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Getting started with social media to promote your research

Imagine a newspaper where you get to choose the sections to include (front page, finance, politics, entertainment, sport etc), and also who writes the articles in each section…  Welcome to twitter…

Is twitter a social media fad for tween girls to share their love of Justin Bieber, or is it a social media tool that can no longer be ignored?  Twitter is now used by health officials to track disease outbreaks, and monitored for security threats in the US.  Worldwide, 21% of internet users actively use twitter each month, and over 55’s are the fastest growing demographic on twitter. So how can academics use it to promote themselves and their research?

First of all, what is twitter?  You create a profile of who you are, and then you ‘follow’ people to see what they say.  By following people who tweet about topics you’re interested in you get a twitter feed filled with information, links, news and updates tailored for you. 

For 50% of twitter users, this is all they do.  But to get the most out of twitter, you need to interact.  You can retweet things you find interesting, as well as creating your own tweets.  Tweets can be about things you hear at conferences, get by email or simply your own thoughts (see hints below on writing good tweets). You now have a global network of people who are interested in the same things you are.

For example, my profile says I’m a health economics PhD student examining costs of cancer care.  I follow organisations like ISPORorg, CHEyork, simplystats, Healtheconall and NCImedia, and people who tweet about health economics, writing and being a PhD student, like Inger Mewburn (thesiswhisperer), James Hayton (3monththesis) and Arthur Phillips (MPH_adapt). 

So why are many academics nervous about getting involved in twitter?  It seems to me to be a combination of misconceptions about the benefits available, and a fear of losing control.

Much of the public perception of twitter is that it is photos of what people ate for breakfast and the inane thoughts of music superstars.  But I conceptualise twitter as my personal newspaper.  I choose if I want to include a food section or an entertainment section in my health economics newspaper.  And if I do want some of these sections, I chose how big they are and who writes the stories that get published.  In addition, twitter also allows me to publish news that forms the content of other people’s newspapers.  And it is this aspect that can get my name, and my research, known internationally. 

The perception that academics will lose control of their content is an interesting one.  Some are worried that unpublished work, such as that presented at conferences, should not be tweeted.  But a conference is a public event, so a presenter wouldn’t present their work if they didn’t want it heard.  My perspective is that while you do potentially lose some control of who hears your message and when and where and how, the benefits of having your work seen by a potentially much larger, more diverse audience than would be in a conference session far outweighs these potential downsides.

Tips for using twitter to promote your research

  • Use your real name
  • Tweet a 70:30 mixture of professional and general interest/personal information
  • Use hashtags when you tweet , and to find people to follow
  • Be active and engaged, but  remember that you don’t have to be ‘on’ all the time
  • Everything you tweet is public and forever
  • Don’t use all 140 characters (to allow others to retweet)
  • Follow the conventions for acknowledging sources of your information
  • If something is said in public, it can be tweeted. But it might sometimes be nice to ask permission first (or let people know you’re ok with it if it is you presenting).
  • For an excellent guide to getting started with Twitter, check out the Mashable guidebook

The most re-tweeted image of all time (817,000 retweets & 300,000  favourites) 

 

 

 

Comparing the Australian and Irish Cancer Registries

Having just moved from Australia to Ireland to do a post-doc at the National Cancer Registry, I was interested in comparing the Australian and Irish cancer registration systems.  Both countries have excellent cancer registries, with some similarities as well as differences between them.  A table comparing the features of each system is below, but the primary differences are around the method of collecting data for the registry, and the amount of information captured.

In Ireland the Department of Health and Children has funded the National Cancer Registry Ireland since 1994.  Cancer registration is not mandatory.  However, data capture is close to complete through a system of active data collection through trained registry employees being stationed at hospitals around the country to collect cancer cases and data.  Most new registrations are identified through the pathology report, however public hospitals also produce lists of cancer cases discharged each year, and death notices are checked as well.  Six to twelve months after a new cancer notification, the tumour registration officer pulls the medical record for each notification, and completes the data entry.  Information is collected on the individual, the cancer and their initial treatments, with the full data list provided in the registry manual (p9) here.  Cancers are registered at the level of the individual, but are analysed at the tumour level.

