Are mHealth Interventions Effective in Improving the Uptake of Sexual and Reproductive Health Services among Adolescents? A Scoping Review

Adolescents continue to face challenges to their sexual and reproductive health (SRH) both locally and internationally. Digital technologies such as the Internet, text messaging, and social media are often viewed as valuable tools for disseminating information on SRH. Mobile health, also known as mHealth, is a medical and public health practise that uses these digital technologies to communicate information. The literature has revealed that mHealth interventions have a positive outcome in delivering SRH information to adolescents. This review aimed to synthesise empirical studies that evaluate mHealth interventions and assess the extent to which these mHealth interventions promote sexual and reproductive health outcomes among young people. This scoping review reviewed the literature across four databases, including EBSCOhost, Scopus, Proquest, and Cochrane, and included 12 articles. The findings have shown that mHealth interventions are effective in enhancing sexual and reproductive health (SRH) knowledge and attitudes among young people in both low-middle and high-income countries. However, comprehensive longitudinal studies are necessary to measure the sustainability and long-term influence of mHealth interventions on behaviour. It is recommended that with artificial intelligence (AI) improvements, there is a possible path to bolstering mHealth interventions.

A digital image colorimetry system based on smart devices for immediate and simultaneous determination of enzyme-linked immunosorbent assays

Standard enzyme-linked immunosorbent assays based on microplates are frequently utilized for various molecular sensing, disease screening, and nanomedicine applications. Comparing this multi-well plate batched analysis to non-batched or non-standard testing, the diagnosis expenses per patient are drastically reduced. However, the requirement for rather big and pricey readout instruments prevents their application in environments with limited resources, especially in the field. In this work, a handheld cellphone-based colorimetric microplate reader for quick, credible, and novel analysis of digital images of human cancer cell lines at a reasonable price was developed. Using our in-house-developed app, images of the plates are captured and sent to our servers, where they are processed using a machine learning algorithm to produce diagnostic results. Using FDA-approved human epididymis protein of ovary IgG (HE4), prostate cancer cell line (PC3), and bladder cancer cell line (5637) ELISA tests, we successfully examined this mobile platform. The accuracies for the HE4, PC3, and 5637 tests were 93%, 97.5%, and 97.2%, respectively. By contrasting the findings with the measurements made using optical absorption EPOCH microplate readers and optical absorption Tecan microplate readers, this approach was found to be accurate and effective. As a result, digital image colorimetry on smart devices offered a practical, user-friendly, affordable, precise, and effective method for quickly identifying human cancer cell lines. Thus, healthcare providers might use this portable device to carry out high-throughput illness screening, epidemiological investigations or monitor vaccination campaigns.

Patient-Specific Mobile Phone-Generated Reminders and Quality of Hypertension Care in Western Kenya

To evaluate the impact of clinician-targeted mHealth-generated care suggestions on compliance with hypertension care guidelines in a resource-limited setting. This study was conducted in 10 rural health clinics in Western Kenya that offered hypertension care through nurses and clinical officers. Sites were grouped into intervention and control groups. Intervention group clinicians had patient-specific care suggestions triggered and displayed on a mobile application, mUzima, for their action. Care suggestions were also triggered in the mHealth application for control arm clinicians but were not displayed. Differences in compliance with hypertension care guidelines were evaluated. The study involved 378 patients with hypertension who had care suggestions generated during visits (217 in intervention group and 161 in control group). There was a higher proportion of adherence to hypertension care guidelines in the intervention group compared to the control group (91.1% vs. 85.7%, p=0.014). The random effects model showed significant variability in compliance rates among study clinicians (variance of 0.44, 95% CI: 0.12 -1.62). When displayed care suggestions were rejected by intervention providers, the most common reason given was 'Previously ordered' (58.8%). Clinicians felt that care suggestions improved awareness of hypertension care guidelines. The successful scaled implementation of mUzima with patient specific care suggestions led to higher adherence to hypertension care guidelines and improved quality of hypertension care. Tailormade m-Health applications in resource constrained settings for hypertension care and other chronic non-communicable diseases has the potential to lead to better adherence to care guidelines and quality of care.

Adjustable Cuffless Smartphone Attachment (ACSA+) for Estimation of Blood Pressure Trends: A Pilot Study

Among the elderly, hypertension remains one of the prevalent health conditions, which requires monitoring and intervention strategies. Nevertheless, regular reporting of blood pressure (BP) from these individuals still poses multiple challenges. However, most people own cell phone and are engaged in phone conversations daily. Here, we propose an adjustable cuffless smartphone attachment (ACSA+) equipped with a PPG sensor for the estimation of BP during phone conversations. ACSA+ can be easily attached to the back of any modern cell phone. ACSA+ will help to continuously collect BP data and store it as a trend line.

