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1.
BMC Pregnancy Childbirth ; 22(1): 485, 2022 Jun 13.
Article in English | MEDLINE | ID: covidwho-1951116

ABSTRACT

BACKGROUND: Access to mass media and emerging technologies (e.g., cell phones, the internet, and social media) is a social determinant of health that has been shown to profoundly influence women's health outcomes. In the African region, where women in rural settings with limited access to care are most vulnerable to maternal mortality and other pregnancy-related morbidities, mobile phone access can be an important and life-saving health determinant. OBJECTIVE: The goal of this study was to examine the association between mobile/cellular phone ownership and health behaviors of post-partum mothers in rural Malawi. METHODS: In this cross-sectional study, we recruited and consented a convenient sample of 174 post-partum mothers of 4- and 5-month-olds who were attending well-child clinics in Gowa, situated in the rural Ntcheu district of Malawi. Using logistic regression models, we hypothesized that compared to non-cell phone owners, mobile phone ownership will be predictive (greater odds) of antenatal visit frequency, exclusive breastfeeding knowledge and practices, health-seeking behaviors, and involvement in motherhood support groups; and protective (lower odds) of infant illnesses, breastfeeding challenges, and post-partum depressive symptoms. RESULTS: Mobile phones were highly prevalent in this rural setting, with 45% (n = 79) of post-partum women indicating they owned at least one cell phone. Cell phone owners tended to have higher levels of education (p < 0.012) and wealth (p < 0.001). Interestingly, mobile phone ownership was only associated with exclusive breastfeeding practices; and phone owners had 75% lower odds of exclusively breastfeeding (adj. OR 0.25; 95% CI: 0.07-0.92, p = 0.038) in multivariable models. Though not statistically significant but clinically meaningful, cell phone ownership was associated with fewer depressive symptoms (adj. OR 0.84; 95% CI: 0.39-1.84, p = 0.67) and more social support (adj. OR 1.14; 95% CI: 0.61-2.13, p = 0.70). CONCLUSIONS: Digital literacy and internet connectivity are social determinants of health, thus delving deeper into mothers' digital experiences to identify and ameliorate their unique barriers to full digital access will be crucial to successful implementation of digital interventions to address post-partum challenges for women in hard-to-reach settings such as ours. Such interventions are of even greater relevance as the Covid-19 pandemic has increased the urgency of reaching vulnerable, marginalized populations.


Subject(s)
COVID-19 , Cell Phone , Cross-Sectional Studies , Female , Humans , Infant , Malawi , Mothers , Outcome Assessment, Health Care , Pandemics , Postpartum Period , Pregnancy
2.
Diabetes Metab Syndr ; 16(5): 102485, 2022 May.
Article in English | MEDLINE | ID: covidwho-1894979

ABSTRACT

BACKGROUND AND AIMS: Self-management is critical to manage the glycemic and metabolic outcomes for patients with diabetes. Telehealth applications are recognized as a potential approach to promote self-management of people with type 2 diabetes. This study aimed to investigate the impact of telehealth on self-management among patients with type 2 diabetes. METHODS: A systematic review was conducted on several databases, including PubMed, EbscoHost Medline, and Science Direct, with the keywords: Diabetes Mellitus AND Mobile-phone based OR Telemedicine OR Telehealth OR Web-based OR Telenursing AND Self-management. Inclusion criteria were articles with type 2 diabetic respondents, published between 2015 and 2020, open-access articles, and had self-management as outcomes. Hence, qualitative, protocol, or review articles, commentaries, letters to editors, and case study/reports were excluded. The Joanna Briggs Institute critical appraisal tools and Cochrane collaboration's tools were used for assessing risk of bias. RESULTS: The total of six studies were included in the qualitative synthesis, with five randomized control trials and one cross-sectional study. Telehealth applications were formed as an online or app-based platform with the key features of educational programs, text or voice messages, consultations and counseling, and active participation of the subjects. Besides improving the self-management outcomes, the telehealth also indicated improvements in positive behaviors, attitudes, and the intention of self-management. CONCLUSION: The study concluded that implementation of telehealth provided positive self-management results among patients with type 2 diabetes. The users need to consider an intensive training, peer or family support, and provision of full support for the patients during the implementation of telehealth.


