AI, Beliefs, Helplessness, Misinformation ...

Viewing this debate and SDGs both as information spaces, and mental health/illness can provide some insights.

'Learned helplessness' is an established phenomenon in psychological studies and history.

Adam Grant in Life&Arts, FTWeekend 29-30 March 2025, p.2. 

( https://adamgrant.net/book/think-again/ )
writes in 'HOW TO UNLEARN HELPLESSNESS'

'Many people believe that in a world of echo chambers and misinformation, it's not possible to talk anyone out of their convictions. They`re wrong. Even a bot can do it.

In recent experiments psychologists recruited thousands of Americans who believed in unfounded conspiracy theories ranging from the moon landing being faked to 9/11 being an inside job. After the participants described their views, the psychologists randomly assigned some of them to discuss these views with an AI chatbot that was prompted to refute them.

After less than 10 minutes of conversation with a ChatGPT-based LLM, more than a quarter of participants felt uncertain about their views - and those doubts persisted two months later. Short exchanges were even enough to move the opinions of strong believers.

Why? It's not just that ChatGPT has access to infinite knowledge. It turns out that AI chatbots are better listeners than the average human. The researchers found that chatbots were persuasive because they presented information that directly challenged the reasons behind people's beliefs.'

Also helpful, as per discussion to consider AI as a new / emerging 'information space' as a literal frontier, a new territory with unknowns that businesses wish to conquer and the public must learn to trust - even as users. What knowledge - understanding is needed of what is happening in the 'box'?

Once again (within Hodges' model) we can potentially draw in (ask questions of - all) the literacies:

3Rs, information, IT, media, culture, spiritual, financial, health, sciences, civic - national, international...

This also means to what extent are existing imbalances in parity of esteem - between the mind and body dichotomy perpetuated, even increased?

It is not surprising that there is an imbalance, in the distribution of datasets - LLMs on huggingface:

https://huggingface.co/docs/hub/en/datasets

e.g. INTRA- INTERPERSONAL [MIND]

BioBert 1.1
UCI ML Drug Review dataset - Subset 

LOST arXiv:2306.05596 [cs.CL]

Mindwell https://doi.org/10.1007/978-981-97-3601-0_34

SCIENCES [BODY]

eScience kidney factomics (PubMed titles)
BioBert 1.1
SAVSNET sample (VetCN) - Important in terms of Zoonotic diseases and planetary health*.

Image datasets: 

Lung Cancer IQ-OTH/NCCD 

Surface Crack Detection 

Oxford-IIIT Pet 

BreastMNIST 

DermaMNIST 

PneumoniaMNIST 

BloodMNIST 

RetinaMNIST

There is overlap also.

Ack. *As mentioned late 2024, the datasets were discussed at: https://www.bcs-sgai.org/health2024/

Posted to HIFA - with some editing

'ChatGPT (40) Differentiating reliable information from misinformation (12)'

Call - Special issue: Learning from Multiple Data Sources for Decision Making in Health Care

The increasing availability of digital data, along with recent developments in Artificial Intelligence, especially in the Machine Learning and Deep Learning fields, led the scientific community to debate whether data alone is sufficient for decision making and scientific exploration. We focus the attention on the healthcare domain, where peculiar issues affect data: indeed, data are usually collected under heterogeneous conditions (i.e., different populations, regimes, and sampling methods), suffer missingness – very often not at random – and their use is strongly constrained by privacy issues. In such a complex setting, this special issue challenges computer scientists to contribute to the above debate by designing and developing innovative methodological approaches, for solving complex decision-making problems in health care, leveraging on observational data.

Topics of interest include, but are not limited to, the following with an emphasis on novel generalizable methods applied to the healthcare domain:

• Causal discovery from multiple data sets.
• Federated causal discovery.
• Causal discovery from heterogeneous data sets.
• Transportability of causal models and inference.
• Neuro-symbolic approaches to learn from heterogeneous data sources.
• Continual learning on streams from multiple data sources.
• Computational intelligent strategies to support causal inference.
• Edge computing for decision making in healthcare.
• Integrative AI methodologies.
• Distributed inference methods.
• Continual Learning.
• Knowledge Discovery and Integration.
• Combination of deductive approaches with ML models.
• Combination of ontologies and/or knowledge-bases with ML to support decision making.

