Evidence of MODEL's performance
STOP AIDS
Background:
Was one of the most effective HIV/ AIDS prevention programs which was focused around the Diffusion of Innovation theory.
Method:
STOP AIDS began by conduction focus group to learn how much gay men already knew about HIV/ AIDS to figure out how to design an effective intervention. After a few sessions though they realized that the focus group had a very strong education effect, while the men shared what they knew about HIV prevention. STOP AIDS then moved on to the next step to expand these focus groups throughout the gay communities, which then launched the diffusion process. Just within 2 years STOP AIDS reached out to 30,000 men.
This study shows that only those early adopters, who make up a relatively small segment of the population, need to initiate a new behavior for it to spread throughout the population. In this specific study a well-known individual in the gay community led the focus groups. He would explain how the virus was spread and would encourage the participants to use preventative behaviors. At the end of each session participants were asked to say a pledge to have safer sex.
Results:
With the small group meetings, and media campaigns it helped to increase awareness of HIV/ AIDS. The rate of new infections dropped precipitously. But after a few years the attendance to the STOP AIDS meetings quickly dropped, and they found it hard to recruit new volunteers. The STOP AIDS program reached its critical mass of early adopters to safer sex. STOP AIDS declared victory and discontinued its operation, only to reopen three years later for new cohorts of younger gay men moving to the city.
How it worked:
Although STOP AIDS had a main focus on using the diffusion of innovation theory, they also relied heavily on the epidemiological concept of targeting a group at high risk spreading the disease, and used other strategies tied in to change the community’s behavior. The model that was used called for identifying the natural opinion leaders in the community, which in this case they used bar staff, and enlisting them to endorse behavior changes.
(Bertrand, 2004)
Limitations:
This idea tried to be replicated in other areas such as London and other countries but found that it did not work out as well due to:
Was one of the most effective HIV/ AIDS prevention programs which was focused around the Diffusion of Innovation theory.
Method:
STOP AIDS began by conduction focus group to learn how much gay men already knew about HIV/ AIDS to figure out how to design an effective intervention. After a few sessions though they realized that the focus group had a very strong education effect, while the men shared what they knew about HIV prevention. STOP AIDS then moved on to the next step to expand these focus groups throughout the gay communities, which then launched the diffusion process. Just within 2 years STOP AIDS reached out to 30,000 men.
This study shows that only those early adopters, who make up a relatively small segment of the population, need to initiate a new behavior for it to spread throughout the population. In this specific study a well-known individual in the gay community led the focus groups. He would explain how the virus was spread and would encourage the participants to use preventative behaviors. At the end of each session participants were asked to say a pledge to have safer sex.
Results:
With the small group meetings, and media campaigns it helped to increase awareness of HIV/ AIDS. The rate of new infections dropped precipitously. But after a few years the attendance to the STOP AIDS meetings quickly dropped, and they found it hard to recruit new volunteers. The STOP AIDS program reached its critical mass of early adopters to safer sex. STOP AIDS declared victory and discontinued its operation, only to reopen three years later for new cohorts of younger gay men moving to the city.
How it worked:
Although STOP AIDS had a main focus on using the diffusion of innovation theory, they also relied heavily on the epidemiological concept of targeting a group at high risk spreading the disease, and used other strategies tied in to change the community’s behavior. The model that was used called for identifying the natural opinion leaders in the community, which in this case they used bar staff, and enlisting them to endorse behavior changes.
(Bertrand, 2004)
Limitations:
This idea tried to be replicated in other areas such as London and other countries but found that it did not work out as well due to:
- lack of community
- lack of education
- struggles with hunger, unemployment, housing, and other poverty
Controlling scurvy in the British navy:
innovations do not sell themselves
Background:
The scurvy control study displayed how slowly an obviously beneficial Innovation spread. In the early days of long sea voyages, scurvy was the number one killer of sailors, over warfare, accidents, and all other causes of death. For example on a ship that traveled around the Cape of Good Hope in 1497, it had a crew of 160 men and 100 of them died from scurvy.
Method:
In 1601 an English captain, James Lancaster, conducted an experiment. James had four ships that were traveling on a journey from England to India. Out of the four ships he gave the crew from one of the ships lemon juice to see the effect it had on prevention of scurvy. By the half-way point of the voyage, 110 out of the 278 men on the other three ships died from scurvy, while the ship that was taking the lemon juice stayed healthy.
Results:
The results from the experiment were so clear that it would make sense for the British Navy to adopt citrus juice for scurvy prevention on all of it ships, but it was not for another 150 years till another experiment was done. A British Navy physician named James Lind conducted an experiment where he gave some scurvy patients a citrus diet and gave others a different diet. The scurvy patients that he gave the citrus diet were cured within a few days, but the citrus supply became exhausted after only six days. It wasn't until 1795 that the British Navy adopted new technological innovation on all their ships, scurvy was immediately whipped out.