Subject(s)
Cell Phone , Diabetes Mellitus, Type 2 , Self-Management , Telemedicine , Cross-Sectional Studies , Diabetes Mellitus, Type 2/therapy , Humans , Telemedicine/methods
3.
J Nutr ; 152(5): 1316-1326, 2022 05 05.
Article in English | MEDLINE | ID: covidwho-1886458

ABSTRACT

BACKGROUND: Although most health facilities in urban Nigeria are privately owned, interventions to promote optimal breastfeeding practices in private facilities have not previously been implemented. OBJECTIVES: We tested the impact of a breastfeeding promotion intervention on early initiation of breastfeeding and exclusive breastfeeding among clients of private facilities in Lagos, Nigeria. METHODS: The intervention included training for health-care providers on the Baby-Friendly Hospital Initiative and breastfeeding counseling skills, provision of interpersonal communication and support to women at facilities and on WhatsApp, distribution of behavior change communication materials, and mobile phone and mass media messaging. We used logistic regression models adjusted for clustering to measure intervention impact in a cohort of women (n = 1200) at 10 intervention and 10 comparison facilities interviewed during their third trimester and at 6 and 24 weeks postpartum. RESULTS: The intervention significantly increased the percentage of infants who were exclusively breastfed at 6 weeks (83% intervention; 76% comparison; P = 0.02) and 24 weeks (66% intervention; 52% comparison; P < 0.001), but had no impact on early initiation of breastfeeding (35% intervention; 33% comparison; P = 0.65). Among infants who were exclusively breastfed at 6 weeks, the odds of continued exclusive breastfeeding at 24 weeks were higher in the intervention arm than in the comparison arm (OR, 1.6; 95% CI: 1.2-2.1). Infants had increased odds of being exclusively breastfed at 6 weeks if their mothers discussed breastfeeding with a private health provider (OR, 2.3; 95% CI: 1.5-3.4), received text or WhatsApp messages about breastfeeding (OR, 1.7; 95% CI: 1.0-2.7), or heard breastfeeding radio spots (OR, 4.2; 95% CI: 1.2-14.7). Infants had increased odds of exclusive breastfeeding at 24 weeks if their mothers participated in a WhatsApp breastfeeding support group (OR, 1.5; 95% CI: 1.0-2.2). CONCLUSIONS: A breastfeeding intervention in private health facilities in Lagos increased exclusive breastfeeding. Implementation of breastfeeding interventions in private facilities could extend the reach of breastfeeding promotion programs in urban Nigeria. This trial was registered at clinicaltrials.gov as NCT04835051.


Subject(s)
Breast Feeding , Cell Phone , Breast Feeding/psychology , Communication , Female , Health Facilities , Humans , Infant , Mass Media , Nigeria , Private Facilities
4.
Int J Environ Res Public Health ; 19(11)2022 05 30.
Article in English | MEDLINE | ID: covidwho-1869616

ABSTRACT

In response to the COVID-19 pandemic, mobile-phone data on population movement became publicly available, including Google Community Mobility Reports (CMR). This study explored the utilization of mobility data to predict COVID-19 dynamics in Jakarta, Indonesia. We acquired aggregated and anonymized mobility data sets from 15 February to 31 December 2020. Three statistical models were explored: Poisson Regression Generalized Linear Model (GLM), Negative Binomial Regression GLM, and Multiple Linear Regression (MLR). Due to multicollinearity, three categories were reduced into one single index using Principal Component Analysis (PCA). Multiple Linear Regression with variable adjustments using PCA was the best-fit model, explaining 52% of COVID-19 cases in Jakarta (R-Square: 0.52; p < 0.05). This study found that different types of mobility were significant predictors for COVID-19 cases and have different levels of impact on COVID-19 dynamics in Jakarta, with the highest observed in "grocery and pharmacy" (4.12%). This study demonstrates the practicality of using CMR data to help policymakers in decision making and policy formulation, especially when there are limited data available, and can be used to improve health system readiness by anticipating case surge, such as in the places with a high potential for transmission risk and during seasonal events.


Subject(s)
COVID-19 , Cell Phone , COVID-19/epidemiology , Humans , Indonesia/epidemiology , Models, Statistical , Pandemics
5.
J Indian Soc Pedod Prev Dent ; 40(1): 74-80, 2022.
Article in English | MEDLINE | ID: covidwho-1810816

ABSTRACT

Context: The ongoing pandemic has affected all the spheres of life and one of the severely affected avenues is the education of a child. The online education has seen an upward curve since the start of COVID-19 pandemic. Schools globally have adopted online class tutorials as the main method to impart education and directly increasing the screen time for a child. Aim: The aim of the present study was to evaluate the cytological effects of prolonged mobile phone usage on the buccal mucosa of children. Settings and Design: Stratified sampling was used for the selection of subjects for the study. After a questionnaire regarding the usage of a mobile phone was distributed among the parents of children. Among them, 90 children were selected on the basis of pattern and frequency of mobile phone usage in the child. Materials and Methodology: The children were divided into three groups based on the per day hours of viewing of mobile phone, i.e., Group 1: Usage of 1-2 h a day, Group 2: Usage of 3-6 h a day, and Group 3: Usage of >6 h a day. The time frame taken into consideration was 1 year after the pandemic started. This was specifically to understand the impact of the online education. Swab was obtained by using the conventional ice-cream stick method from the buccal mucosa. Statistical Analysis: The samples were subjected to histological and microscopical analysis to observe for cytological changes. One-way ANOVA was used to determine the statistical significance if any. Results: The results obtained clearly showed that Group 3 (>6 h usage per day) showed the highest number of cellular and chromosomal aberrations which was significant. Conclusion: The results indicated that impact due to the prolonged screen time on the buccal mucosa is significant. A direct proportionality was seen between the apoptotic changes and chromosomal aberrations and the number of daily hour usage.