The Goldilocks Dilemma on Balancing User Response and Reflection in mHealth Interventions: Observational Study

Background

Mobile health (mHealth) has the potential to radically improve health behaviors and quality of life; however, there are still key gaps in understanding how to optimize mHealth engagement. Most engagement research reports only on system use without consideration of whether the user is reflecting on the content cognitively. Although interactions with mHealth are critical, cognitive investment may also be important for meaningful behavior change. Notably, content that is designed to request too much reflection could result in users' disengagement. Understanding how to strike the balance between response burden and reflection burden has critical implications for achieving effective engagement to impact intended outcomes.

Objective

In this observational study, we sought to understand the interplay between response burden and reflection burden and how they impact mHealth engagement. Specifically, we explored how varying the response and reflection burdens of mHealth content would impact users' text message response rates in an mHealth intervention.

Methods

We recruited support persons of people with diabetes for a randomized controlled trial that evaluated an mHealth intervention for diabetes management. Support person participants assigned to the intervention (n=148) completed a survey and received text messages for 9 months. During the 2-year randomized controlled trial, we sent 4 versions of a weekly, two-way text message that varied in both reflection burden (level of cognitive reflection requested relative to that of other messages) and response burden (level of information requested for the response relative to that of other messages). We quantified engagement by using participant-level response rates. We compared the odds of responding to each text and used Poisson regression to estimate associations between participant characteristics and response rates.

Results

The texts requesting the most reflection had the lowest response rates regardless of response burden (high reflection and low response burdens: median 10%, IQR 0%-40%; high reflection and high response burdens: median 23%, IQR 0%-51%). The response rate was highest for the text requesting the least reflection (low reflection and low response burdens: median 90%, IQR 61%-100%) yet still relatively high for the text requesting medium reflection (medium reflection and low response burdens: median 75%, IQR 38%-96%). Lower odds of responding were associated with higher reflection burden (P<.001). Younger participants and participants who had a lower socioeconomic status had lower response rates to texts with more reflection burden, relative to those of their counterparts (all P values were <.05).

Conclusions

As reflection burden increased, engagement decreased, and we found more disparities in engagement across participants' characteristics. Content encouraging moderate levels of reflection may be ideal for achieving both cognitive investment and system use. Our findings provide insights into mHealth design and the optimization of both engagement and effectiveness.

Google effects on memory: a meta-analytical review of the media effects of intensive Internet search behavior

People are increasingly using the web for fact-checking and other forms of information seeking. The "Google effects" refers to the idea that individuals rely on the Internet as a source of knowledge rather than remembering it for themselves. However, few literature review have yet comprehensively examined the media effects of this intensive Internet search behavior. In this study, by carrying out meta-analysis, we found that google effects is closely associated with cognitive load, behavioral phenotype and cognitive self-esteem. And this phenomenon is also more likely to happen while using a mobile phone to browse the Internet rather than a computer. People with a larger knowledge base are less susceptible to the consequences of Internet use than those with a smaller knowledge base. The media effect was stronger for persons who had used the Internet before than for those who had not. And meta-analyses show that participants in North America (parameter = -1.0365, 95%CI = [-1.8758, -0.1972], p < 0.05) are more susceptible to frequent Internet search behavior relative to other regions. Overall, google effects on memory challenges the way individuals seek and read information, and it may lead to changes in cognitive and memory mechanisms.

Comparison of Shoulder Range of Motion Quantified with Mobile Phone Video-Based Skeletal Tracking and 3D Motion Capture-Preliminary Study

BACKGROUND

The accuracy of human pose tracking using smartphone camera (2D-pose) to quantify shoulder range of motion (RoM) is not determined.

METHODS

Twenty healthy individuals were recruited and performed shoulder abduction, adduction, flexion, or extension, captured simultaneously using a smartphone-based human pose estimation algorithm (Apple's vision framework) and using a skin marker-based 3D motion capture system. Validity was assessed by comparing the 2D-pose outcomes against a well-established 3D motion capture protocol. In addition, the impact of iPhone positioning was investigated using three smartphones in multiple vertical and horizontal positions. The relationship and validity were analysed using linear mixed models and Bland-Altman analysis.

RESULTS

We found that 2D-pose-based shoulder RoM was consistent with 3D motion capture (linear mixed model: R2 > 0.93) but was somewhat overestimated by the smartphone. Differences were dependent on shoulder movement type and RoM amplitude, with adduction the worst performer among all tested movements. All motion types were described using linear equations. Correction methods are provided to correct potential out-of-plane shoulder movements.

CONCLUSIONS

Shoulder RoM estimated using a smartphone camera is consistent with 3D motion-capture-derived RoM; however, differences between the systems were observed and are likely explained by differences in thoracic frame definitions.