Peer Review Process:

All submitted papers will undergo a rigorous peer-review process featuring at least two reviewers. All submissions should follow the guidelines for authors available at the Journal of Biomedical Informatics website (http://www.elsevier.com/locate/yjbin). JBI’s editorial policy outlined on that page will be strictly enforced by special issue reviewers.

Note that JBI emphasizes the publication of papers that introduce innovative and generalizable methods of interest to the informatics community. Specific applications can be described to motivate the methodology being introduced, but papers that focus solely on a specific application are not suitable. A few examples of papers focused on methods previously published in JBI include: Kyrimi, et al. [1], Huang, et al. [2], Kocbek et al. [3], Houston et al. [4], García Del Valle et al. [5], Graudenzi et al. [6] and Sims et al. [7].

In particular, the authors of [1] showed the relevance of causal models and expert knowledge to develop credible models, i.e., capable of achieving good predictive performances when transported from the study cohort to the target population. Furthermore, [2] tackles the relevant issue of partially overlapping variables when data are collected from multiple data sources. This problem is extremely relevant both in theoretical and practical terms for decision making in the healthcare sector.

The contribution provided in [3] stressed the importance of working in a multi-source context by demonstrating how the linking of different repositories can improve the overall understanding of patients' conditions. Similarly, in [4] the authors extended this concept by introducing a methodology to evaluate to audit the data quality of the sources exploited by healthcare information systems. Then, in [5] the multi-source concept is transferred within the multi-modal environment and the authors surveyed the importance of considering different modalities to obtain a better disease understanding.

The works in [6] and [7] focuses on the importance of data. In [6] a data integration framework is defined for characterizing the metabolic deregulations that distinguish cancer phenotypes, by projecting RNA-seq data onto metabolic networks without the need for metabolic measurements; in [7] a biomedical informatics method is introduced that uses multiple public health data sources to perform surveillance of methadone-related adverse drug events. Interestingly, even if patient data are not linked between different data sources, results show that the integration of multiple public data sources can capture more cases and provide more clinical details than individual data sources alone.

Key requirements for JBI ML papers in addition to presenting novel methods (not simply application of existing methods to a new healthcare domain) are as follows: 1) projects must have clinicians involved in research question/problem formulation, defining input data, and assessing the results. 2) An explanation (with clinicians) of how the proposed method would fit into the clinical workflow is expected. It must be translational to practice. 3) Data sets should preferably be collected from hospitals after the research question was formulated, thus avoiding the use of available data (MIMIC) to define a very wide research problem that could potentially be answered with available open datasets (as an example: detecting if someone has COVID from Chest X-Rays would not be acceptable, as the gold standard test is the laboratory test). 4) As for explainability, SHAP values and related diagrams would not be enough: the paper should clearly describe and explain how clinicians use the visualization to make decisions. For further details please refer to https://www.sciencedirect.com/journal/journal-of-biomedical-informatics/publish/guide-for-authors.

Further details available -

Submission process, Questions, and References 

My source: 

https://aixia.it/en/gruppi/hc/

August 2022 - Journal of Health Care for the Poor and Underserved

To JHCPU readers,

 

The August 2022 issue of the Journal of Health Care for the Poor and Underserved (JHCPU) has been released:

https://muse.jhu.edu/issue/48370

The Note from the Editor appears below. Following the link will bring you to the full table of contents.

With best wishes for the new academic year,

Ginny Brennan

 

Note from the Editor

Public Health and Politics

Positioned at the nexus of social science and health, the Journal's work is necessarily political. One of the many concerns in the U.S. as we approach the Fall of 2022 is the U.S. Supreme Court's June decision in Dobbs v. Jackson Women's Health Organization to overturn Roe v. Wade and with it the Constitutional guarantee of the right to abortion, abrogating women's moral autonomy over their reproductive health. In this issue, Frohwirth and colleagues consider another contested site in the reproductive health care landscape—contraception affected by abortion policy—as they assess the impact on women in Iowa of a 2017 reduction in Medicaid coverage of contraceptive care. Due to the new law, patients enrolled in the state family planning program could no longer access subsidized care at publicly funded clinics affiliated with abortion provision, and over 15,000 patients had to find to find a new family planning provider. The researchers learned in their qualitative study that high fees for visits and contraceptive methods, restrictive or inadequate insurance coverage, and access barriers such as long appointment wait times were the most common barriers to preferred contraceptive care, and these barriers compounded one another. Furthermore, barriers grew once the more restrictive Iowa Medicaid policy was in place. The authors conclude that policy changes supportive of contraceptive care would decrease vulnerability and increase reproductive autonomy.

