Digital health communication - T lectures
Lecture 1
Persuasive health technology
Leaning goal: understanding the basics of behavior change (interventions)
“Persuasive health technology is any technology purposely designed to influence, reinforce,
change, or shape related attitudes or behaviors”
eHealth (= health application): the use of information communication technologies (ICT’s;
computers of any kind) to deliver or support the delivery of health services.
mHealth: the use of mobile wireless technologies for public health
Behavior change - COM-B model
Integration of 19 theories/frameworks
Three main determinants/ sources of behavior:
- Capability: whether a person has the knowledge, skills and abilities to engage in a
behavior. (psychological: knowledge or psychological skills. Physical: physical skill,
strength or stigma)
- Motivation: all the internal processes that trigger or inhibit a behavior and that ultimately
result in us performing a particular behavior instead of any other possible competing
behavior. (reflective: beliefs, self identity, intentions, goals,
plans. Automatic: emotions, feelings, associative learning,
habits and drives)
- Opportunity: external factors that make execution of
behavior possible (environmental; time, location, money
and resources. Social: social norms, environmental and
social cues)
-> interactions between determinants (and behavior). Tool to
identify barriers to behavior change and to plan interventions.
Designing interventions: behavior change wheel and behavior change techniques (BCT’s)
,Behavior change intervention: Coordinated set of activities/BCTs designed
to change specific behaviors patterns, usually spanning multiple
intervention functions.
Behavior change techniques (BCT) taxonomy
- BCT: a component of an intervention designed to alter or redirect
causal processes that regulate behavior; that is a, technique is
proposed to be an active ingredient
- For each intervention function several BCTs have been identified that contribute to this
function
- 93
Persuasive technology
Features of health application (e.g. implemented behavior change techniques) -> determinants
of behavior (constructs form behavior change theories) -> behavior change
Potential impact: (m)Health apps in app store
In 2021 350k health applications in the app store
Learning goal: Understanding main factors increasing and decreasing the impact of
digital health applications of behavior change
Impact - what is the evidence? - healthy eating behavior
Aim: this systematic review and meta-analysis aimed to determine the effectiveness of
smartphone apps for changing nutrition behaviors and nutrition related health outcomes.
Current status: which behavior change techniques are employed most often?
-> most apps included 4 different behavior change techniques.
Overall, a small significant effect of app based mobile interventions on nutrition behavior and
nutrition related outcomes.
Other meta-analyses/reviews
Physical activity: interventions were only effective (significant) when the intervention duration
was 3 months or less (compared with longer interventions).
Medicine adherence: 7/11 studies showed mobile app increases medicine adherence
Alcohol intake: brief web-based interventions decreased the number of alcoholic drinks
consumed
Digital (web) school based behavior change 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.
-> mixed findings, short(er) term effects larger, quality of evidence limited.
Maximizing the impact of digital health applications: two main factors
- The effective component should be evidence based: the application employs features
that target determinants from health behavior theories/ features that are based on
established behavior 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 low impact
Low impact because technologie does not work, low support of healthcare professionals, not
designed with user in mind resulting in low uptake.
-> real impact of eHealth technologies is unknown
Learning goal: Understand and explain the importance of theory use in the development
of digital health applications.
Employing theory in digital health applications
In non digital interventions: effectiveness of intervention is higher when theory based and when
it employs one or more behavioral change techniques.
Aims: provide overview of extent of theory use in digital health applications. Determine
importance of the extent of theory use.
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 uses was higher, namely:
- At least one or more theoretical constructs are explicitly linked to an intervention
technique
- When theory constructs are included in evaluations (measured pre and post intervention)
U@uni
Multi device digital health intervention to stimulate health behavior (e.g. fruit and vegetable
intake, physical activity, alcohol consumption, smoking) among young people during the
transition for school to university.
Lecture 2
Intention to treat versus protocol analysis
Intention to treat analysis: a comparison of treatment groups that includes all randomized
participants in the groups to which they were randomly assigned, regardless of adherence or
withdrawal.
, Per protocol analysis : a comparison of treatment groups that includes only those participants
who completed the treatment originally allocated.
Two possible but very different interpretations of the results:
- The significant effect is caused by the intervention being effective. The effect of the
intervention was marginally significant in the whole population but reached significance
in the per-protocol analysis. One may conclude that the intervention itself is effective: if
participants go through all intervention elements (e.g. they receive the intended dose of
the effective ingredient), the effect is significant.
- The significant effect may be due to the higher motivation of the participants (remaining)
in this group instead of the effect of the intervention. The individuals included in the
per-protocol analysis are those that (at their own initiative) completed all intervention
elements. Self-selection may be occurring here. Individuals completing all modules may
be individuals that are extra motivated for behavior change.
Learning goal: understand the main characteristics and assumptions of rational models
of health behavior. Know the main behavioral determinants of these models and how to
influence these by digital health communication.
