In our first Research Services "Explore!" lunch and learn session for 2019-2020, we will explore logic models and how this traditional program evaluation tool can also be used in health research.
How to Accelerate the Dissemination & Impact of Your Research WorkKatja Reuter, PhD
This presentation is part of the Digital Scholar Training Series at USC and CHLA. Learn more about the initiative: http://sc-ctsi.org/digital-scholar/
News story: http://sc-ctsi.org/index.php/news/new-digital-scholar-training-initiative-helps-researchers-better-utilize-we#.VDhIWWK9mKU
Want to work with students to promote OER? Learn how to collaborate with student government and other leaders on faculty outreach, survey collection, and more with the Student PIRGs.
Evaluation for Impact and Learning Asia Value Advisors Nov 6 2014Victor Kuo
The workshop will overview intermediate and advanced concepts of evaluating the impact of philanthropic foundations as well as the organizational systems that support impact evaluation and learning within foundations. Main topics include: prioritizing evaluation audiences and purposes, selecting among a range of evaluation designs (randomized controlled trials, quasi-experimental designs, correlational studies, descriptive studies); organizational readiness for evaluation and learning; and organizational learning. A range of practical tools for developing evaluation projects and for building organizational practices in evaluation and learning will also be shared. Current debates, criticisms, and possible ways forward will be presented using select cases and illustrations. Participants will be encouraged to bring their own examples, offer honest appraisals, and identify ways to advance their own philanthropic work. (This workshop is at an intermediate level; basic concepts of evaluation will be reviewed briefly in the context of more advanced topics.)
How to Accelerate the Dissemination & Impact of Your Research WorkKatja Reuter, PhD
This presentation is part of the Digital Scholar Training Series at USC and CHLA. Learn more about the initiative: http://sc-ctsi.org/digital-scholar/
News story: http://sc-ctsi.org/index.php/news/new-digital-scholar-training-initiative-helps-researchers-better-utilize-we#.VDhIWWK9mKU
Want to work with students to promote OER? Learn how to collaborate with student government and other leaders on faculty outreach, survey collection, and more with the Student PIRGs.
Evaluation for Impact and Learning Asia Value Advisors Nov 6 2014Victor Kuo
The workshop will overview intermediate and advanced concepts of evaluating the impact of philanthropic foundations as well as the organizational systems that support impact evaluation and learning within foundations. Main topics include: prioritizing evaluation audiences and purposes, selecting among a range of evaluation designs (randomized controlled trials, quasi-experimental designs, correlational studies, descriptive studies); organizational readiness for evaluation and learning; and organizational learning. A range of practical tools for developing evaluation projects and for building organizational practices in evaluation and learning will also be shared. Current debates, criticisms, and possible ways forward will be presented using select cases and illustrations. Participants will be encouraged to bring their own examples, offer honest appraisals, and identify ways to advance their own philanthropic work. (This workshop is at an intermediate level; basic concepts of evaluation will be reviewed briefly in the context of more advanced topics.)
The Dynamic Role of Social Media in Medical EducationMichael Gisondi
Grand Rounds lecture presented at Palmetto Health Richland Emergency Medicine Residency Program / University of South Carolina School of Medicine, August 2016.
Social Media Provides a Unique Platform for Clinical Information Exchange: Ex...Cheryl Crow
The "Pediatric Occupational Therapists" Facebook group consists of over 24,000 OTs, COTAs and students and provides a forum for members "assist, support and guide each other." Hundreds of posts are discussed weekly, yet little is understood about this relatively new medium. This poster contaisn a description of conversation content and a discussion of the potential benefits and drawbacks to engagement on this medium. Results show that the most frequently discussed topics are specific case scenarios and general clinical advice. Advantages of participation include real time clinical information sharing and clinical support, and drawbacks include privacy concerns and the lack of curation of information.
Social media is a powerful and widespread source of information and connectivity. Many in research are wondering whether and how to use social media to improve awareness and retention for their clinical trials. Quorum Review's Regulatory Attorney, Dominic Chiarelli, presents about the power of social media and practical tips for how to best harness social media in research.