Hypertension Diagnosis and Management in Africa Using Mobile Phones: A Scoping Review

Target 3.4 of the third Sustainable Development Goal (SDG) of the United Nations (UN) General Assembly proposes to reduce premature mortality from non-communicable diseases (NCDs) by one-third. Epidemiological data presented by the World Health Organization (WHO) in 2016 show that out of a total of 57 million deaths worldwide, approximately 41 million deaths occurred due to NCDs, with 78% of such deaths occurring in low-and-middle-income countries (LMICs). The majority of investigations on NCDs agree that the leading risk factor for mortality worldwide is hypertension. Over 75% of the world's mobile phone subscriptions reside in LMICs, hence making the mobile phone particularly relevant to mHealth deployment in Africa. This study is aimed at determining the scope of the literature available on hypertension diagnosis and management in Africa, with particular emphasis on determining the feasibility, acceptability and effectiveness of interventions based on the use of mobile phones. The bulk of the evidence considered overwhelmingly shows that SMS technology is yet the most used medium for executing interventions in Africa. Consequently, the need to define novel and superior ways of providing effective and low-cost monitoring, diagnosis, and management of hypertension-related NCDs delivered through artificial intelligence and machine learning techniques is clear.

An augmentation aided concise CNN based architecture for COVID-19 diagnosis in real time

Over 6.5 million people around the world have lost their lives due to the highly contagious COVID 19 virus. The virus increases the danger of fatal health effects by damaging the lungs severely. The only method to reduce mortality and contain the spread of this disease is by promptly detecting it. Recently, deep learning has become one of the most prominent approaches to CAD, helping surgeons make more informed decisions. But deep learning models are computation hungry and devices with TPUs and GPUs are needed to run these models. The current focus of machine learning research is on developing models that can be deployed on mobile and edge devices. To this end, this research aims to develop a concise convolutional neural network-based computer-aided diagnostic system for detecting the COVID 19 virus in X-ray images, which may be deployed on devices with limited processing resources, such as mobile phones and tablets. The proposed architecture aspires to use the image enhancement in first phase and data augmentation in the second phase for image pre-processing, additionally hyperparameters are also optimized to obtain the optimal parameter settings in the third phase that provide the best results. The experimental analysis has provided empirical evidence of the impact of image enhancement, data augmentation, and hyperparameter tuning on the proposed convolutional neural network model, which increased accuracy from 94 to 98%. Results from the evaluation show that the suggested method gives an accuracy of 98%, which is better than popular transfer learning models like Xception, Resnet50, and Inception.

Mobile Phone Use and Risks of Overall and 25 Site-Specific Cancers: A Prospective Study from the UK Biobank Study

BACKGROUND

The association between mobile phone use and incident cancers remains uncertain. We aimed to investigate the relationships of mobile phone use with incident overall and 25 site-specific cancers in men and women.

METHODS

A total of 431,861 participants ages 38 to 73 years without prior cancers were included from the UK Biobank. Of these, 46.7% were male. Participants who used a mobile phone at least once per week to make or receive calls were defined as mobile phone users. The study outcomes were incident overall and 25 site-specific cancers.

RESULTS

During a median follow-up of 10.7 years, 35,401 (17.5%) men and 30,865 (13.4%) women developed overall cancer. Mobile phone use was significantly associated with higher risks of incident overall cancer [HR, 1.09; 95% confidence interval (CI): 1.06-1.12], nonmelanoma skin cancer (NMSC; HR, 1.08; 95% CI: 1.03-1.14), urinary tract cancer (HR, 1.18; 95% CI:1.05-1.32), and prostate cancer (HR, 1.19; 95% CI: 1.13-1.25) in men, and incident overall cancer (HR, 1.03; 95% CI: 1.00-1.06), NMSC (HR, 1.07; 95% CI: 1.01-1.13), and vulva cancer (HR, 1.74; 95% CI: 1.00-3.02) in women, but not with other cancers. Among mobile phone users, there was a dose-response relationship of length of mobile phone use with incident NMSC in men and women, and prostate cancer in men (all Ptrend < 0.05).

CONCLUSIONS

There was a dose-response relationship of length of mobile phone use with incident NMSC in men and women, and prostate cancer in men.

IMPACT

Our findings underscore the importance of limiting mobile phone use or keeping a distance from mobile phone for primary prevention of NMSC and prostate cancer.

Hybrid Cardiac Rehabilitation Program in a Low-Resource Setting: A Randomized Clinical Trial

Importance

While effective, cardiovascular rehabilitation (CR) as traditionally delivered is not well implemented in lower-resource settings.

Objective

To test the noninferiority of hybrid CR compared with traditional CR in terms of cardiovascular events.

