Health behavior lies at the core of any successful public health intervention. While we will examine the behavior of individual in depth in this course, we also recognize by way of the Ecological Model that individual behavior is encouraged or constrained by the behavior of families, social groups, communities, organizations and policy makers. We recognize that behavior change is not a simplistic process but requires an understanding of dimensions like frequency, complexity and cultural congruity. Such behavioral analysis is strengthened through the use of a toolkit of theoretical models and practical frameworks. While many of such models and frameworks exist, in this course we will review the Health Belief Model, Social Learning Theory, Theory of Reasoned Action, the Trans-Theoretical Model and the PRECEDE Framework. After building your behavioral analysis toolkit with these examples, you will see that actual behavior change program planning uses a combination of ideas and variables from different models, theories and frameworks. Ultimately we aim to encourage course participants to apply the idea that successful programs are theory based as they go about involving people in improving their health.
Diffusion/Adopter Characteristics
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來自 Johns Hopkins University 的課程
Diagnosing Health Behaviors for Global Health Programs
8 個評分
從本節課中
Process Models and PRECEDE
Here you will be introduced to Process Models and take a look at PRECEDE for the first time.
與講師見面
William Brieger, DrPHProfessor, Health Systems Program of the Department of International Health
Bloomberg School of Public Health
The third process model is the adoption, diffusion model.
This was developed by Rogers and Shoemaker,
looking at various kinds of adoption of new ideas,
whether farmers would grow new kinds of crops or use new fertilizers.
Whether physicians would prescribe new kinds of drugs.
So this model has been used for many different kinds of behavior,
not just health behavior.
The idea, word diffusion, one can think of physics.
The idea of molecules filling up a vacuum.
One can think about epidemics and the spread of a disease through a population.
A new idea or a new behavior is the same.
It enters into a population and a few people will try it.
Others will observe.
If they see the results are positive, they may try it too.
This graphic representation of the diffusion process starts off at
the left-hand side with a few innovators who may possibly be more educated or
maybe less tied down by social norms than the community and
are willing to take a risk and try new ideas.
The X axis in this graph represents time.
Different innovations may take longer or
shorter time to be adopted depending on their characteristics.
Which we'll talk about.
Mixing salt sugar solution may be the easier innovation to adopt and
buying car safety seats which cost a little more money.
Or digging a family latrine, which involves more resources, so
different innovations may spread at different rates depending on their nature.
What's important to recognize in this diffusion model is that not everyone
will try it once, not everyone will be at the same stage, and
that there are some people that would be harder to reach, more resistant to change.
This is a good warning for
some of our educational programs in that time is necessary.
We have the issue of diminishing returns.
It may take longer and take more resources to reach the late
adopters at the right hand end of the curve.
It's possible that provision of information, mass media, etc.,
may be a good way to reach the innovators and get them started.
The need to work through social groups, spreading information
may help the majority adopt the idea but more personalized
outreach which would be more expensive may be needed to reach late adopters.
And it's quite possible that after a certain point of time,
that adoption would stop.
This is certainly recognized in terms of commercial marketing of products.
A particular company selling soft drinks might be very happy
if they have ten percent of the market for their particular soft drink.
And therefore they would never expect the whole population to adopt their drink.
They're satisfied that they will make enough profit if
they can get a few innovators and early adopters.
In public health we set goals such as 80% immunization coverage and
the river blindness program.
65% of people taking the drug ivermectin every year.
These kinds of goals are set that may run counter
to our understanding of ideas spreading in human populations.
Not everybody is going to jump on the bandwagon at once.
Some people may be resistant.
Some people may take longer to convince.
Some people may never want to engage in the behavior.
So we have to be very careful about our expectations for public health measures,
controlling a disease, and the reality of human behavior and their voluntary
choices and assessments and perceptions of the technologies that we have to offer.
As we had seen in the previous slide with the distribution of the different types of
innovators, there are several distinctive groups of people,
and their willingness to try new ideas.
We notice the people at the end of the curve are the innovators.
They actively seek new information.
They're willing to take risks.
They actually have access to information.
This implies, of course, contact with the outside world,
not just being confined to hearing gossip from within their community,
maybe they have [LAUGH] Internet access, maybe they travel often to
buy goods in the capital and come back and tell people what they learned.
