The South Australia Health Chronic Disease Self-Management Internet Trial

Abstract

Objectives. To evaluate the effectiveness of an online chronic disease self-management program for South Australia residents. Method. Data were collected online at baseline, 6 months, and 12 months. The intervention was an asynchronous 6-week chronic disease self-management program offered online. The authors measured eight health status measures, seven behaviors, and four utilization measures; self-efficacy; and health care satisfaction. Results. Two hundred fifty-four South Australian adults with one or more chronic conditions completed baseline data. One hundred forty-four completed 6 months and 194 completed 1 year. Significant improvements (p < .05) were found at 6 months for four health status measures, six health behaviors, self-efficacy, and visits to emergency departments. At 12 months, five health status indicators, six health behaviors, self-efficacy, and visits to emergency departments remained significant. Satisfaction with health care trended toward significance. Discussion. The peer-led online program was both acceptable and useful for this population. It appeared to decrease symptoms, improve health behaviors, self-efficacy, and reduce health care utilization up to 1 year. This intervention also has large potential implications for the use of a public health education model for reaching large numbers of people. It demonstrates that an Internet self-management program, which includes social media, can reach rural and underserved people as well as be effective and reduce health care costs. If this intervention can be brought to scale, it has the potential for improving the lives of large numbers of people with chronic illness. It represents a way the medical care and public health sectors can interact.

Keywords

chronic disease Internet self-management self-tailoring

The setting for this study is South Australia, a large and sparsely populated state covering nearly a million square kilometers with a population of fewer than 1,700,000, of whom 1.7% are aboriginal people. Sixty-nine percent of South Australians live in the major urban areas, with the remaining 31% residing in smaller towns or nonurban areas (Australian Bureau of Statistics, 2011). In 2009, 80.1% of Australians had Internet access (Internet World Stats, 2010).

In Australia, like the rest of the world, chronic disease and comorbidity are increasing problems. The World Health Organization (2005) estimates that by 2020, more than 65% of all deaths will be caused by chronic diseases. Approximately 70% of the burden of disease and injury borne by the Australian population can be attributed to chronic conditions (Department of Human Service, Government of South Australia, 2010). As of 2007, 46% of people in South Australia have a chronic condition, and 15% are estimated to suffer two or more chronic diseases (South Australia, Department of Health, Statewide Service Strategy Division, 2009).

Even though the above data are impressive, it may underestimate the problem, as mental health conditions are often not considered in chronic disease statistics. Approximately 20% of Australians have a mental illness (anxiety, mood, and/or substance use disorders), and 59% of those with a mental illness also have a physical illness (Australian Bureau of Statistics, 2009). Thus, chronic physical and/or mental illness affects more than half of the South Australian population. Chronic disease affects quality of life. In a national Australian study, Walker (2007) found that disability increased with the number of chronic conditions and that people with comorbid chronic conditions are more likely to suffer psychological distress.

Health education has long focused on the prevention of chronic conditions, and these efforts should continue. As discussed by Bodenheimer, Chen, and Bennet (2009), if well funded and coordinated across many sectors, public health efforts may slow the trend of increasing chronic disease. Even if this occurs, chronic illness will continue to increase, necessitating a need for health systems around the world to reconfigure to meet this growing global challenge. Starting in 1998 with Wagner’s chronic care model and continuing into present-day policy, chronic disease self-management is seen as part of the solution. Both South Australia Health (South Australia, Department of Health, Statewide Service Strategy Division, 2009) and U.S. Department of Health and Human Services (2010) call for self-management programs as a means of meeting the needs of those with multiple chronic conditions.

A specific example of a self-management intervention is the Chronic Disease Self-Management Program (CDSMP). Unlike disease-specific programs, the CDSMP imparts skills that are common across chronic diseases. Thus, its participants can have almost any mental or physical chronic condition. The CDSMP is peer led and uses face-to-face small groups meeting 2.5 hours a week for 6 weeks.

