Spring 2016

Advances in Measuring Behavior

PHTH 5228
Bouvé College of Health Sciences

Credit Hours:		3 SH
Class Location:		Ryder Hall 435
Class Time:		5:00-7:30 PM Wednesdays (Remote participation is possible)
First Class:		Wed Jan 13, 2014
Last Class:		Wed Apr 20, 2014
Final exam:		None
Discussion group:		piazza.com/northeastern/spring2016/phth5228
Instructor:		Stephen Intille, Ph.D.
Office:		910-177 (9th Fl) (Office 924)
Office Hours:		Tue 8:30-9:30, immediately after class, or arranged via email
Email:		...@neu.edu

Catalog Description:

Offers a survey and project-oriented course examining current and emerging methods of measuring human behavior known to impact human health. Discusses some of the most common instruments used to measure everyday behaviors and considers how emerging technologies may change how these behaviors are measured in the future. Explores the measurement of behaviors such as the following: activities of daily living, dietary decision making, patterns-of-eating behavior, physical activity, sedentary behavior/posture, screen time, activity in the community, social-connectedness, stress and stressful events, affective state, medication adherence, use of alcohol and addictive substances, risky behaviors, and physiological states that can be measured using wearable devices in the field (e.g., heart rate and blood pressure). Prereq. Senior or graduate standing.

Levels: Graduate, Undergraduate
Type: Seminar

Prerequisites:

No course prerequisites. The tools necessary to develop the project will be made available and described in class, but students do need to be comfortable with basic use of computers and mobile phones and have an interest in using technology for advanced behavioral measurement. Students are not required to know how to program computers, and this course does not require programming expertise.

Course Objectives:

By the conclusion of this course, students will be able to:

• Describe why behavior measurement is important for public health and public health research,
• Explain why it is difficult to measure behavior,
• Compare and contrast how a variety of behaviors are measured today and the pros/cons of the most popular instruments used in research,
• Critique papers describing new instruments,
• Describe how emerging technologies may change behavior measurement,
• Describe some of the new systems/software available today that could be used to measure behavior,
• Use low-fidelity prototyping to construct ideas for new instruments that may use emerging technologies, and
• Evaluate a prototype implementation of a new instrument created by the student and analyze the results of small-scale feasibility testing.

Classroom Format: 

Most classes will consist of a short introductory overview lecture or discussion on measuring a particular human behavior followed by student presentations on instruments described in the readings. Some classes will be devoted to pilot testing of project ideas using low-fidelity (i.e. paper) prototyping and instruction on how to convert existing surveys to run on mobile devices (using off-the-shelf ecological momentary assessment software). Weekly readings consist of research articles.

For each topic area, students will (1) learn why measuring the behavior is important for public health, (2) read and discuss research papers on measuring these behaviors and the design, validation, and use of 2-3 surveys/instruments commonly used in recent research, (3) read and discuss 1-3 research papers measuring the same behavior using an emerging technology, and (4) explore how the measurement of the behavior might be improved in the future. Some classes may include guest visits by researchers who have used or developed specific instruments or who are working with the students in the same general area as the projects. Coursework will consist of presentations on reading material, short assignments identifying and organizing research papers on measurement of particular behaviors, and an extended paper assignment where students propose a new measurement technology and an experiment to convincingly validate that technology. If the makeup of the students permits, the class may actually try to implement and test one or more of the ideas proposed in a collaborative project.

Required and Optional Texts:

This course has a moderate but steady reading load with an average of 5-8 research papers per week. Readings will be available online. Those that are not will be distributed in class or available in a course reader.

Additional Materials: 

None required. Phones and/or smartwatches will be provided for testing the projects as needed.