Subject(s)
COVID-19 , Cell Phone , Child , Chromosome Aberrations , Cross-Sectional Studies , Humans , Mouth Mucosa/pathology , Pandemics
6.
PLoS One ; 17(4): e0267595, 2022.
Article in English | MEDLINE | ID: covidwho-1808577

ABSTRACT

With the rapid proliferation of mobile telephony and the establishment of an IT-enabled payment and settlement system, Bangladesh nowadays is experiencing a remarkable growth in the usage of mobile financial services (MFS). As more and more people are opting to use this service, a huge number of mobile accounts are opened every day and a substantial amount of money is deposited, withdrawn and transferred frequently through the mobile network. This ever-increasing amount of mobile money flowing through the network may have a sizeable impact on the overall money supply of the country. Thus far, no systematic study has been conducted to quantify the impact of the mobile money on the conventional money supply of Bangladesh. In this study, we attempt to quantify the contribution of mobile money on the money supply which is an important quantity-based nominal anchor of monetary policy in Bangladesh. Apart from deriving algebraic relationships between money supply and e-money, here we have empirically shown that during the 03 years span of 2018-2021, MFS transactions account for nearly 10.88% and 11.29% of total narrow and broad money supply of Bangladesh as on January 2021. Besides, we also qualitatively discuss the impact of e-money on an important price-based nominal anchor of monetary policy in Bangladesh, i.e., interest rate. Based upon the above discussion, here we argue that MFS can act as an effective tool to slash interest rate by a reasonable proportion through adding significantly to the overall supply of money in Bangladesh.


Subject(s)
Cell Phone , Bangladesh , Humans , Policy
7.
PLoS One ; 17(4): e0264860, 2022.
Article in English | MEDLINE | ID: covidwho-1808558

ABSTRACT

Compartmental models are often used to understand and predict the progression of an infectious disease such as COVID-19. The most basic of these models consider the total population of a region to be closed. Many incorporate human mobility into their transmission dynamics, usually based on static and aggregated data. However, mobility can change dramatically during a global pandemic as seen with COVID-19, making static data unsuitable. Recently, large mobility datasets derived from mobile devices have been used, along with COVID-19 infections data, to better understand the relationship between mobility and COVID-19. However, studies to date have relied on data that represent only a fraction of their target populations, and the data from mobile devices have been used for measuring mobility within the study region, without considering changes to the population as people enter and leave the region. This work presents a unique case study in Andorra, with comprehensive datasets that include telecoms data covering 100% of mobile subscribers in the country, and results from a serology testing program that more than 90% of the population voluntarily participated in. We use the telecoms data to both measure mobility within the country and to provide a real-time census of people entering, leaving and remaining in the country. We develop multiple SEIR (compartmental) models parameterized on these metrics and show how dynamic population metrics can improve the models. We find that total daily trips did not have predictive value in the SEIR models while country entrances did. As a secondary contribution of this work, we show how Andorra's serology testing program was likely impacted by people leaving the country. Overall, this case study suggests how using mobile phone data to measure dynamic population changes could improve studies that rely on more commonly used mobility metrics and the overall understanding of a pandemic.


Subject(s)
COVID-19 , Cell Phone , Andorra , COVID-19/epidemiology , Humans , Pandemics , SARS-CoV-2
8.
Front Cell Infect Microbiol ; 12: 806077, 2022.
Article in English | MEDLINE | ID: covidwho-1775644