Several papers in this issue bear on the construction of datasets or use datasets in new and sophisticated ways. We publish them aware of the fact that database construction is central to many highly political debates. Qato and colleagues introduce an intermediate-level variable—the nursing home—into an analysis of the distribution of COVID19 vaccination among nursing home residents. Looking at over 12,000 nursing homes in terms of the racial heterogeneity of the residents, the authors find that residents of the quantile of homes that were more predominantly non-Hispanic White were significantly more likely to be vaccinated (mean vaccinated 85.65%) than residents of the quantile that was least predominantly non-Hispanic White (mean vaccinated 72.74%). The authors of this short article conclude, "A higher proportion of White residents per facility was associated with higher resident COVID-19 vaccination rates reflecting continued disparities in quality of care during the pandemic."

While it is not construed formally as a variable, the construct of neighborhood in the paper by DiFiore and colleagues reveals significant patterns in the distribution of food insecurity. They assess food insecurity in relationship to perceived neighborhood safety, social cohesion, informal social control, and crime, adjusted for demographics, socioeconomic status, and neighborhood characteristics. The participants in the study were 300 mothers and female caregivers of Medicaid-enrolled two- to four-year old children in Philadelphia. Greater food security was associated with higher perceived neighborhood safety and social cohesion, and lower police-recorded violent crime rates. The evidence of this research suggests that the structural condition of living in a supportive neighborhood social environment may protect against food insecurity.

Kong and colleagues conducted COVID19/food security research, using longitudinal data to assess the interrelationships among food insecurity, mental health, and the COVID19 pandemic. They found that food insecurity was associated with stress, depression, and anxiety. They also found that these conditions improved over time during the pandemic among food-secure participants but worsened among food-insecure participants. The pandemic appears to worsen the already vicious cycle connecting food insecurity and mental health.

Two papers based on the Youth Risk Behavior Survey (YRBS) argue for enriched variables for coding race and ethnicity. Jones and Satter analyze mental health outcomes based on race and ethnicity and, in doing so, they observe that over 80% of respondents to the YRBS who self-identified as American Indian/Alaska Native also self-identified as Hispanic. American Indians/Alaska Natives are often multi-racial and of Hispanic/Latino ethnicity, and therefore outcomes differ widely depending on whether one examines American Indian/Alaska Native alone or in combination with other racial/ethnic variables. Also using the YRBSS, Braun and colleagues assessed tobacco and alcohol use and adolescent sexual practices among Black, bi/multi-racial, and White adolescents. They find that results differed across all three groups, leading them to conclude that nuanced racial categories are called for.

It is our hope that these and the many other papers in this quarter's issue—through their attention to social, scientific, and political decisions affecting health and health care—will serve to advance health justice, either through or in spite of the political process.

Virginia M. Brennan, PhD, MA

Editor, JHCPU

Associate Professor, Meharry Medical College

My source:
Spiritof1848 Listserv WWW.SPIRITOF1848.ORG #Spiritof1848

PhD Opportunity: An Atlas of Health and Social Inequalities

 

Excited to announce that we have funding for a +3 studentship in the UCL Department of Geography for the project “An Atlas of Health and Social Inequalities”. The research will be carried out in association with the Health Foundation and will comprise the creation of a range of innovative datasets presented through a series of ground-breaking maps and graphics. The project will centre on the Health Foundation’s Social and Economic Value of Health: Place programme, which is designed to generate new knowledge about the ways in which the physical and mental health of a population shapes their social and economic outcomes. The Health Foundation have funded a number of research projects already that focus on understanding the relationship between a given population’s health and the health of individuals within that population.

The PhD will benefit from insights from these projects and focus on the creation of a nationwide atlas to demonstrate the social and economic value of health. It will produce a series of research-led maps created from innovative and granular datasets to demonstrate the new ways that health data can be visualised. These will convey a range of variables including health metrics such as mortality, self-reported health, prevalence of specific health conditions, and social and economic outcomes including employment, pay, structural changes to industrial sector composition and social fragmentation.

The work will be supervised by myself (James.Cheshire AT ucl.ac.uk) and Dr Anwar Musah (a.musah AT ucl.ac.uk), to whom enquiries may be directed. The successful applicant will hold a First or Upper Second Class honours degree in a quantitative social science or computer science discipline and/or similar Masters qualification.

For further details on eligibility etc please see here.

