Patients and Stakeholders' Perspectives Regarding the Privacy, Security, and Confidentiality of Data Collected via Mobile Health Apps in Saudi Arabia: Protocol for a Mixed Method Study

BACKGROUND

There is data paucity regarding users' awareness of privacy concerns and the resulting impact on the acceptance of mobile health (mHealth) apps, especially in the Saudi context. Such information is pertinent in addressing users' needs in the Kingdom of Saudi Arabia (KSA).

OBJECTIVE

This article presents a study protocol for a mixed method study to assess the perspectives of patients and stakeholders regarding the privacy, security, and confidentiality of data collected via mHealth apps in the KSA and the factors affecting the adoption of mHealth apps.

METHODS

A mixed method study design will be used. In the quantitative phase, patients and end users of mHealth apps will be randomly recruited from various provinces in Saudi Arabia with a high population of mHealth users. The research instrument will be developed based on the emerging themes and findings from the interview conducted among stakeholders, app developers, health care professionals, and users of mHealth apps (n=25). The survey will focus on (1) how to improve patients' awareness of data security, privacy, and confidentiality; (2) feedback on the current mHealth apps in terms of data security, privacy, and confidentiality; and (3) the features that might improve data security, privacy, and confidentiality of mHealth apps. Meanwhile, specific sections of the questionnaire will focus on patients' awareness, privacy concerns, confidentiality concerns, security concerns, perceived usefulness, perceived ease of use, and behavioral intention. Qualitative data will be analyzed thematically using NVivo version 12. Descriptive statistics, regression analysis, and structural equation modeling will be performed using SPSS and partial least squares structural equation modeling.

RESULTS

The ethical approval for this research has been obtained from the Biomedical and Scientific Research Ethics Committee, University of Warwick, and the Medical Research and Ethics Committee Ministry of Health in the KSA. The qualitative phase is ongoing and 15 participants have been interviewed. The interviews for the remaining 10 participants will be completed by November 25, 2023. Preliminary thematic analysis is still ongoing. Meanwhile, the quantitative phase will commence by December 10, 2023, with 150 participants providing signed and informed consent to participate in the study.

CONCLUSIONS

The mixed methods study will elucidate the antecedents of patients' awareness and concerns regarding the privacy, security, and confidentiality of data collected via mHealth apps in the KSA. Furthermore, pertinent findings on the perspectives of stakeholders and health care professionals toward the aforementioned issues will be gleaned. The results will assist policy makers in developing strategies to improve Saudi users'/patients' adoption of mHealth apps and addressing the concerns raised to benefit significantly from these advanced health care modalities.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/54933.

GCT-03. MonoGerm: A proposed phase II trial of carboplatin or vinblastine monotherapy induction prior to radiotherapy for intracranial germinoma

BACKGROUND: Intracranial germinoma is chemosensitive but radiotherapy (RT) is needed for cure. In localised disease, three-drug standard-of-care (SOC) inpatient chemotherapy is used to reduce RT fields/dose. Concomitant diabetes insipidus is common, making chemotherapy delivery challenging. Small studies have demonstrated benefits from single-agent carboplatin or vinblastine in germinoma as an alternative to SOC. However, this needs prospective evaluation in a clinical trial. METHODS: We developed a trial, with a patient-public-involvement workstream, primarily evaluating whether single-agent chemotherapy (carboplatin or vinblastine) is non-inferior to SOC for inducing radiological complete response (CR) in localised disease, and is associated with reduced toxicity and improved quality-of-life (QoL), evaluated through patient-reported-outcome-measures (PROMs). RESULTS: The resultant proposed multi-centre, phase II proof-of-principle trial will investigate, in parallel, two single agents as monotherapy induction, in children/teenagers/adults with intracranial germinoma. Trial features include: a) Bayesian statistical design determining whether CR rate for either agent is sufficiently non-inferior to SOC; b) ‘Flip-flop’ design with alternating, continuous enrolment to the two single-agents, interim assessments after each recruited cohort, and early stopping rules for inferiority; c) Safety MRI, after 6-weeks of chemotherapy with real-time central-radiological-review; d) Proof-of-principle vinblastine monotherapy arm for metastatic patients awaiting definitive craniospinal-irradiation; e) State-of-the-art integrated imaging acquisition, QoL/PROM, pharmacokinetics and circulating microRNA studies to maximise information/learning; f) European and North American neuroradiological response criteria comparison and prospective evaluation of new consensus criteria. CONCLUSIONS: Trial results will: a) establish whether monotherapy is a treatment option in this setting, which may be practice-altering; b) use QoL/PROM data to inform on optimal treatment if results similar; c) use embedded radiological assessments to develop intracranial germinoma trials and facilitate European/US study comparisons; d) describe vinblastine pharmacokinetic data to inform future dosing schedules in this and other malignancies; and e) quantify circulating microRNAs, facilitating future non-invasive diagnosis/risk-stratification.

