scholarly journals Key Variables for Effective eHealth Designs for Individuals With and Without Mental Health Disorders: 2^12-4 Fractional Factorial Experiment (Preprint)

2020 ◽  
Author(s):  
Armando J Rotondi ◽  
Jonathan Grady ◽  
Barbara H Hanusa ◽  
Gretchen L Haas ◽  
Michael R Spring ◽  
...  
Keyword(s):  
Mental Illness ◽  
Success Rate ◽  
Reading Level ◽  
Fractional Factorial ◽  
Mental Illnesses ◽  
Factorial Experiment ◽  
Classification And Regression Tree ◽  
Mixed Effect ◽  
Design Elements ◽  
Design Variables

BACKGROUND eHealth applications not only offer the potential to increase service convenience and responsiveness but also expand the ability to tailor services to improve relevance, engagement, and use. To achieve these goals, it is critical that the designs are intuitive. Limited research exists on designs that work for those with a severe mental illness (SMI), many of whom have difficulty traveling for treatments, reject or infrequently seek treatment, and tend to discontinue treatments for significant periods. OBJECTIVE This study aims to evaluate the influence of 12 design variables (eg, navigational depth, reading level, and use of navigational lists) on the usability of eHealth application websites for those with and without SMI. METHODS A 2<sup>12-4</sup> fractional factorial experiment was used to specify the designs of 256 eHealth websites. This approach systematically varied the 12 design variables. The final destination contents of all websites were identical, and only the designs of the navigational pages varied. The 12 design elements were manipulated systematically to allow the assessment of combinations of design elements rather than only one element at a time. Of the 256 websites, participants (n=222) sought the same information on 8 randomly selected websites. Mixed effect regressions, which accounted for the dependency of the 8 observations within participants, were used to test for main effects and interactions on the ability and time to find information. Classification and regression tree analyses were used to identify effects among the 12 variables on participants’ abilities to locate information, for the sample overall and each of the 3 diagnostic groups of participants (schizophrenia spectrum disorder [SSD], other mental illnesses, and no mental illness). RESULTS The best and worst designs were identified for each of these 4 groups. The depth of a website’s navigation, that is, the number of screens users needed to navigate to find the desired content, had the greatest influence on usability (ability to find information) and efficiency (time to find information). The worst performing designs for those with SSD had a 9% success rate, and the best had a 51% success rate: the navigational designs made a 42% difference in usability. For the group with other mental illnesses, the design made a 50% difference, and for those with no mental illness, a 55% difference was observed. The designs with the highest usability had several key design similarities, as did those with the poorest usability. CONCLUSIONS It is possible to identify evidence-based strategies for designing eHealth applications that result in significantly better performance. These improvements in design benefit all users. For those with SSD or other SMIs, there are designs that are highly effective. Both the best and worst designs have key similarities but vary in some characteristics. CLINICALTRIAL

Effective e-health design for those with, and without, mental health disorders: shallow navigation, concentrated contents, modest number of links, one screen area for links. (Preprint)

2018 ◽  
Author(s):  
Armando Rotondi ◽  
Jonathan Grady ◽  
Barbara H. Hanusa ◽  
Michael R. Spring ◽  
Kaleab Z. Abebe ◽  
...  
Keyword(s):  
Mental Illness ◽  
Severe Mental Illness ◽  
Success Rate ◽  
Fractional Factorial ◽  
Mental Illnesses ◽  
Schizophrenia Spectrum Disorders ◽  
Design Elements ◽  
Website Usability ◽  
Schizophrenia Spectrum ◽  
Health Applications