Design, Setting, and Participants

This pragmatic, multicenter, parallel arm, open-label randomized clinical trial (the Hybrid Cardiac Rehabilitation Trial [HYCARET]) with blinded outcome assessment was conducted at 6 referral centers in Chile. Adults aged 18 years or older who had a cardiovascular event or procedure, no contraindications to exercise, and access to a mobile telephone were eligible and recruited between April 1, 2019, and March 15, 2020, with follow-up until July 29, 2021.

Interventions

Participants were randomized 1:1 in permuted blocks to the experimental arm, which received 10 center-based supervised exercise sessions plus counseling in 4 to 6 weeks and then were supported at home via telephone calls and text messages through weeks 8 to 12, or the control arm, which received the standard CR of 18 to 22 sessions with exercises and education in 8 to 12 weeks.

Main Outcomes and Measures

The primary outcome was cardiovascular events or mortality. Secondary outcomes were quality of life, return to work, and lifestyle behaviors measured with validated questionnaires; muscle strength and functional capacity, measured through physical tests; and program adherence and exercise-related adverse events, assessed using checklists.

Results

A total of 191 participants were included (mean [SD] age, 58.74 [9.80] years; 145 [75.92%] male); 93 were assigned to hybrid CR and 98 to standard CR. At 1 year, events had occurred in 5 unique participants in the hybrid CR group (5.38%) and 9 in the standard CR group (9.18%). In the intention-to-treat analysis, the hybrid CR group had 3.80% (95% CI, -11.13% to 3.52%) fewer cardiovascular events than the standard CR group, and relative risk was 0.59 (95% CI, 0.20-1.68) for the primary outcome. In the per-protocol analysis at different levels of adherence to the intervention, all 95% CIs crossed the noninferiority boundary (eg, 20% adherence: absolute risk difference, -0.35% [95% CI, -7.56% to 6.85%]; 80% adherence: absolute risk difference, 3.30% [95% CI, -3.70% to 10.31%]). No between-group differences were found for secondary outcomes except adherence to supervised CR sessions (79.14% [736 of 930 supervised sessions] in the hybrid CR group vs 61.46% [1201 of 1954 sessions] in the standard CR group).

Conclusions and Relevance

The results suggest that a hybrid CR program is noninferior to standard center-based CR in a low-resource setting, primarily in terms of recurrent cardiovascular events and potentially in terms of intermediate outcomes. Hybrid CR may induce superior adherence to supervised exercise. Clinical factors and patient preferences should inform CR model allocation.

Trial Registration

ClinicalTrials.gov Identifier: NCT03881150.

Development of a Non-Contact Sensor System for Converting 2D Images into 3D Body Data: A Deep Learning Approach to Monitor Obesity and Body Shape in Individuals in Their 20s and 30s

This study demonstrates how to generate a three-dimensional (3D) body model through a small number of images and derive body values similar to the actual values using generated 3D body data. In this study, a 3D body model that can be used for body type diagnosis was developed using two full-body pictures of the front and side taken with a mobile phone. For data training, 400 3D body datasets (male: 200, female: 200) provided by Size Korea were used, and four models, i.e., 3D recurrent reconstruction neural network, point cloud generative adversarial network, skinned multi-person linear model, and pixel-aligned impact function for high-resolution 3D human digitization, were used. The models proposed in this study were analyzed and compared. A total of 10 men and women were analyzed, and their corresponding 3D models were verified by comparing 3D body data derived from 2D image inputs with those obtained using a body scanner. The model was verified through the difference between 3D data derived from the 2D image and those derived using an actual body scanner. Unlike the 3D generation models that could not be used to derive the body values in this study, the proposed model was successfully used to derive various body values, indicating that this model can be implemented to identify various body types and monitor obesity in the future.

The impact of spatial connectivity on NPIs effectiveness

BACKGROUND

France implemented a combination of non-pharmaceutical interventions (NPIs) to manage the COVID-19 pandemic between September 2020 and June 2021. These included a lockdown in the fall 2020 - the second since the start of the pandemic - to counteract the second wave, followed by a long period of nighttime curfew, and by a third lockdown in the spring 2021 against the Alpha wave. Interventions have so far been evaluated in isolation, neglecting the spatial connectivity between regions through mobility that may impact NPI effectiveness.

METHODS

Focusing on September 2020-June 2021, we developed a regionally-based epidemic metapopulation model informed by observed mobility fluxes from daily mobile phone data and fitted the model to regional hospital admissions. The model integrated data on vaccination and variants spread. Scenarios were designed to assess the impact of the Alpha variant, characterized by increased transmissibility and risk of hospitalization, of the vaccination campaign and alternative policy decisions.