IMG-11. A COMPUTERISED CLINICAL DECISION SUPPORT SYSTEM FOR DIAGNOSING CHILDREN’S BRAIN TUMOURS USING FUNCTIONAL IMAGING AND MACHINE LEARNING

INTRODUCTION: Magnetic resonance imaging is a key investigation in the diagnosis of childhood solid tumours. Advanced techniques such as diffusion weighted imaging (DWI), magnetic resonance spectroscopy (MRS) and perfusion imaging probe the underlying cellular, chemical and vascular nature of the disease. Coupled with machine learning these scanning methods show improvement in diagnostic accuracy compared with conventional imaging. Advanced image analysis is not routinely available in hospitals. We present a clinical decision support system (CDSS) developed for advanced MR analysis and interpretation. METHOD: The CDSS was developed in house. The Children’s Cancer and Leukaemia Group Functional Imaging Group (CCLGFIG) Database, a national resource, was used to provide a repository of cases together with their advanced imaging and machine learning diagnostic classifiers. A new case is displayed alongside cases in the repository with known diagnoses, including summary statistics for relevant diagnostic categories. The CDSS was made available to radiologists, in their clinical environment for technical and clinical evaluation. Structured interviews were undertaken. The CDSS was developed as a computer app for multi-centre distribution. RESULTS: 436 MRS, 240 DWI and 85 perfusion cases were available for building repositories. Machine learning classifiers showed diagnostic accuracies for the major childhood brain tumour types of 85-95%. Comparison of MRS with a data repository was found to improve non-invasive diagnosis. Results from the CDSS can be uploaded to the CCLGFIG to support multicentre research. Positive feedback on the CDSS from clinicians included: ready access to advanced analysis; simple and efficient integration into clinical workflow; and assisted interpretation of advanced analysis. DISCUSSION: Advanced MR analysis techniques provide improved non-invasive diagnostic accuracy but are difficult to implement on clinical systems due to technical, infrastructure and training limitations. CONCLUSION: We have successfully released a CDSS for paediatric cancer within the hospital environment and assessed its suitability for clinical use.

The role of diffusion tensor imaging metrics in machine learning-based characterisation of paediatric brain tumors and their practicality for multicentre clinical assessment

Aims

Magnetic resonance imaging (MRI) is a valuable tool for non-invasive diagnosis of paediatric brain tumours. The rarity of the disease dictates multi-centre studies and imaging biomarkers that are robust to protocol variability. We investigated diffusion tensor MRI (DT-MRI), combined with machine learning, as an aid to diagnosis and evaluated the robustness of the imaging metrics.

Method

A multi-centre cohort of 52 clinical DT-MRI scans (20 medulloblastomas (MB), 21 pilocytic astrocytomas (PA), 11 ependymomas (EP)) were analysed retrospectively. Histograms for regions of solid tumour for fractional anisotropy (FA), mean diffusivity (MD), pure anisotropic diffusion (q) and pure isotropic diffusion (p) were compared to assess diagnostic capability. Linear discriminate analysis (LDA) was used for classification and validated using leave-one-out-cross-validation (LOOCV).

Results

Histogram medians for FA, MD, q and p were all different between tumor groups (P<.0001, Kruskal Wallis test). Median MD, p and q values were highest in PA, then EP and lowest in MB (P<.0001, Pairwise Wilcox test). FA median was higher for EP than PA (P=.004) with no significant difference between EP and MB (P=.591). ROC analysis showed that median MD, q and p perform best as a diagnostic marker (AUC= 0.92 to 0.99). LOOCV showed an overall accuracy of the LDA classification, ranging between 67% - 87%. FA values were highly dependent on protocol parameters, whereas pure anisotropic diffusion, q, was not.

Conclusion

DT-MRI metrics from multi-centre acquisitions can classify paediatric brain tumours. FA is the least robust metric to protocol variability and q provides the most robust quantification of anisotropic behaviour.

Classification of paediatric brain tumours by diffusion weighted imaging and machine learning

To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10⁻³ mm² s⁻¹ with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.

Multicentre study of perfusion magnetic resonance imaging in paediatric brain tumours

Studies in adults have shown that brain tumour perfusion correlates with grade. These studies are dominated by gliomas grade II to IV which are rare in children. The standard method, Dynamic Susceptibility Contrast MRI, provides estimates of relative cerebral blood volume (rCBV) but contrast agent leakage affects rCBV accuracy. The majority of perfusion studies have been conducted at single centres and variation in acquisition protocols makes the generalizability of results questionable. The aim of this study was to compare leakage-corrected rCBV with grade in paediatric brain tumours at multiple centres. Scans were analysed from 85 patients at 4 centres on 6 scanners prior to treatment. MRI protocols varied between centres. Histological diagnoses including grade were obtained. Whole-tumour median rCBV was significantly higher in the 45 high grade than the 40 low grade tumours (2.54 ± 1.63 ml/100ml vs 1.68 ± 1.36 ml/100ml, p=0.010). Low grade tumours, particularly pilocytic astrocytomas (grade I), displayed more contrast agent leakage consistent with their appearance on contrast enhanced images and required more leakage correction than high grade tumours. This finding differs from that in adults where contrast agent uptake is usually associated with higher grade. A cut-off of 1.70 ml/100ml for rCBV gave sensitivity and specificity of 76% and 65% respectively for discriminating grade. In summary, perfusion MRI can be used to help distinguish between low and high grade paediatric brain tumours. This finding is robust across multiple centres and acquisition protocols but correction should be made for leakage of contrast agent from the vessels.