When evaluated in a randomized trial, the CDSMP was found to improve health status (self-rated health, role function, fatigue, and health distress), health-related behaviors (exercise, practice of relaxation techniques, and communication with physicians), and self-efficacy (SE). It also reduced health care utilization (nights in hospital). Most of these effects were found to persist for up to 2 years (Lorig et al., 1999; Lorig, Ritter, et al., 2001). There have been several trials of the small-group CDSMP for participants with chronic diseases in diverse populations, including Spanish speakers in the United States, Chinese in both China and Australia, Bangladeshis in London, and African Americans in the United States (Fu et al., 2003; Goeppinger, Armstrong, Schwartz, Ensley, & Brady, 2007; Griffiths et al., 2005; Lorig, Ritter, & González, 2003; Swerissen et al., 2006). A large randomized national study in England demonstrated quality-of-life benefits (improvements in energy, role limitations, psychological state) and improved health behaviors (exercise and partnership with health care providers; Kennedy et al., 2007). In addition, there was a 94% “probability of the intervention being cost-effective” (Richardson et al., 2007, p. 365). From March 2010 to March 2011, more than 33,000 Americans, both English and Spanish speakers, were CDSMP participants (Administration on Aging, 2011).

Although large numbers of people have attended the CDSMP, there are those who do not like small groups, live in isolated areas where groups are not available, or have disabilities that make it difficult to attend groups. Thus, it seems that if we are to reach larger portions of the population, it would be useful to have the same intervention offered via a different medium. The Internet Chronic Disease Self-Management Program (ICDSMP) was designed for this purpose.

Both the content and the process of the 6-week ICDSMP are based on and similar to that of the small-group program. Specifically, both programs have the same content and integrate self-efficacy (SE) theory throughout (Bandura, 1997). Both are led by trained peers, are highly interactive, and place emphasis on participants assisting each other. Both are 6 weeks long, include planning and problem solving as key elements, and use the same book. They differ in that in the CDSMP participants and leaders talk face-to-face in real time, whereas in the ICDSMP, participants and leaders interact asynchronously using threaded bulletin boards. Also the Internet groups are larger, 20 to 25 persons compared with 10 to 15 participants in the CDSMP. (Details of the ICDSMP can be found in the next section.)

The ICDSMP was evaluated with a population from all over the United States in a 1-year randomized trial. Like the small-group program, it was found to improve health status (health distress, pain, fatigue, and shortness of breath) and SE, as well as to reduce emergency department visits (Lorig, Ritter, Laurent, & Plant, 2006). A second longitudinal (nonrandomized) study for people served by the English National Health Service found that the ICDSMP was both feasible and associated with positive results (improved health indicators and health behaviors and reduced medical utilization; Lorig et al., 2008).

All of the above served as background for the current implementation study, which took place in the state of South Australia. The purpose of the study is to answer the following research questions:

Research Question 1: Could the ICDSMP be successfully implemented in South Australia?

Research Question 2: Could the ICDSMP reach rural and aboriginal people less served by the CDSMP?

Research Question 3: Would the ICDSMP be effective in terms of changes in health behaviors, health status, health care utilization, and reduction in lost workdays?

Method

Intervention

The ICDSMP is based on SE theory (Bandura, 1997) and uses processes to enhance efficacy to manage chronic diseases, including skills mastery, reinterpretation of symptoms, modeling, and group persuasion. In previous studies of the small-group CDSMP, 6-month improvements in SE were found to be associated with seven improved health indicators and two improved health behavior outcomes at 1 year (Lorig, Ritter, & Jaquez, 2005).

The content was determined by a literature review of the self-management activities taught in disease-specific courses and a series of 11 focus groups held with people with a number of different chronic conditions (Clark et al., 1991). From these, we found that about 80% of the content and problems were common across diseases. We used this common content as the basis for forming the content in the program. Content included assisting participants to design individualized exercise programs; use of cognitive symptom management techniques such as relaxation, visualization, distraction, and self-talk; methods for managing negative emotions such as anger, fear, and depression; an overview of medications; aspects of physician–patient communication; healthy eating; fatigue management; action planning; feedback; and methods for solving problems that result from living with a chronic disease (see Table 1).

Table 1.

Workshop Overview

	Week 1	Week 2	Week 3	Week 4	Week 5	Week 6
Overview of self-management and chronic health conditions	X
Making an action plan	X	X	X	X	X	X
Relaxation/cognitive symptom management	X		X	X	X	X
Feedback/problem solving		X	X	X	X	X
Difficult emotions		X	X
Fitness/exercise		X	X
Better breathing			X
Fatigue			X
Eating well				X
Advance directives				X
Communication				X
Medications					X
Making treatment decisions					X
Depression					X
Informing the health care team						X
Working with your health care professional						X
Future plans						X

The password-protected program consists of (a) interactive web-based self-management instructions (please see below for details), (b) four bulletin board discussion groups (problem solving, action planning, difficult emotions, and celebrations) for social networking, (c) a section of interactive web-based self-management tools, and (d) a book, Living a Healthy Life with Chronic Conditions (Lorig, Holman, et al., 2006), which the participants receive through the mail.