NU Innovation in Teaching Series: Social Media in Medical EducationMichael Gisondi
"The Dynamic Role of Social Media in Medical Education" presented at The Garage of Northwestern University in the Innovation in Teaching Series by Dr. Michael Gisondi, Associate Professor of Emergency Medicine and Medical Education, Northwestern University Feinberg School of Medicine. October 17, 2016.
Better Research Papers: Workshop Your Handout - Faculty WorkshopMargot
Tuesday, August 26th, 2014, led by Margot Hanson and Michele Van Hoeck
BETTER RESEARCH PAPERS: WORKSHOP YOUR HANDOUT
2:00-3:30 PM, LIBRARY GREEN ROOM
Would you like to see higher quality research papers from students? Are you discouraged by grading papers with weak sources or insufficient citation? Drawing on recommendations from studies of student research habits, as well as librarian experience working with Cal Maritime students, attendees will work with a partner to revise one of their own research assignment handouts (prompts).
NOTE: Please bring a paper copy of one of your research paper assignments to the workshop.
Discussion of research uptake and impact activities and reflections from our work on unsafe abortions in Zambia: ESRC DFID Poverty Alleviation ConferenceTuesday 9 September 2014
You Are What You Tweet - Physicians, Professionalism, and Social MediaDavid Marcus
A brief intro to social media and discussion on the way that GME educators should approach SoMe. Delivered at the Lenox Hill Hospital GME Sub-Committee Retreat on March 31st, 2016.
Researchers, Reporters & Everything in BetweenKara Gavin
A talk about how academic researchers can understand and navigate the news media and institutional communications landscape, prepared for the University of Michigan National Clinician Scholars Program
The Dynamic Role of Social Media in Medical EducationMichael Gisondi
Grand Rounds lecture presented at Palmetto Health Richland Emergency Medicine Residency Program / University of South Carolina School of Medicine, August 2016.
Social Media Provides a Unique Platform for Clinical Information Exchange: Ex...Cheryl Crow
The "Pediatric Occupational Therapists" Facebook group consists of over 24,000 OTs, COTAs and students and provides a forum for members "assist, support and guide each other." Hundreds of posts are discussed weekly, yet little is understood about this relatively new medium. This poster contaisn a description of conversation content and a discussion of the potential benefits and drawbacks to engagement on this medium. Results show that the most frequently discussed topics are specific case scenarios and general clinical advice. Advantages of participation include real time clinical information sharing and clinical support, and drawbacks include privacy concerns and the lack of curation of information.
Social media is a powerful and widespread source of information and connectivity. Many in research are wondering whether and how to use social media to improve awareness and retention for their clinical trials. Quorum Review's Regulatory Attorney, Dominic Chiarelli, presents about the power of social media and practical tips for how to best harness social media in research.
NU Innovation in Teaching Series: Social Media in Medical EducationMichael Gisondi
"The Dynamic Role of Social Media in Medical Education" presented at The Garage of Northwestern University in the Innovation in Teaching Series by Dr. Michael Gisondi, Associate Professor of Emergency Medicine and Medical Education, Northwestern University Feinberg School of Medicine. October 17, 2016.
Better Research Papers: Workshop Your Handout - Faculty WorkshopMargot
Tuesday, August 26th, 2014, led by Margot Hanson and Michele Van Hoeck
BETTER RESEARCH PAPERS: WORKSHOP YOUR HANDOUT
2:00-3:30 PM, LIBRARY GREEN ROOM
Would you like to see higher quality research papers from students? Are you discouraged by grading papers with weak sources or insufficient citation? Drawing on recommendations from studies of student research habits, as well as librarian experience working with Cal Maritime students, attendees will work with a partner to revise one of their own research assignment handouts (prompts).
NOTE: Please bring a paper copy of one of your research paper assignments to the workshop.
