
19:34
Handout https://www.digitalhealthcrc.com/wp-content/uploads/2020/09/CriticalReadingHandout.pdf

21:19
Millie from Newcastle looking for water in western NSW using geophysics!

21:40
Sydney, Fidelity of implementation of Inquiry learning in IBPYP classroom. MOther of 23 year old twins.

21:40
Hi all, i’m Kate from SA-Adelaide, and researching palliative care bereavement support, and on the lawn mowing theme, i am using a push lawnmower for exercise :)

21:53
Hello, this is Neha. I am pursuing my PhD with UTS and currently working as a Lecturer with various universities in Sydney.

21:55
Hi everyone, I’m study at Flinders university (Adelaide). My project is focusing on PTSD and meta-awareness :)

22:08
Hi, my name is Macey, I am in Canberra, currently completing my PhD in nursing, looking at partnership nursing.

22:32
Sorry forgot to mention my topic: Big data analytics

23:52
To be effective

23:58
for my literature review!

24:02
to not miss relevant data

24:03
To help me scan through a large amount of literature quickly

24:07
I want to fully understand the issues surrounding my topic

24:11
To analyse the gaps in research

24:23
To judge the quality of previous research

24:36
to improve future research/experiment

26:26
yes!

26:45
yes, definitely use it to construct my own methods

27:20
Will these slides be available afterwards?

27:36
Thank you!

28:20
making connections

28:25
Deeper thought and understandig

28:29
assess the strengths and weaknesses of the article

28:41
interpretation

28:42
To create a new understanding by combining literature/research

28:48
Analysis

29:01
to analyse different facts

33:38
yes looks ideal

33:45
perfect

41:47
››thank you it is what i am aiming for though easy to get lost in the process

41:48
I really like this it makes sense thank you

41:51
All good here

42:21
Very clear. Thanks

52:35
method, assumptions, participants

52:39
overreaching conclusions based on limited data collection

52:47
the experience of the target group

53:04
Data, methods and interpretation of results

53:06
yes

53:24
Alignment between methods and theoretical models

53:43
objective methodology result

53:53
qual data and participants,

54:16
yes

54:25
method used, models/ framework, (?)

54:44
education

55:11
ag research

55:19
geoscience

55:26
Archaeology

55:28
science - nanotechnology

55:33
Soil Science

55:35
Cyber Security, Internet of Things...

55:45
social history

57:15
Ecological relevance & statistical significance

57:15
woman-centredness, a feminist lens

57:30
Personal touch

57:33
accuracy, school/classroom applications and voice of educators

57:42
accessible, duty of care, less theory, applicability

57:45
Real-world applicability, Accuracy...

58:03
recnency probably a factor too

58:11
Indigenous perspectives/ inclusion, applicability for the field

58:14
social justice, real world applicability

58:14
Model generation: Experimental or Theoretical

58:16
psychometric sound (validity and reliability)?

58:43
Bias present

58:56
cost effectiveness, applicability, accuracy, time

01:05:04
https://www.digitalhealthcrc.com/wp-content/uploads/2020/09/CriticalReadingHandout.pdf

01:07:08
target audience, age, location, risk level, disease type

01:07:34
attitude toward cancer predictive in groups if non high rik women and men to analyse the factors that may influence their intenion to use these tes. Women are more motivated to get genetic testing

01:07:54
to investigate the attitudes toward cancer predictive genetic testing in a group of non-high-risk women and men and to analyze the factors that may influence their intention to use these tests.

01:07:56
Separate questionnaires for males and females, only outpatients and the use of non-high-risk patients

01:08:15
4 hospitals, age women and men between 30 -74, investigating attitudes towards testing

01:08:16
Non-high risk men and women, outpatients, 859 participants, face-to-face interviews, 30-74 ages

01:08:18
Paticipants 30 and 74 years

01:08:22
no participant had history of cancer

01:08:30
Focus on attitudes

01:08:38
attitude toward cancer predictive in groups , different questionnaire by gender, face-to face interviews, age

01:08:42
two different questionaires

01:09:08
investigated attitudes and what influences participants to use a test. Questionaire used - used stats and compared male and female

01:10:02
atritudes toward a certain testing type

01:10:16
clear

01:11:16
This implies reading more than one?