For 6 weeks, participants (approximately 25 per workshop) log on at will several times each week. Participants are told that the program will take a total of 1 to 2 hours weekly. The home page provides access to the weekly activities, which include the following:

Learning Center: Here the weekly program content is offered in 20 to 30 new web pages. Besides reading and interacting with the Learning Center web pages, there is a weekly question. Participants type in their answers, which are then posted on the appropriate bulletin board. For example, in Week 1 participants are asked, “What problems do you have with your long-term health condition?” The answers for Week 1 are posted on the problem-solving bulletin board, where they can be read and responded to by all participants. Participants are also asked to make and post a specific weekly action plan. This goes to the action-planning bulletin board and can also be read by all participants.

Discussion Center: This is the social networking area of the website, where participants can communicate with each on the four interactive threaded bulletin boards discussed above. Everything posted on the boards can be read and responded to by all participants and by the facilitators. These boards are populated by responses that participants and facilitators make in the Learning Center, as well by direct response. Participants and facilitators can log on to these bulletin boards as often as they choose to read posts from others, reply to posts, and/or start a new discussion.

My Tools: This consists of exercise and medication logs, audio relaxation exercises, and links to other health-related websites. It is an area where participants can keep individual plans, notes, and journals. Things posted on My Tools can only be read by the posting participant and cannot be seen by other participants or the facilitators.

Post Office: This is an internal messaging center where participants and facilitators can leave private messages for one another. Messages left in the Post Office can only be seen by those to whom the messages have been sent.

Help: This is a section where participants can review a program tutorial, read the privacy policy (in this case, the study informed consent), or e-mail the facilitators or program administrators.

Consistent with SE theory, the program was designed to encourage each participant to self-tailor the intervention. In tailored Internet interventions, the program asks the participants questions and then gives tailored algorithmic responses based on the answer to these questions. Self-tailoring makes the assumption that an informed individual, supported by peers, will make commitments to behavior changes that are both meaningful and healthful. Thus, the Learning Center gives information about how to deal with varied aspects of chronic disease, but it is the individual participant who makes the decision about what behaviors he or she will undertake each week. This is done by having participants make a weekly action plan for anything they would like to do the coming week. For example, one participant may plan to walk 15 minutes a day after dinner 3 days a week, whereas another participant may make a plan to paint his bathroom for 2 hours on Saturday and 2 hours on Sunday.

Once the action plan is made, participants are asked to rate from 1 to 10 how sure they are that they will complete the plan. If their confidence is low, facilitators post the action-planning board in the Discussion Center, asking the participant about potential problems and making suggestions about how the plan might be modified. If confidence is high, the facilitators say that this is a good plan and wish the participant success. The motto is always that participants should do what is “real” for them as opposed to trying to reach the “ideal.” The latter is often not seen by participants as obtainable. It is our belief that self-tailoring allows participants to gain confidence or SE in their ability to manage and try ever more complex behaviors. Each week each participant does “his or her own thing:” exercise, change the way he or she eats, work at making new social contacts, or go to bed earlier. Self-tailoring is also used in several other ways. Each participant and each group of participants generate their own discussion topics. The topics may be guided by the weekly questions, but it is participant answers that determine the essence of the discussions. These may differ from workshop to workshop, although there are often common themes.

Participants also self-tailor how they will use the program. Although they must read new Learning Center content each week, they determine how often to log on, when to log on, how much time and when to respond in the Discussion Center, and which tools they use in My Tools.

Facilitators

Facilitation was not an automated process. Rather, two peers facilitated each workshop with one facilitator logging on at least once a day. For this intervention, peers were defined as people living in South Australia with one or more chronic conditions. They came from both rural and urban South Australia. Facilitators were previously trained, small-group CDSMP leaders who had led small-group workshops. For the current study, facilitators were further trained through (a) webinars led by Stanford University staff and (b) one face-to-face session led by South Australian health professionals who were trainers in the CDSMP. The South Australian health professionals had also been trained to administer and facilitate the ICDSMP. Facilitators assisted participants by reminding them to log on, modeling action planning and problem solving, offering encouragement, and posting to the bulletin boards. They also monitored the daily posts of all participants and reported inappropriate posts to the South Australia program administrators. The facilitators then consulted with the investigators and took action as required. All facilitation took place online, either within the program pages or by e-mail. Unlike the small-group program leaders, facilitators did not deliver content, as this was scripted in the Learning Center.