Discussion of research uptake and impact activities and reflections from our work on unsafe abortions in Zambia: ESRC DFID Poverty Alleviation ConferenceTuesday 9 September 2014
You Are What You Tweet - Physicians, Professionalism, and Social MediaDavid Marcus
A brief intro to social media and discussion on the way that GME educators should approach SoMe. Delivered at the Lenox Hill Hospital GME Sub-Committee Retreat on March 31st, 2016.
Researchers, Reporters & Everything in BetweenKara Gavin
A talk about how academic researchers can understand and navigate the news media and institutional communications landscape, prepared for the University of Michigan National Clinician Scholars Program
Building Research Partnerships for Public Health ImpactDr. Ebele Mogo
How can collaborative research be used to drive social impact? A presentation as a panelist at the Society for Social Medicine's Early Career Researcher Workshop 2020
Presentation on Social Media presented Wednesday, November 19, 2014 at University of Minnesota, Division of Gynecologic Oncology Annual Translational Working Group Research Day
Connectivism: building mastery in connectingHelen Bevan
The slides from the workshop run by Helen Bevan, Christian von Plessen and Goran henriks at the Jonkoping Microsystem Festival on 28th February 2018 #qmicro
An ever greater emphasis is being put upon the need for academic research to make an impact in the real world, whether that be supporting teaching; helping organizations to be better managed; influencing public bodies and policymakers; contributing to economic development; or benefitting society and the environment. While citations are the established measure of academic influence, and downloads and altmetrics can be seen as measures of ‘attention;’ funders and institutions are now looking for evidence of measurable change. This presentation explores how the academy and industry view the impact of academic output, will explore evidence of theory being applied in practice, and look at how pathways to impact are achieved.
All in a Twitter: Using Social Media to Propel Your ScienceBryn Robinson
Using traditional methods of sharing research results - journals, conference presentations - have done an arguably poor job at true knowledge dissemination, both to other researchers and to those outside the field of study. In this presentation, I shared some tips for, and some examples of, increasing awareness and uptake of research results through social media strategies.
The Role of Social Media in Research Dissemination, Review and DevelopmentHelen Madamba
#HealthXPH Philippine Healthcare Social Media Summit 2017 "Social Media and Health Research: Connections that Matter" last April 25, 2017 at Marco Polo Hotel in Cebu City
Patient Engagement for Data Science, Technology & EngineeringCHICommunications
Learn the necessities and relationship between patient engagement and data science, engineering and technology.
Presented by Trish Roche, CHI's Knowledge Translation Practice Lead, this presentation is geared towards professionals in data science looking to hone their skills in patient engagement.
From the event "Specimen Science: Ethics and Policy Implications," held at Harvard Law School on November 16, 2015.
This event is a collaboration between The Center for Child Health and Policy at Case Western Reserve University and University Hospitals Rainbow Babies & Children’s Hospital; the Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School; the Multi-Regional Clinical Trials Center of Harvard and Brigham and Women's Hospital; and Harvard Catalyst | The Harvard Clinical and Translational Science Center. It is supported by funding from the National Human Genome Research Institute and the Oswald DeN. Cammann Fund at Harvard University.
For more information, visit our website at http://petrieflom.law.harvard.edu/events/details/specimen-science-ethics-and-policy
Professor Elizabeth Waters, Coordinating Editor of the Cochrane Public Health Review Group & Melbourne School of Population Health, University of Melbourne
Patient Engagement in Health Economic and Outcomes Research: Current and Future ISPOR Initiatives, presentation from the ISPOR 20th International meeting Philadelphia, May 2015, by the Patient Centered Special Interest Group
What is knowledge mobilization really all about? This is the question that the Saskatchewan Alliance for Youth and Community Well-being (SAYCW) asked me to answer on May 26, 2015.
A presentation to the Health Psychology in Public Health Network annual on practical, policy and research challenges in applying research to public health practice
Presented by John Young (ODI) and Laura Harper (Wellcome) at the Public Engagement Workshop, 2-5 Dec. 2008, KwaZulu-Natal South Africa, http://scienceincommunity.wordpress.com/
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
What is a Logic Model, and How Can it Help Me Organize My Research?
1. Explore!
What's a logic model, and
how can it help me
organize my research?