How it worked:
One would think that innovation to a beneficial behavior would lead to quick results for all, but due to other hypothesis people were not willing to innovate so easily. The crew thought that it wouldn't be just that simple and that there were better remedies to cure scurvy so they weren't willing to all innovate to the cure of scurvy through citrus. (Rogers, 2000 )
The scurvy control study displayed how slowly an obviously beneficial Innovation spread. In the early days of long sea voyages, scurvy was the number one killer of sailors, over warfare, accidents, and all other causes of death. For example on a ship that traveled around the Cape of Good Hope in 1497, it had a crew of 160 men and 100 of them died from scurvy.
Method:
In 1601 an English captain, James Lancaster, conducted an experiment. James had four ships that were traveling on a journey from England to India. Out of the four ships he gave the crew from one of the ships lemon juice to see the effect it had on prevention of scurvy. By the half-way point of the voyage, 110 out of the 278 men on the other three ships died from scurvy, while the ship that was taking the lemon juice stayed healthy.
Results:
The results from the experiment were so clear that it would make sense for the British Navy to adopt citrus juice for scurvy prevention on all of it ships, but it was not for another 150 years till another experiment was done. A British Navy physician named James Lind conducted an experiment where he gave some scurvy patients a citrus diet and gave others a different diet. The scurvy patients that he gave the citrus diet were cured within a few days, but the citrus supply became exhausted after only six days. It wasn't until 1795 that the British Navy adopted new technological innovation on all their ships, scurvy was immediately whipped out.
How it worked:
One would think that innovation to a beneficial behavior would lead to quick results for all, but due to other hypothesis people were not willing to innovate so easily. The crew thought that it wouldn't be just that simple and that there were better remedies to cure scurvy so they weren't willing to all innovate to the cure of scurvy through citrus. (Rogers, 2000 )
Shared Electronic Records and diffusion of Innovation
Background:
The basis of this innovation known as the SCR developed from the expressed need to advance health care and record keeping into the 21st century. As the technology was further developed several sites were selected to adapt to the new technology and help to develop better use of changing technology in the field of health care (BMJ, 2008).
Method:
Four sites were selected as "early adapter" locations to be observed throughout the study. The first site began in 2007 A research advisory group was established and they worked to evaluate the innovation and its influence on work among the early adapter sites. The goal of the study soon became "interpretation rather than prediction." Data was recorded through interviews, observation, and documentation; both quantitative and qualitative forms of data were collected (BMJ, 2008).
Results;
As expected moving from the early adapters to other levels of the diffusion of innovation model was not as simple as passing out flyers or playing a radio ad. To combat this issue "interpersonal influence" grew from the use of opinion leaders, "who travelled the country to explain what the SCR was, hear the concerns of their fellow general practitioners, and try to make their audiences more receptive to the programme." These popular events then led to practitioners becoming in favor of implementing the SCRs (BMJ, 2008).
The basis of this innovation known as the SCR developed from the expressed need to advance health care and record keeping into the 21st century. As the technology was further developed several sites were selected to adapt to the new technology and help to develop better use of changing technology in the field of health care (BMJ, 2008).
Method:
Four sites were selected as "early adapter" locations to be observed throughout the study. The first site began in 2007 A research advisory group was established and they worked to evaluate the innovation and its influence on work among the early adapter sites. The goal of the study soon became "interpretation rather than prediction." Data was recorded through interviews, observation, and documentation; both quantitative and qualitative forms of data were collected (BMJ, 2008).
Results;
As expected moving from the early adapters to other levels of the diffusion of innovation model was not as simple as passing out flyers or playing a radio ad. To combat this issue "interpersonal influence" grew from the use of opinion leaders, "who travelled the country to explain what the SCR was, hear the concerns of their fellow general practitioners, and try to make their audiences more receptive to the programme." These popular events then led to practitioners becoming in favor of implementing the SCRs (BMJ, 2008).
Combining evidence and diffusion of innovation theory to enhance influenza immunization.
Background: For children with chronic conditions becoming sick can be much bigger of an issue than it is for others. At Cincinnati Children's Hospital Medical Center the influenza immunization was given to a group of 200 Cystic Fibrosis (CF) Patients and the implementation followed the steps of the Diffusion of Innovation to implement the practice in other clinics. (Britto, Pandzik, Meeks & Kotagal , 2006)
Method:
The main intervention strategies were: (1) engagement of interested, nurse-led teams, (2) A collaborative learning session, (3) A tool kit including literature, sample goals, reminder postcards, communication strategies, and team member roles and processes, (4) open-access scheduling and standing orders (5) A simple Web-based registry, (6) facilitated vaccine ordering, (7) recall phone calls, and (8) weekly results posting. (Britto, et. al, 2006)
Results:
As a result,of the study 60.0% (762/1,269) of the population was immunized. And the highest rate of immunization was reported in the CF clinic. (Britto, et. al, 2006)
Method:
The main intervention strategies were: (1) engagement of interested, nurse-led teams, (2) A collaborative learning session, (3) A tool kit including literature, sample goals, reminder postcards, communication strategies, and team member roles and processes, (4) open-access scheduling and standing orders (5) A simple Web-based registry, (6) facilitated vaccine ordering, (7) recall phone calls, and (8) weekly results posting. (Britto, et. al, 2006)
Results:
As a result,of the study 60.0% (762/1,269) of the population was immunized. And the highest rate of immunization was reported in the CF clinic. (Britto, et. al, 2006)
Mobile banking Adoption: Application of diffusion of innovation
Background:
According to the ICT Indicators Report (2011), mobile phone services in Saudi Arabia were offered in 1995, and by 2011, the total number of subscribers was 56.1 million, comprising 198% penetration rate (as cited in Al-Jabri and Sohail, 2012). The ICT Indicators Report (2011) further states a 5% to 46% internet penetration increase along with an increase in the number of internet users from one million in 2001 to 13 million by the end of 2011 (as cited in Al-Jabri and Sohail, 2012). While there are many studies that define adoption in terms of implementation, usage, utilization, or satisfaction, this particular study focuses on satisfaction, which is the most widely used single measure of adoption (Al-Jabri and Sohail, 2012).