In Australia, each state has an independent cancer registry, which reports a standardised minimum dataset to the National Cancer Statistics Clearinghouse at the Australian Institute for Health and Welfare (AIHW).  The New South Wales (NSW) registry, managed by the Cancer Institute NSW, is described here as an example.  Throughout Australia reporting of cancers (other than basal and squamous cell carcinomas of the skin) is mandatory, and whenever a hospital, pathology lab or radiotherapy centre deals with someone with cancer they are required by law to notify the cancer registry.  Basic demographic, cancer and doctor information is obtained and supplemented with pathology reports and death certificates; however this is less extensive than in the Irish system.  Cancers are registered at the tumour level.

Both registries produce very similar statistics such as incidence, prevalence and mortality rates, as well as specialised publications for topic areas of specific interest to the country.  Data is made available by both registries to the government and other researchers, following appropriate ethical review and de-identification.

Table 1: Features of the Irish and Australian cancer registries compared

Feature National Cancer Registry (NCR)   Ireland New South Wales (NSW) Central   Cancer Registry Australia Association of   Cancer Registries (AACR)
Funding Department of Health and Children NSW Health through Cancer Institute NSW Department of Health
Established 1994 1991.  Dataset dates back to   1972 1982
Direction provided by National Cancer Registry Board Cancer Information and Registries Advisory Committee within Cancer   Institute NSW The AACR Executive Committee advises the AIHW on the direction of the   National Cancer Statistics Clearinghouse (NCSCH) work program and the   development of publication topics and strategies, and provides technical   advice on the operation of the NCSCH.
Functions
  1.   to   identify, collect, classify, record, store and analyse information relating   to the incidence and prevalence of cancer and related tumours in Ireland
  2.   to   collect, classify, record and store information in relation to each newly   diagnosed individual cancer patient and in relation to each tumour which   occurs
  3.   to promote   and facilitate the use of the data thus collected in approved research and in   the planning and management of services;
  4.   to publish   an annual report based on the activities of the Registry;
  5.   to furnish   advice, information and assistance in relation to any aspect of such service   to the Minister.
  1.   act as a   population based register of all cancers in NSW residents
  2.   monitor   and undertake surveillance of new cases of cancer, survival and deaths in NSW
  3.   supply   timely and accurate data based on a total record of all cases diagnosed in   residents of NSW

 

 

  1.   analyse   and report on the data in its national repository of cancer incidence and   mortality statistics;
  2.   support   research based on these data; and
  3.   develop   and improve cancer statistics generally.
How are cancers registered The reporting of cancer is not mandatory, however the NCR uses active   ascertainment and follow up to ensure that there is accurate and complete   recording of all cases diagnosed. Tumour Registration Officers employed by   the registry are based at hospitals nationally.  The main source of notification of new   cases is a pathology report, however each public hospital provides a list of people   discharge with cancer which is checked against the registry, as well as   checking death notices and receiving notifications from registries in the UK. All Australian states and territories have legislation that makes the   reporting of all cancers (other than basal and squamous cell carcinomas of   the skin) mandatory. State and territory population-based cancer registries   receive information on cancer diagnoses from a variety of sources such as   hospitals, pathology laboratories, radiotherapy centres and registries of   births, deaths and marriages. When any of these institutions deal with   someone with cancer, they are required by law to notify the cancer   registries. The cancer   registry in each state or territory sends information to the National Cancer Statistics Clearing House at the AIHW to compile into a   national database of cancer incidence, the Australian Cancer Database.Cancer   data are also made available to the World Health Organization, state and local government   authorities, health care institutions, health professionals and medical   researchers.
What information is collected The medical records are retrieved 6 – 12 months after notification to   complete case information and capture relevant treatment information.  Validation checks are performed at the   point of entry and internal verifications are carried out monthly.  See page 9 of the manual (www.ncri.ie/ncri/foifiles/Manual.doc)   for details of data collected. The CCR records new cancer cases and does not capture cancer   recurrence.demographic information, brief medical details describing the cancer   and a record of at least one episode of care. The data are supplemented by   pathology reports and death certificates.
  •   name and   address
  •   sex
  •   date and   country of birth
  •   Aboriginal   or Torres Strait Islander descent
  •   clinical   details about the cancer
  •   the   notifying institution and doctor
Definition of a cancer Cancers are registered at the level of the individual, but are   analysed at the level of the cancer.  Metastasise   are associated with the primary tumour and not considered separate cancers. A case of cancer is the occurrence of a primary malignant neoplasm in   one organ of a particular person.    Therefore a case of malignant melanoma in an individual counts as one   case.  If the same person then develops   leukemia, this counts as a second case.