CLICK HERE TO APPLY (Deadline 4th April)

My source: Spirit of 1848

Does “#AI” stand for Augmenting Inequality in the era of Covid-19 healthcare? c/o BMJ

Fig 1 Cascading effects of health inequality and discrimination manifest in the design and use of artificial intelligence (AI) systems [BMJ]

Original graphic surgically re-rendered as per the knowledge (care) domains of Hodges' model:

individual

|

INTERPERSONAL : SCIENCES

humanistic ----------------------------------------------- mechanistic

SOCIOLOGY : POLITICAL

|

group

My source:

Does “#AI” stand for Augmenting Inequality in the era of Covid-19 healthcare? | via @bmj_latest https://t.co/P3zgVBeI4p

— Rob McCargow #MoveForJack (@RobMcCargow) March 16, 2021

Deep *and* Broad ... Hodges' model is no blank slate ...

"Beyond deep learning

Steeper than expected

Different researchers have different ideas about how to try to improve things. One idea is to widen the scope, rather than the volume, of what machines are taught. Christopher Manning, of Stanford University's AI Lab, points out that biological brains learn from far richer data-sets than machines. Artificial language models are trained solely on large quantities of text or speech. But a baby, he says, can rely on sounds, tone of voice or tracking what its parents are looking at, as well as a rich physical environment to help it anchor abstract concepts in the real world. This shades into an old idea in AI research called "embodied cognition", which holds that if minds are to understand the world properly, they need to be fully embodied in it, not confined to an abstracted existence as pulses of electricity in a data-centre.

Biology offers other ideas, too. Dr Brooks argues that the current generation of AI researchers "fetishise" models that begin as blank slates, with no hand-crafted hints built in by their creators. But "all animals are born with structure in their brains," he says. 'That's where you get instincts from.'" p.11.

The Economist, Technology Quarterly: Artificial intelligence and its limits. The Economist, June 13 2020, 435:9198. [and image source].

'Deep and Broad' - as required.

Open Data as Open Educational Resources: 4th March 1400-1700 UCL

Next Thursday evening I'm heading to London for Drupalcamp Saturday and Sunday. On the Friday afternoon I'm attending:

Open Data can be understood as “universally participatory data”, which is openly shared by government agencies, NGOs, academic institutions or international organisations.

Open Data can be used in Higher Education using real life scenarios, bringing together students, academics and researchers working towards overcoming local and global real problems.

In this way students can develop transversal, research and citizenship skills, by working with the same raw materials researchers and policy makers use, contributing with the society in new and yet-unimagined ways.

 The event will be featuring

• Santiago Martín: University College London
• Mor Rubistein: Open Knowledge International
• Leo Havemann: Birkbeck, University of London
• Dr Carla Bonina: University of Surrey  
• William Hammonds: Universites UK
• Dr Fabrizio Scrollini: Latin American Open Data Initiative
• Dr Tim Coughlan: Open University  

WHEN

Friday, 4 March 2016 from 14:00 to 17:00 (GMT)

WHERE

Medawar G01 Lankester Lecture Theatre: UCL, Gower Street, London, United Kingdom -

Online Metaphor Map launched

Hi

Here at the University of Glasgow we have just completed a three-year-long project which traces metaphor over the entire history of the English language, creating the first ever Metaphor Map resource. It contains thousands of metaphorical connections which can be accessed through a visual or text-based interface.

If you're interested you can visit the site here:
http://www.glasgow.ac.uk/metaphor

Or you can read more below:
--------------------------------------

English language metaphors are “as old as the hills” – or 13 centuries old at the very least – researchers at the School of Critical Studies at the University of Glasgow have found.

They have just completed a three-year-long project which traces metaphor over the entire history of the English language, creating the first ever Metaphor Map resource which contains the thousands of metaphorical connections that the researchers have identified.

“This project is unique in its scope. While a considerable amount of work on metaphor has been done over the past 40 years, it has never been possible to achieve this level of comprehensiveness until now,” said Dr Wendy Anderson, Principal Investigator on the “Mapping Metaphor with the Historical Thesaurus” project.‌‌

The Metaphor Map is based on the data contained in the Historical Thesaurus of English, which took from 1966-2009 to compile, and its own parent resource, the Oxford English Dictionary. The researchers, who have been funded by the Arts and Humanities Research Council (AHRC), have been able to identify well over 10,000 metaphorical connections between different categories and track how language use has changed over the centuries.

“These findings support the view that metaphor is pervasive in language and a major mechanism of meaning-change,” said Dr Anderson.