RESULTS

The spatial model better captured the heterogeneity observed in the regional dynamics, compared to models neglecting inter-regional mobility. The third lockdown was similarly effective to the second lockdown after discounting for immunity, Alpha, and seasonality (51% vs 52% median regional reduction in the reproductive number R0, respectively). The 6pm nighttime curfew with bars and restaurants closed, implemented in January 2021, substantially reduced COVID-19 transmission. It initially led to 49% median regional reduction of R0, decreasing to 43% reduction by March 2021. In absence of vaccination, implemented interventions would have been insufficient against the Alpha wave. Counterfactual scenarios proposing a sequence of lockdowns in a stop-and-go fashion would have reduced hospitalizations and restriction days for low enough thresholds triggering and lifting restrictions.

CONCLUSIONS

Spatial connectivity induced by mobility impacted the effectiveness of interventions especially in regions with higher mobility rates. Early evening curfew with gastronomy sector closed allowed authorities to delay the third wave. Stop-and-go lockdowns could have substantially lowered both healthcare and societal burdens if implemented early enough, compared to the observed application of lockdown-curfew-lockdown, but likely at the expense of several labor sectors. These findings contribute to characterize the effectiveness of implemented strategies and improve pandemic preparedness.

Fungal bioleaching of metals from WPCBs of mobile phones employing mixed Aspergillus spp.: Optimization and predictive modelling by RSM and AI models

In the present study, optimization and prediction models for fungal bioleaching for effective metal extraction from waste printed circuit boards (WPCBs) of mobile phones were developed employing central composite design (CCD) of response surface methodology (RSM), and two artificial intelligence (AI) models, i.e., artificial neural network (ANN) and, support vector machine (SVM), respectively. Two continuous process parameters, such as pH (4-9) and pulp density (1-10 g/L), and the bioleaching approaches, viz., one-step and two-step, were experimentally optimized for the extraction of targeted metals, i.e., Cu, Ni, and Zn from WPCBs by mixed cultures of Aspergillus niger and Aspergillus tubingensis. Datasets were then used for predictive modelling using AI tools. Results showed that the highest simultaneous bioleaching of Cu, Ni, and Zn, with an extraction efficacy of about 86%, 51%, and 100%, respectively, achieved at an optimal condition of pH 5.7 and pulp density of 3 g/L following the two-step bioleaching approach. Effective metal extraction in the two-step approach could be attributed to the abundant production of organic acids with a content of about 16.3 g/L, 8.4 g/L, and 0.5 g/L of citric acid, oxalic acid, and malic acid, respectively. Further, the predictive modelling revealed that the ANN model was found to predict the fungal bioleaching responses more accurately as compared to the SVM model with R2 values exceeding 0.96 for all targeted metals. This research demonstrates the applicability of the optimization and prediction models for efficient metal extraction from WPCBs using mixed Aspergillus spp. following the two-step approach.

Exploring the use of mobile phones by children with intellectual disabilities: experiences from Haryana, India

PURPOSE

Covid-induced lockdowns have increased the importance of technology in education. Though access to technology as well as availability of the internet remain a major concern for a lot of children in the global south, children with intellectual disabilities are disadvantaged even more as most of the e-content is developed keeping in mind the average learner.

MATERIALS AND METHODS

Unstructured interviews were conducted with children with intellectual disabilities studying in government schools in Haryana as well as their teachers and parents. Thematic analysis of the interviews was conducted to understand the use-patterns of mobile phones by children with intellectual disabilities.

RESULTS

Findings suggest that these children are learning to use mobile phones on their own or with some support and are able to navigate the complexities of these smartphones quite well. They use these devices mostly for their entertainment. This paper then reflects on the need and strategies to develop these technologies in ways that they can be used as effective tools for teaching children with intellectual disabilities, especially in the inclusive education system in developing countries.

CONCLUSION

The paper reflects on the need to develop technology and tools using flexible and exploratory designs to enhance the learning processes for children with intellectual disabilities from the lower income strata.IMPLICATIONS FOR REHABILITATIONThis study highlights the importance of being able to use mobile phones by children with intellectual disabilities belonging to low income families.Following this, the article argues for designing of mobile phones suitable for use by children with intellectual disabilities using playfulness and explorations, andBuilding e-content keeping the elements of playfulness and exploration which can enhance the learnings of this group of students which is often ignored.

A novel mobile phone and tablet application for automatized calculation of pain extent

BACKGROUND

Pain drawings (PDs) are used for assessing pain extent as a complementary outcome to other pain measurements, consisting of shading a body chart template to report the location and extent of pain. However, the accuracy and reliability of digital PDs remain controversial due to the heterogeneity of methods used. This study aimed to develop an easy-to-use application for assessing its diagnostic accuracy in comparison with the classic paper-and-pencil method.