BACKGROUND E-health applications are an avenue to improve service responsiveness, convenience, and appeal, and tailor treatments to improve relevance, engagement, and use. It is critical to user engagement that the designs of e-health applications are intuitive to navigate. Limited research exists on designs that work for those with a severe mental illness, many of whom infrequently seek treatment, and tend to discontinuation medications and psychosocial treatments. OBJECTIVE The purpose of this study was to evaluate the influence of 12 design elements (e.g., website depth, reading level, use of navigational lists) on the usability of e-health application websites for those with, and without, mental health disorders (including severe mental illness). METHODS A 212-4 fractional factorial experimental design was used to specify the designs of 256 e-health websites, which systematically varied the 12 design elements. The final destination contents of all websites were identical, only the navigational pages varied. Three subgroups of participants comprising 226 individuals, were used to test these websites (those with schizophrenia-spectrum disorders, other mental illnesses, and no mental illness). Unique to this study was that the 12 design elements were manipulated systematically to allow assessment of combinations of design elements rather than only one element at a time. RESULTS The best and worst designs were identified for each of the three subgroups, and the sample overall. The depth of a website’s navigation, that is, the number of screens/pages users needed to navigate to find desired content, had the strongest influence on usability (ability to find information). The worst performing design for those with schizophrenia-spectrum disorders had an 8.6% success rate (ability to find information), the best had a 53.2% success rate. The navigational design made a 45% difference in usability. For the subgroup with other mental illnesses the design made a 52% difference, and for those with no mental illness a 50% difference in success rate. The websites with the highest usability all had several key similarities, as did the websites with the poorest usability. A unique finding is that the influences on usability of some design elements are variable. For these design elements, whether they had a positive or negative effect, and the size of its effect, could be influenced by the rest of the design environment, that is, the other elements in the design. This was not the case for navigational depth, a shallower hierarchy is better than a deeper hierarchy. CONCLUSIONS It is possible to identify evidence-based strategies for designing e-health applications that result in a high level of usability. Even for those with schizophrenia, or other severe mental illnesses, there are designs that are highly effective. The best designs have key similarities, but can also vary in some respects. Key words: schizophrenia, severe mental illness, e-health, design, website, usability, website design, website usability, fractional factorial design.

Prescriptive Power: Biologism, Biopsychiatry and Drug-centred Psychopharmacology

Somatechnics ◽  
2019 ◽  
Vol 9 (2-3) ◽  
pp. 291-309
Author(s):  
Francis Russell
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Social Justice ◽  
Cultural Theory ◽  
Human Experience ◽  
Mental Illnesses ◽  
False Consciousness ◽  
The Subject ◽  
Biological Ontology ◽  
Health Discourse

This paper looks to make a contribution to the critical project of psychiatrist Joanna Moncrieff, by elucidating her account of ‘drug-centred’ psychiatry, and its relation to critical and cultural theory. Moncrieff's ‘drug-centred’ approach to psychiatry challenges the dominant view of mental illness, and psychopharmacology, as necessitating a strictly biological ontology. Against the mainstream view that mental illnesses have biological causes, and that medications like ‘anti-depressants’ target specific biological abnormalities, Moncrieff looks to connect pharmacotherapy for mental illness to human experience, and to issues of social justice and emancipation. However, Moncrieff's project is complicated by her framing of psychopharmacological politics in classical Marxist notions of ideology and false consciousness. Accordingly, she articulates a political project that would open up psychiatry to the subjugated knowledge of mental health sufferers, whilst also characterising those sufferers as beholden to ideology, and as being effectively without knowledge. Accordingly, in order to contribute to Moncrieff's project, and to help introduce her work to a broader humanities readership, this paper elucidates her account of ‘drug-centred psychiatry’, whilst also connecting her critique of biopsychiatry to notions of biologism, biopolitics, and bio-citizenship. This is done in order to re-describe the subject of mental health discourse, so as to better reveal their capacities and agency. As a result, this paper contends that, once reframed, Moncrieff's work helps us to see value in attending to human experience when considering pharmacotherapy for mental illness.

scholarly journals Use of a Consultation Service Following Pharmacogenomic Testing in Psychiatry

CNS Spectrums ◽  
2021 ◽  
Vol 26 (2) ◽  
pp. 179-180
Author(s):  
Daniel Dowd ◽  
David S. Krause
Keyword(s):  
Mental Illness ◽  
Drug Interactions ◽  
Metabolic Pathways ◽  
Patient Characteristics ◽  
Healthcare Resource Utilization ◽  
Machine Learning Algorithms ◽  
Mental Illnesses ◽  
Variable Response ◽  
Drug Induced ◽  
Commercial Laboratory