Structural neuroimaging in psychosis: a systematic review and economic evaluation

OBJECTIVES

To establish the clinical effectiveness and cost-effectiveness of structural neuroimaging [structural magnetic resonance imaging (MRI) or computed tomography (CT) scanning] for all patients with psychosis, particularly a first episode of psychosis, relative to the current UK practice of selective screening only where it is clinically indicated.

DATA SOURCES

Major electronic databases were searched from inception to November 2006.

REVIEW METHODS

A systematic review of studies reporting the additional diagnostic benefit of structural MRI, CT or combinations of these in patients with psychosis was conducted. The economic assessment consisted of a systematic review of economic evaluations and the development of a threshold analysis to predict the gain in quality-adjusted life-years (QALYs) required to make neuroimaging cost-effective at commonly accepted threshold levels (20,000 pounds and 30,000 pounds per QALY). Sensitivity analyses of several parameters including prevalence of psychosis were performed.

RESULTS

The systematic review included 24 studies of a diagnostic before-after type of design evaluating the clinical benefit of CT, structural MRI or combinations in treatment-naive, first-episode or unspecified psychotic patients, including one in schizophrenia patients resistant to treatment. Also included was a review of published case reports of misidentification syndromes. Almost all evidence was in patients aged less than 65 years. In most studies, structural neuroimaging identified very little that would influence patient management that was not suspected based on a medical history and/or physical examination and there were more incidental findings. In the four MRI studies, approximately 5% of patients had findings that would influence clinical management, whereas in the CT studies, approximately 0.5% of patients had these findings. The review of misidentification syndromes found that 25% of CT scans affected clinical management, but this may have been a selected and therefore unrepresentative sample. A threshold analysis with a 1-year time horizon was undertaken. This combined the incremental cost of routine scanning with a threshold cost per QALY value of 20,000 pounds and 30,000 pounds to predict the QoL gain required to meet these threshold values. Routine scanning versus selective scanning appears to produce different results for MRI and CT. With MRI scanning the incremental cost is positive, ranging from 37 pounds to 150 pounds; however, when scanning routinely using CT, the result is cost saving, ranging from 7 pounds to 108 pounds with the assumption of a 1% prevalence rate of tumours/cysts or other organic causes amenable to treatment. This means that for the intervention to be viewed as cost-effective, the QALY gain necessary for MRI scanning is 0.002-0.007 and with CT scanning the QALY loss that can be tolerated is between 0.0003 and 0.0054 using a 20,000 pounds threshold value. These estimates were subjected to sensitivity analysis. With a 3-month time delay, MRI remains cost-incurring with a small gain in QoL required for the intervention to be cost-effective; routine scanning with CT remains cost-saving. When the sensitivity of CT is varied to 50%, routine scanning is both cost-incurring or cost-saving depending on the scenario. Finally, the results have been shown to be sensitive to the assumed prevalence rate of brain tumours in a psychotic population.

CONCLUSIONS

The evidence to date suggests that if screening with structural neuroimaging was implemented in all patients presenting with psychotic symptoms, little would be found to affect clinical management in addition to that suspected by a full clinical history and neurological examination. From an economic perspective, the outcome is not clear. The strategy of neuroimaging for all is either cost-incurring or cost-saving (dependent upon whether MRI or CT is used) if the prevalence of organic causes is around 1%. However, these values are nested within a number of assumptions, and so have to be interpreted with caution. The main research priorities are to monitor the current use of structural neuroimaging in psychosis in the NHS to identify clinical triggers to its current use and subsequent outcomes; to undertake well-conducted diagnostic before-and-after studies on representative populations to determine the clinical utility of structural neuroimaging in this patient group, and to determine whether the most appropriate structural imaging modality in psychosis should be CT or MRI.

Improving collaboration between Primary Care Research Networks using Access Grid technology

Access Grid (AG) is an Internet2-driven, high performance audio-visual conferencing technology used worldwide by academic and government organisations to enhance communication, human interaction and group collaboration. AG technology is particularly promising for improving academic multi-centre research collaborations. This manuscript describes how the AG technology was utilised by the electronic Primary Care Research Network (ePCRN) that is part of the National Institutes of Health (NIH) Roadmap initiative to improve primary care research and collaboration among practice-based research networks (PBRNs) in the USA. It discusses the design, installation and use of AG implementations, potential future applications, barriers to adoption, and suggested solutions.