METHODS

A test-retest reliability study was conducted, recruiting 95 patients with musculoskeletal pain symptoms. Participants shaded 2 sets of 3 different PDs (paper-and-pencil PD, digital PD using the finger and digital PD using the digital stylus). Intraclass correlation coefficients (ICC), standard error of measurement and minimal detectable changes (MDC) were calculated for each method. Finally, repeated measure analysis of variance assessed the mean differences between trials and methods and the convergent validity between methods was calculated using Pearson's correlation coefficients.

RESULTS

All methods were excellently reliable (all, ICC>0.94). However, digital PDs obtained higher ICCs (ICC≥0.970) and greater accuracy to detect whether changes reflect a real change and are not due to a measurement errors (MDC = 0.72%-0.80 % for digital PDs versus MDC = 1.13 % for paper-and-Pencil PDs). No significant score differences were found among the instruments for assessing pain extent (p > 0.05). Finally, the PAIN EXTENT app showed adequate convergent validity (r > 0.850).

CONCLUSION

The PAIN EXTENT app is a fast and easy-to-use instrument compatible with operative systems and devices commonly used for assessing and monitoring pain extent in the clinical and research settings.

The Use of mHealth in Promoting Therapeutic Adherence: A Scoping Review

Nonadherence to therapy negatively impacts mortality and quality of life and results in suboptimal efficacy of treatment regimens, threats to patient safety, and increased healthcare costs for disease management. Mobile health solutions can offer users instruments that can promote therapeutic adherence. The objective of this review is to investigate the impact mobile health systems have on therapeutic adherence. Specifically, we want to map the main systems used, the functions implemented, and the different methods of adherence detection used. For this purpose, a scoping review was conducted. The following databases were consulted: PubMed, Cochrane Library, EBSCO (including APA PsycINFO, CINAHL Plus with Full Text, ERIC), including English-language studies published in the last 10 years (2012-2022). The main mobile health systems used are as follows: applications, automated messaging, interactive voice response, and mobile video games. The main features implemented to support medication management were as follows: reminders, self-monitoring instruments, educational support, and caregiver involvement. In conclusion, the use of interactive mobile health instruments intended for use by the patient and/or caregiver can improve objectively and subjectively detected therapeutic adherence. The use of these systems in the therapeutic pathway of users, with a special focus on people with comorbidities and in polypharmacy treatment, represents a challenge to improve caregiver health.

The effect of using mobile phone applications for intelligent pelvic floor rehabilitation on elderly female patients with stress urinary incontinence

BACKGROUND

Stress urinary incontinence is prevalent among women and the incidence increases with age.

OBJECTIVE

To explore the effect of intelligent pelvic floor muscle rehabilitation on elderly female patients with incontinence.

METHODS

A total of 209 patients with urinary incontinence who were treated with pelvic floor muscle rehabilitation at Peking University International Hospital from September 2020 to January 2022 were selected by convenient sampling. All subjects were divided into the 50-60 year old patient group (n= 51) and over 60 years old patient group according to age (n= 158). The subjects of different age group were divided into an experimental group and a control group. The patients in the control group received routine nursing and health education, and the patients in the observation group received a combination of mobile application use and smart dumbbells. Based on this, we constructed an intervention model for intelligent, continuous pelvic floor rehabilitation. After 7 and 12 weeks, pelvic floor muscle function knowledge and exercise compliance in the two groups were evaluated. The improvement of urinary incontinence symptoms, pelvic floor muscle strength grades and quality-of-life scales were evaluated.

RESULTS

The results showed that pelvic floor knowledge and exercise compliance in the experimental group were better than in the control group at 7 and 12 weeks after intervention (P< 0.05). There was no significant difference in pelvic floor muscle strength and quality of life between the two groups at 7 weeks after intervention (P> 0.05). However, there was a significant difference in pelvic floor muscle strength and quality of life between the two groups at 12 weeks after intervention (P< 0.05). There was no significant difference between different age groups.

CONCLUSION

The intelligent pelvic floor rehabilitation model that combines a mobile application with smart dumbbells can maintain and strengthen the clinical treatment effect for elderly patients with urinary incontinence.

The effects of radiofrequency electromagnetic fields exposure on tinnitus, migraine and non-specific symptoms in the general and working population: A systematic review and meta-analysis on human observational studies

BACKGROUND

Applications emitting radiofrequency electromagnetic fields (RF-EMF; 100 kHz to 300 GHz) are widely used for communication (e.g. mobile phones), in medicine (diathermy) and in industry (RF heaters).

OBJECTIVES

The objective is to systematically review the effects of longer-term or repeated local and whole human body radiofrequency electromagnetic field (RF-EMF) exposure on the occurrence of symptoms. Primary hypotheses were tinnitus, migraine and headaches in relation to RF-EMF exposure of the brain, sleep disturbances and composite symptom scores in relation to whole-body RF-EMF exposure.

