Technology use in mental health practice and research: Legal and ethical risks

Mental health professionals are tasked with upholding guidelines, principles, and standards set forth by professional organizations and local jurisdictions. Simultaneously, providers are increasingly expected to utilize technology with research participants and patients in psychotherapy and to communicate with other professionals. Digital methods such as text messaging, data storage, record keeping, and videoconferencing have all moved the boundaries of professional work beyond physical office spaces. This synergy between mental healthcare delivery and technology use has empowered providers to think beyond traditional models of care and reach populations who otherwise might not be able to receive services. However, the development and understanding of ethical and legal concern have been hampered by few training opportunities and the absence of competency standards. This article provides specific areas of risk, example scenarios where technology is used, and recommendations for providers to consider.     

Implementation of e-mental health for depression and anxiety: A critical scoping review

The aim of this review was to scope the growth and development of implementation research of e-mental healthcare programs for anxiety and depression, the research and evaluation tools used, and the specific implementation processes and outcomes examined. A search of four electronic databases (MEDLINE, EMBASE, PsycINFO, and CINAHL) was conducted from January 2000 to January 2019. Of 33 studies identified, most (n = 28) were published in the last five years. Only 10 used an implementation framework to guide implementation or evaluation. Most studies reported on acceptability (n = 28), appropriateness (n = 23), and feasibility (n = 17). Less commonly reported implementation outcomes were fidelity (n = 10) and adoption (n = 7); with penetration (n = 4), sustainability (n = 3), and implementation cost (n = 2) being studied rarely. Of the 21 studies that used surveys to study implementation outcomes, less than half used a previously published survey (n = 9). More rigorous implementation studies, underpinned by strong theory and real-world understanding, are urgently needed.     

Multimodal e-mental health treatment for depression: a feasibility trial

Background

Internet interventions for depression have shown less than optimal adherence. This study describes the feasibility trial of a multimodal e-mental health intervention designed to enhance adherence and outcomes for depression. The intervention required frequent brief log-ins for self-monitoring and feedback as well as email and brief telephone support guided by a theory-driven manualized protocol.

Objective

The objective of this feasibility trial was to examine if our Internet intervention plus manualized telephone support program would result in increased adherence rates and improvement in depression outcomes.

Methods

This was a single arm feasibility trial of a 7-week intervention.

Results

Of the 21 patients enrolled, 2 (9.5%) dropped out of treatment. Patients logged in 23.2 ± 12.2 times over the 7 weeks. Significant reductions in depression were found on all measures, including the Patient Health Questionnaire depression scale (PHQ-8) (Cohen’s d = 1.96, P < .001), the Hamilton Rating Scale for Depression (d = 1.34, P < .001), and diagnosis of major depressive episode (P < .001).

Conclusions

The attrition rate was far lower than seen either in Internet studies or trials of face-to-face interventions, and depression outcomes were substantial. These findings support the feasibility of providing a multimodal e-mental health treatment to patients with depression. Although it is premature to make any firm conclusions based on these data, they do support the initiation of a randomized controlled trial examining the independent and joint effects of Internet and telephone administered treatments for depression.     

Security Middleware Infrastructure for DICOM Images in Health Information Systems

In health care, it is mandatory to maintain the privacy and confidentiality of medical data. To achieve this, a fine-grained access control and an access log for accessing medical images are two important aspects that need to be considered in health care systems. Fine-grained access control provides access to medical data only to authorized persons based on priority, location, and content. A log captures each attempt to access medical data. This article describes an overall middleware infrastructure required for secure access to Digital Imaging and Communication in Medicine (DICOM) images, with an emphasis on access control and log maintenance. We introduce a hybrid access control model that combines the properties of two existing models. A trust relationship between hospitals is used to make the hybrid access control model scalable across hospitals. We also discuss events that have to be logged and where the log has to be maintained. A prototype of security middleware infrastructure is implemented.     