Course Schedule/Outline:

(Note: schedule and readings may be modified slightly during the semester)

Class	Subjects	Readings Due (Beginning of class)	Assignments Due (Beginning of class)
Wed Jan 13 (Class 1)	Introduction to the course; Why measure behavior?	None
	Using the research tools to find measurement 'geneaology'
Wed Jan 20 (Class 2)	Overview of emerging technologies for measuring behavior (Electronic EMA, sensors, CS-EMA, CAT)	Booth, 1977, A short history of blood pressure measurement Stone, Shiffman, et al., 2002, Patient non-compliance with paper diaries Smyth and Stone, 2003, Ecological Momentary Assessment research in behavioral medicine S. S. Intille, Technological innovations enabling automatic, context-sensitive ecological momentary assessment Rappaport and Smith, 2010, Environment and disease risks Kix, 2011, Something in the water Sikkes et al., 2011, A systematic review of Instrumental Activities of Daily Living scales in dementia: Room for improvement	Complete IRB training and send Stephen a PDF showing your certificate of completion Responses to survey email
	Common Data Elements Toolkits	Hamilton et al., 2011, The PhenX Toolkit: Get the Most From Your Measures PhenX Demographic surveys PhenX Anthrometric surveys Skim: PhenX Toolkit Skim: GEM Skim: CDE
Wed Jan 27 (Class 3)	Experience sampling Day Reconstruction Method	Bolger et al., 2003, Diary Methods: Capturing Life as it is Lived Kahneman et al., 2004, A survey method for characterizing daily life experience: The Day Reconstruction Method Review: Experience Sampling and Ecological Momentary Assessment with Mobile Phones Hartung et al., 2010, Open Data Kit: Tools to Build Information Services for Developing Regions Froehlich et al., 2007, MyExperience: A System for In Situ Tracing and Capturing of User Feedback on Mobile Phones Hicks et al, 2010, AndWellness: an open mobile system for activity and experience sampling Gerken et al., 2010, Pocket Bee Websites to skim over: MobXamp, MyExperience, ESP, Affect-Sampler, AndWellness, UrbanSensing, T2 Mood Tracker, invivodata, OpenDataKit, PRIMIExperience, CAESSA,	Research assignment #1 due
	Experience sampling on watches	Kim et al., 2013, Co-variation of depressive mood and locomotor dynamics evaluated by ecological momentary assessment in healthy humans Kim et al., Systematic comparison between ecological momentary assessment and day reconstruction method for fatigue and mood states in healthy adults, 2013
Wed Feb 3 (Class 4)	Discussion Assignment #1
	uEMA and class project	uEMA paper/grant submissions and review responses (Blackboard)
Wed Feb 10 (Class 5)	Data entry via habits? Thinking creativily about using citizen scientists	Tierney, 2011, To Choose is to Lose: Do you Suffer from Decision Fatigue? (Blackboard) Chapter selection from Duhigg, The Power of Habit: Why We Do What We Do in Life and Business Overview of the Precision Medicine Initiative Silvertown, 2009, A new dawn for citizen science Bonetta, 2009, New citizens for the life sciences Aanensen et al., 2009, EpiCollect: Linking smartphones to web applications for epidemiology, ecology and community data collection	Research assignment #2 due
Wed Feb 17 (Class 6)	Discussion Assignment #2
	Introduction to paper prototyping and in-class design exercise	Rettig, 1994, Prototyping for Tiny Fingers Clark, 2010, TapWorthy Chapter 3: Tiny Touchscreen (Blackboard) Colborn, 2011, Simple and Usable Displace, Hide, Organize, and Remove Chapters (Blackboard) Reinventing the emoticon Conner, 2015, Experience sampling and ecological momentary assessment with mobile phones M. Richtel, 2014, E-Cigarettes, by Other Names, Lure Young and Worry Experts
Wed Feb 24 (Class 7)	Measuring stress, stressful events, and stress management; Measuring affective state Measuring physiological state (HR, blood pressure, GSR)	Cranford et al., 2006, A Procedure for Evaluating Sensitivity to Within-Person Change: Can Mood Measures in Diary Studies Detect Change Reliably? Killingsworth and Gilbert, 2010, A Wandering Mind is an Unhappy Mind Wilhelm and Grossman, 2010, Emotions beyond the laboratory: Theoretical fundaments, study design, and analytic strategies for advanced ambulatory assessment Goodwin, Velicer, and Intille, 2008, Telemetric monitoring in the behavior sciences G. Kolatanov, 2015, 2 Numbers to Make Your Head Swim	Paper prototyping assignment due
	Project planning discussion