01:12:12
to investigate the attitudes, analyze the factors that may influence their intention, studied a sample, were asked to answer a questionnaire, descriptive statistics and univariate comparisons used..

01:13:06
age range - 50 to 80

01:13:15
They used different questionares - use the same questionnaire for both genders

01:13:28
different target participants, (someone who had that cancer in the family)

01:13:30
compaing different age groups within the seses - maybe women of 30 would do differently to one of 70 for example

01:13:31
qualitative interviews

01:13:36
Use the same questionnaire and study high risk patients

01:13:40
High-risk women and men

01:13:42
one gender group

01:13:52
Does the alternatives not refer to the choices of the writer?

01:14:02
Publishing in another journal

01:14:19
ok

01:14:31
Different types of cancer - one that affects both men and women

01:14:35
motivation and awareness

01:15:02
social demographic of people- not just government employees, and the education of participants

01:19:13
if women are more likely to get tested, this may be related to education given to women about their health

01:21:44
how gender, age, demographic influence people awareness on the risk of having cancer

01:21:54
alternative, to explore willingness/attitude to testing for those who are at higher risk, focussing on how to encourage testing (only if there is value in knowing of course), greater risk in this alternative, greater chance of benefit (based on testing with a purpose of reducing risk of disease), targeted to reduce development of illness

01:22:29
Two different questionairs - how can you compare the attitudes if there are different questionnaires? One questionnaire would be better

01:23:56
2 types of cancer, 2 types of gender, 2 types of quiz - difficult to compare...

01:24:40
alternative, changing the age range from 18 to 30, 31 to 50, 51 to 74. Coz at different generation they might have different education level.

01:25:32
(a general question) can we apply this 4-step process to the abstract only (at least for the first pass) before delving into the details? Or do you recommend reading the whole paper before starting this process?

01:25:47
yes, a version but more structured

01:25:55
I think so, not 100% sure until I tackle a new article

01:26:34
What happens when you are new to the subject? How can you effectively evaluate the strength and weakness?

01:26:48
great thanks!

01:27:12
need to read conclusions as well

01:29:41
Yes.

01:36:05
generally how long it takes to do a critical reading of a reasonably difficult paper?

01:43:08
Hi Cassily, I can see the applications to this for your example - the article I chose seems to be a lot more about the method development to solve a problem - method 1, method 2, optional extra to both methods allows issue to be somewhat resolved. For something like this is it okay to have a lot less choices than the example we went through together?

01:43:08
easier in own field

01:43:12
a new way of thinking

01:43:15
paper survey used to ask about service delivery resulting, in loss of ability to explore the role in depth, personal interview

01:43:23
Agreed about easier in own field

01:43:29
yes easier in own field

01:43:36
Could have used different thresholds in experiments. Point of view on the alternative is that it could significantly alter the results. Supportive evidence could be of using different models and more specific models

01:43:40
Its new and keeps me asking questions but it slows me down

01:43:44
yes it is easier in own feild

01:46:04
would we look critically at the aims of a study or just the choices?

01:46:07
thank you!

01:46:09
thank you. very helpful

01:46:10
Thank you!

01:46:10
Thank you

01:46:11
thank you very much

01:46:12
Thank you for the session

01:46:16
thank you it has been really helpful

01:46:17
Thank you

01:46:17
thank you

01:46:19
Many thanks

01:46:22
Thank you

01:46:23
Thank you Cassily :)

01:46:25
Thanks

01:46:31
great, thank you

01:46:38
Thank you so much.

01:46:41
Thank you

01:46:44
Thank you, Cassily!

01:46:46
Thank you so much!! This was super useful :)

01:47:21
Thanks heaps...

01:47:59
Thank you :)