AbstractBackgroundThere is a plethora of drugs available to psychiatrists for treatment of mental illness, which can vary in efficacy, tolerability, metabolic pathways and drug-drug interactions. Psychotropics are the second most commonly listed therapeutic class mentioned in the FDA’s Table of Pharmacogenomic Biomarkers in Drug Labeling. Pharmacogenomic (PGx) assays are increasingly used in psychiatry to help select safe and appropriate medication for a variety of mental illnesses. Our commercial laboratory offers PGx expert consultations by PharmDs and PhDs to clinician-users. Our database contains valuable information regarding the treatment of a diverse and challenging population.MethodsGenomind offers a PGx assay currently measuring variants of 24 genes relevant for selection of drugs with a mental illness indication. Since 2012 we have analyzed > 250,000 DNA samples. Between 10/18 - 8/20 6,401 reports received a consult. The data contained herein are derived from those consults. Consultants record information on prior meds, reason for failure or intolerability, potential risk-associated or useful drugs based on the genetic variants. Consultants only recommend specific drugs and doses consistent with a published PGx guideline.ResultsThe 5 most commonly discussed genes were SLC6A4, MTHFR, CACNA1C, COMT and BDNF. The 3 most commonly discussed drugs were fluoxetine, lithium and duloxetine. The most common reasons for drug failure were inefficacy and drug induced “agitation, irritability and/or anxiety”. SSRIs were the most common class of discontinued drug; sertraline, escitalopram and fluoxetine were the three most commonly reported discontinuations and were also the 3 most likely to be associated with “no improvement”. Aripiprazole was the most commonly reported discontinued atypical antipsychotic. The providers rated 94% of consultations as extremely or very helpful at the time of consult. An independent validation survey of 128 providers confirmed these ratings, with 96% reporting a rating of “very helpful” or “extremely helpful”. In addition, 94% reported that these consults were superior to PGx consults provided through other laboratories. Patient characteristics captured during consults via a Clinical Global Impressions-Severity (CGI-S) scale revealed that the majority of patients were moderately (54%) or markedly ill (23%). The most frequent symptoms reported were depression, anxiety, insomnia and inattentiveness.DiscussionThe large variety of psychotropic drugs available to providers, and their highly variable response rates, tolerability, capacity for drug-drug interactions and metabolic pathways present a challenge for even expert psychopharmacologists. Consultation with experts in PGx provides additional useful information that may improve outcomes and decrease healthcare resource utilization. This database may provide future opportunities for machine learning algorithms to further inform implications of included gene variants.FundingGenomind, Inc.

scholarly journals Development of Machine Learning Models for Prediction of Smoking Cessation Outcome

2021 ◽  
Vol 18 (5) ◽  
pp. 2584
Author(s):  
Cheng-Chien Lai ◽  
Wei-Hsin Huang ◽  
Betty Chia-Chen Chang ◽  
Lee-Ching Hwang
Keyword(s):  
Machine Learning ◽  
Smoking Cessation ◽  
Success Rate ◽  
Prediction Models ◽  
Smoking Status ◽  
Medical Center ◽  
Machine Learning Algorithms ◽  
Classification And Regression Tree ◽  
Support Vector ◽  
Smoking Cessation Outcome

Predictors for success in smoking cessation have been studied, but a prediction model capable of providing a success rate for each patient attempting to quit smoking is still lacking. The aim of this study is to develop prediction models using machine learning algorithms to predict the outcome of smoking cessation. Data was acquired from patients underwent smoking cessation program at one medical center in Northern Taiwan. A total of 4875 enrollments fulfilled our inclusion criteria. Models with artificial neural network (ANN), support vector machine (SVM), random forest (RF), logistic regression (LoR), k-nearest neighbor (KNN), classification and regression tree (CART), and naïve Bayes (NB) were trained to predict the final smoking status of the patients in a six-month period. Sensitivity, specificity, accuracy, and area under receiver operating characteristic (ROC) curve (AUC or ROC value) were used to determine the performance of the models. We adopted the ANN model which reached a slightly better performance, with a sensitivity of 0.704, a specificity of 0.567, an accuracy of 0.640, and an ROC value of 0.660 (95% confidence interval (CI): 0.617–0.702) for prediction in smoking cessation outcome. A predictive model for smoking cessation was constructed. The model could aid in providing the predicted success rate for all smokers. It also had the potential to achieve personalized and precision medicine for treatment of smoking cessation.

scholarly journals Priority vaccination for mental illness, developmental or intellectual disability

2021 ◽  
pp. medethics-2021-107247
Author(s):  
Nina Shevzov-Zebrun ◽  
Arthur L Caplan
Keyword(s):  
Mental Illness ◽  
Living Arrangement ◽  
State Level ◽  
Elevated Risk ◽  
Mental Illnesses ◽  
Healthcare Personnel ◽  
Diverse Populations ◽  
Federal Level ◽  
Control And Prevention ◽  
Prevention Guidelines