An evaluation of personal health information remnants in second-hand personal computer disk drives

Background

The public is concerned about the privacy of their health information, especially as more of it is collected, stored, and exchanged electronically. But we do not know the extent of leakage of personal health information (PHI) from data custodians. One form of data leakage is through computer equipment that is sold, donated, lost, or stolen from health care facilities or individuals who work at these facilities. Previous studies have shown that it is possible to get sensitive personal information (PI) from second-hand disk drives. However, there have been no studies investigating the leakage of PHI in this way.

Objectives

The aim of the study was to determine the extent to which PHI can be obtained from second-hand computer disk drives.

Methods

A list of Canadian vendors selling second-hand computer equipment was constructed, and we systematically went through the shuffled list and attempted to purchase used disk drives from the vendors. Sixty functional disk drives were purchased and analyzed for data remnants containing PHI using computer forensic tools.

Results

It was possible to recover PI from 65% (95% CI: 52%-76%) of the drives. In total, 10% (95% CI: 5%-20%) had PHI on people other than the owner(s) of the drive, and 8% (95% CI: 7%-24%) had PHI on the owner(s) of the drive. Some of the PHI included very sensitive mental health information on a large number of people.

Conclusions

There is a strong need for health care data custodians to either encrypt all computers that can hold PHI on their clients or patients, including those used by employees and subcontractors in their homes, or to ensure that their computers are destroyed rather than finding a second life in the used computer market.     

Pseudonymization of Radiology Data for Research Purposes

Medical image processing methods and algorithms, developed by researchers, need to be validated and tested. Test data would ideally be real clinical data especially that clinical data is varied and exists in large volumes. Nowadays, clinical data is accessible electronically and has important value for researchers. However, the usage of clinical data for research purposes should respect data confidentiality, patient right to privacy, and patient consent. In fact, clinical data is nominative given that it contains information about the patient such as name, age, and identification number. Evidently, clinical data needs to be de-identified to be exported to research databases. However, the same patient is usually followed during a long period of time. The disease progression and the diagnostic evolution represent extremely valuable information for researchers as well. Our objective is to build a research database from de-identified clinical data while enabling the data set to be easily incremented by exporting new pseudonymous data, acquired over a long period of time. Pseudonymization is data de-identification, such that data belonging to an individual in the clinical environment still belong to the same individual in the de-identified research version. In this paper, we explore various software architectures to enable the implementation of an imaging research database that can be incremented in time. We also evaluate their security and discuss their security pitfalls. As most imaging data accessible electronically is available with the digital imaging and communication in medicine (DICOM) standard, we propose a de-identification scheme that closely follows DICOM recommendations. Our work can be used to enable electronic health record (EHR) secondary usage such as public surveillance and research, while maintaining patient confidentiality.     

Using evidence-based internet interventions to reduce health disparities worldwide

Health disparities are a persistent problem worldwide. A major obstacle to reducing health disparities is reliance on "consumable interventions," that is, interventions that, once used, cannot be used again. To reduce health disparities, interventions are required that can be used again and again without losing their therapeutic power, that can reach people even if local health care systems do not provide them with needed health care, and that can be shared globally without taking resources away from the populations where the interventions were developed. This paper presents the argument that automated self-help evidence-based Internet interventions meet the above criteria and can contribute to the reduction of health disparities worldwide. Proof-of-concept studies show that evidence-based Internet interventions can reach hundreds of thousands of people worldwide and could be used in public sector settings to augment existing offerings and provide services not currently available (such as prevention interventions). This paper presents a framework for systematically filling in a matrix composed of columns representing common health problems and rows representing languages. To bring the benefits of evidence-based Internet interventions to the underserved, public sector clinics should establish eHealth resource centers, through which patients could be screened online for common disorders and provided with evidence-based Internet intervention services not currently available at the clinics. These resources should be available in the patients' languages, in formats that do not require literacy, and that can be accessed with mobile devices. Such evidence-based Internet interventions should then be shared with public sector clinics as well as individuals anywhere in the world. Finally, this paper addresses sustainability and describes a continuum of evidence-based Internet interventions to share nationally and across the world. This approach to expanding health service delivery will significantly contribute to a reduction of health disparities worldwide, adding to the often-quoted slogan, "Think globally, act locally," a third line: "Share globally."     