They are often different in terms of their age,
beliefs, occupation, they may be at the edge as it were of the community.
Younger people, maybe an occupation such as a teacher as opposed to a farmer.
People that would have access to new ideas.
The early adopters are people also that seek new information.
They belong to organizations with a national Base like a local chapter of boy
or a girl scouts or a red cross or something like that.
They have access to technical experts such as health workers they
may attend clinic regularly and find out information.
They have a bit higher income generally younger they accept risks.
But they're not willing to take the first plunge.
They're going to watch the innovators to see.
We have following them the overall majority,
the people that make up the bulk of the curve, the adoption curve.
They are receptive to new ideas but they don't actually seek them out.
They wait and see what happens.
They belong to local groups, local clubs, community based organizations.
Generally, they value the opinion of the leaders of their group,
the social leaders, the people, experienced people in the community,
who know something about life in that community.
They have a generally average income.
Finally, we have the late adopters at the left end of the curve.
Possibly they're complacent, skeptical, neighbors,
mass media may be their source of information.
They're definitely waiting to see what will happen.
They may be older, security minded, lower income, less contact or
very little contact with the outside world, as we'll be talking later in our
module on the community, they may be disadvantaged groups that don't have
access to ideas, income, communication in order to help them change.
So the interesting thing with this is that not only are this innovation moves through
the community and slowly picks up while other people watch to see what happens.
But the people who start the innovation are different in social and
economic terms, education terms than those who wait, and
this has serious implications for our programming.
We may have to adopt different strategies to reach the different groups.
People who are innovators,
or early adopters, may respond very well to mass media.
People who are in the majority, or late adopters,
may need more interventions geared toward social groups, and
working through existing organizations, and house to house outreach.
So we have to recognize it in order to reach people with information.
We have to take different approaches because their social and
economic characteristics also include their characteristics in terms of
information accessing, and willingness to take risks.
The diffusion theory considers that the rate of adoption of
a particular new idea or innovation depends on these four factors.
One is the characteristic of the innovation itself.
We've already talked about in health-belief model,
how people doubt the efficacy of the guinea worm filter.
What is it about that particular technology or
innovation that we have to offer?
Is there cultural congruence?
Does the new behavior resemble or fit into people's lifestyle?
Is it complex or simple?
Are there many steps involved, equipment, etc?
Or is it a very simple matter?
Getting a child an immunization may be relatively simple for the mother,
assuming she can get to the clinic.
But mixing salt-sugar solution may be more complex, more steps.
An important characteristic of the innovation is
how well its benefits can be perceived once people adopt and use it.
The farmer who is adopting a new type of seed or grain has to wait some weeks or
months until the seed germinates, and then again until harvest time.
But there is a known period of time where you can see a result.
Sometimes our public health benefits are difficult to perceive.
If a mother has her child immunized against measles,
we won't see the measles and we won't see the lack of measles visibly.
And so it may take quite a bit of time before
the mother perceives that her child has not gotten sick.
So sometimes we want to have people perceive the negative so it's difficult.
On the other hand,
if a child is having diarrhea, become very weak, dehydration may have started.
In our oral rehydration therapy corners at clinics,
once the child has started to take the oral therapy.
Mothers can observe within an hour or
less that the child is starting to become more lively and active.
So when people can see the benefits they're more likely to take an action.
Another thing that helps is the ability for people to try out the new idea.
Very few people would buy a new car without test driving it.
And this is true for a number of other innovations.
Some are difficult when we encourage family compounds to dig their own latrine,
and we want them to use the ventilated improve latrine
with the ventilation pipe that keeps it less smelly and keeps it cleaner.
It's difficult for people to say, I'm going to build one and test it,
and then abandon it, because it does cost some money.
So it's incumbent upon the planners to have some sample VIP latrines for
people to try.
Possibly at the market, etc.
And then another thing that's important to recognize,
we talked about the issue of soft drink companies competition or alternatives.
There may be other innovations that people perceive perform the same function.
We talked about filtering water to make it clean and prevent getting worm.
People may see the filter as simply as something to make the water clean, and
they may be very happy to use alum or allow it to settle as an alternative.
Why go through the trouble of filtering?
So the characteristics of the nature of that innovation itself may encourage or
may make it difficult for people to adopt it.
As we noted in our other models, demographic and
personal characteristics influence people's perceptions,
their willingness to try new things, their personality, their assertiveness.