Bryn Robinson, PhD
Research Engagement Manager
Horizon Research Services
2. Outline
• What is a logic model?
• Why would you use one in health research?
• How do you build a logic model?
• Examples
• References and resources
3. Example: Vaccination Education
Letters with
information to
parents or
guardians
Information for public
health nurses to
share with families
Brochures
for parents
Posters in
doctors’ offices
and schools
Social
media
engagement
Website with
information
Public
information
sessions
4. What is a Logic Model?
• Visualization tool for applied research
• Identifies relationships:
• What you plan to do
• How you plan to do it
• What will then happen as a result of your actions
6. Activities
• What are you doing to make change?
• Is there a logical order to these events?
7. Example: Vaccine Education
• Distributing information:
• Information letters
• Brochures
• Website
• Social media posts
• Posters
• Hosting public talks
• Slides
Distributing and
Hosting are the
activities.
Clearly identify
something you do,
vs. what you need to
do it.
9. These are some inputs.
Ask:
Who is creating content?
How is it being produced?
What are your costs?
Example: Vaccine Education
• Information letters
• Website
• Brochures
• Slides for public talks
• Social media posts
• Posters
10. Outputs vs. Outcomes
• Frequent source of confusion
• Outputs
• “How do I know my activity happened?”
• Outcomes
• “How do I know my activity worked?”
11. Example: Vaccine Education
• Information letters
• Website
• Brochures
• Slides for public talks
• Social media posts
• Posters
Outputs: How do I know
the activities happened?
Indicators could be
manually or automatically
generated
# website visits
# attendees to talk
12. Example: Vaccine Education
• Information letters
• Website
• Brochures
• Slides for public talks
• Social media posts
• Posters
Outcomes: How do I know
the activities worked?
Did awareness increase?
Did knowledge improve?
Did vaccination rates
change?
13. Assumptions
• The underlying “if-then” assumptions represent the program’s
theory of change: how we think a policy or program will lead to
desired outcomes.
15. Example: Vaccination Education
Brochures sent
home for parents
Social media
engagement
Website with
information
Public information
sessions
ACTIVITIES OUTCOMES
Increased parental
awareness
Increased parental
knowledge
Improved
vaccination rates
OUTPUTS
# taken / # distributed
# likes & shares
# comments
# sessions
# attendees
# visits
# link shared
INPUTS
Graphic design
Content (Evidence)
Presenters
Staff on social
media
Production costs
Salary for staff
Staff to get evidence
16. PATIENTS
500 patients newly
diagnosed with
cancer, eligible for
this treatment
Example: Applying for a Grant
Three types of
assays to
diagnose cancer
Three
experimental
assays to
diagnose cancer
Patient-reported
outcomes
STUDY ACTIVITIES & INDICATORS STUDY GOALS
Identify strategies
for best diagnosing
this cancer
Explore new
methods of
characterizing
illness at molecular
level
Understand quality
of life and how
treatment impacts it
Progression-free survival
Overall survival
# identified biomarkers
# new mutations
# new mechanisms
Scores on quality of
life measures
Recruiting at the
following sites…
• Site 1
• Site 2
• Site 3
20. Resources
U Sask: Logic Models for Program Evaluation: https://teaching.usask.ca/articles/logic-models-purpose-and-parts.php
U Wisconsin: Program Development and Evaluation: https://fyi.extension.wisc.edu/programdevelopment/logic-models/
CDC: Making Logic Models Work for You: https://www.cdc.gov/dhdsp/pubs/docs/cb_september_2013.pdf
Community Tool Box: https://ctb.ku.edu/en
Examples:
• Allied Health Intervention for Older Adults in ED – Cassarino et al 2019 (10.1136/bmjopen-2019-032645)
• Addressing Social Inequity through Recreation – Elsborg et al 2019 (10.1186/s12889-019-7428-3)
21. Questions?
Bryn Robinson, PhD
Research Engagement Manager, Office of Research Services
ResearchServices@HorizonNB.ca
@brynphd
#ResearchAtHorizon #RechercheChezHorizon
Editor's Notes
When we create a program, an activity, an intervention, it is typically with the thought that, “If we deliver X then Y will occur”.