Design/Recruitment

A convenience sample, consisting of all participants in the South Australia ICDSMP, was used. The sample was likely representative of South Australians with chronic disease who were willing and able to participate in an Internet-based CDSMP, but it was less likely to be representative of all Australians with chronic disease.

Recruitment was largely carried out by the South Australian Principal Project Officer with support from the Department of Health Media Unit. The main recruitment methods were advertising via print and radio media, although e-mail networks, organizational referrals, clinical referrals, and postings on websites were also used. Support organizations, such as Council on the Aging and Parkinson’s South Australia Incorporated, distributed information to their members.

To enter the study, potential participants (those who were interested in the study but had not yet been consented) went to the study website, where the study was briefly explained. They were then invited to leave their contact information on a secure portion of the site accessible only to the investigators. Within 2 weeks, they were invited by e-mail to join the study by entering a secure site, where they read an online consent statement that had been approved by the Stanford Institutional Review Board. They indicated their consent and then completed the baseline questionnaire. They were then assigned to a workshop with 16 to 25 other participants.

To be eligible for participation, one had to live in South Australia, have at least one long-term health condition, not have been in active treatment for cancer in the past year, and not be pregnant. Participants had to be at least 18 years old and not have taken part in one of the small-group Chronic Disease Self-Management courses in the community or related courses (e.g., Challenging Arthritis or the Positive Self-Management Program for people with HIV or AIDS). There were no other exclusion criteria.

Questionnaires/Data Collection

Data were collected by self-administered (online) questionnaires at baseline, 6 months, and 12 months. Baseline questionnaires included demographic and chronic disease information. Baseline and follow-up questionnaires included eight health indicators. Pain/physical discomfort, shortness of breath, and tiredness were measured by visual numeric scales (VNS; Ritter, González, Laurent, & Lorig, 2006). The VNS were adaptations of visual analogue scales (VAS; Dixon & Bird, 1981; Downie, Leatham, Rhind, Pickup, & Wright, 1978; Downie, Leatham, Rhind, Wright, et al., 1978). VNS differed from VAS in that they used size of lines, shading, numbers, and words, rather than just a double-anchored line. VNS were found to correlate (r = .72) with same-worded VAS and had a 94% completion rate compared with a 76% rate for the VAS (Ritter et al., 2006). The impact of disease on role activities such as work, recreation, and social activities was measured by The Illness Intrusiveness Scale (Devins et al., 1983; Devins et al., 1990). The Health Distress Scale, adapted from the Medical Outcomes Study, focused on the distress specifically associated with health problems (Stewart, Hays, & Ware, 1992). Self-Rated Global Health came from the U.S. National Health Survey and has been found to be predictive of future health status (Idler & Angel, 1990). The eight-item Health Assessment Instrument measured disability and was also used in the U.S. National Health Survey (Fries, Spitz, Kraines, & Holman, 1980). Participants reported the number of days that illness prevented participation in normal activities over the past 6 months. This question was adapted from the Behavioral Risk Factor Surveillance System Survey (Centers for Disease Control and Prevention, 2011). For all eight health indicator variables, a lower score was more desirable (e.g., less pain).

Seven health-related behaviors were measured. These included stretching and strengthening exercise, aerobic exercise (in minutes per week), use of techniques to improve communication with health care providers (a three-item, 6-point scale), and number of times mental stress management techniques were used in the past week. These instruments were developed and validated by the Stanford Patient Education Research Center during use in previous studies (Lorig et al., 1996). Participants also reported the number of alcohol drinks in the past week (Centers for Disease Control and Prevention, 2011). They were asked how often they adhered to their medication regime over the past 6 months (Morisky, Green, & Levine, 1986) and how often they followed their recommended health behaviors. The latter question was adapted from the Morisky adherence scale. For the health-related behaviors, higher scores were desirable (e.g., more aerobic exercise). In addition, for those who were working, we asked how many days of work they had missed because of their illness.

Four utilization measures were used: self-reported visits to medical doctors (general practitioners and specialists), emergency department visits, visits to other health professional (nurses, allied health professionals), and days in the hospital. In a previous study, we found that self-report of medical visits correlated r = .70 with chart audit data, and discrepancies were consistent over time and across treatment groups (Ritter et al., 2001).