Methods:
First, a focus group of eight graduate students having exposure to mobile banking was conducted. The list of variables relating to adoption of mobile banking was revealed to the participants, and they were asked to select and assess the variables they felt were relevant when undertaking mobile banking (Al-Jabri and Sohail, 2012). Second, a survey (measured with a five-Likert scale) was developed, consisting of the demographic characteristics of each respondent and capture information on the constructs of diffusion of innovation theory (DIT), such as relative advantage, complexity, compatibility, observability, trialability, and perceived risk. Third, a pilot test was conducted on 20 randomly selected mobile banking users studying in the university campus. The received feedback indicated that some of the questions lacked clarity in meaning. Finally, the target population was all adult individuals residing in Jeddah, Riyadh, and tricities of Dhahran-Khobar-Dammam of Saudi Arabia (Al-Jabri and Sohail, 2012).
Results:
Out of the 1500 participants who received a survey, 466 were usable responses, of which 330 were mobile banking users and 136 potential mobile banking users (Al-Jabri and Sohail, 2012).
Some data from the study follows (Al-Jabri and Sohail, 2012):
The hypothesis that relative advantage will have a positive effect on mobile banking adoption was supported. Compatibility was the most important determinant to predict adoption of mobile banking. Observability was also significant as it allowed customers a very convenient and effective way to manage their financial transactions. Complexity and trialability had an insignificant effect. Furthermore, perceived risk had a negative effect on adoption, which meant that customers feared their PIN code may get lost and/or tampered with. (Al-Jabri and Sohail, 2012)
According to the ICT Indicators Report (2011), mobile phone services in Saudi Arabia were offered in 1995, and by 2011, the total number of subscribers was 56.1 million, comprising 198% penetration rate (as cited in Al-Jabri and Sohail, 2012). The ICT Indicators Report (2011) further states a 5% to 46% internet penetration increase along with an increase in the number of internet users from one million in 2001 to 13 million by the end of 2011 (as cited in Al-Jabri and Sohail, 2012). While there are many studies that define adoption in terms of implementation, usage, utilization, or satisfaction, this particular study focuses on satisfaction, which is the most widely used single measure of adoption (Al-Jabri and Sohail, 2012).
Methods:
First, a focus group of eight graduate students having exposure to mobile banking was conducted. The list of variables relating to adoption of mobile banking was revealed to the participants, and they were asked to select and assess the variables they felt were relevant when undertaking mobile banking (Al-Jabri and Sohail, 2012). Second, a survey (measured with a five-Likert scale) was developed, consisting of the demographic characteristics of each respondent and capture information on the constructs of diffusion of innovation theory (DIT), such as relative advantage, complexity, compatibility, observability, trialability, and perceived risk. Third, a pilot test was conducted on 20 randomly selected mobile banking users studying in the university campus. The received feedback indicated that some of the questions lacked clarity in meaning. Finally, the target population was all adult individuals residing in Jeddah, Riyadh, and tricities of Dhahran-Khobar-Dammam of Saudi Arabia (Al-Jabri and Sohail, 2012).
Results:
Out of the 1500 participants who received a survey, 466 were usable responses, of which 330 were mobile banking users and 136 potential mobile banking users (Al-Jabri and Sohail, 2012).
Some data from the study follows (Al-Jabri and Sohail, 2012):
- "58% male;
- "93% Saudi nationals;
- "72.7% between the ages of 18-25 years old;
- "54.5% are students;
- "75.8% visit their bank 1-4 times a month;
- "43.7% used mobile banking for one year or more"
The hypothesis that relative advantage will have a positive effect on mobile banking adoption was supported. Compatibility was the most important determinant to predict adoption of mobile banking. Observability was also significant as it allowed customers a very convenient and effective way to manage their financial transactions. Complexity and trialability had an insignificant effect. Furthermore, perceived risk had a negative effect on adoption, which meant that customers feared their PIN code may get lost and/or tampered with. (Al-Jabri and Sohail, 2012)