Wed Mar 2 (Class 8)	Measuring diet	Thompson and Subar, Dietary Assessment Methodology (On Blackboard) Boushey et al., Use of technology in children's assessment Thompson et al., 2010, Need for technological innovation in dietary assessment
	Measuring eating behaviors and decision making	Amft and Troster, 2008, Recognition of dietary activity events using on-body sensors (skim) Van't Riet et al., The importance of habits in eating behaviour. An overview and recommendations for future research
Wed Mar 9	No class - Spring Break
Monday Mar 14
Wed Mar 16 (Class 9)	Experiment critique and discussion	L. J. Cronbach and P. E. Meehl, 1955, Construct validity in psychological tests
	Measuring physical activity/exercise	van Poppel et al., 2010, Physical Activity Questionnaires for Adults: A Systematic Review of Measurement Properties (On Blackboard) Ainsworth, 2008, How Do I Measure Physical Activity in my Patients? Tudor-Locke et al., 2011, Pedometry Methods for Assessing Free-Living Adults (On Blackboard)
	Measuring sedentary behavior/posture	Healy et al., 2011, Measurement of Adults’ Sedentary Time in Population-Based Studies Kozey-Keadle et al., 2011, Validation of Wearable Monitors for Assessing Sedentary Behavior
Wed Mar 23 (Class 10)	Introduction to item response theory	Pilkonis et al., 2011, Item banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS): Depression, anxiety, and anger Baylor et al., 2011, An introduction to item response theory and rash models for speech-language pathologists	Research assignment #3 (study idea critique)
	Measuring sleep	Buysse et al., 1898, The Pittsburgh Sleep Quality Index: A New Instrument for Psychiatric Practice and Research Johns, 1991, A new method for measuring daytime sleepiness: The Epworth Sleepiness Scale Van De Water et al, 2011, Objective measurements of sleep for non-laboratory settings as alternatives to polysomnography – a systematic review Lockley et al., 1999, Comparison between subjective and actigraphic measurement of sleep and sleep rhythms How I Achieved Better Sleep McCrae et al., 2005, Sleep Complaints, Subjective and Objective Sleep Patterns, Health, Psychological Adjustment, and Daytime Functioning in Community-Dwelling Older Adults
Wed Mar 30 (Class 11)	Measuring screen time (TV, computer, video games) and exposure to media	Bryant et al., 2006, Measurement of television viewing in children and adolescents: A systematic review Potter, 2008, The Importance of Considering Exposure States When Designing Survey Research Studies Info on the Portable People Meter: Article1 and Article2 Evans and Wobbrock, 2011, Input Observer: Measuring Text Entry and Pointing Performance from Naturalistic Everyday Computer Use Optional: Steeves et al., 2012, A Review of Different Behavior Modification Strategies Designed to Reduce Sedentary Screen Behaviors in Children Optional: Jennes and Pierson, 2011, Audience Measurement and Digitalisation: Digital TV and Internet
	Project planning and discussion	Riley, Serrano, Nilsen, and Atienza, 2015, Mobile and wireless technologies in health behavior and the potential for intensively adaptive interventions (Blackboard)
Wed Apr 6 (Class 12)	Measuring risky behaviors (i.e., driving, home safety)	Naito et al., 2010, A Browsing and Retrieval System for Driving Data M. Akamatsu, Measuring driving behavior	Final paper part 1 due
	Measuring activity in the community (i.e. use transportation, context) ; Measuring social-connectedness/social-interaction/isolation	Eagle et al, 2009, Inferring friendship network structure by using mobile phone data E. Berscheid, M. Snyder, and A. M. Omoto, The Relationship Closeness Inventory: Assessing the closeness of interpersonal relationships S. Golder and M. Macy, 2014, Digital Footprints: Opportunities and challenges for online social research
Wed Apr 13 (Class 13)	Measuring activities of daily living (ADLs, iADLs)	Boissy et al., 2007, The eSMAF: a software for the assessment and follow-up of functional autonomy in geriatrics Le et al., 2008, Health Smart Home for elders – A tool for automatic recognition of activities of daily living Optional: Zingmond et al., 2011, Association of Claims-based Quality of Care Measures With Outcomes Among Community-dwelling Vulnerable Elders
	Pain	Turk et al., 2006, Developing patient-reported outcome measures for pain clinical trials: IMMPACT recommendations
Wed Apr 20 (Class 14)	Project presentations	None	Final presentation and project due