ABSTRACT

Background: Mobile phones of healthcare workers (HCWs) can act as fomites in the dissemination of microbes. This study was carried out to investigate microbial contamination of mobile phones of HCWs and environmental samples from the hospital unit using a combination of phenotypic and molecular methods. Methods: This point prevalence survey was carried out at the Emergency unit of a tertiary care facility. The emergency unit has two zones, a general zone for non-COVID-19 patients and a dedicated COVID-19 zone for confirmed or suspected COVID-19 patients. Swabs were obtained from the mobile phones of HCWs in both zones for bacterial culture and shotgun metagenomic analysis. Metagenomic sequencing of pooled environmental swabs was conducted. RT-PCR for SARS-CoV-2 detection was carried out. Results: Bacteria contamination on culture was detected from 33 (94.2%) mobile phones with a preponderance of Staphylococcus epidermidis (n/N = 18/35), Staphylococcus hominis (n/N = 13/35), and Staphylococcus haemolyticus (n/N = 7/35). Two methicillin-sensitive and three methicillin-resistant Staphylococcus aureus, and one pan-drug-resistant carbapenemase producer Acinetobacter baumannii were detected. Shotgun metagenomic analysis showed high signature of Pseudomonas aeruginosa in mobile phone and environmental samples with preponderance of P. aeruginosa bacteriophages. Malassezia and Aspergillus spp. were the predominant fungi detected. Fourteen mobile phones and one environmental sample harbored protists. P. aeruginosa antimicrobial resistance genes mostly encoding for efflux pump systems were detected. The P. aeruginosa virulent factor genes detected were related to motility, adherence, aggregation, and biofilms. One mobile phone from the COVID-19 zone (n/N = 1/5; 20%) had positive SARS-CoV-2 detection while all other phone and environmental samples were negative. Conclusion: The findings demonstrate that mobile phones of HCWs are fomites for potentially pathogenic and highly drug-resistant microbes. The presence of these microbes on the mobile phones and hospital environmental surfaces is a concern as it poses a risk of pathogen transfer to patients and dissemination into the community.


Subject(s)
COVID-19 , Cell Phone , Methicillin-Resistant Staphylococcus aureus , Humans , Methicillin-Resistant Staphylococcus aureus/genetics , Reverse Transcriptase Polymerase Chain Reaction , SARS-CoV-2/genetics
9.
Front Public Health ; 9: 745524, 2021.
Article in English | MEDLINE | ID: covidwho-1775916

ABSTRACT

This paper presents an OSA patient interactive monitoring system based on the Beidou system. This system allows OSA patients to get timely rescue when they become sleepy outside. Because the Beidou position marker has an interactive function, it can reduce the anxiety of the patient while waiting for the rescue. At the same time, if a friend helps the OSA patients to call the doctor, the friend can also report the patient's condition in time. This system uses the popular IoT framework. At the bottom is the data acquisition layer, which uses wearable sensors to collect vital signs from patients, with a focus on ECG and SpO2 signals. The middle layer is the network layer that transmits the collected physiological signals to the Beidou indicator using the Bluetooth Low Energy (BLE) protocol. The top layer is the application layer, and the application layer uses the mature rescue interactive platform of Beidou. The Beidou system was developed by China itself, the main coverage of the satellite is in Asia, and is equipped with a high-density ground-based augmentation system. Therefore, the Beidou model improves the positioning accuracy and is equipped with a special communication satellite, which increases the short message interaction function. Therefore, patients can report disease progression in time while waiting for a rescue. After our simulation test, the effectiveness of the OSA patient rescue monitoring system based on the Beidou system and the positioning accuracy of OSA patients have been greatly improved. Especially when OSA patients work outdoors, the cell phone base station signal coverage is relatively weak. The satellite signal is well-covered, plus the SMS function of the Beidou indicator. Therefore, the system can be used to provide timely patient progress and provide data support for the medical rescue team to provide a more accurate rescue plan. After a comparative trial, the rescue rate of OSA patients using the detection device of this system was increased by 15 percentage points compared with the rescue rate using only GPS satellite phones.


Subject(s)
Cell Phone , Sleep Apnea, Obstructive , China , Humans , Monitoring, Physiologic , Sleep Apnea, Obstructive/diagnosis
10.
Nature ; 603(7903): 864-870, 2022 03.
Article in English | MEDLINE | ID: covidwho-1747206

ABSTRACT

The COVID-19 pandemic has devastated many low- and middle-income countries, causing widespread food insecurity and a sharp decline in living standards1. In response to this crisis, governments and humanitarian organizations worldwide have distributed social assistance to more than 1.5 billion people2. Targeting is a central challenge in administering these programmes: it remains a difficult task to rapidly identify those with the greatest need given available data3,4. Here we show that data from mobile phone networks can improve the targeting of humanitarian assistance. Our approach uses traditional survey data to train machine-learning algorithms to recognize patterns of poverty in mobile phone data; the trained algorithms can then prioritize aid to the poorest mobile subscribers. We evaluate this approach by studying a flagship emergency cash transfer program in Togo, which used these algorithms to disburse millions of US dollars worth of COVID-19 relief aid. Our analysis compares outcomes-including exclusion errors, total social welfare and measures of fairness-under different targeting regimes. Relative to the geographic targeting options considered by the Government of Togo, the machine-learning approach reduces errors of exclusion by 4-21%. Relative to methods requiring a comprehensive social registry (a hypothetical exercise; no such registry exists in Togo), the machine-learning approach increases exclusion errors by 9-35%. These results highlight the potential for new data sources to complement traditional methods for targeting humanitarian assistance, particularly in crisis settings in which traditional data are missing or out of date.


