Internet- and mobile phone based, automated programs for patients

Internet- and mobile phone based, automated programs for patients

„ Jean-François ETTER, PhD

„ IMSP, Faculty of Medicine, University of Geneva, Switzerland

„ E-mail: [email protected]

„ SSMI, Lausanne, May 13, 2011

Internet or mobile phone interventions

♦ Re-usable interventions, marginal cost = 0

(vs. consumables such as in-person visit, drugs)

♦ Low threshold :

- some prefer to avoid face-to-face contact - rural medical desert

- low cost

♦ Screening, early detection:

medical care seeked earlier

♦ Ageing, chronic diseases, costs

- more patients, fewer health professionals

- treat more people with less money and fewer staff - prevention better than cure

♦ SPAN: Smoking, Nutrition, Alcohol, Physical activity

Content of interventions

♦ Automated programs, with tailored feedback and follow-up - virtual coach, virtual therapist

♦ Tests + feedback, screening, early detection:

- e.g. BMI, depression, alcohol abuse, tobacco dependence

♦ Share, provide + obtain support - personal stories, blogs

♦ Support from real people (peers or professionals):

- support groups (my problem => the problem I share with others) - discussion forums

- ‘chat’

- 1 to 1 counseling by health professional

♦ Mobile, timely interaction (assessment and feedback) - e.g. smoking lapse, pill taking

Automated programs: aims

♦ Inform, educate

♦ Change attitudes, self-confidence

♦ Skills training

♦ Emotional support, encouragement

♦ Change behavior

- adherence, use of medications - participation in medical care

- smoking cessation, alcohol use, diet, etc.

♦ Maintain change over time

Automated online programs: principles

♦ Should be based on theory, e.g.

- transtheoretical model of behavior change - CBT, motivational interviewing

♦ Evaluation

- validated questionnaires

♦ Automated, individually-tailored feedback:

- written report, pictures, videos, audio files - personal action plan, exercises

♦ Follow-up

- tailored e-mails, SMS

♦ Personal page accessed with password:

- progress reports and graphs

Automated online programs: applications

♦ Addictions (tobacco, alcohol)

♦ Mental health

- Depression, anxiety

♦ Health promotion, prevention:

- Physical activity, weight loss, diet

♦ Chronic diseases self-management:

- Asthma, diabetes, chronic pain

♦ Participation in healthcare, adherence

♦ Patient education

♦ Patient empowerment (ability to influence + understand own health)

« health management » vs. treatment

♦ Etc…

Impact = Reach * Efficacy

„ RE-AIM framework for health promotion

(Glasgow et al., Am J Public Health 1999;89:1322)

„ Reach

„ Efficacy

„ Adoption

by health care settings, workplaces

„ Implementation

whether patients use it as intended, adherence

„ Maintenance over time

Reach

„ Switzerland:

. 75% of population have access to Internet . >90% have a mobile phone

„ Mobile phones: high usage even in low-income people / countries

„ 24 / 7 / 365

„ Low cost for users, once equipped

„ Everywhere, even in remote, rural areas (medical desert), or for patients with limited access to healthcare system (e.g. mothers of young children, older people, handicap)

„ Many people with mental health problems do not seek treatment

„ e.g. online screening for alcohol: early detection + treatment

„ Translation: worldwide impact

Reach: retain visitors, obtain several visits

„ Chronic, relapsing conditions

„ Long term treatment

„ Support for several attempts to change, over several years

„ Challenges:

- Retain participants over many years - Obtain high exposure among visitors

. Number of pages seen

. Time spent on website / smart phone app . Obtain several visits per visitor

Hard-to-reach audiences

„ People not motivated to change, or ambivalent, or unaware

„ Illiteracy, low SES, immigrants (if no translation)

„ Older people

(may change over time as more retired people used Internet professionally)

How to reach smokers who are not motivated to quit?

„ What specific features should be developed for them ?

47

25 2 17

9

Problemignor Ambivalent Precont Contempl Prepar

Source:

Tabakmonitoring 2010

Switzerland: % smokers

20-69 years 16-19 years

Switzerland: increasing social gap

„ By impacting only high SES, current smoking prevention

interventions / policies inadvertently increased health inequalities

How to reach the low SES, the illiterate ?