Perceived SE, which reflects participants’ confidence to manage their own health condition, was measured. This scale was developed from previously validated SE instruments, and data derived from it have an internal consistency of .91 (Lorig et al., 1996). Satisfaction with the health care system was measured by six questions developed for the British online program. (Readers may access instruments and descriptions of their psychometric properties at http://patienteducation.stanford.edu/research/)

Data Analyses

Outcomes at 6 months were compared with baseline using paired t tests. To ascertain if any gains within the first 6 months were maintained for up to 1 year, outcomes at 1 year were compared with 6 months and with baseline, also using paired t tests. All participants who returned questionnaires were included in the analyses regardless of whether they had participated in the program or not. Intent-to-treat analyses were also conducted, and all participants were included. Data for those missing a questionnaire were substituted by using the last-known responses (Streiner & Geddes, 2001). This is a conservative analysis that assumes that the participants neither benefited nor were harmed by the intervention.

To further explore the effects of the intervention on specific conditions, subgroup analyses were conducted for those with arthritis, diabetes, or mental health conditions. For each group, outcomes for those with the specific condition were compared with outcomes for those without. Mental health conditions were a special interest, as the ICDSMP had not previously been evaluated with this population.

The number of health indicators that improved by at least .3 effect sizes was examined. Effect size is Cohen’s d, defined as the change score divided by the baseline standard deviation of each health indicator (Cohen, 1988). Fischer et al. (1999) found this effect size to be personally important for people with chronic conditions.

Results

Between December 2008 and July 2009, 308 persons left contact information. Eighty-three percent (n = 254) completed baseline questionnaires (Figure 1). A variety of sources were used for recruitment. Newspaper advertisements or announcements were the most frequent means by which participants found the program website (31%), followed by organizational referrals (16%), e-mails (15%), and websites (12%).

Figure 1.

Participants in program

Of the 254 who completed the baseline questionnaire, 249 participants completed registration and were assigned to a workshop. Eleven online workshops were held between January and July 2009. Of the 249 who registered, 20 dropped or withdrew mainly because of worsening health, and 229 logged on to at least one session of the program. The mean number of logons per participant was 25.4 (SD = 1.7). The mean number of sessions participated in was 4.8, out of a possible six weekly sessions (SD = 1.7). The percentage of the original 229 participants who participated in a given weekly session varied from 97% for Session 1 to 65% for Session 6. Among those who participated in a session, the mean number of logins per session varied from 4.6 (SD = 4.0) for Session 1 to 3.7 (SD = 5.5) for Session 6 (p = .003 for the difference in mean number of logons comparing Session 1 with Session 6).

Participants were predominantly Caucasian (98%, with 2.0% Aboriginal) and female (68%). The median age was 45, and 41% had a higher education degree. Fifty-nine percent of the participants reported more than a single chronic disease. The mean number of chronic conditions was 1.9 (SD = 1.1). Arthritis was the most common condition reported (40%). This was followed by mental health conditions (28%) and type 2 diabetes (26%), with a large number (50%) reporting a diverse variety of other diseases (Table 2). Participants who indicated that they had a mental health condition (self-defined using yes or no) also indicated their type of mental health condition(s). Depression was the most common (75% of those reporting a mental health condition), followed by anxiety (26%). Alcohol or substance abuse was not specifically included as a mental health condition, and only one participant indicated “alcoholism” as his mental health condition. Particular efforts were made to recruit rural residents and males, who were considered less served by South Australian small-group CDSMP programs. Approximately 50% of the participants were from rural (“country”) areas, with the other 50% coming from metropolitan areas.

Table 2.

Baseline Demographic Characteristics (N = 254)

Variable	%
Male	31.5
Have degree	40.9
Aboriginal	2.0
Age (years)
≤40	15.6
41-55	40.9
56-70	36.2
≥71	8.3
Employed	42.9
Chronic condition
Arthritis	40.1
Asthma	18.5
Cancer	6.2
Chronic obstructive pulmonary disease	5.5
Type 1 diabetes	4.7
Type 2 diabetes	26.0
Heart disease	13.4
Lung disease	4.7
Mental health condition	27.6
Other chronic condition (e.g., back problems, migraines, chronic fatigue syndrome, etc.)	50.5

Comparing demographic variables and baseline outcome values of those completing and not completing 6-month questionnaires, there was only one statistically significant difference. Noncompleters had lower values on medication adherence at baseline (4.3 vs. 4.7; p = .002, Cohen’s d effect size = .443). There were no significant baseline differences between those who completed 12-month questionnaires and those who did not.