Subject(s)
COVID-19 , Cell Phone , Machine Learning , Relief Work , COVID-19/epidemiology , Data Analysis , Humans , Pandemics , Poverty
11.
BMJ Open ; 12(3): e056076, 2022 03 10.
Article in English | MEDLINE | ID: covidwho-1741635

ABSTRACT

OBJECTIVES: Efforts to understand the factors influencing the uptake of reproductive, maternal, newborn, child health and nutrition (RMNCH&N) services in high disease burden low-resource settings have often focused on face-to-face surveys or direct observations of service delivery. Increasing access to mobile phones has led to growing interest in phone surveys as a rapid, low-cost alternatives to face-to-face surveys. We assess determinants of RMNCH&N knowledge among pregnant women with access to phones and examine the reliability of alternative modalities of survey delivery. PARTICIPANTS: Women 5-7 months pregnant with access to a phone. SETTING: Four districts of Madhya Pradesh, India. DESIGN: Cross-sectional surveys administered face-to-face and within 2 weeks, the same surveys were repeated among two random subsamples of the original sample: face-to-face (n=205) and caller-attended telephone interviews (n=375). Bivariate analyses, multivariable linear regression, and prevalence and bias-adjusted kappa scores are presented. RESULTS: Knowledge scores were low across domains: 52% for maternal nutrition and pregnancy danger signs, 58% for family planning, 47% for essential newborn care, 56% infant and young child feeding, and 58% for infant and young child care. Higher knowledge (≥1 composite score) was associated with older age; higher levels of education and literacy; living in a nuclear family; primary health decision-making; greater attendance in antenatal care and satisfaction with accredited social health activist services. Survey questions had low inter-rater and intermodal reliability (kappa<0.70) with a few exceptions. Questions with the lowest reliability included true/false questions and those with unprompted, multiple response options. Reliability may have been hampered by the sensitivity of the content, lack of privacy, enumerators' and respondents' profile differences, rapport, social desirability bias, and/or enumerator's ability to adequately convey concepts or probe. CONCLUSIONS: Phone surveys are a reliable modality for generating population-level estimates data about pregnant women's knowledge, however, should not be used for individual-level tracking. TRIAL REGISTRATION NUMBER: NCT03576157.


Subject(s)
Cell Phone , Pregnant Women , Child , Child Health , Cross-Sectional Studies , Feasibility Studies , Female , Humans , India , Infant , Infant, Newborn , Pregnancy , Reproducibility of Results , Surveys and Questionnaires , Telephone
12.
J Med Internet Res ; 24(2): e30524, 2022 02 15.
Article in English | MEDLINE | ID: covidwho-1714892

ABSTRACT

There is a fundamental need to establish the most ethical and effective way of tracking disease in the postpandemic era. The ubiquity of mobile phones is generating large amounts of passive data (collected without active user participation) that can be used as a tool for tracking disease. Although discussions of pragmatism or economic issues tend to guide public health decisions, ethical issues are the foremost public concern. Thus, officials must look to history and current moral frameworks to avoid past mistakes and ethical pitfalls. Past pandemics demonstrate that the aftermath is the most effective time to make health policy decisions. However, an ethical discussion of passive data use for digital public health surveillance has yet to be attempted, and little has been done to determine the best method to do so. Therefore, we aim to highlight four potential areas of ethical opportunity and challenge: (1) informed consent, (2) privacy, (3) equity, and (4) ownership.


Subject(s)
Cell Phone , Public Health Surveillance , Humans , Informed Consent , Morals , Privacy , Public Health
13.
BMC Health Serv Res ; 22(1): 106, 2022 Jan 25.
Article in English | MEDLINE | ID: covidwho-1703683