“This helps us to see how our language shapes our understanding – the connections we make between different areas of meaning in English show, to some extent, how we mentally structure our world,” she added.

“Over the past 30 years, it has become clear that metaphor is not simply a literary phenomenon; metaphorical thinking underlies the way we make sense of the world conceptually. When we talk about ‘a healthy economy’ or ‘a clear argument’ we are using expressions that imply the mapping of one domain of experience (e.g. medicine, sight) onto another (e.g. finance, perception).

“When we describe an argument in terms of warfare or destruction (‘he demolished my case’), we may be saying something about the society we live in. The study of metaphor is therefore of vital interest to scholars in many fields, including linguists and psychologists, as well as to scholars of literature.”

The Metaphor Map is still a work in progress, but once complete it will also include tens of thousands of examples of words with metaphorical senses; to date, around a quarter of these have been put online.

The researchers plan to launch a parallel Metaphor Map for data from Old English (prior to 1150AD) in August, at the International Society of Anglo Saxonists conference in Glasgow. The team, led by Dr Anderson and Research Associate Dr Ellen Bramwell, is also working on another project, “Metaphor in the Curriculum”, to create materials on metaphor for schools. This is funded by the AHRC’s Follow-on Funding for Impact and Engagement strand.
----
Kind regards
Brian
-----
Brian Aitken MA(Hons) MSc
Digital Humanities Research Officer
School of Critical Studies
Room 506
13 University Gardens
University of Glasgow
G12 8QJ

Email: brian.aitken AT glasgow.ac.uk
Web: http://blogs.arts.gla.ac.uk/digital-humanities/
My source:
Humanist Discussion Group, Vol. 29, No. 133.
Department of Digital Humanities, King's College London
www.digitalhumanities.org/humanist

Ngrams: E-portfolios, nursing theory, models of nursing...: Do the lines run true?

For the latest module I'm looking at e-portfolios in nursing education and possibly wider afield. In the FT Weekend Life & Arts there is an extract -

Capitalism’s secret love affair with bureaucracy

- from David Graeber’s book: The Utopia of Rules: On Technology, Stupidity, and the Secret Joys of Bureaucracy published this week on March 12. It includes a graph from Google Books Ngram a word count through time of 'bureaucracy'. I'd read about Ngrams and tried them quite some time ago, but never used them. Now's my chance.

The graph below began with e-portfolio and eportfolio. I tried nursing e-portfolio... but these were not found. With conceptual framework the scale was disrupted. Adding models of nursing and nursing theory provided a frame that also nicely encompasses, at least in this rendering, conceptual space and threshold concepts.

At the risk of asking too much of the graph if not the source, we might be disappointed that models of nursing is not running concurrent with e-portfolio and reassured that nursing theory has waned but is 'still up there'. This is to forget though that the count for e-portfolio here is general not nursing specific.

Ngrams are another tool and a dynamic one no doubt, when the API is utilised, the data downloaded and words are re-examined over time. In answer to the title's question, I do not believe the lines do run true but this is about nursing and e-portfolios.

Response to: Pros and cons of pulling behavioral and social data into EHRs [Government Health IT]

Mike Miliard Editor of Healthcare IT News posted an item:

Pros and cons of pulling behavioral and social data into EHRs

To put my reply in context here is the start of Mike's post:

Should more types of health data figure into electronic health records?

On the one hand, the Institute of Medicine put out a call for doing just that on the grounds that behavioral and social data can benefit population health practices to ultimately improve the care of individual patients. For physicians who already complain that EHRs are burdensome and distract from care delivery, on the other hand, the idea of making electronic records more complex, perhaps even cluttered, will inevitably be unwelcome news. ...

Talk about a work in progress? How long does it take to get this right? Of course health and social care data is always ongoing, as governments change, policy, medicine, local government, social care, technology and society too.

As Mike notes for many physicians the EHR is already burdensome. My context is quite different being nursing, mental health, and crisis-oriented in the community. I've defined small research-based datasets in the past and it is a fascinating pursuit. Trying to have the data defined and reporting ready before the 'door opens'. Doing this retrospectively is no fun at all.

At work when I visit someone in a residential care or nursing home, do I record this as 'home', or 'community' in the absence of the aforementioned categories? Is this ageism?