Also, we have to consider communication factors.
How do people learn about these new ideas?
Through which channels does the information come?
Do they get it through the mass media?
Through an in personal?
Or through an interpersonal?
Through friends, through relatives, through other people who have tried it?
What kind of media do people use to access information?
Is there a town crier?
Is there a loudspeaker in the market?
Do they get mailings?
And what are their perceptions of these media?
We've done studies on use of radio, attention to radio in rural communities
in Africa and found, interestingly enough, while people tend to have radios,
there are gender differences on how people use them.
Men value the radio for news programs and they'll turn it on at specific times.
Women may not use radio much, but if they turn it on, it's more as background.
So, music, whatever, to make their work go better.
Ironically, radio is used quite often to send information and
messages about immunization, about diarrheal diseases,
about things that mothers are expected to do to take care of their children.
But mothers listening habits and
mothers perceptions of the radio are different than fathers.
So fathers may hear the information but say it's not for me.
Mothers may not really pay attention, but
it's just background noise while they're busy doing their other work.
So we have to think about how people perceive of the different communication
channels that we send our information through.
And ironically,
more people who are educated listen than those who are less educated.
This is again, like I said, ironic because many times people
promoting the mass media as a way of providing health information,
say that you don't need to be educated, that's the benefit of using the radio.
But interestingly enough we found that people with more education were attracted
to the radio.
It could be an economic issue that they had better jobs and could afford it.
It could have been the type of programming that they were interested in and
understood it.
They were more involved in politics or
more used to seeking information from the outside.
We also found that again, men, as I mentioned,
we're more likely to listen than women.
And they also have different programming preferences.
Men would prefer the news.
Women, if they had the radio on, it was more as background noise.
Here again, is another irony,
the idea that much of health messaging is geared toward women,
oral rehydration, immunization, things to do to take care of their children.
But if they have the radio on they're not actually attending to it
as a information source but have it as a background companion noise.
Interestingly enough and one of the things that's said again about the benefit of
radio is that you can use batteries.
Well, we found that people who lived in sections of town that had
electricity were more likely to listen than those who didn't.
This again may be an economic issue because batteries, although they're cheap,
do wear out.
And if people are especially playing the radio to play music cassette tapes as well
as that, they'll run out quite quickly.
So here, again, we get back to this issue of cost and
factors influencing the behavior.
Then, finally, the types of messages that were recalled, people recalled more
messages about outbreaks, yellow fever, cholera, that type of thing.
And less about things from the clinic.
Less about health issues such as oral rehydration, immunization.
They got this kind of information more often from the clinic and
local community sources.
So while the radio has been said to be an important way of providing information,
it doesn't reach everyone.
And again, people don't get all the messages that are provided.
They don't attend to those.
This, from the innovation point of view,
is important in the sense that if you are trying to promote a new innovation,
trying to promote oral rehydration, tendons immunization.
And you think you can do this through certain communication channels,
you're not likely to reach all the people.
The radio in this case may be good for the early adopters.
But it may not be good for the late majority.
It may not be good for women or minority groups or
people living in poorer sections of town without electricity.
And finally, a fourth factor that would influence adoption are the characteristics
of the change agent.
The person who is promoting the new behavior or the innovation.
Here comes the concepts of homophily or heterophily, how similar or
different, how alike or how different is the change agent in terms of age,
gender, ethnic group, educational level, etc.,
from the people in the community who are expected to adopt the innovation.
One thing that's found is the more similar people are,
the more often they communicate, the more information they share among themselves,
the easier communication is, but At the same time, there is less new information.
People will share the same gossip, the same ideas, the same values.
If people are different, it's harder to communicate but
it's more likely that they will talk about different things, new things.
There's a challenge in public health that the change agent needs to be similar
enough to the people, to be able to communicate freely but different enough so
that he or she has some new ideas to introduce.
This means it's important for the health worker on coming to a new community
to attend ceremonies, to be visible in the market, to interact with people so
that he or she can become more similar more accepted by the community.
But at the same, because he or
she is different, be in a position to introduce some new ideas.
In fact research has shown that, when in terms of mental health,
when clients and therapists share a common language, or
ethnic origin, there is more interaction, clients come for more sessions.
