest that the digital-version readings are similar to the standard paper-version readings, the participants preferred devices with larger screen (e.g. tablet). Also, the smartphone-compatible oximeter is a weak predictor to detect central sleep apnoea in stable heart failure participants. value, where applicable are presented and discussed.
RESULTS
Results showed that app-based screening group had significant (OR:1.7, 95% CI: 1.2–2.4) eye care utilisation compared to their traditional screening counterparts. A good correlation between clinical Snellen and smartphone visual acuity measurements (ρ=.91) is observed. For depression screening, the ROC curve is .8012, indicating that mental-health ratings are comparable to Patient Health Questionnaire-9 (PHQ-9) results, and could be used as a depression screening tool in practice. Although the findings of cognitive impairment suggest that the digital-version readings are similar to the standard paper-version readings, the participants preferred devices with larger screen (e.g. tablet). Also, the smartphone-compatible oximeter is a weak predictor to detect central sleep apnoea in stable heart failure participants.
CONCLUSIONS
The review observed a significant statistical relationship between the app and standard clinical screening. Critical considerations when designing, developing, and deploying smartphone solutions is laid forth to provide equitable healthcare solutions without barriers. Furthermore, the findings might increase the research prospects to evaluate smartphone solutions as valid and reliable screening solutions.
Conversion of Urine Protein–Creatinine Ratio or Urine Dipstick Protein to Urine Albumin–Creatinine Ratio for Use in Chronic Kidney Disease Screening and Prognosis