Is there a digital dividend to come to the physician's aid? Surely increasingly the physical measurements and observations in medicine, surgical... can be automatically captured, disseminated and presented accordingly? Surely, it is possible today to bring in other data as the context changes? If we can autofill on words, we should be able to auto-fill the dataset as context shifts? There are many algorithms out there already 'alive and countin-the-clickin'  in the milliseconds.

It seems Mr Miliard is writing about one way to define 'integrated care'?

It isn't just 'public health' though;
it must combine, be inclusive of - 'public mental health'.

The focus of the article is the Institute of Medicine's report:

Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2

Mike lists eight domains from the report and these are mapped to Hodges' model below:

individual
INTERPERSONAL : SCIENCES

humanistic ------------------------------------------- mechanistic

SOCIOLOGY : POLITICAL

group

educational attainment, stress, depression	physical activity, stress
social isolation, intimate partner violence (for women of reproductive age)	financial resource strain, neighborhood median household income

I've included stress twice as there are at least two forms: anxiety - internal; and environmental - external.

'Voronoi treemap' by Michael Balzer, (2005)

'Voronoi treemap' by Michael Balzer, (2005)

Images courtesy of Princeton Architectural Press via Brain Pickings

The Book of Trees - on a table in Waterstones, Manchester this evening.

Privacy: Open Data, Individual and Group

The vertical axis of Hodges' model is the individual - group, or self through to collective. Health and social care constantly negotiates this from the ideals and delivery of person-centred care to public mental health. So often for health professionals the emphasis is on the individual, the person's care needs, their strengths, their rights, outcomes and feedback on care received. The same individual focus is also ascribed to records and information. Protection of data, maintaining confidentiality is an essential duty of health care  professionals.  

Earlier this year the government's care.data scheme was placed on hold. 'Open' is the way of the world: open access, open source, open data and open government. Increasingly the group as an entity needs to considered in what may be a new way, as Floridi writes:

The idea that groups may have a right to privacy is not new, and it is open to debate, but it has not yet received all the attention it deserves, although it is becoming increasingly important.

 ...

Open data is more likely to treat types (of customers, users, citizens, demographics population, etc.) rather than tokens (you, Alice, me), and hence groups rather than individuals. But re-identifiable groups are ipso facto targetable groups.It is therefore a very dangerous fallacy to think that, if we protect personal data that identify individuals, the protection of the groups will take care of itself. p.23.

Luciano Floridi. Group Privacy. The Philosophers' Magazine. Issue 65, 2nd Quarter 2014. pp. 22-23.

Here is a related book (on my list) a BMJ award winner:

The Private Life, Josh Cohen:
https://granta.com/products/the-private-life/

The war over private life spreads inexorably. Some seek to expose, invade and steal it, others to protect, conceal and withhold it. Either way, the assumption is that privacy is a possession to be won or lost.

But what if what we call private life is the one element in us that we can't possess? Could it be that we're so intent on taking hold of the privacy of others, or keeping hold of our own only because we're powerless to do either? ...

ERCIM News No. 99 Special theme: "Software Quality"

Dear ERCIM News Reader,

ERCIM News No. 99 has just been published at
http://ercim-news.ercim.eu/en99

Special Theme: "Software Quality"
http://ercim-news.ercim.eu/en99/special/

And on the occasion of ERCIM’s 25th anniversary, we published a selection of articles on the future challenges of ICST:
http://ercim-news.ercim.eu/en99/challenges-for-icst

Keynote by Willem Jonker, CEO EIT ICT Labs: "The Future of ICT: Blended Life"
http://ercim-news.ercim.eu/en99/keynote/the-future-of-ict-blended-life



This issue is also available for download as:
pdf:  http://ercim-news.ercim.eu/images/stories/EN99/EN99-web.pdf
epub: http://ercim-news.ercim.eu/images/stories/EN99/EN99.epub

Next issue: No. 100, January 2015 - Special Theme: "Scientific Data Sharing"

Thank you for your interest in ERCIM News.
Feel free to forward this message to others who might be interested.

Best regards,
Peter Kunz
ERCIM News central editor

Better information means better care

BBC Radio 4: Inside Health 21 January 2013

Margaret McCartney and Mark Porter ask whether the anonymity of patient records on a new NHS database can be guaranteed?

NHS: Your records:

Using information about the care you have received, enables those involved in providing care and health services to improve the quality of care and health services for all. The role of the Health and Social Care Information Centre (HSCIC) is to ensure that high quality information is used appropriately to improve patient care. 