But how do we know X happened?
Did X actually lead to Y – or did it lead to Z instead?
What resources do you need to make all this happen?
Are these the right activities to do?
How do you know these happened?
Logic models are a tool with origins in program planning and evaluation, but are valuable in clinical health research, especially as our questions become more applied in nature. We see this in the terms out there to describe research: e.g., implementation science, KT, studies on cost-effectiveness
Logic models are a road map that illustrate how we think doing an activity will lead to a particular outcome (or what is known in PE parlance as “theory of change”).
It links projected outcomes with processes, the underlying theoretical assumptions of the program, and the shared relationships between the different components.
How a proposed program or activity is SUPPOSED to work
The “what we did” and how it leads to the “so what”
Can focus on any level of a policy, program or project: the entire organization, one of its component departments or programs, or just specific parts of that department or a program. Of course, the boundary between “what” and “so what” will vary accordingly. Examples later will so that.
Great tool to map out the parts of a research project, especially those that have a number of sub-studies or arms, and/or those that employ a number of different methodologies (e.g., mixed methods design).
Parts of the logic model – terms and definitions that we need to cover first
They can differ across discipline and project scope, but will frequently illustrate:
Inputs: The resources needed to implement the activities
Activities: What the program and its staff do with those resources
Outputs: Tangible products, capacities, or deliverables that result from the activities
Outcomes: Changes that occur in other people or conditions because of the activities and outputs
Impacts: [Sometimes] The most distal/long-term outcomes
Moderators/Assumptions: Contextual factors that are out of control of the program but may help or hinder achievement of the outcomes
Activities are the actions undertaken by the program or partners to produce outputs that then lead to desired outcomes; in other words, activities are what we do.
Decide whether the activities should be ordered sequentially. If so:
Think about the “logical” relationship among the activities—which may or may not be the same as how they unfold over time— and determine if some activities need to occur before others can be implemented
Above is the various “things” that we had on our earlier slide. When we look at these, we can see that they are really referring to two types of knowledge translation activities for this education program
What you need to do it = Inputs. Inputs are resources that go into a program or intervention; they are what we invest.
They include financial, personnel, and in-kind resources from any source.
Think about broad categories such as staff, equipment, data, funds, and partnerships.
Ask yourself: What are the key inputs without which the program cannot be implemented?
To identify the inputs for our activities, we would ask questions shown above. This exercise rapidly identifies where we may have made assumptions about who is doing what, or how much time is going into this program’s development and implementation.
What I find here is that people will quickly learn to scale back a program to essential parts to make change based on available resources, or to identify the need to apply for grants and other sources of funding.
Outputs are the direct, tangible results of activities; they are what we get.
Essential link between what we do, and what we want to happen.
Often forgotten, but always important to take a step back and ensure you have ways to capture these.
If you are proposing to do X, and that your theory of X is that it leads to Y, then you have to make sure X actually happened.
What are the key parts of the activity that had to take place so that the outcome could have a chance of taking place?
• Outcomes are effects of the program or initiative and may be indicated as short-term, intermediate, or long-term outcomes; outcomes are what we achieve.
What this begins to highlight is where we tend to see some challenges early in the design. For example, perhaps in this case the researcher was not planning on measuring any of these – just assuming that it would work; or, they were only going to measure at the end, not knowing what the baseline knowledge or awareness was.
What we hope has happened in this case, then, is that the person came up with the strategy because of a pre-implementation level of awareness and knowledge that then needed to be addressed through said strategy.
This is where we then uncover some truths that are fundamental to the design and success of the strategy
Think of broad categories: PEST (political, economic, social, and technological)
What supports and structures are you assuming are in place for this to work?
Be especially conscious of key moderators without which the program cannot be implemented
This is especially where the stakeholders who review your program model can help you avoid a lot of problems, remove barriers, etc.