Coronavirus vaccines have made their debut. Now, allocation practices have stepped into the spotlight. Following Centers for Disease Control and Prevention guidelines, states and healthcare institutions initially prioritised healthcare personnel and elderly residents of congregant facilities; other groups at elevated risk for severe complications are now becoming eligible through locally administered programmes. The question remains, however: who else should be prioritised for immunisation? Here, we call attention to individuals institutionalised with severe mental illnesses and/or developmental or intellectual disabilities—a group highly susceptible to the damages of COVID-19, recent research shows, and critical to consider for priority vaccination. The language describing both federal-level and state-level intentions for this population remains largely vague, despite the population’s diversity across age, diagnosis, functional status and living arrangement. Such absence of specificity, in turn, leaves room for confusion and even neglect of various subgroups. We review data stressing this group’s vulnerability, as well as select state plans for priority vaccination, highlighting the importance of clarity when describing intentions to vaccinate, or even generally care for, diverse populations composed of distinct subgroups in need.

Multidisciplinary approach about contraception in a day hospital of mental health

2017 ◽  
Vol 41 (S1) ◽  
pp. s848-s848
Author(s):  
C.M. Calahorro ◽  
M. Guerrero Jiménez ◽  
B.M. Girela Serrano
Keyword(s):  
Mental Illness ◽  
Reproductive Health ◽  
Mental Illnesses ◽  
Healthy Population ◽  
Day Hospital ◽  
Attitudes And Practices ◽  
Hospital Patients ◽  
Unwanted Pregnancies ◽  
Competing Interest ◽  
Healthy Sexuality

BackgroundWomen with mental illness are a disadvantaged group both in terms of their gender and because of their mental disorders, and they experience serious problems related to reproductive health.The high rates of unplanned and unwanted pregnancies among women with schizophrenia underscore the importance of understanding their attitudes and practices related to family planning. Different studies reveal that even though many sexually active women with serious mental illnesses do not want to become pregnant, they do not use birth control.ObjectivesRelease last data about contraception methods among patients with severe mental illness after doing a bibliographical review. Also reflect present setup in Motril day hospital women patients and their relationship with sexuality and contraception. At the same time we intend to clarify and unify the proceedings on ethical problems respecting subject's autonomy, beneficence, qualification and minors’ protection.MethodsData were collected through face-to-face interviews and a questionnaire based on the literature and prepared by the researchers which was designed to determine the kinds of reproductive health issues the patients were experiencing.ResultsIt was found that female patients with psychiatric disorders had more negative attributes with regard to contraception approach and sexuality compared with a corresponding healthy population.ConclusionsWe reached an agreement about future contraception approaches in Motril day hospital users as part of the global treatment offered in our section.MotrilHospital gynaecology service has facilitated the proceedings for contraceptive subcutaneous implants insertion in those indicated women.Day hospital patients were instructed individually and through group work about healthy sexuality.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Skills-based intervention to enhance collaborative decision-making: systematic adaptation and open trial protocol for veterans with psychosis

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Emily B. H. Treichler ◽  
Borsika A. Rabin ◽  
William D. Spaulding ◽  
Michael L. Thomas ◽  
Michelle P. Salyers ◽  
...  
Keyword(s):  
Decision Making ◽  
Mental Illness ◽  
Service Delivery ◽  
Serious Mental Illness ◽  
Qualitative Interviews ◽  
Skills Training ◽  
Mental Illnesses ◽  
Open Trial ◽  
Collaborative Decision Making ◽  
Collaborative Decision

Abstract Background Collaborative decision-making is an innovative decision-making approach that assigns equal power and responsibility to patients and providers. Most veterans with serious mental illnesses like schizophrenia want a greater role in treatment decisions, but there are no interventions targeted for this population. A skills-based intervention is promising because it is well-aligned with the recovery model, uses similar mechanisms as other evidence-based interventions in this population, and generalizes across decisional contexts while empowering veterans to decide when to initiate collaborative decision-making. Collaborative Decision Skills Training (CDST) was developed in a civilian serious mental illness sample and may fill this gap but needs to undergo a systematic adaptation process to ensure fit for veterans. Methods In aim 1, the IM Adapt systematic process will be used to adapt CDST for veterans with serious mental illness. Veterans and Veteran’s Affairs (VA) staff will join an Adaptation Resource Team and complete qualitative interviews to identify how elements of CDST or service delivery may need to be adapted to optimize its effectiveness or viability for veterans and the VA context. During aim 2, an open trial will be conducted with veterans in a VA Psychosocial Rehabilitation and Recovery Center (PRRC) to assess additional adaptations, feasibility, and initial evidence of effectiveness. Discussion This study will be the first to evaluate a collaborative decision-making intervention among veterans with serious mental illness. It will also contribute to the field’s understanding of perceptions of collaborative decision-making among veterans with serious mental illness and VA clinicians, and result in a service delivery manual that may be used to understand adaptation needs generally in VA PRRCs. Trial registration ClinicalTrials.gov Identifier: NCT04324944