- Human behavior is under the voluntary control of the individual -> behavior is planned
- If you successfully change the determinants of behavior you will be successful in
changing the behavior
-> rational models:
Rational models: the theory of planned behavior
Lecture 1
Persuasive health technology
Leaning goal: understanding the basics of behavior change (interventions)
“Persuasive health technology is any technology purposely designed to influence, reinforce,
change, or shape related attitudes or behaviors”
eHealth (= health application): the use of information communication technologies (ICT’s;
computers of any kind) to deliver or support the delivery of health services.
mHealth: the use of mobile wireless technologies for public health
Behavior change - COM-B model
Integration of 19 theories/frameworks
Three main determinants/ sources of behavior:
- Capability: whether a person has the knowledge, skills and abilities to engage in a
behavior. (psychological: knowledge or psychological skills. Physical: physical skill,
strength or stigma)
- Motivation: all the internal processes that trigger or inhibit a behavior and that ultimately
result in us performing a particular behavior instead of any other possible competing
behavior. (reflective: beliefs, self identity, intentions, goals,
plans. Automatic: emotions, feelings, associative learning,
habits and drives)
- Opportunity: external factors that make execution of
behavior possible (environmental; time, location, money
and resources. Social: social norms, environmental and
social cues)
-> interactions between determinants (and behavior). Tool to
identify barriers to behavior change and to plan interventions.
Designing interventions: behavior change wheel and behavior change techniques (BCT’s)
,Behavior change intervention: Coordinated set of activities/BCTs designed
to change specific behaviors patterns, usually spanning multiple
intervention functions.
Behavior change techniques (BCT) taxonomy
- BCT: a component of an intervention designed to alter or redirect
causal processes that regulate behavior; that is a, technique is
proposed to be an active ingredient
- For each intervention function several BCTs have been identified that contribute to this
function
- 93
Persuasive technology
Features of health application (e.g. implemented behavior change techniques) -> determinants
of behavior (constructs form behavior change theories) -> behavior change
Potential impact: (m)Health apps in app store
In 2021 350k health applications in the app store
Learning goal: Understanding main factors increasing and decreasing the impact of
digital health applications of behavior change
Impact - what is the evidence? - healthy eating behavior
Aim: this systematic review and meta-analysis aimed to determine the effectiveness of
smartphone apps for changing nutrition behaviors and nutrition related health outcomes.
Current status: which behavior change techniques are employed most often?
-> most apps included 4 different behavior change techniques.
Overall, a small significant effect of app based mobile interventions on nutrition behavior and
nutrition related outcomes.
Other meta-analyses/reviews
Physical activity: interventions were only effective (significant) when the intervention duration
was 3 months or less (compared with longer interventions).
Medicine adherence: 7/11 studies showed mobile app increases medicine adherence
Alcohol intake: brief web-based interventions decreased the number of alcoholic drinks
consumed
Digital (web) school based behavior change 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.
-> mixed findings, short(er) term effects larger, quality of evidence limited.
Maximizing the impact of digital health applications: two main factors
- The effective component should be evidence based: the application employs features
that target determinants from health behavior theories/ features that are based on
established behavior 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 low impact
Low impact because technologie does not work, low support of healthcare professionals, not
designed with user in mind resulting in low uptake.
-> real impact of eHealth technologies is unknown
Learning goal: Understand and explain the importance of theory use in the development
of digital health applications.
Employing theory in digital health applications
In non digital interventions: effectiveness of intervention is higher when theory based and when
it employs one or more behavioral change techniques.
Aims: provide overview of extent of theory use in digital health applications. Determine
importance of the extent of theory use.
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 uses was higher, namely:
- At least one or more theoretical constructs are explicitly linked to an intervention
technique
- When theory constructs are included in evaluations (measured pre and post intervention)
U@uni
Multi device digital health intervention to stimulate health behavior (e.g. fruit and vegetable
intake, physical activity, alcohol consumption, smoking) among young people during the
transition for school to university.
Lecture 2
Intention to treat versus protocol analysis
Intention to treat analysis: a comparison of treatment groups that includes all randomized
participants in the groups to which they were randomly assigned, regardless of adherence or
withdrawal.
, Per protocol analysis : a comparison of treatment groups that includes only those participants
who completed the treatment originally allocated.
Two possible but very different interpretations of the results:
- The significant effect is caused by the intervention being effective. The effect of the
intervention was marginally significant in the whole population but reached significance
in the per-protocol analysis. One may conclude that the intervention itself is effective: if
participants go through all intervention elements (e.g. they receive the intended dose of
the effective ingredient), the effect is significant.
- The significant effect may be due to the higher motivation of the participants (remaining)
in this group instead of the effect of the intervention. The individuals included in the
per-protocol analysis are those that (at their own initiative) completed all intervention
elements. Self-selection may be occurring here. Individuals completing all modules may
be individuals that are extra motivated for behavior change.
Learning goal: understand the main characteristics and assumptions of rational models
of health behavior. Know the main behavioral determinants of these models and how to
influence these by digital health communication.
- Human behavior is under the voluntary control of the individual -> behavior is planned
- If you successfully change the determinants of behavior you will be successful in
changing the behavior
-> rational models:
Rational models: the theory of planned behavior