As the result of a programming problem, 58 participants in three workshops were not sent the automated e-mail asking them to complete the 6-month questionnaire (Figure 1). This resulted in a reduced number of cases and some reduction in statistical power. Table 3 presents the mean baseline scores and change scores at 6 months for the 144 participants who completed the 6-month questionnaire. Four of eight health indicators had statistically significant improvements at the p < .05 level (health distress, illness intrusiveness, days illness prevented normal activities, and self-reported general health, with Cohen’s d effect sizes ranging from .16 for days illness prevented normal activities to .33 for health distress). After adjusting p values for multiple comparisons (Bonferroni correction, criteria p < .006), three health indicators remained significant. When the same analyses were repeated using intent-to-treat methodology as described above (Streiner & Geddes, 2001), the results were virtually identical.

Table 3.

South Australia Health, 6-Month Change Scores (N = 144)

Outcome Measure	Baseline Mean (SD)	6-Month Change, Mean (SD)	p
Health indicators
Self-reported health ↓	3.61 (0.87)	−0.21 (0.67)	<.001
Disability ↓	0.36 (0.36)	0.02 (0.25)	(.416)
Illness intrusiveness role function ↓	4.21 (1.23)	−0.27 (0.80)	<.001
Pain ↓	4.93 (3.34)	0.02 (2.39)	(.917)
Shortness of breath ↓	3.40 (3.12)	−0.01 (2.28)	.971
Fatigue ↓	7.09 (1.98)	−0.32 (2.02)	.060
Health distress ↓	2.61 (1.15)	−0.38 (0.92)	<.001
Days illness prevented participation in normal activities/past 6 months ↓	46.5 (55.3)	−9.00 (50.7)	.040
Health behaviors
Practice mental stress management times/week ↑	2.01 (3.88)	0.69 (3.72)	.032
Communication with doctor ↑	2.84 (1.14)	0.24 (1.05)	.008
Minutes of aerobic exercise/past week ↑	96.9 (97.8)	22.1 (89.8)	.004
Minutes of stretch/strength exercise ↑	41.1 (62.4)	7.08 (55.7)	.131
Alcohol drinks/week ↓	3.34 (5.96)	−0.87 (3.10)	.001
Medication adherence (0-5 scale) ↑	4.75 (0.62)	0.08 (0.47)	.048
Health behavior adherence (0-5 scale) ↑	2.93 (1.40)	0.36 (1.32)	.001
Health care satisfaction ↑	2.40 (1.03)	0.15 (1.07)	.157
Self-efficacy to manage conditions ↑	4.99 (2.01)	0.61 (1.61)	<.001
Health care utilization
Physician visits/past 6 months	8.27 (6.59)	−0.10 (6.77)	.864
Emergency room visits/past 6 months	0.31 (0.81)	−0.15 (0.68)	.011
Other health visits/past 6 months	8.19 (11.8)	−0.10 (10.4)	.207
Nights in hospital/past 6 months	2.50 (8.87)	−0.70 (8.46)	.326

Note. Parentheses surrounding the probability indicate that the change was negative—that is, condition or behavior became worse. An up-arrow (↑) indicates that a higher score is desirable, whereas a down-arrow (↓) indicates that a lower score is the desired outcome.

Six of seven health behaviors (mental stress management, communication with doctor, aerobic exercise, alcoholic drinks, medication adherence, and health behavior adherence) improved and were statistically significant at the p < .05 level. Adjusting for multiple comparisons (p > .007 level) reduced the number of significant improved behaviors to four. SE showed statistically significant improvements. Among health care utilization measures, all showed slight reductions. Only emergency room visits was statistically significant (both with and without Bonferroni correction).

When the number of days of work missed because of illness was assessed among the 55 participants who were employed at baseline and 6 months, there was a reduction of 1.4 days. However, with the small number of cases, this was not statistically significant.

When participants with mental health conditions were compared with those with no mental health conditions, there were no statistical differences in 6-month change scores for any outcomes. Similarly, when participants with arthritis were compared with those without arthritis, there were no significant differences. Finally, when participants with type 2 diabetes were compared with those without type 2 diabetes, there was only one significant difference. Health distress improved more for those without diabetes (−.49 vs. −.10; p = .02, Cohen’s d effect size = .470).

At 6 months, 75% of the participants improved by at least .3 Cohen’s d effect size for at least one of seven health indicators (not including illness days). Forty-five percent of participants improved .3 or greater effect size on at least two indicators.

At 1 year (Table 4), improvements were maintained. All workshop participants were offered the questionnaire, with 194 (85%) completing them. Compared with baseline, five of eight health indicators were statistically significant, whereas disability, pain, and shortness of breath showed little change from baseline. Once again, six of seven health behaviors were significantly improved. Emergency department visits continued to show statistically significant reduction (p < .049). Self-efficacy also remained statistically higher than at baseline. Intent-to-treat analyses of the 1 year data resulted in the same results. When 1-year results were compared with 6-month results, there were no significant differences among those who completed both questionnaires (N = 137). Only one outcome difference had a p value less than .2. At 1 year, physician visits between 6 and 12 months had decreased a mean .58 days compared with between baseline and 6 months (p = .051).