 

My sources, and for more information:

Cancer registration in Australia

http://www.cancerinstitute.org.au/data-and-statistics/cancer-registries/nsw-central-cancer-registry-data-access

http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/3414.0main+features782011%20%28Edition%202%29

http://www.aihw.gov.au/cancer/aacr/

Cancer registration in Ireland

http://www.ncri.ie/ncri/index.shtml

www.ncri.ie/ncri/foifiles/Manual.doc

http://www.ncri.ie/pubs/pubfiles/CompletenessQuality.pdf

 

Multiple regression ‘cheat sheet’

This was a ‘cheat sheet’ I put together during the ACSPRI 2012 Winter Program course “Fundamentals of Multiple Regression” (Fun Reg). The cheat sheet simply summarises the concepts, formula’s and assumptions often used in regression analysis which were discussed in the course.

Fun Reg Cheat Sheet

This was a fantastic course that I would highly recommend to anyone looking to use regression in their research. The course description is below for your information, and you can check out the full range of courses they run at http://www.acspri.org.au/courses

Fundamentals of multiple regression: This course provides an introduction to, and the fundamentals of multiple regression, covering enough of the statistical material for the intelligent use of the technique. The approach is informal and applied rather than emphasising proofs of relevant theorems. The course begins with a review of bivariate regression and extends the relevant principles to the case of multiple regression. Particular attention is given to the application of multiple regression to substantive problems in the social sciences. By the end of the course, the student will have a knowledge of the principles of multiple regression, and the ability to conduct regression analyses, interpret the results, and to inspect elementary regression diagnostics to test the underlying model assumptions. This course provides the foundations necessary for progression to ‘Applied Multiple Regression Analysis’, and to subsequent advanced-level courses in structural equation modelling and log-linear modelling.

Resources for Emerging Researchers

This blog post was originally written for and published by the Health Services Research Association of Australia and New Zealand (HSRAANZ) Emerging Researcher Group (ERGO) section of the December 2012 Newsletter. It has been, and will continue to be, updated as I find out about new resources.

 

The number of resources for PhD students and emerging researchers available on the internet has increased exponentially in recent years.  To assist in discovering those which can be the most helpful in navigating the difficult and often confusing (but very rewarding) path to an academic career, the ERGO group (with the assistance of the PhD Group at CHERE) has put together a list of online resources.  The list is aimed at early career researchers, including PhD students, but many of the resources listed may be of interest to anyone working in health services research.

Websites / blogs

Following the blogs of people in your field can expose you to the latest research, as well as upcoming conferences, funding opportunities.  There are also a number of websites and blogs aimed specifically at PhD students and early career researchers, often with a focus on writing.

Name Summary Web / Twitter
Incidental Economist “Contemplating health care with a focus on research, an eye on reform” http://theincidentaleconomist.com/
@IncidentalEcon
Thesis Whisperer “newspaper style blog dedicated to helping research students” http://thesiswhisperer.com/
@thesiswhisperer
Healthecon-all Subscription email list which distributes messages to the international health economics community.  Set up in 1995 it has 1300 members https://www.jiscmail.ac.uk/cgi-bin/webadmin?A0=HEALTHECON-ALL
@healtheconall
Academic HE Blog UK-centric blog for news, analysis and developments in health economics http://aheblog.com/
@aheblog
PHTwitter Journal Club ‘Meets’ fortnightly to discuss selected public health related academic papers http://phtwitjc.wordpress.com/
@PHTwitJC
Simply stats 3 biostats profs post interesting ideas, article links and advice for new statisticians. http://simplystatistics.org/
@simplystats
3-month thesis “uncommon guide to thesis writing & phd life” http://3monththesis.com/
@3monththesis
AcWriMo Academic Writing Month – set a writing goal, make it public, work on it in Nov 2012 #AcWriMo

 

Twitter feeds are another good way of staying in touch with people and organizations who work in a similar area.