Internet-based interventions to promote mental health help-seeking in elite athletes: an exploratory randomized controlled trial

Background

Mental disorders are more common in young adults than at any other life stage. Despite this, young people have low rates of seeking professional help for mental health problems. Young elite athletes have less positive attitudes toward seeking help than nonathletes and thus may be particularly unlikely to seek help. Interventions aimed at increasing help-seeking in young elite athletes are warranted.

Objective

To test the feasibility and efficacy of three Internet-based interventions designed to increase mental health help-seeking attitudes, intentions, and behavior in young elite athletes compared with a control condition.

Methods

We conducted a randomized controlled trial (RCT) of three brief fully automated Internet-based mental health help-seeking interventions with 59 young elite athletes recruited online in a closed trial in Australia. The interventions consisted of a mental health literacy and destigmatization condition, a feedback condition providing symptom levels, and a minimal content condition comprising a list of help-seeking resources, compared with a control condition (no intervention). We measured help-seeking attitudes, intentions and behavior using self-assessed surveys. Participation was open to elite athletes regardless of their mental health status or risk of mental illness.

Results

Of 120 athletes initially agreeing to participate, 59 (49%) submitted a preintervention or postintervention survey, or both, and were included in the present study. Adherence was satisfactory, with 48 (81%) participants visiting both weeks of assigned intervention material. None of the interventions yielded a significant increase in help-seeking attitudes, intentions, or behavior relative to control. However, at postintervention, there was a trend toward a greater increase in help-seeking behavior from formal sources for the mental health literacy/destigmatization condition compared with control (P = .06). This intervention was also associated with increased depression literacy (P = .003, P = .005) and anxiety literacy (P = .002, P = .001) relative to control at postintervention and 3-month follow-up, respectively, and a reduction in depression stigma relative to control at postintervention (P = .01, P = .12) and anxiety stigma at 3-month follow-up (P = .18, P = .02). The feedback and help-seeking list interventions did not improve depression or anxiety literacy or decrease stigmatizing attitudes to these conditions. However, the study findings should be treated with caution. Due to recruitment challenges, the achieved sample size fell significantly short of the target size and the study was underpowered. Accordingly, the results should be considered as providing preliminary pilot data only.

Conclusions

This is the first RCT of an Internet-based mental health help-seeking intervention for young elite athletes. The results suggest that brief mental health literacy and destigmatization improves knowledge and may decrease stigma but does not increase help-seeking. However, since the trial was underpowered, a larger trial is warranted.

Trial Registration

2009/373 (www.clinicaltrials.gov ID: {"type":"clinical-trial","attrs":{"text":"NCT00940732","term_id":"NCT00940732"}}NCT00940732), cited at http://www.webcitation.org/5ymsRLy9r.     

De-identification of unstructured paper-based health records for privacy-preserving secondary use

Whenever personal data is processed, privacy is a serious issue. Especially in the document-centric e-health area, the patients’ privacy must be preserved in order to prevent any negative repercussions for the patient. Clinical research, for example, demands structured health records to carry out efficient clinical trials, whereas legislation (e.g. HIPAA) regulates that only de-identified health records may be used for research. However, unstructured and often paper-based data dominates information technology, especially in the healthcare sector. Existing approaches are geared towards data in English-language documents only and have not been designed to handle the recognition of erroneous personal data which is the result of the OCR-based digitization of paper-based health records.     

大学生安全感与家庭环境因素的关系

目的了解大学生安全感与家庭环境因素的关系。方法采用家庭环境量表中文版(FES-CV)和安全感量表(SQ),对634名在校大学生进行调查。结果大学生安全感处于中等偏上水平,理科大学生在安全感总分和人际安全感因子的得分低于文科大学生(t=2.07,2.34;P0.05);非单亲家庭的男大学生在安全感中的确定控制感因子得分低于单亲男大学生(t=2.15,P0.05)。家庭环境亲密度、情感表达、独立性、娱乐性、道德宗教观、组织性、知识性与大学生安全感呈正相关(P0.05),家庭环境矛盾性、控制性与安全感呈负相关(P0.01);家庭环境亲密度、娱乐性、情感表达、矛盾性依次进入安全感回归方程。结论大学生家庭环境对其安全感有重要影响。大学生的安全感也因性别、家庭类型、文理科而有差别。     