Table 4.

South Australia Health, 12-Month Change Scores (N = 194)

Outcome Measure	Baseline Mean (SD)	12-Month Change, Mean (SD)	p
Health indicators
Self-reported health ↓	3.57 (0.86)	−0.13 (0.77)	.022
Disability ↓	0.36 (0.36)	0.01 (0.29)	(.713)
Illness intrusiveness role function ↓	4.17 (1.24)	−0.27 (1.03)	<.001
Pain ↓	5.12 (3.35)	−0.03 (2.54)	.888
Shortness of breath ↓	3.56 (3.09)	−0.12 (2.86)	.547
Fatigue ↓	7.06 (2.02)	−0.37 (2.16)	.018
Health distress ↓	2.64 (1.12)	−0.42 (0.96)	<.001
Days illness prevented participation in normal activities/past 6 months ↓	43.92 (54.3)	−9.70 (57.8)	.023
Health behaviors
Practice mental stress management times/week ↑	1.78 (3.98)	0.72 (4.29)	.023
Communication with doctor ↑	2.77 (1.07)	0.33 (1.06)	<.001
Minutes of aerobic exercise/past week ↑	103 (133)	32.2 (130)	<.001
Minutes of stretch/strength exercise ↑	41.2 (67.1)	21.0 (84.0)	<.001
Alcohol drinks/week ↓	3.36 (6.03)	−0.56 (2.97)	.011
Medication adherence (0-5 scale) ↑	4.55 (1.06)	0.08 (0.79)	.145
Health behavior adherence (0-5 scale) ↑	2.88 (1.43)	0.30 (1.45)	.004
Health care satisfaction ↑	2.34 (1.03)	0.17 (1.21)	.087
Self-efficacy to manage conditions ↑	5.07 (2.03)	0.48 (1.94)	<.001
Health care utilization
Physician visits/past 6 months	7.69 (6.12)	−0.30 (6.06)	.493
Emergency room visits/past 6 months	0.26 (0.74)	−0.10 (0.69)	.049
Other health visits/past 6 months	7.69 (11.0)	−0.70 (13.0)	.455
Nights in hospital/past 6 months	2.16 (7.89)	−0.65 (8.95)	.314

There were no statistically significant differences between those with mental health conditions compared with those with no mental health conditions for 12-month change scores. When we compared those with arthritis to those with no arthritis, those with arthritis had greater reductions in pain at 12 months (p = .008) and less increase in stretching and strengthening exercise (p = .04). At 12 months, those with type 2 diabetes once again had significantly less improvement in health distress, compared with those without type 2 diabetes (p = .02).

Discussion

Feasibility

The ICDSMP appears to be feasible in South Australia. Recruitment was completed on schedule and resulted in a population representative of South Australia Internet users. The one exception is an underrepresentation of men. This may have been because of heavy recruitment in the arthritis community, where women are overrepresented. However, men have also been underrepresented in our other Internet and small-group Chronic Disease Self-Management Studies. In addition, the 75% retention rate between initial expression of interest on the website and actual participation in the program was higher than found in both the U.S. ICDSMP study and the English implementation study.

Reach

Rural (50%) and aboriginal (2%) participants were slightly overrepresented. People with mental health conditions were also overrepresented (28% compared with the estimated 20% of Australians who have a mental health condition within any single year). Thus, it appears that the ICDSMP both reached and was acceptable to these underserved populations.

Effectiveness

There are indications that the South Australia ICDSMP led to 6-month decreases in symptoms and improvement in health behaviors and SE. In addition, emergency room visits decreased. The benefits seen at 6 months were maintained for at least 1 year. The finding of long-term maintenance of improvements was similar to that found in previous studies of the ICDSMP. Although we do not have a clear explanation, we believe that it is because of participants improving their SE and incorporating behavior and other changes into their lives in a personally meaningful manner.

Only 55 participants were employed over the first 6 months. In a larger sample, the reduction of 1.4 days of missed work would likely have been statistically significant, but in this study it was not. If the same reduction can be replicated in a larger study of workers with chronic conditions, it could have implications for workplace health education interventions.