Human rights of people with mental illness diagnosis: perceptions among service users, family members and health professionals in Tunisia

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mayssa Rekhis ◽  
Sami Ouanes ◽  
Abir Ben Hamouda ◽  
Rym Rafrafi
Keyword(s):  
Mental Illness ◽  
Human Rights ◽  
Family Members ◽  
Mental Illnesses ◽  
Service Users ◽  
Content Type ◽  
People With Mental Illness ◽  
The Family ◽  
The Right ◽  
Main Factor

Purpose This study aims to assess the awareness about the rights of people with mental illness in the main psychiatric hospital in Tunisia among the service users, the family members and the staff. Design/methodology/approach The Convention of Rights of People with Disabilities mandates that State Parties initiate and maintain campaigns and human rights training to promote understanding of the rights of people with mental illnesses, considered as a main factor for their fulfillment. Service users, family members and staff evaluated, through a survey, the importance of ten rights for persons with mental illness, stated in the convention. Findings Disparities were found in the perception of the different rights by and between the three groups. The highest levels of awareness were associated with the freedom from torture or degrading treatment and the right to live with dignity and respect, whereas the lower importance were assigned to the right to participation in recovery plans, to give consent and to exercise legal capacity. Originality/value The lack of awareness and the poor perception of rights of people with mental illness is one of the barriers to their achievement. More training and awareness raising is necessary.

scholarly journals Severe persistent mental illness

1992 ◽  
Vol 16 (12) ◽  
pp. 743-745 ◽  
Author(s):  
Peter F. Liddle
Keyword(s):  
Mental Illness ◽  
Mental Hospital ◽  
Community Care ◽  
Community Setting ◽  
Detailed Examination ◽  
Mental Illnesses ◽  
Persistent Mental Illness ◽  
Realistic Appraisal

Many patients with persistent mental illnesses enjoy a better life in a community setting than would be possible in a long stay mental hospital. Furthermore, the available evidence indicates that most such patients get better while living in the community. Unfortunately, community care has not served all patients well. Much of the difficulty can be attributed to lack of resources. However, there is also a tendency by planners to underestimate the severity of patients' disabilities. A realistic appraisal demands a detailed examination of the problems of patients whose needs have not been met by community care. One important issue is that of patients who fall through the net of community care and another is that of patients who have not but nonetheless have not survived in the community. This paper addresses the question of the needs of this latter group.

A Fractional-Factorial Numerical Technique for Stress Analysis of Glass-To-Metal Lead Seals

1994 ◽  
Vol 116 (2) ◽  
pp. 98-104 ◽  
Author(s):  
Barry Mathieu ◽  
Abhijit Dasgupta
Keyword(s):  
Closed Form ◽  
Numerical Technique ◽  
Mechanical Vibration ◽  
Maximum Principal Stress ◽  
Design Guidelines ◽  
Fractional Factorial ◽  
Design Variables ◽  
Load Carrying ◽  
Glass Seals ◽  
Glass Seal

Fracture of glass seals in metallic hermetic electronic packaging is a significant failure mode because it may lead to moisture ingress and also to loss of load carrying capacity of the glass seal. Seal glasses are intrinsically brittle and their fracture is governed by the stresses generated. This study investigates stresses in lead seals caused by handling, testing, mechanical vibration, and thermal excursions. Loads considered are axial tension, bending, and twisting of the lead. More general loading can be handled by superposition of these results. Factorial techniques, commonly used in multi-variable Design of Experiments (DoE), are used in conjunction with finite element parametric simulations, to formulate closed-form regression models which relate the maximum principal stress within the glass seal to the type of loading and geometry. The accuracy of the proposed closed-form equations are verified through analysis of residuals. The analysis reveals the sensitivity of the magnitude of the seal stress to design variables such as the materials and geometry of the seal, lead, and package. Manufacturing-induced problems such as defects and flaws are not considered. An additional purpose for presenting this study is to illustrate the use of design of experiment methods for developing closed-form models and design guidelines from simulation studies, in a multi-variable problem.

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