Analysis of the Security and Privacy Requirements of Cloud-Based Electronic Health Records Systems

Background

The Cloud Computing paradigm offers eHealth systems the opportunity to enhance the features and functionality that they offer. However, moving patients’ medical information to the Cloud implies several risks in terms of the security and privacy of sensitive health records. In this paper, the risks of hosting Electronic Health Records (EHRs) on the servers of third-party Cloud service providers are reviewed. To protect the confidentiality of patient information and facilitate the process, some suggestions for health care providers are made. Moreover, security issues that Cloud service providers should address in their platforms are considered.

Objective

To show that, before moving patient health records to the Cloud, security and privacy concerns must be considered by both health care providers and Cloud service providers. Security requirements of a generic Cloud service provider are analyzed.

Methods

To study the latest in Cloud-based computing solutions, bibliographic material was obtained mainly from Medline sources. Furthermore, direct contact was made with several Cloud service providers.

Results

Some of the security issues that should be considered by both Cloud service providers and their health care customers are role-based access, network security mechanisms, data encryption, digital signatures, and access monitoring. Furthermore, to guarantee the safety of the information and comply with privacy policies, the Cloud service provider must be compliant with various certifications and third-party requirements, such as SAS70 Type II, PCI DSS Level 1, ISO 27001, and the US Federal Information Security Management Act (FISMA).

Conclusions

Storing sensitive information such as EHRs in the Cloud means that precautions must be taken to ensure the safety and confidentiality of the data. A relationship built on trust with the Cloud service provider is essential to ensure a transparent process. Cloud service providers must make certain that all security mechanisms are in place to avoid unauthorized access and data breaches. Patients must be kept informed about how their data are being managed.     

Effectiveness and impact of networked communication interventions in young people with mental health conditions: a systematic review

Objective

Examine the effectiveness and impacts of the networked communication technologies used by health care professionals for the treatment of adolescents/young adults with mental health disorders.

Methods

Nine electronic databases were searched. Quantitative and qualitative study designs were included, technologies were described and a narrative synthesis of all included studies was undertaken.

Results

20,925 papers were identified from which 12 interventions met the inclusion criteria. Three categories of networked communication were identified: email and/or web-based electronic diary (n = 6); videoconference (n = 5); and virtual reality (n = 1). Three studies reported statistically significant improvements in symptoms post intervention; all involved email communication. Patients were willing to use networked communication in routine care in nine studies.

Conclusions

Networked communication technologies can increase the opportunity for communication between patient and health care professionals. Limited improvements in quality of life and continuity of care for patients were reported. Patients and health care professionals expressed some satisfaction with technologies. Further research exploring concerns over privacy and security is needed.

Practice implications

Networked communication technologies have the potential to be a useful addition to mental health services delivery, however the impact and effectiveness of these technologies is inconclusive.     

Uptake of mental health websites in primary care: Insights from an Australian longitudinal cohort study of depression

Objective

To describe the characteristics of primary care attendees with depressive symptoms who use mental health websites.

Therapist training in evidence‐based interventions for mental health: A systematic review of training approaches and outcomes

A lack of effective therapist training is a major barrier to evidence‐based intervention (EBI) delivery in the community. Systematic reviews published nearly a decade ago suggested that traditional EBI training leads to higher knowledge but not more EBI use, indicating that more work is needed to optimize EBI training and implementation. This systematic review synthesizes the training literature published since 2010 to evaluate how different training models (workshop, workshop with consultation, online training, train‐the‐trainer, and intensive training) affect therapists’ knowledge, beliefs, and behaviors. Results and limitations for each approach are discussed. Findings show that training has advanced beyond provision of manuals and brief workshops; more intensive training models show promise for changing therapist behavior. However, methodological issues persist, limiting conclusions and pointing to important areas for future research.     