NHS England has therefore commissioned a programme of work on behalf of the NHS, public health and social care services to address gaps in information. Our aim is to ensure that the best possible evidence is available to improve the quality of care for all.  ...

http://www.nhs.uk/NHSEngland/thenhs/records/healthrecords/Pages/care-data.aspx

INTERPERSONAL : SCIENCES
humanistic ------------------------------------------- mechanistic
SOCIOLOGY : POLITICAL

individual

my interests	scientific interests
social interests	commercial interests

group - population

ERCIM News No. 96 Special theme: "Linked Open Data"

Dear ERCIM News Reader,

ERCIM News No. 96 has just been published at
http://ercim-news.ercim.eu/en96

Special Theme: "Linked Open Data"
http://ercim-news.ercim.eu/en96/special/
Guest editors: Irini Fundulaki (Institute of Computer Science, FORTH) and Sören Auer (University of Bonn and Fraunhofer IAIS)

Keynote: "Linked Data: The Quiet Revolution" by Wendy Hall

This issue for download
pdf: http://ercim-news.ercim.eu/images/stories/EN96/EN96-web.pdf
epub: http://ercim-news.ercim.eu/images/stories/EN96/EN96.epub

Next issue: No. 97, April 2014 - Special Theme: "Cyber-Physical Systems"
(see the call at http://ercim-news.ercim.eu/call)

Thank you for your interest in ERCIM News.
Feel free to forward this message to others who might be interested.

Best regards,
Peter Kunz
ERCIM News central editor

--------------------------------------------------
An initiative for the ERCIM members: Call for Participation - identifying the emerging grand challenges in ICST http://kwz.me/74

FatFonts - fonts with real weight: Giving space and data form

Links now appear broken ...

How it works (from fatfonts.org):

Fatfonts are designed so that the amount of dark pixels in a numeral character is proportional to the number it represents. For example, “2″ has twice the ink than “1″, “8″ has two times the amount of dark ink than “4″ etc. You can see this easily in the set of characters below:

Source for the above and animated: http://visual.ly/fatfonts-player?view=true

My source: Jacob Aron, Making numbers punch their weight, New Scientist, 5 May 2012, 214, 2863, p.12.

Hodges' model: Lazy data, organisations and domain outreach (HSJ Ack.)

In the (northern) summer Dr Mark Davies (NHS Information Centre) noted that:

We have lots of data but it's lazy data. We have to make it work and turn it into actionable data - data we can do something with.

Interview: The hard data man's soft spot. Health Service Journal, 2 August, 2012. p.17.

There are many ways that we can put data to work. In the interview with HSJ Dr Davies also highlighted the common and not unexpected emphasis upon the organisational views of the world. Here in England in management the current preoccupation is the preparation for April 2013 of clinical commissioning groups. The NHS has an incredible resource in its data. Whether or not the volume involved qualifies as big data is debatable, but in the interview Dr Davies continues:

 Professionals have a duty to measure, to compare and open up their data to scrutiny. "We talk about the purchaser provider split," he says. "But I think that is the wrong purchaser and provider. It is the split between the tax payer and public services that is important. ..." p.17.

I've mapped this to Hodges' model below. You could say that taxation is POLITICAL and it clearly is, but it is also part of what is frequently termed the social contract. For me this is why Dr Davies' views matter.

Looking at the model we can also see the task ahead in the many ways (domains) in which data can be put to work.

INTERPERSONAL : SCIENCES

SOCIOLOGY : POLITICAL

PURPOSE	lazy data (inertia!) actionable data (information - knowledge)
public tax payers	ORGANISATIONS /                    \ PURCHASER  PROVIDER (citizens) public services

Integrated Health and Social Care Data: GIS torch

Last month the HSJ announced plans to integrated health and social care data (July 5th, pp. 6-7). The purpose is specific to support care commissioning, but ...

The related topic of integrated care is a round-robin element of policy debate. It may go quiet for a time, but it is there, needing to be fed in successive governmental and policy turns.

You might reasonably expect that integrated health and social care data, would be a by-product of integrated care. So the fact that data integration remains a 'to-do' demonstrates the patchwork nature of care integration and the many levels by which it can be defined: commissioning, practice (within domain) across care domains, budget, teams - disciplines, service organisations, care and education, public involvement and data.

I hope the integration of health and social care data at the commissioning level might also put data into the hands of clinicians and social care teams - integrated of course!