ABSTRACT

BACKGROUND: Despite the availability of a range of contraceptive methods, young people around the world still face barriers in accessing and using them. The use of digital technology for the delivery of health interventions has expanded rapidly. Intervention delivery by mobile phone can be a useful way to address young people's needs with regard to sexual and reproductive health, because the information can be digested at a time of the recipients' choosing. This study reports the adaptation of an evidence-based contraceptive behavioural intervention for young people in Zimbabwe. METHODS: Focus group discussions and in depth interviews were used to evaluate the 'fit' of the existing intervention among young people in Harare, Zimbabwe. This involved determining how aligned the content of the existing intervention was to the knowledge and beliefs of young Zimbabweans plus identifying the most appropriate intervention deliver mode. The verbatim transcripts were analysed using a thematic analysis. The existing intervention was then adapted, tested and refined in subsequent focus group discussions and interviews with young people in Harare and Bulawayo. RESULTS: Eleven key themes resulted from the discussions evaluating the fit of the intervention. While there were many similarities to the original study population, key differences were that young people in Zimbabwe had lower levels of personal and smart mobile phone ownership and lower literacy levels. Young people were enthusiastic about receiving information about side effects/side benefits of the methods. The iterative testing and refinement resulted in adapted intervention consisting of 97 messages for female recipients (94 for male), delivered over three months and offered in English, Shona and Ndebele. CONCLUSIONS: Young people in Zimbabwe provided essential information for adapting the existing intervention. There was great support for the adapted intervention among the young people who took part in this study. The adapted intervention is now being implemented within an integrated community-based sexual and reproductive health service in Zimbabwe.


Subject(s)
Cell Phone , Contraceptive Agents , Adolescent , Contraception , Female , Humans , Male , Reproductive Health , Zimbabwe
14.
Sci Rep ; 12(1): 2627, 2022 02 16.
Article in English | MEDLINE | ID: covidwho-1692539

ABSTRACT

This study aimed to evaluate the effectiveness of wireless emergency alerts (WEAs) on social distancing policy. The Republic of Korea has been providing information to the public through WEAs using mobile phones. This study used five data sets: WEA messages, news articles including the keyword "COVID-19," the number of confirmed COVID-19 patients, public foot traffic data, and the government's social distancing level. The WEAs were classified into two topics-"warning" and "guidance"-using a random forest model. The results of the correlation analysis and further detailed analysis confirmed that the "warning" WEA topic and number of news articles significantly affected public foot traffic. However, the "guidance" topic was not significantly associated with public foot traffic. In general, the Korean government's WEAs were effective at encouraging the public to follow social distance recommendations during the COVID-19 pandemic. In particular, the "warning" WEA topic, by providing information about the relative risk directly concerning the recipients, was significantly more effective than the "guidance" topic.


Subject(s)
COVID-19/prevention & control , Cell Phone , Disease Notification/methods , Physical Distancing , Humans , Mass Media , Public Health Practice , Republic of Korea
15.
J Arthroplasty ; 37(3): 431-437.e3, 2022 03.
Article in English | MEDLINE | ID: covidwho-1682921

ABSTRACT

BACKGROUND: We conducted a randomized controlled trial to evaluate the effectiveness of acceptance and commitment therapy (ACT) delivered via a mobile phone messaging robot to patients who had their total hip arthroplasty or total knee arthroplasty procedures postponed due to the COVID-19 pandemic. METHODS: Ninety patients scheduled for total hip arthroplasty or total knee arthroplasty who experienced surgical delay due to the COVID-19 pandemic were randomized to the ACT group, receiving 14 days of twice daily automated mobile phone messages, or the control group, who received no messages. Minimal clinically important differences (MCIDs) in preintervention and postintervention patient-reported outcome measures were utilized to evaluate the intervention. RESULTS: Thirty-eight percent of ACT group participants improved and achieved MCID on the Patient-Reported Outcome Measure Information System Physical Health compared to 17.5% in the control group (P = .038; number needed to treat [NNT] 5). For the joint-specific Hip Disability and Osteoarthritis Outcome Score Joint Replacement and Knee Disability and Osteoarthritis Outcome Score Joint Replacement (KOOS JR), 24% of the ACT group achieved MCID compared to 2.5% in the control group (P = .004; NNT 5). An improvement in the KOOS JR was found in 29% of the ACT group compared to 4.2% in the control group (P = .028; NNT 5). Fourteen percent of the ACT group participants experienced a clinical important decline in the KOOS JR compared to 41.7% in the control group (P = .027; NNT 4). CONCLUSION: A psychological intervention delivered via a text messaging robot improved physical function and prevented decline in patient-reported outcome measures in patients who experienced an unexpected surgical delay during the COVID-19 pandemic. LEVEL OF EVIDENCE: 1.