Course subject content is tentative and may change during the semester.  Students will be notified of such changes.

Grading Procedures and Criteria:

Prior experience suggests that work in this course will generally fall into one of four categories:

• Superior, striking, or unexpected pieces of work with excellent effort demonstrating a mastery of the subject matter and a thoughtful use of concepts discussed in class; work that shows imagination, clarity of presentation, originality, creativity, effort, and attention to detail.
• Good work demonstrating a capacity to use the subject matter, with adequate preparation and clear presentation.
• Work that is adequate but that would benefit from increased effort or preparation.
• Work that needs more effort.

Course work falling into these categories correspond roughly to A, B, C, and D grades. The final grade for the course will be computed by weighting the results from each assignment according to the following formula:  

• Class presentation(s) (10%)
• Research assignment #1 (10%)
• Research assignment #2 (10%)
• Paper prototyping assignment (10%)
• Research assignment #3 (Study idea critiques) (10%)
• Study paper draft #1 (20%)
• Final project paper and presentation (25%).
• Engagement (5%)

Research assignments
Students will identify a health-related behavior or state and develop an annotated bibliography tracing the the history of measurement of the behavior and identifying the major methods of measurement used today and potentially used in the future. The assignments will be evaluated based on thoroughness of the research and organization of the information acquired. The third assignment will involve critiquing ideas proposed by other students.

Paper prototyping assignment
Students will develop an idea for a microinteraction behavioral data collection experiment, based on techniques discussed in class. The assignment will be evaluated based on thoroughness of the work and evidence the strategies for fast evaluation of the technology have been used.

Class presentations 
Students will make presentations on the behavior measurement methods or technology described in the readings. Students will be provided with a template for the presentations using a variation of the Pecha Kucha format, which keeps presentations concise (6.5 minutes). Students will be expected to have practiced the presentation in advance. Presentations will be graded on adherence to the format and overall presentation clarity, as well as demonstration by the student of a thorough understanding of the topic being discussed and ability to launch a class discussion about the material. In a small class, students will present most classes. Presentations will be less frequent if more students enroll.

Engagement
All students are expected to have completed all assigned readings prior to each class. Actively engaging in verbal exchanges of ideas and concepts will be a major component of learning in this course. This will be stimulated by readings and class presentations and discussions. Therefore everyone will be expected to actively and positively listen to others and to communicate their ideas during class. Some students are less comfortable speaking in class than others, but open discussion of ideas and even disagreement is essential.  Therefore, all students are expected to read course materials prior to class and will be called upon at times even if they do not raise their hands. Participation does not result from talking a lot, but as a result of critical thinking and articulation of ideas.

Preliminary final paper
Students will write an 4+ page paper (CHI format) on the experiment they propose. The paper should include references to relevant scientific literature and a description of the pros/cons of the new technology relevant to the older methods. The paper should discuss how both the old and new methods have (or will or could be) validated. The paper will be evaluated on how well the project shows that the student has mastered and can creatively apply the topics in the course, as well as clarity, grammar, spelling, attention to detail, and overall organization. This paper will evolve into a final paper.