Identify what links in the program logic will be facilitated or impeded by the presence or absence of sufficient levels of the moderator. Remember moderators can facilitate or impede the ability of one activity/output to generate a successor activity/output, one activity/output to generate an outcome, a proximal outcome to generate a more distal outcome
You’ve considered which aspects of the program to emphasize, the target population, and the type of logic model needed; it’s now time to design your logic model. While many logic models are presented in a linear diagram from left to right, logic models can be presented visually in various forms, designs, and levels of technicality. As mentioned earlier, there are some common components of logic models that are often useful in describing your program: inputs, activities, outputs, outcomes, and impacts.
Have people review it
Update it after your program has been running – do assumptions still hold true?
Are you still doing the same activities? Which outcomes and deliverables have been achieved?
Create a narrative to go with the logic model. A one-page logic model will not be able to capture all the nuances of the program. The narrative will help explain the components of the logic model and how they work together to accomplish the outcomes. The narrative should include the following:
An expanded description of the activities, outcomes, and other components of the logic model
Any key linkages between activities, between activities and outcomes, and between different outcomes
Attribution v. contribution to outcomes, etc.
Stakeholder expectations for what will be accomplished, etc.
If it is important to see the link between each input and the activity it affects, then draw arrows from each input to the related activity
A few more examples of logic models that I’ve developed for research, to show you that it’s not always one formula to produce them, or as detailed in the operations of a program as others.
This one was for a grant submission, as part of a massive project with many parts: 6 separate “studies” with additional layers of PROMs. Wanted to show funders the overall gist of the proposed project, so I modified the approach to show activities with outcomes (as showing straight outputs would be too detailed for these purposes, e.g., # assays performed, etc.), and how the overall goals the team had to write for the grant are linked to different parts of the overall study.
This one was produced for a group that was recently reviewing its programs, and wanted a way to guide their future research so that it aligns with values and priority areas identified in a recent strategic planning session. It’s also an example that your models do not have to absolutely adhere to the linear model with columns; you can start with that but then as you link the parts and consider that narrative that you’re creating, there may be other ways to better illustrate things.
To recap, logic models can help you focus your work and clearly illustrate the linkages among investments and results that creates a theory of change.
Identify missing resources:
We focus more on the what we will do and the change that we think is going to have
We usually start with an idea of what we want to do and how we think we will change something
Which starts us later in the logic model, and then we can forget to critically look at the earlier stages
It’s a bullet list – doesn’t have to be to the SKU# of the test tube you’re purchasing but if you’re designing a trial and don’t have materials for lab kit figured in, then you run the risk of missing something
Show gaps in X to Y
Uncover hidden assumptions about our programs or activities that we have had
At the very least, one of the reasons that I would recommend using logic models for research studies, is that by mapping this information, you have to explicitly consider areas that do not have enough resources, or where assumptions are being made
Can help us course-correct:
Lets us see in these earlier stages when things are going off the rails.
It might takes years to reach the outcome of interest (education), because there are so many changes that need to occur in the black box before that time. Logic models help to capture the contents of the black box.
These are adaptable, so if we realize that we did not achieve our short-term outcomes, we need to look at our model. Can we achieve our long-term outcomes still? Is there another step or another measure that shows this change?
Check that our assumptions are appropriate:
Verify that our expectations for the program’s effectiveness are sound and realistic.
Knowledge translation: Can demonstrate progress:
Communicate information about our program to internal and external stakeholders in a reader-friendly, visual manner.
It shows funders progress – if they are interested in ROI, again may not happen for years, but we can show that our program or project is still making a difference and is on the right path.
Ensure that there is clarity and consensus among those who fund and deliver the program about the resources available to deliver the program, the key program activities and what they produce, and the program’s expected outcomes
Logic models are easy to use
You don’t need fancy materials
Paper and coloured pens or markers
Power Point
Gather your information
Protocol
Budget justification documents
Lab manuals that delineate processes
Informed consent documents that outline process
Websites, program brochures
Data from strategic planning meetings with stakeholders
Start sketching it out: Post-It notes, or paper and markers
If you’re stuck, go online and get inspired:
Then make it digital: PowerPoint
Make sure you circulate for feedback – great gap analysis