Fulfilling the promise of mental health technology to reduce public health disparities: Review and research agenda

Despite significant promise, the full impact of mental health technologies has yet to be realized. With overall mental health service utilization still below 50%, those with a disorder, racial/ethnic minority, low SES, and rural populations receive services at even lower rates. Mental health technologies have been designed and proposed to address the barriers exacerbating these disparities and low utilization. However, research on these tools, which to date has appropriately prioritized effectiveness, requires significant shifts to test the ways these tools may reduce disparities. This article reviews these tools and outlines a potential framework for research that can guide the translation of these technologies into data‐driven dissemination and implementation strategies.     

A Region-Based Lossless Watermarking Scheme for Enhancing Security of Medical Data

This paper presents a lossless watermarking scheme in the sense that the original image can be exactly recovered from the watermarked one, with the purpose of verifying the integrity and authenticity of medical images. In addition, the scheme has the capability of not introducing any embedding-induced distortion in the region of interest (ROI) of a medical image. Difference expansion of adjacent pixel values is employed to embed several bits. A region of embedding, which is represented by a polygon, is chosen intentionally to prevent introducing embedding distortion in the ROI. Only the vertex information of a polygon is transmitted to the decoder for reconstructing the embedding region, which improves the embedding capacity considerably. The digital signature of the whole image is embedded for verifying the integrity of the image. An identifier presented in electronic patient record (EPR) is embedded for verifying the authenticity by simultaneously processing the watermarked image and the EPR. Combining with fingerprint system, patient’s fingerprint information is embedded into several image slices and then extracted for verifying the authenticity.     

De-identification methods for open health data: the case of the Heritage Health Prize claims dataset

Background

There are many benefits to open datasets. However, privacy concerns have hampered the widespread creation of open health data. There is a dearth of documented methods and case studies for the creation of public-use health data. We describe a new methodology for creating a longitudinal public health dataset in the context of the Heritage Health Prize (HHP). The HHP is a global data mining competition to predict, by using claims data, the number of days patients will be hospitalized in a subsequent year. The winner will be the team or individual with the most accurate model past a threshold accuracy, and will receive a US $3 million cash prize. HHP began on April 4, 2011, and ends on April 3, 2013.

Objective

To de-identify the claims data used in the HHP competition and ensure that it meets the requirements in the US Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule.

Methods

We defined a threshold risk consistent with the HIPAA Privacy Rule Safe Harbor standard for disclosing the competition dataset. Three plausible re-identification attacks that can be executed on these data were identified. For each attack the re-identification probability was evaluated. If it was deemed too high then a new de-identification algorithm was applied to reduce the risk to an acceptable level. We performed an actual evaluation of re-identification risk using simulated attacks and matching experiments to confirm the results of the de-identification and to test sensitivity to assumptions. The main metric used to evaluate re-identification risk was the probability that a record in the HHP data can be re-identified given an attempted attack.

Results

An evaluation of the de-identified dataset estimated that the probability of re-identifying an individual was .0084, below the .05 probability threshold specified for the competition. The risk was robust to violations of our initial assumptions.

Conclusions

It was possible to ensure that the probability of re-identification for a large longitudinal dataset was acceptably low when it was released for a global user community in support of an analytics competition. This is an example of, and methodology for, achieving open data principles for longitudinal health data.     

A Privacy Preservation Model for Health-Related Social Networking Sites

The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users'' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS.     

集中居住农民的心理健康状况及安全感的比较

目的:比较集中居住农民与自然村居住农民心理健康状况与安全感状况的差异,探究集中居住农民心理健康状况与安全感的关系。方法:采用症状自评量表和安全感量表对集中居住农民124人和自然村居住农民143人进行测量,并用SPSS 16.0进行统计分析。结果:1集中居住农民在SCL-90总均分(t=-3.466,P0.05)和各因子得分(t=-2.533,-3.442,-3.843,-2.947,-3.341,-2.351,-2.714,-3.011,-2.500,-2.453;P0.05)都显著低于自然村居住农民;2集中居住农民在安全感量表中确定控制感因子得分(t=2.192;P0.05)显著高于自然村居住农民;3集中居住农民的心理健康与安全感成正相关(P0.01)。结论:在短时期内,集中居住农民心理健康状况和确定控制感优于自然村居住农民,并且其心理健康状况与安全感有密切联系。