Final project design, presentation, and revised final paper
Students will complete an 8+ page paper (CHI format) on the experiment they propose, taking into account the feedback they received on the draft and the additional readings and research they have done. Students will present their work in a final presentation and hand in a high-quality scientifically-written paper. Presentations will be graded on adherence to the format and overall presentation clarity, as well as demonstration by the student of a thorough understanding of the topic being discussed.

Note: Students with technical backgrounds, such as CCIS or Health Informatics students, will have the option of developing a more advanced behavioral measurement system in lieu of the course paper requirement.  

Classroom Policies:

Students are expected to demonstrate qualities of academic integrity: a commitment, even in the face of adversity, to five fundamental values:  honesty, trust, fairness, respect and responsibility.  
 
University policy dictates that students must seek the instructor’s permission to tape record class lectures.  I will always allow the use of tape recorders to support your learning.

To facilitate discussion and learning, electronic devices must be turned off in class, including laptops, tablets, and phones. Slides shown in class will be available on the course website after each class. 

Despite the dinner time meeting time of our class, students should not eat in class out of respect for others.

Writing/Presentation Policies:

Assignments that involve writing and presentation will be judged on clarity of presentation as well as content. Students who are having difficulty with writing will be referred to the Northeastern University Writing Center.

Late Policy:

Prior to an assignment due date, a student may request an extension for extenuating circumstances.  It is the discretion of the instructor to permit late assignments.  Unexcused late assignments will be subject to a reduction of one half letter grade for every two days late.

Academic Honesty:

All students are expected and encouraged to discuss the topics raised by this course with each other. Ideas or content (including graphical content) incorporated from an outside source or another student must be documented appropriately in the app submissions, write-ups, and presentations. Students must abide by the NU Code of Student Conduct and Academic Integrity Policy. Acts of academic dishonesty will be referred to the Office of Student Conduct and Conflict Resolution.

Academic honesty is fundamental to the learning process. As a reminder,  

• Students are expected to present as their own only that which is clearly their own work in tests and in any material submitted for credit.  Students may not assist others in presenting work that is not their own. 
• Purchasing term papers from commercial firms or individuals is a serious violation of University policy.  Offenders are subject to disciplinary action (Office of Judicial Affairs). (Undergraduate and Graduate Student Handbook, 2000-2001, p.108)
• Any member of the academic community who witnesses an act of academic dishonesty should report it to the appropriate faculty member or department chair (or equivalent).  The charge will be investigated and if sufficient evidence is presented the case will be referred to the Northeastern University Student Judicial Hearing Board.
• Plagiarizing includes: representing someone’s else’s work as your own, insufficient acknowledgement, receiving or giving unauthorized help on choosing a topic, analyzing data, or drawing conclusions.  Students should not use the same paper or portions of a paper for two courses without explicit permission from professors of both courses.

Any student found cheating on an assignment will receive a zero on that assignment.  A second offense will result in a failing grade for the entire course.

Accommodation:

Students who have a disability are encouraged to seek accommodations though the University Disability Resource Center.  If the Disability Resource Center has formally approved you for an academic accommodation in this class, please present Prof. Intille with your "Professor Notification Letter" during the first week of the semester and speak privately with me about your needs for accommodations and strategies to support your success. This information will be kept confidential.

Title IX:

Title IX makes it clear that violence and harassment based on sex and gender are Civil Rights offenses subject to the same kinds of accountability and the same kinds of support applied to offenses against other protected categories such as race, national origin, etc. If you or someone you know has been harassed or assaulted, you can find the appropriate resources here: http://www.northeastern.edu/oidi/titleix/.

Trace:

The instructor will distribute optional mid-term and final course evaluations, to be returned anonymously. Responses to the questions help to improve this course during the current semester and for future students. Significant modifications to the design of this course have been made based on prior surveys returned.

All students are also strongly encouraged to use the TRACE (Teacher Rating and Course Evaluation) system near the end of the course to evaluate this course. A reminder about TRACE should arrive via email about two weeks before the end of the course.