„ Prevalence of illiteracy = 10-15%

„ Involve target audience in the development of programs / apps

„ Work with specialized social / healthcare providers

„ Develop specific contents / supports - Video

- Audio (podcasts) - Pictures, comics

„ Add TV, radio component to intervention

Efficacy of automated, online systems

„ Many RCTS have been published in recent years + several meta-analyses

„ Smoking cessation:

24 years of RCTs of online interventions

1^st RCT on Compuserve was conducted in 1987 *

„ Next slides: reviews and meta-analyses only

„ * Schneider SJ, Walter R, O‘Donnell R. Computerized communication as a medium for behavioral smoking cessation treatment: controlled evaluation. Comp Hum Behav 1990;6(2):141-151.

„ * Schneider, 1986. S.J. Schneider , Trial of an on-line behavioral smoking cessation program.

Computers in Human Behavior 2 (1986), pp. 277–286

Smoking: 9 RCTs using the Web: OR=1.40

Myung SK, McDonnell DD, Kazinets G, Seo HG, Moskowitz JM. Effects of Web- and computer-based smoking cessation programs: meta-analysis of randomized controlled trials.

Arch Intern Med. 2009;169:929-37.

Smoking, meta-analysis:

11 RCTs on Web: RR=1.80

• Web-based, tailored, interactive smoking cessation interventions were effective compared with untailored booklets or e-mail interventions

[rate ratio (RR) 1.8; 95% confidence interval (CI) 1.4–2.3], increasing 6-month abstinence by 17% (95% CI 12–21%).

• Fully automated interventions increased smoking cessation rates (RR 1.4, 95% CI 1.0–2.0), but evidence was less clear-cut for non- automated interventions.

• Shahab L, McEwen A. Online support for smoking cessation: a systematic review of the literature. Addiction. 2009;104:1792-804.

Smoking: Cochrane review

• 20 RCTs

• Heterogeneity, little pooling

• Conclusions: “Some Internet-based interventions can assist smoking cessation, especially if

- the information is appropriately tailored to the users and - frequent automated contacts with the users are ensured,

however trials did not show consistent effects”.

• Civljak et al. Internet-based interventions for smoking cessation. Cochrane Database Syst Rev. 2010;9:CD007078.

Cochrane: Tailored interactive internet versus non tailored / non internet, smoking abstinence at short term follow-up.

Efficacy: online alcohol interventions

„ Meta-analysis, 17 RCTs

„ Median effect size = 0.54 (medium effect size)

„ White A., et al. Online Alcohol Interventions: A Systematic Review. J Med Internet Res 2010;12:e62

Efficacy:

online CBT for depression and anxiety

„ Meta-analysis, 26 RCTs

„ CBT, self-help

„ Effect size

0.42 to 0.65 for depression (medium effect size)

0.29 to 1.74 for anxiety (medium to large effect size)

„ Griffiths et al. The efficacy of internet interventions for depression and anxiety disorders: a review of randomised controlled trials. Med J Australia 2010;192:S4

Efficacy: online interventions for depression

„ Meta-analysis, 12 RCTs

„ Total N=2446

„ Effect size = 0.41 (medium effect size)

„ Andersson et al. Internet-based and other computerized psychological treatments for adult depression:

a meta-analysis. Cogn Behav Ther. 2009;38:196-205.

Efficacy: online interventions for anxiety

„ Meta-analysis, 19 RCTs

„ Effect size = 0.49-1.14 (medium to large effect sizes)

„ Similar to effect sizes for therapist-delivered treatment

„ Reger et al. A meta-analysis of the effects of internet- and computer-based cognitive-behavioral treatments for anxiety. J Clin Psychol. 2009 Jan;65(1):53-75.

Efficacy: online interventions for weight loss

„ Review: 18 studies

„ Results: heterogeneity

„ Half the studies showed effectiveness

„ Neve et al. Effectiveness of web-based interventions in achieving weight loss and weight loss maintenance in overweight and obese adults: a systematic review with meta-analysis. Obes Rev.

2010;11:306-21.

Efficacy: online interventions for chronic pain

„ Meta-analysis: 11 studies

„ CBT

„ Effect size = 0.29 (small effect)

„ Macea et al. The efficacy of web-based cognitive behavioral interventions for chronic pain: a systematic review and meta-analysis. J Pain. 2010;11:917-29.