There are also change agent characteristics such as
cultural competence, their ability to listen
that will influence how effective they are in promoting a new idea.
In previous slides looking at the adoption,
we've had our bell shape or normally distributed innovation curve.
The next slide shows the same data presented as a cumulative curve.
And this is important to consider especially in the case of
innovations where not everyone is going to adopt them.
As you can see when you plot the cumulative
frequency of sales of the Guinea worm filter can see
the curve accelerating in the beginning, but then leveling off.
And if you keep track of this and start to see this leveling off,
it's a good indicator that you have reached or saturated your audience.
And in this particular case we got into
the majority we pass the early adopters but we sort of hit a dead end.
People eventually were telling us that majority of people,
that they didn't believe the filter would work.
Many of the more traditionally minded people talked about
the Guinea worm being part of their body and couldn't be prevented.
Other people were saying that they didn't think that the innovation itself was of
good quality.
They would prefer the government to give them wells, as opposed to buying a filter.
So looking at the adoption curve from this angle helps us see how
the process is going on, and where we're running into roadblocks.
The next graph looks at the adoption of salt sugar solution for oral rehydration.
Here again, asking mothers in the community questions about
their experience with this, have they tried it.
And we can see that with different innovations,
people are at different stages.
With the condoms for the young people, more people were at pre-contemplative and
contemplative.
For salt-sugar solution, many of them have tried it and are using it.
So that it's important to know that when there are more people at the action
maintenance stage, then we have to revise our health education strategies.
And say okay, now that we've gotten information out, people have tried it.
Now we have to think about how we can maintain,
how we can reinforce the existing behaviors to prevent relapse.
This is a major problem in health education programs.
People achieve an initial success in bringing about change.
But then they switch to something else, okay?
Now let's do education and HIV AIDS, or now let's education of seat belt use.
And forget about programming for what they've achieved.
And what happens as anything again in the commercial sector will tell you,
if you stop your advertising,
if you stop your promotion, people will switch to other products.
So we need to realize this that even when we do achieve at a point in
time a good level of adoption that we have to still take action to maintain that.
Another example from CDC's, morbidity, mortality weekly review.
This is a useful publication that you can get directly from the CDC website.
It shows that with condom use in homosexual and bisexual men that when they
looked at this behavior over a period of five years, that there wasn't much change.
The graph in the next slide shows that a majority of people were in
the maintenance stage.
But further discussions found that yes, there was back and forth among the stages.
In other words, there was relapse.
The questions they ask, and here again, we're talking about operationalizing some
of our variables and using our theoretical models to understand these behaviors.
They found that self efficacy was an important characteristic,
it was an important variable in helping people to maintain condom use even
when under difficult circumstances, such as when taking drugs or alcohol.
So these were some of the things that were important in terms of the action and
maintenance of that behavior.
Similarly they operationalized and
got information on perception of social support peer support social norms,
and found again, that that was a positive factor associated with moving forward
from the contemplation up through the action and maintenance stage.
So again, the interaction between our trans-theoretical stages
where are people at in adopting the behavior, as well as our theoretical
models giving us variables understand why people are at the stage they are at and
what is likely to facilitate or be a barrier to them moving forward.
This of course again raises the issue of relapse behavior and
a couple of years ago an article in the news paper in the Baltimore Sun
was talking about AIDS cases rising again in the San Francisco.
And seeing the epidemiological information
that the number of positive cases was tripling.
What was happening?
Because some major achievements had been
made in terms of preventive interventions prior to that.
Well they found of course, there were new generations of gay men in the community.
And there were also new things happening in the medical front in terms of
drugs that would at least halt the symptoms, if not cure the disease.
So what happened is they found relapse behavior
that the reports of always using condoms fell.
From 70% in 94 down to 54% in 1999.
And again, what people were saying is that they don't feel threatened,
they don't feel at risk any more because the new drugs
make them feel that they are less vulnerable.
So here again, relapsed behavior, linking that in with our other theoretical models,
in this particular case the health belief model will help us understand what happens
that the environment changes and therefore perception of risk changes.
So we need to be constantly monitoring the adoption of innovations,
we need to be monitoring people's progress through the different stages of change.
Keep vigilant in terms of our health education throughout the process to
reinforce and maintain the behavior otherwise we will get relapses,
as seen in the case of condom use and prevention of AIDS.