  • Health economics – @ScHARR – HEDS; @HERC_Oxford; #healtheconomics;
  • PhD students / early career researchers – @PhD2Published; @hildabast; #PhDchat; #Ecrchat;

 

Organisations to join

The following organizations have opportunities or resources specifically for early career researchers and/or PhD students

Name Early career researcher specific activities and resources Web / Twitter
HSRAANZ
  • Discounted student membership prices and conference registration
  • Special interest group for emerging researchers (ERGO)
  • ERGO facebook page with sharing of information, resources and opportunities
  • Mentoring program
  • ERGO specific activities at bi-annual conference (including ERGO dinner and ERGO lunchtime session)
  • ERGO seminars and workshops
  • Job opportunities advertised through mailing list
  • PhD Student prize
www.hsraanz.org
ISPOR
  • Discounted student membership prices and conference registration
  • Research tools repository
  • Many educational opportunities (although not specific to ECR)
  • Job opportunities listing
http://www.ispor.org/
iHEA
  • Discounted student membership prices and conference registration
  • PhD scholarships for conference attendance
https://www.healtheconomics.org/
AHES
  • PhD scholarships for annual conference
http://www.ahes.org.au/
ISOQOL
  • New Investigators Special Interest Group
  • New Investigators Blog
http://newinvestigators-isoqol.blogspot.ie/

iPhone / iPad apps

These apps will all make your student / research life easier!

Name Summary
Dropbox To access all your docs from any computer, and this can include your EndNote library.  There is a special promotion at the moment if you have a student/uni email address you get an extra 3Gb storage
Endnote for iPad Access your EndNote library on the go. You will need to set up an EndNote web account, but then your articles, including PDF’s will be available anywhere, anytime.
GoodNotes To review/revise documents
EverNote For taking notes
TeamViewer To access your computer remotely
Toodledo To do list
Pomodoro Timers
  • Pomodoro Time Management Lite by rapidrabbit
  • Simple Pomodoro Timer from SourcePad
  • 30/30  – a more flexible version – you can set various time limits for a list of tasks, and it will tell you when to move on to the next one
  • http://mytomatoes.com/  –  a free online timer for desktop based pomodoros

Feedback?

Do you have an iPad app you couldn’t live without, or a blog that you really enjoy?  We would love to keep expanding and updating this list of resources, so please let us know if you have other resources that you find useful as an early career researcher.

My experience of working with data that isn’t ‘mine’

This blog post was originally written for and published by the Health Services Research Association of Australia and New Zealand (HSRAANZ) Emerging Researcher Group (ERGO) section of the August 2012 Newsletter.

 

During my PhD I was lucky enough to be offered access to a large dataset for analysis.  This was a fantastic opportunity, which has strengthened my PhD and my data management and analysis skills.  Logistically however, it was not always easy.  I learnt a number of lessons that I thought other early career researchers may find useful.

There were four main issues I encountered:

Physically accessing the data

The data was held at another institution, who had received ethics approval and access to the data on the basis that it was kept confidential and did not leave their secure building.  I therefore needed to go to their site to conduct the analysis.  Whilst this was not foreseen to be an issue, there was a huge amount of red tape to get access to the university building, a desk, a computer, a log-in etc, because I was neither a staff member nor a student at that university.

To avoid these issues, start planning logistics early, and be realistic about what you need.  ‘Hot desking’ is not as easy as it sounds, so if you need your own computer, or a larger than average hard drive, be specific.  Make sure you ask very specific questions very early on about how you will access buildings and resources such as stationary and software etc.

Working with data that wasn’t ‘mine’

It takes extra time to get to know your data when you haven’t been involved in collecting it.  A data dictionary can be extremely helpful in these situations, and it is worth continuing to ask for one, if it is not provided with your data.  The other issue with working with data that isn’t yours, is that you may end up waiting for other people to prepare or clean datasets before you can use them.  Obviously this impacts on timelines, so build in a generous buffer into your project plans.

Working with a very large dataset

My working data file was over 60Gb, and analysis code often took days to run.  The computer system at the University was not really configured to cope with work being done overnight, and so often my programs would get interrupted by virus scans and automated backups.  I ended up using a local drive and doing my own backups, to avoid the issue, but in future I would try to sort this out before starting.

Working off site

Finally, I have already covered some of the access issues of working off site, but the other issues this raised was that it was quite isolating.  There was no one there who was really responsible for my work or who understood my project and methods, and I couldn’t sit down and show my data to anyone at my PhD office.  It was also difficult to integrate time to be in two offices into my daily schedule.  Meetings and events often prevented me going for days at a time, by which time I had forgotten what I was working on!  The solution to this was to get as organized as possible, to keep detailed notes of what I did each day, and to use tools such as dropbox (where allowed) to keep track of things.