Subject(s)
Acceptance and Commitment Therapy , Arthroplasty, Replacement, Hip , COVID-19 , Cell Phone , Osteoarthritis, Knee , Humans , Osteoarthritis, Knee/surgery , Pandemics , SARS-CoV-2
16.
Int Ophthalmol ; 42(6): 1749-1762, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1653602

ABSTRACT

BACKGROUND AND OBJECTIVE: Age-related macular degeneration (AMD) is one of the most common reasons for blindness in the world today. The most common treatment for wet AMD is the intravitreal injections for inhibiting vascular-endothelial-derived growth factor (VEGF). This treatment usually involves multiple injections and thus multiple clinic visits, which not only causes increased cost on national health services but also causes exposure to the hospital environment, which is sometimes high risk considering current COVID crisis. The treatment, in spite of the above concerns, is usually effective. However, in some cases, either the medicine fails to produce the anticipated favourable outcome, resulting in waste of time, medication, efforts, and above all, psychological distress to the patients. Hence, early predictability of anatomical as well as functional effectiveness of the treatment appears to be a very desirable capability to have. METHOD: A machine learning approach using adaptive neuro-fuzzy inference system (ANFIS) of two-sample prediction model has been presented that requires only the baseline measurements and changes in visual acuity (VA) as well as macular thickness (MAC) after four months of treatment to estimate the values of VA and MAC at 8 and 12 months. In contrast to most of the AI techniques, ANFIS approach has shown the capability of the algorithm to work with very small dataset as well, which makes it a perfect candidate for the presented solution. RESULTS: The presented model has shown to have a very high accuracy (> 92%) and works in near-real-time scenarios. It has been converted into a smart phone App, OphnosisAMD, for convenient usage. With this App, the clinician can visualize the progression of the patient for a specific treatment and can decide on continuing or changing the treatment accordingly. The complete AI engine developed with the ANFIS algorithm is localized to the phone through the App, implying that there is no need for internet or cloud connectivity for this App to function. This makes it ideal for remote usage, especially under the current COVID scenarios. CONCLUSIONS: With a smart AI-based App on their fingertips, the presented system provides ample opportunity to the doctors to make a better decision based on the estimated progression, if the same drug is continued with (good/fair prognosis) or alternate treatment should be sought (bad prognosis). From a functional point of view, a prediction algorithm is triggered through simple entry of the relevant parameters (baseline and 4 months only). No internet/cloud connectivity is needed since the algorithm and the trained network are fully embedded in the App locally. Hence, using the App in remote and/or non-connected isolated areas is possible, especially in the secluded patients during the COVID scenarios.


Subject(s)
COVID-19 , Cell Phone , Wet Macular Degeneration , Aged, 80 and over , Angiogenesis Inhibitors/therapeutic use , Artificial Intelligence , Humans , Intravitreal Injections , Prognosis , Ranibizumab , Treatment Outcome , Vascular Endothelial Growth Factor A , Wet Macular Degeneration/diagnosis , Wet Macular Degeneration/drug therapy
17.
PLoS One ; 16(12): e0260931, 2021.
Article in English | MEDLINE | ID: covidwho-1632675

ABSTRACT

During the COVID-19 pandemic, US populations have experienced elevated rates of financial and psychological distress that could lead to increases in suicide rates. Rapid ongoing mental health monitoring is critical for early intervention, especially in regions most affected by the pandemic, yet traditional surveillance data are available only after long lags. Novel information on real-time population isolation and concerns stemming from the pandemic's social and economic impacts, via cellular mobility tracking and online search data, are potentially important interim surveillance resources. Using these measures, we employed transfer function model time-series analyses to estimate associations between daily mobility indicators (proportion of cellular devices completely at home and time spent at home) and Google Health Trends search volumes for terms pertaining to economic stress, mental health, and suicide during 2020 and 2021 both nationally and in New York City. During the first pandemic wave in early-spring 2020, over 50% of devices remained completely at home and searches for economic stressors exceeded 60,000 per 10 million. We found large concurrent associations across analyses between declining mobility and increasing searches for economic stressor terms (national proportion of devices at home: cross-correlation coefficient (CC) = 0.6 (p-value <0.001)). Nationally, we also found strong associations between declining mobility and increasing mental health and suicide-related searches (time at home: mood/anxiety CC = 0.53 (<0.001), social stressor CC = 0.51 (<0.001), suicide seeking CC = 0.37 (0.006)). Our findings suggest that pandemic-related isolation coincided with acute economic distress and may be a risk factor for poor mental health and suicidal behavior. These emergent relationships warrant ongoing attention and causal assessment given the potential for long-term psychological impact and suicide death. As US populations continue to face stress, Google search data can be used to identify possible warning signs from real-time changes in distributions of population thought patterns.