Efficacy: education of patients with breast cancer

„ Review: 14 articles (incl. 9 RCTs)

„ N=2374 participants

„ Interactive, Internet-based programs

„ Positive effects on patients’ knowledge

„ Ryhänen et al. The effects of Internet or interactive computer-based patient

education in the field of breast cancer: a systematic literature review. Patient Educ Couns. 2010;79:5-13.

Efficacy: mobile phone intervention for diabetes / glycaemic control

„ Meta-analysis: 22 trials

„ 1657 participants

„ Most interventions = mobile phone + Internet

„ Median follow-up duration = 6 months

„ Reduced glycated hemoglobin values [ HbA(1c) ] by:

- 0.5%, 95% confidence interval, 0.3-0.7%

- 6 mmol/mol; 95% confidence interval 4-8 mmol/mol

„ Conclusion: “statistically significant improvement in glycaemic control and self-management in diabetes care”

„ Liang et al. Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis. Diabetic Medicine. 2011 Apr;28:455-63.

Efficacy: summary

„ Many studies, large N, several meta-analysis

„ Proven efficacy across various health problems and behaviors

„ RCTs mainly of automated interventions

„ Fewer RCTs of other features / services

(e.g. peer groups, discussion forums, mobile phone interv.)

„ Large variability of effects

„ Usually, follow-up <12 months

„ And…

several studies show that the effect of online, automated

interventions is similar to the effect of face-to-face counseling

Efficacy: open questions

„ Which service is best suited to each category

(age, sex, education, motivation, severity of disease)

„ Participant’s characteristics that predict outcome?

„ Moderators / mediators

„ Assess unintended effects

- substitute for face-to-face counseling ?

„ Effect of web / mobile phone interventions, over and above

traditional interventions, in intergrated programs (self-help materials, helplines, clinics)

Quality

„ Too often, low quality of programs / interventions / apps

„ Depth of coverage for key topics is often minimal

„ Potential adverse consequences of low quality programs:

- interventions perceived as ineffective - missed opportunities

- decreased self-efficacy if attempt to change behavior fails - misleading information

… on treatments (recommendations to avoid effective treatments or to use ineffective ones)

… on the nature of disease

„ Online social support:

- for whom is it effective?

- adverse outcomes (conflicts + e.g. pro-anorexia websites)

112

71

39 37

31 29 28 26

22 20 18 17 13

0 20 40 60 80 100 120

N answers

PM Quit Assist QuitNet.com RJ Reynolds Lungusa.com WebMD.com

Committed Quitters cancer.org

Stopsmoking.com Quitsmoking.com

Quitsmoking.About.com Anti-smoking.org

Nicorette.com Smokefree.gov

USA: smoking cessation websites most cited by smokers

Web survey, 2005, 706 participants Etter JF. Nicotine & Tobacco Research, 2006;8:S27

5.9 6.4 6.2 6.7

6.1 6.7 6.5 5.5

6

7 7.2 6.1

7.4

0 1 2 3 4 5 6 7 8 9 10

Quality 1-10

PM Quit Assist QuitNet.com RJ Reynolds Lungusa.com WebMD.com

Committed Quitters cancer.org

Stopsmoking.com Quitsmoking.com

Quitsmoking.About.com Anti-smoking.org

Nicorette.com Smokefree.gov

USA: highest quality websites (1-10 score)

Social media: adverse outcomes

„ Conflicts, mobbing on discussion forums

„ Normality by numbers:

e.g. heavy drinking = normal in groups of heavy drinkers

„ E.g. pro-anorexia, pro-suicide websites

Adoption, implemention, maintenance

„ Adoption

- by target audience

- by health care settings - at the workplace

„ Implementation

- do patients use these interventions as intended ? - adherence

„ Maintenance over time

- viability, durability of web sites / mobile phone apps - many websites / programs disappear after a few years

- many of the interventions tested were experimental and are no longer available

- multiple sources of funding

Adoption: integration virtual + real world

Collaborations with:

„ Doctors, pharmacists, dentists, hospitals

„ Smoking cessation clinics

„ Helplines

„ Schools, workplaces

„ Government agencies

„ NGOs

„ Pharma companies

„ Large websites (not just health-related websites)

Conclusions

„ High reach

„ Efficacy of fully-automated programs, various fields

„ Efficacy of other Internet / mobile phone features / services ?

„ Complementary to clinic visit

„ Potential for development:

- integration in healthcare systems

- health disparities: develop interventions that reach + are effective in low SES

- translate + export to low-income countries

„ Who should pay for the products and services provided by this new industry?