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Summary: Digital Health Communication (Master: CIS/CIW/NMD/BDM) 2024
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- Tilburg University (UVT)
Digital Health Communication Summary T & D Lectures, lecture notes and book summary for exam 2024.
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You're better off reading the lecture slides, this is an exact copy of that. And it even has some mistakes in it that make it harder to understand.
Voorbeeld van de inhoud
DIGITAL HEALTH COMMUNICATION EXAMT1 PERSUASIVE HEALTH TECHNOLOGY
Persuasive health technology: any technology purposely designed to influence, reinforce, change, or
shape health-related attitudes or behaviours (activity trackers/mobile application supporting
behaviour change, web-based tobacco prevention programs)
eHealth: (=health applications): the use of information communication technologies (ICT, like
computers of any kind) to deliver, or support the delivery of, health services (example: VR treatment
for pain reduction)
mHealth: the use of mobile wireless technology for public health (example: health insurance apps)
COM-B model: integration of 19 theories/frameworks
- Capability: whether a person has the knowledge, skills and abilities to engage in a behaviour
- Motivation: all the internal processes that trigger or inhibit a behaviour, and that ultimately
result in performing a particular behaviour instead of any other competing behaviour
- Opportunity: external factors that make execution of a behaviour possible
COM-B model:
- Interactions between determinants (and behaviour)
- Tool to identify barriers to behaviour change and to plan interventions
,Behaviour Change Wheel
Behaviour change intervention: coordinated set of activities/BCTs designed to change specified
behaviour patterns, usually spanning multiple intervention functions
Behaviour changes techniques (BCTs) Taxonomy:
- BCT: a component of an intervention designed to alter or redirect causal processes that
regulate behaviour; a technique is proposed to be an ‘active ingredient’
- For each intervention function, several BCTs have been identified that contributes to this
function
Persuasive technology:
Potential impact: trust in the effectiveness
- Increasing implementation of digital health solutions in hospitals
- Insurance companies develop their own apps
Article: Effectiveness of mobile health intervention apps on nutrition behaviours
Aim: determine the effectiveness of smartphone apps for changing nutrition behaviour and
nutrition-related health outcomes
Current status: which health Behaviour Change Techniques are employed most often?
Results:
- Overall, a small significant effect of app-based mobile interventions on nutrition behaviours
and nutrition-related outcomes.
, - Only studies targeting short term (<3 months) and/or intermediate-term (3-6 months)
follow-up intervals yielded significant (small)effect sizes; effects of long term (>6 months)
follow up not significant.
Other meta-analyses/reviews:
- Physical activity: interventions were only effective (significant) when the intervention
duration was 3 months or less (compared to longer interventions)
- Medicine adherence: 7/11 studies show app increased medicine adherence
- Alcohol intake: brief web-based interventions decreased the number of alcoholic drinks
consumed
- Digital (web) school-based behaviour changes interventions increased fruit and vegetable
intake and physical activity and reduced screen time in adolescents immediately after the
intervention; effects not sustained at follow up and no effects for alcohol intake and smoking
o Quality of studies/evidence low – very low
> Mixed findings, short(er) term effects larger, quality of evidence limited
Maximizing the impact of digital health applications:
- The effective components should be evident based: the application employs features that
target determinants from health behaviour theories / features that are based on behavioral
change techniques
- The uptake of the application should be sufficient: the app should be designed based on
scientific theories of technology acceptance and engagement. The app should be human-
centered.
A holistic framework to improve the uptake and impact of eHealth technologies
- High-tech with a low impact
- Low impact not because technology does not work
o Low support of health care professionals
o Not designed with user in mind, resulting in low uptake
- Real impact of eHealth technologies unknown
CEHRES roadmap:
Employing theory in digital health applications
, - In non-digital health interventions: effectiveness of intervention is higher when theory-based
and when it employs one or more behavioral change technique
- Aims:
o Provide overview of extent of theory use in digital health applications
o Determine importance of the extent of theory use
Extent of theory use in digital apps targeting weight management:
- Mentioning/referencing a theory:
o Just mentioning 18/24
o Explicitly describing the relationship between the theoretical constructs and
behaviour of interest 9/24
- Applications of the theory in intervention development
o Used theoretical predictors to select/develop intervention techniques 17/24
o Using theory/predictors to tailor intervention techniques to recipients 4/24
- Measurement and testing theory:
o Measuring theory-relevant constructs before and after the intervention 6/24
o Report reliability and validity of scales to measure theory-relevant constructs 3/24
- Building and refining theory:
o Discussing findings in relation to the theory 5/24
o Provided support for the theory (theory-relevant constructs were reported to
significantly mediate the relationship between the intervention and observed
behavioral change 1/24
o Reported using intervention results to build and/or refine the theory uppon which
the intervention was based, or formulate suggestions for future refinement 0/24
Importance of theory use in digital health applications
More likely to find a significant positive effect of the digital health intervention on weight related
outcomes when extent of theory use was higher, namely:
- At least one or more theoretical constructs are explicitly linked to an intervention technique
- When theoretical constructs are included in evaluations (measured pre and post
intervention)
T1.1: A THEORY-BASED ONLINE HEALTH BEHAVIOR INTERVENTION: STUDY PROTOCOL
,This study introduces an online program called U@Uni aimed at stimulating young adults adopt
healthier habits as they transition from school to university. The program uses three techniques to
encourage healthier behaviors: self-affirmation, theory-based messages, and implementation
intentions. By targeting behaviors like alcohol consumption, physical activity, fruit and vegetable
intake, and smoking, the program hopes to improve the health of students. If successful, this
approach could be used in other universities to promote healthy behaviors among new
undergraduates. However, there are some challenges, such as recruiting participants and ensuring
their engagement with the intervention. Additionally, the study is only being conducted at one
university, which could lead to potential contamination between the intervention and control
groups. Despite these challenges, the study aims to provide valuable insights into promoting healthy
behaviors during a significant life transition.