Subject(s)
COVID-19/psychology , Cell Phone/statistics & numerical data , Search Engine/statistics & numerical data , Socioeconomic Factors , Suicide/psychology , Geographic Information Systems , Humans , Mental Health/statistics & numerical data , New York City , Quarantine/statistics & numerical data , Search Engine/trends , Stress, Psychological , Time Factors , United States
18.
J Health Econ ; 82: 102581, 2022 03.
Article in English | MEDLINE | ID: covidwho-1620828

ABSTRACT

The COVID-19 pandemic has forced federal, state, and local policymakers to respond by legislating, enacting, and enforcing social distancing policies. However, the impact of these policies on healthcare utilization in the United States has been largely unexplored. We examine the impact of county-level shelter in place ordinances on healthcare utilization using two unique datasets-employer-sponsored insurance for over 6 million people in the US and cell phone location data. We find that introduction of these policies was associated with reductions in the use of preventive care, elective care, and the number of weekly visits to physician offices, hospitals and other health care-related industries. However, controlling for county-level exposure to the COVID-19 pandemic as a way to account for the endogenous nature of policy implementation reduces the impact of these policies. Our results imply that while social distancing policies do lead to reductions in healthcare utilization, much of these reductions would have occurred even in the absence of these policies.


Subject(s)
COVID-19 , Cell Phone , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Pandemics/prevention & control , Patient Acceptance of Health Care , Policy , United States/epidemiology
19.
PLoS One ; 16(12): e0261758, 2021.
Article in English | MEDLINE | ID: covidwho-1597654

ABSTRACT

BACKGROUND: Non-adherence to Tuberculosis (TB) medication is a serious threat to TB prevention and control programs, especially in resource-limited settings. The growth of the popularity of mobile phones provides opportunities to address non-adherence, by facilitating direct communication more frequently between healthcare providers and patients through SMS texts and voice phone calls. However, the existing evidence is inconsistent about the effect of SMS interventions on TB treatment adherence. Such interventions are also seldom developed based on appropriate theoretical foundations. Therefore, there is a reason to approach this problem more rigorously, by developing the intervention systematically with evidence-based theory and conducting the trial with strong measurement methods. METHODS: This study is a single-blind parallel-group design individual randomized control trial. A total of 186 participants (93 per group) will be individually randomized into one of the two groups with a 1:1 allocation ratio by a computer-generated algorithm. Group one (intervention) participants will receive daily SMS texts and weekly phone calls concerning their daily medication intake and medication refill clinic visit reminder and group two (control) participants will receive the same routine standard treatment care as the intervention group, but no SMS text and phone calls. All participants will be followed for two months of home-based self-administered medication during the continuation phases of the standard treatment period. Urine test for the presence of isoniazid (INH) drug metabolites in urine will be undertaken at the random point at the fourth and eighth weeks of intervention to measure medication adherence. Medication adherence will also be assessed by self-report measurements using the AIDS Clinical Trial Group adherence (ACTG) and Visual Analogue Scales (VAS) questionnaires, and clinic appointment attendance registration. Multivariable regression model analysis will be employed to assess the effect of the Ma-MAS intervention at a significance level of P-value < 0.05 with a 95% confidence interval. DISCUSSION: For this trial, a mobile-assisted medication adherence intervention will first be developed systematically based on the Medical Research Council framework using appropriate behavioural theory and evidence. The trial will then evaluate the effect of SMS texts and phone calls on TB medication adherence. Evidence generated from this trial will be highly valuable for policymakers, program managers, and healthcare providers working in Ethiopia and beyond. TRIAL REGISTRATION: The trial is registered in the Pan-Africa Clinical Trials Registry with trial number PACTR202002831201865.


Subject(s)
Medication Adherence , Tuberculosis , Cell Phone , Humans , Single-Blind Method , Text Messaging
20.
Sci Rep ; 11(1): 24171, 2021 12 17.
Article in English | MEDLINE | ID: covidwho-1593554

ABSTRACT

The transmission of COVID-19 is dependent on social mixing, the basic rate of which varies with sociodemographic, cultural, and geographic factors. Alterations in social mixing and subsequent changes in transmission dynamics eventually affect hospital admissions. We employ these observations to model and predict regional hospital admissions in Sweden during the COVID-19 pandemic. We use an SEIR-model for each region in Sweden in which the social mixing is assumed to depend on mobility data from public transport utilisation and locations for mobile phone usage. The results show that the model could capture the timing of the first and beginning of the second wave of the pandemic 3 weeks in advance without any additional assumptions about seasonality. Further, we show that for two major regions of Sweden, models with public transport data outperform models using mobile phone usage. We conclude that a model based on routinely collected mobility data makes it possible to predict future hospital admissions for COVID-19 3 weeks in advance.


Subject(s)
Algorithms , COVID-19/transmission , Cell Phone/statistics & numerical data , Hospitalization/statistics & numerical data , Models, Theoretical , Patient Admission/statistics & numerical data , COVID-19/epidemiology , COVID-19/virology , Disease Transmission, Infectious/statistics & numerical data , Forecasting/methods , Geography , Hospitalization/trends , Humans , Pandemics/prevention & control , Patient Admission/trends , Retrospective Studies , SARS-CoV-2/physiology , Sweden/epidemiology , Travel/statistics & numerical data
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