Combining the baseline to 6-month and 6-month-to-1-year reports, there was a mean reduction of.25 emergency department visits over 1 year. Assuming a cost of $1,000 per visit, this reduction would make the ICDSMP at best cost-effective and at least cost-neutral.

It is important to consider clinical significance, “a result (e.g., a treatment effect) that is large enough to be of practical importance to patients and health providers” (The Cochrane Collaborative, 2010, “Clinically Significant”). Using this definition, one must define the change in effect size that is of personal and practical importance to patients. Fischer et al. (1999) found this to be about .25 for people with arthritis. The .3 standard for meeting clinical significance in this study was based on the work of Fischer, as well as on the standards set by Cohen (1988), where an effect size of .2 is considered a small effect size and .5 is considered a moderate effect size.

In a study such as this, one would not expect a large effect size for a number of reasons. First any improvement is achieved above and beyond standard medical health care. Second, people with chronic conditions tend to decline over time. Thus, any improvement is against this trend. Finally, participants were not chosen for the severity of symptoms, and few participants had all of the symptoms that were tested. Those participants without a symptom at baseline could not improve on that symptom, and any change for those participants biased results in favor of the null hypothesis. The same is true for behaviors. Not all participants needed to change all behaviors. Participants benefited from the intervention in different ways. Thus, we presented the percentage of participants benefiting from the intervention for at least one health indicator with a clinically significant effect size (.30). Seventy-five percent of the participants met these criteria.

Participants with mental health conditions (predominantly depression) benefited in a way similar to people without these conditions. Thus, it appears that the Australian ICDSMP was appropriate for people with both mental and physical chronic illness.

Limitations

Because this was not a randomized study, all findings should be interpreted with caution. This trial was intended as a “real-world” implementation within a state health care system and thus could not include a randomized control group. As such, it was comparable with the implementation of the original small-group program within the U.S.-based Kaiser health care system and of the ICDSMP within the English national health care system and used similar methodology (Lorig et al., 2008; Lorig, Sobel, Ritter, Laurent, & Hobbs, 2001).

Even though 6-month “dropouts” did not differ at baseline from those who completed later questionnaires, because of the lack of a control group, we cannot be absolutely certain that “dropouts” did not affect the outcomes. It remains possible that those who became sicker were more likely to skip the later questionnaires. Thus, it would be highly desirable to conduct a randomized trial of the ICDSMP within the South Australian or larger Australian context. We need additional evidence such as offered here to support standard care guidelines in the developing realm of online medical support (Gustafson, Brennan, & Hawkins, 2007).

Internet-based interventions are limited to those who are literate and who have Internet access. However, such interventions offer an option to those who, because of health or remoteness, are unable to or who prefer not to participate in small-group interventions. If we are to truly reach large populations, we must have different modes of offering similar interventions. This approach takes into consideration the needs and preferences of the entire population. It offers the advantage over face-to-face interventions of not being time or location dependent. The ICDSMP should not be viewed as a replacement for the small-group CDSMP but rather as an additional means of reaching a broader population.

A programming error resulted in a reduced number of cases at 6 months. Thus, additional change scores might have been statistically significant with a larger number of cases. For example, the decrease in fatigue was not statistically significant at 6 months (p = .060) but was at 1 year (p = .018), even though the magnitude of change is not very different (−.32 vs. −.37). For this reason, among others, we also looked at the number of changes with moderate or higher effect sizes.

Implications

The relative success in recruiting rural participants and those with mental illness suggests that the program was appropriate for reaching South Australians who are often underserved. The South Australia ICDSMP was associated with a number of beneficial outcomes for individuals as well as the health care system. For individuals, there were improvements in self-reported health and reductions in health distress and illness intrusiveness. There were improvement in health behaviors, such as aerobic exercise and communication with practitioners. SE increased. Improvements at 6 months were generally maintained for up to 1 year. For the health care system, there were potential savings from reduction in emergency room visits.

This study contributes to the evidence base of online support programs and points to the acceptability and applicability of self-tailored programs. It confirmed the success of the implementation of the original ICDSMP in England (Lorig et al., 2008) in the Australian context. The results were encouraging. The program could complement the existing community-based CDSMP. It should be considered as an additional means of providing self-management and self-care support.

Footnotes

Authors’ Note

Nicole Brookes, Audra Garner, Christina Lum, and Angela Devlin assisted with recruitment and data management. David Kelly assisted in the South Australia implementation of the program and the preparation of progress reports.

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article:

Lorig and Laurent receive royalties from the book used in the program. Lorig, Laurent, and Plant potentially receive licensing fees if the online program is further disseminated.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

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