The local insights that could flow would represent a real, tangible benefit. The news item stresses the potential value for commissioners. There are as ever several caveats:

• To what extent can health and social care staff influence the shape of the dataset?
• Is it crystallized (centralised) already?
• Can the new role for councils in public health finally ignite the GIS torch to illuminate what is really happening in the local community?

It happens that:

data 'integration' 

also = data 'orientating'

So - come on policy people, commissioners and managers, don't leave the workforce out of the loop. Staff on the ground are disoriented enough by the relentless pace of change. They need a sat-nav for care. Give them the torch they need.

What is that you say? They don't have the time to critique their (integrated) practice, to formulate their questions. And anyway - they don't have the access or the skills to use the informatics resources, let alone the nous to interpret the data! Well, if that is the case then shame on you.

IdN Extra 07: Infographics — Designing Data

Visiting Manchester twice this past fortnight I'd noticed this IdN special issue on infographics in the Cornerhouse shop. The shop's only small but there is lots to dive into - arts, media, design and philosophy.

When a database becomes a thing of beauty

Infographics or information graphics are visual representations of information, data or knowledge. They are often used when complex information needs to be presented as quickly and effectively as possible, such as signs and maps. Infographics can be as simple as a bar chart or a pie graph to represent percentages in business information; or as elaborative as some of the examples in this book to communicate stories in newspapers and magazine.

Infographics can be entertaining when the information they represent is of personal interest; but it is especially fun and challenging when the topic may be as dry as representing concepts in technical manuals or scientific statics.

 <->

I don't know if it's the reduced scale, or my right eye talking but some of the text descriptions are difficult to read. The graphics and ideas are stunning, both in themselves and the questions they provoke.

Visual Methodologies Workshop in Newcastle

After Oxford Drupal Education Camp this Friday-Saturday proceedings move on to a NE workshop.

If your focus is on person-centered health care then the volume of data involved that pertaining to the individual can be readily apprehended. At least the example of a single episode of care. Of course, there are exceptions, people who might be the subject of special case studies so complex is their condition and pathology. Data volumes do vary markedly from person to person. A great deal of generated data in an individual instance might be taken for granted. In the reported findings, for example, of an MRI scan that is included in a referral. When provided existing diagnoses do much to enrich the information and knowledge contained in a referral, whilst reducing possible avenues for further data gathering.

Once we move from individuals to groups and populations then the volumes involved quickly become massive. Purposes and context reflect this change in scale; codified, anonymised, aggregated the individual is lost.

Both my day-to-day work and study of Hodges' model (in nursing, informatics, literacy...) are centered on individuals. 'Caseness' in a clinical word: a referral, home visits for the day, face-to-face interaction, care concepts in assessments, plans. ... Then there is envisioning a nurse-patient (carer) interaction, or individual's episode of care through Hodges' model. As per the model's structure, however, groups and populations must also be represented. This duality of personal and data scales makes this workshop on visual methodologies of instant relevance. The two days next week cover (with my emphasis):

Introduction to working with visual methodologies: understanding epistemologies and disciplinary boundaries

• Mapping
• Story-boarding
• Artefacts

Quality in visual methods: ethics, validity and reliability
Doing visual methods: lived examples of managing data capture, synthesis, analysis and dissemination
Modes of analysis: focusing on methodological and epistemological influence on the research process

Workshop part 1: working with self-created data
Workshop part 2: creating shared analytic frameworks for self-created data
Overarching ideas and ways forward for thinking about visual methodology

Hodges' model can be readily interpreted and presented as a map and a series of story boards. The model can also support analysis, synthesis: well, this is my belief that is shared by some people.

I have completed modules on research methods, but it seems increasingly that research methods, methodologies, data structures and algorithms overlap. It may be that advances in media, technology, data gathering and improved access to data sets is having this effect. Perhaps more integrative and open attitudes (interdisciplinarity) towards quantitative and qualitative research also accounts for this blurring; or it could just be me? Whatever is the case, I'm really looking forward to the programme, meeting the facilitators and students. I am hoping this will inform my project as per the aims of the workshop:

• Consider the role of visual methods in data collection, research ethics, synthesis, analysis and dissemination;
• Explore the theoretical prospectives, epistemological traditions and latest practices that have shaped the development of visual methodologies; and
• Enable participants to translate how visual methodologies can be used to support their own research.

I'll try and post from Oxford this Friday - Saturday and from Newcastle next week. From Newcastle I'll be heading to Edinburgh for the Scottish Ruby Conference. Lots to follow as I put 10 days unpaid leave to use.