- What added value is expected from the use of digital technologies, according to the authors?
They hold the potential to deliver interventions designed to promote healthy lifestyle habits
to large sections of the population, can incorporate interactive materials in order to
maximize engagement and are 24-hours a day available and so can be assesed at critical
moments.
- Which theories are used in the development of the intervention?
Self-affirmation, theory-based messages, and implementation intention.
- What argumentation do the authors use for selecting these specific theories?
o People often resist messages about the health risks of certain behaviors to maintain
their self-integrity, because messages about future health risks threaten peoples’
physical integrity and their sense of being sensible, rational, “adaptively and morally
adequate” people.
o It is necessary for health messages to target the key motivational factors that
underlie such behavior.
o There is a “intention-behavior gap” and this obstacle to interventions seek to
promote healthy lifestyle habits, since interventions may increase people’s
intentions to change but fail to secure the corresponding change in behavior.
- How are these theories translated into intervention components?
o Self-affirmation task: participants will be asked to select their most important
personal value from a list of eight commonly held personal values or to provide their
own, and to briefly provide a reason why the value is important to them.
o Theory-based messages pertaining to each of the four targeted health behaviors,
which identified the key behavioral, normative and control beliefs underlying new
students’ intentions and behavior for each of the four health behaviors.
o A planner that contains instructions to form implementation intentions to facilitate
the translation of good intentions into action
T1.2: AN ONLINE HEALTH BEHAVIOUR INTERVENTION FOR NEW UNIVERSITY STUDENTS
,This study tested an online program to help new university students adopt healthier habits. They
sent emails to students before they started university, inviting them to join. The program included
self-affirmation exercises, health messages, and tasks to plan healthy behaviors. The results showed
that the program didn't significantly change most health behaviors like eating more fruits and
vegetables or being more active. However, it did have some positive effects, like reducing smoking
among students and lowering alcohol use based on a test.
Even though they improved student engagement compared to before, the program didn't make big
changes in the main health habits they targeted. They suggest that future programs should focus on
just one healthy habit at a time for better results.
- In the introduction it is described that the current study is a repeat trial. What were the main
findings of the first study, according to the introduction? What reasons do the authors
mention for repeating the original trial?
The trial was compromised by several limitations, which resulted in low levels of
engagement with the intervention
- Did they find any effects for the primary outcomes?
The effect of the intervention on fruit and vegetable intake approached significance
- Explain what a per-protocol analysis is and why do you think the authors perform that
analysis. Why do you think the authors mention that the results of the per-protocol should
be treated with caution?
A per-protocol analysis is a type of analysis in intervention studies where the outcomes are
assessed based on the participants' adherence to the prescribed intervention. It should be
treated with caution to control for selection bias, generalizability and randomization impact.
- What explanation do the authors give for the small effect sizes?
o The intervention sought to target four health behaviours in a single intervention and
online interventions that target several health behaviours typically have smaller
effects.
o Levels of engagement with the intervention were still relatively low.
o The baseline sample recruited into the study reported engaging in the
recommended health behaviours at a similar or greater extent than 16–24-year-olds
in England.
D1 OUTLINE OF CEHRES ROADMAP AND CONTEXTUAL INQUIRY
,CeHReS roadmap: provides guidelines for a holistic development, implementation, and evaluation
approach of e-health technologies.
Holistic approach: interrelationships between people, context, and technology are the key in the
development of e-health.
A good fit between these factors increases the chances of an intervention reaching it goals
To ensure this fit:
- The e-health development process should be flexible and iterative
- E-health development enquires multi-disciplinary development teams
Theoretical backbone of the roadmap: models and methods derived from:
- Persuasive design: COM-B model / behavior change wheel
- Participatory development
- Human centered design
- Business modelling
Behavior change wheel:
CHAPTER 7 EHEALTH
Holism: constructs as technology, people and context are all interrelated and interdependent, and
are all part of one whole instead of separate elements
,CeHRes Roadmap pillars:
- eHealth development is a participatory development process
- eHealth development creates new infrastructures for improving healthcare health, and well-
being
- eHealth development is intertwined with implementation
- eHealth development is coupled with Persuasive Design
- eHealth development requires continuous evaluation cycles
Five phases:
- Contextual inquiry
- Value specification
- Design
- Operalization
- Summative evaluation
EHealth development is flexible and iterative: one phase does not have to be finished before the
other
Multidisciplinary development teams:
o Professionals focused on the development, implementation and evalution of the
technology (designers, technicians, project managers,researchers)
o People whose involvement ensures that the technology fits the target population
and context (patients, healthcare professionals)
CHAPTER 8 THE CONTEXTUAL INQUIRY
The contextual inquiry has several main objectives:
- The relevant stakeholders have to be identified: anyone who affects or is affected by the
technology
o Literature scan/review
, o Expert recommendations
o Snowball sampling with stakeholders
- The identified stakeholders have to be analyzed: it should be clear what the tasks and roles
of the stakeholders are in order to identify the key stakeholders
o Stakeholder salience: mapped based on power, legitimacy and urgency
o Stakeholder map
- The current situation, its weak and strong points have to be described in order to find out if
and in what way an eHealth technology can contribute to the current situation.
The identified issues can be related to, efficiency, effectiveness, timely delivery of care and safety of
healthcare.
The main outcomes of the contextual inquiry should be an overview of: current situation; rules,
regulations and ethical issues of context; possibilities and conditions for the use of technology.
T2 PERSUASVIVE HEALTH TECHNOLOGY PART 2
Intention-to-threat versus per protocol analysis:
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