METHODS

Eligibility criteria: We included case-control and prospective cohort studies in the general population or workers estimating local or whole-body RF-EMF exposure for at least one week.

INFORMATION SOURCES

We conducted a systematic literature search in various databases including Web of Science and Medline. Risk of bias: We used the Risk of Bias (RoB) tool developed by OHAT adapted to the topic of this review.

SYNTHESIS OF RESULTS

We synthesized studies using random effects meta-analysis.

RESULTS

Included studies: We included 13 papers from eight distinct cohort and one case-control studies with a total of 486,558 participants conducted exclusively in Europe. Tinnitus is addressed in three papers, migraine in one, headaches in six, sleep disturbances in five, and composite symptom scores in five papers. Only one study addressed occupational exposure.

SYNTHESIS OF RESULTS

For all five priority hypotheses, available research suggests that RF-EMF exposure below guideline values does not cause symptoms, but the evidence is very uncertain. The very low certainty evidence is due the low number of studies, possible risk of bias in some studies, inconsistencies, indirectness, and imprecision. In terms of non-priority hypotheses numerous exposure-outcome combinations were addressed in the 13 eligible papers without indication for an association related to a specific symptom or exposure source.

DISCUSSION

Limitations of evidence: This review topic includes various challenges related to confounding control and exposure assessment. Many of these aspects are inherently present and not easy to be solved in future research. Since near-field exposure from wireless communication devices is related to lifestyle, a particular challenge is to differentiate between potential biophysical effects and other potential effects from extensive use of wireless communication devices that may compete with healthy behaviour such as sleeping or physical activity. Future research needs novel and innovative methods to differentiate between these two hypothetical mechanisms.

INTERPRETATION

This is currently the best available evidence to underpin safety of RF-EMF. There is no indication that RF-EMF below guideline values causes symptoms. However, inherent limitations of the research results in substantial uncertainty.

OTHER

Funding: This review was partially funded by the WHO radioprotection programme.

REGISTRATION

The protocol for this review has been registered in Prospero (reg no CRD42021239432) and published in Environment International (Röösli et al., 2021).

The effects of distraction on younger drivers: A neurophysiological perspective

Distracted driving remains a significant cause of traffic accidents globally, including in Australia. However, many younger drivers still admit to using a phone while driving. A simulated driving study investigated the neurophysiological effects of visual, auditory, and higher-order cognitive (i.e., requiring the use of executive functions) distraction on young drivers. In total, 24 young adults aged 18-25 years completed four 8 min simulated driving sessions while concurrently engaging in various distractor tasks. Neurophysiological arousal was measured via EEG. Additionally, subjective workload and objective driving performance were assessed. Frontal beta and gamma power exhibited their highest levels during tasks involving higher-order cognitive and visual demands. The higher-order cognitive condition was rated as the most mentally demanding. In comparison, the visual condition had the most significant impact on both the standard deviation of speed and standard deviation of lateral positioning. This study has significant implications for all road users, particularly those aged 18-25 years, and it reinforces the importance of not using a phone while driving.

Can phone surveys be representative in low- and middle-income countries? An application to Myanmar

For decades, in-person data collection has been the standard modality for nationally and sub-nationally representative socio-economic survey data in low- and middle-income countries. As the COVID-19 pandemic rendered in-person surveys impossible and unethical, the urgent need for rapid monitoring necessitated researchers and statistical agencies to turn to phone surveys. However, apart from pandemic-related factors, a variety of other reasons can render large segments of a population inaccessible for in-person surveys, including political instability, climatic shocks, and remoteness. Such circumstances currently prevail in Myanmar, a country facing civil conflict and political instability since the February 2021 military takeover. Moreover, Myanmar routinely experiences extreme weather events and is characterized by numerous inaccessible and remote regions due to its mountainous geography. We describe a novel approach to sample design and statistical weighting that has been successfully applied in Myanmar to obtain nationally and sub-nationally representative phone survey data. We use quota sampling and entropy weighting to obtain a better geographical distribution compared to recent in-person survey efforts, including reaching respondents in areas of active conflict. Moreover, we minimize biases towards certain household and respondent characteristics that are usually present in phone surveys, for example towards well-educated or wealthy households, or towards men or household heads as respondents. Finally, due to the rapidly changing political and economic situation in Myanmar in 2022, the need for frequent and swift monitoring was critical. We carried out our phone survey over four quarters in 2022, interviewing more than 12,000 respondents in less than three months each survey. A survey of this scale and pace, though generally of much shorter duration than in-person interviews, could only be possible on the phone. Our study proves the feasibility of collecting nationally and sub nationally representative phone survey data using a non-representative sample frame, which is critical for rapid monitoring in any volatile economy.

A meta-analysis of the risk of salivary gland tumors associated with mobile phone use: the importance of correct exposure assessment

OBJECTIVES

To investigate the risk of developing salivary gland tumors associated with the use of mobile phones.

CONTENT

There have been a number of epidemiological studies conducted to assess for a possible association between mobile phone usage and the development of intracranial tumours, however results have been conflicting. We conducted an extensive literature search across four different databases was conducted. After selecting the articles relevant to the area of study, a total of seven studies were included in this meta-analysis, with no restrictions set on publication date or language. Studies were qualitatively assessed using the Newcastle-Ottawa scale. No significant association between the use of mobile phones and salivary gland tumors was observed (OR=1.06, 95% CI=0.86-1.32). No evidence for publication bias was detected.

SUMMARY AND OUTLOOK

Our findings indicate no significant association between mobile phone usage and salivary gland tumours. However, there were many limitations encountered in these studies, suggesting that the observed result may not be an accurate estimate of the true carcinogenic risk of mobile phones, especially for heavy long-term users. In fact, the studies included in this meta-analysis highlight the need to correctly define exposure assessment in order to ascertain the risk of a certain variable.

Expanding the UTAUT2 framework to determine the drivers of mobile shopping behaviour among older adults

In the current severe aging of the population, the problem of "digital divide" of the elderly has become increasingly prominent, and the elderly market represents a vast demographic that is increasingly becoming an important customer segment for mobile shopping in the future. However, there is currently insufficient attention given to the research on mobile shopping behavior among older adults. This study tries to answer what are the driving factors of mobile phone shopping behavior among the elderly? The purpose of this study is to analyze the factors that drive the elderly's mobile phone shopping behavior, and to establish a mobile phone shopping acceptance model for the elderly to predict the factors of the elderly's behavioral intention of using smart phones. Based on the second edition of Unified Theory of Acceptance and Use of Technology theory (UTAUT 2), this study proposed a mobile phone shopping acceptance model for the elderly. The study collected valid data from 389 Chinese elderly people through questionnaires and analyzed them using structural equation models. The results showed that utilitarian, anxiety, trust, performance expectancy, effort expectancy, social influence, facilitating conditions and habit directly impact the older adults' intention to engage in mobile shopping. Additionally, facilitating conditions, habit and the older adults' intention to engage in mobile shopping act as driving factors for actual use behavior. This study further expands the UTAUT theoretical model, provides a theoretical basis for the research of mobile shopping behavior of the elderly, and enricues the application groups and fields of the UTAUT theoretical model. The results of this study provide inspiration for the development, design and marketing of age-appropriate mobile shopping products, and contribute to the realization and further adoption of age-appropriate mobile shopping, and also contribute to promoting the active aging of the elderly.

Perceptions of HIV patients on the use of cell phones as a tool to improve their antiretroviral adherence in Northwest, Ethiopia: a cross-sectional study

BACKGROUND

Human immuno deficiency virus (HIV) is one of the most infectious diseases that cause death. A Medication non-adherence in HIV patient has been caused by factors such as not taking medications as prescribed by a physician, withdrawing from medication, missing appointments, and forgetfulness. To improve patients' antiretroviral adherence, supporting them with mobile phone applications is advisable. This study aimed to assess HIV patients' perceptions towards the use of cell phones to improve antiretroviral adherence.

METHODS AND MATERIALS

An institutional-based cross-sectional study was conducted among 423 HIV patients at a comprehensive specialized hospital in northwest Ethiopia from June to July 2022. Study participants were selected using systematic random sampling techniques and the data collection tool was adopted and modified for different literatures. Data were collected through an online data collection tool, and STATA-14 software was used for analysis. Descriptive statistics and binary logistic regression were used. The variables with a P-value equal to or less than 0.2 in bivariable logistic regression were entered into a multivariable logistic regression, and model fitness was assessed.

RESULTS

A total of 410 study subjects have participated, making a response rate of 97%. In this study, 62% (95% CI: 57-67%) of HIV patients had a positive perception regarding the use of mobile phones to improve antiretroviral adherence. Perceived usefulness of mobile phones [AOR = 4.5, (95% CI: 2.2-9.1)], perceived ease of mobile phone use [AOR = 3.9, (95% CI: 2.0-7.5), age [AOR = 3.0, (95% CI: 1.5-6.2)], and educational status [AOR = 5.0, (95% CI: 2.3-10.0)] were significantly associated with HIV patients' perception of mobile phones' use to improve antiretroviral adherence.

CONCLUSIONS

More than half of the respondents had positive perception regarding the use of mobile phones to enhance their adherence to treatment. Perceived usefulness, perceived ease of use, age, and educational status was significantly associated with perception of mobile phone use to enhance antiretroviral therapy adherence. Therefore, the government have to encourage and support patients in incorporating mobile phones into their antiretroviral therapy (ART) follow-up through training.