Associate Professor Frances Kay-Lambkin PhDNational Health and Medical Research Council Research Fellow

It’s worth a try…Integrating technology into the treatment of mental health and addictive disorders

Global eHealth Research & Innovation Cluster, UoN

The mental health of

Australians

NSMHWB (2007)

Comorbidity is the rule◉ 25-50% of people experience comorbidity– >1 mental disorder

– One mental disorder and 1+ physical conditions

◉ Every year, approx. 340,000 Australians experience the combination of a mental health and alcohol/other drug problem– Excluding tobacco alone

– Increasing by approx. 10% annuallyAIHW (2012) Comorbidity of mental disorders & physical conditions

Sacks et al. (2013) J Substance Ab Treat, 44: 48-493Rush (2007) Am J Psychiatry, 164(2): 201-204

Treatment access is poor◉ In Australia, the proportion of adults with

current mental health problems using traditional services has not increased:– 38% in 1997 vs. 35% in 2007.

– Physical disorders = 80%.

◉ Despite government initiatives– Estimated annual investment $3.2 billion.

– Australia – BOiMHC – 10 sessions with psychologist.

Australian Bureau of Statistics (2008). ABS Cat No. 4326.0

Christensen & Hickie (2010). Medical J Aust 192(11): S53-S56.

Why don’t people seek treatment?

Individual determinants Structural determinants

•Mental health literacy •Support systems

•Attitudes to services •Referral pathways

•Attitudes to conditions •Payment systems

•Perceived stigma •Geographical isolation

•Time commitments •Lack of relevant services

•Reliance on self

(Barker, et al., 2005; Rickwood, et al., 2007)

How do we overcome these barriers?

The potential of e-health to respond...◉ E-health = rapidly expanding field of health

information and communication technology.

◉ Widespread recognition within health sector that better use of e-health initiatives should play a critical role in improving the healthcare system.

◉ Increasing acceptance for individuals to take a more active role in protecting their health and participating in their own health care.

Access to technology…bridging the digital divide Gen

PopMild Dep

Mod-Sev Dep

Risky Drink

Harmful Drink

Psychosis PTSD + AOD

Mobile 44% 34% 37% 46% 41% 34% 34%

Mobile with Internet 22% 23% 30% 21% 41% 30% 48%

Internet 84% 84% 79% 87% 100% 65% 66%

Gen Pop=General Population (N=894) – no MH/AOD Mild Dep=PHQ-9 score 5-9 (N=188) Mod-Sev Dep=PHQ-9 score ≥ 10 (N=67) Risky Drink=AUDIT score 8-15 (N=135) Harmful Drink=AUDIT score ≥ 16 (N=22) Psychosis=Current diagnosis (N=115) PTSD+AOD=Current AOD treatment (N=29)

Previous use of the Internet for…

Gen Pop

Mild Dep

Mod-Sev Dep

Risky Drink

Harmful Drink

Psychosis PTSD + AOD

Mental Health

9% 19% 39% 12% 27% 18% 17%

AOD 2% 6% 5% 2% 32% 7% 31%

Gen Pop=General Population (N=894) – no MH/AOD Mild Dep=PHQ-9 score 5-9 (N=188 Mod-Sev Dep=PHQ-9 score ≥ 10 (N=67 Risky Drink=AUDIT score 8-15 (N=135) Harmful Drink=AUDIT score ≥ 16 (N=22) Psychosis=Current diagnosis (N=115) PTSD+AOD=Current AOD treatment (N=29)

Potential of eHealth in comorbidity

Individual determinants Structural determinants

•Mental health literacy •Support systems

•Attitudes to services •Referral pathways

•Attitudes to conditions •Payment systems

•Perceived stigma •Geographical isolation

•Time commitments •Lack of relevant services

•Reliance on self

(Barker, et al., 2005; Rickwood, et al., 2007)

Does eHealth deliver for comorbidity?

• Self-Help for Alcohol/other drugs and DEpression

• 10 modules of CBT/MI and mindfulness– Behavioural activation– Managing thoughts– Problem solving– Drink/drug refusal– Coping with cravings– Relapse prevention

SHADE (www.shadetreatment.com)

iTreAD (www.itread.com.au)

• Online monthly monitoring• 4 sessions of CBT for

depression and binge drinking– Challenging thoughts– Behavioural activation– Coping with cravings

• Online social networking

• Serious game for depression and alcohol misuse– See links between mood

and drinking

• Pilot testing underway– Engagement of young

people– Effective in translating key

CBT messages to real life

SHADoW

Will eHealth overcome attitudinal barriers?◉ Will populations with addictive disorders,

who are typically low-treatment seeking access eHealth to support their concerns?– ?pride, ?fear of stigma, ?manage on their own

Consider using the Internet…

Gen Pop

Mild Dep

Mod-Sev Dep

Risky Drink

Harmful Drink

Psychosis PTSD + AOD

M Health Treatment

17% 28% 39% 21% 45% 33% 55%

AOD Treatment

7% 10% 7% 11% 36% 20% 62%

Gen Pop=General Population (N=894) – no MH/AOD Mild Dep=PHQ-9 score 5-9 (N=188 Mod-Sev Dep=PHQ-9 score ≥ 10 (N=67 Risky Drink=AUDIT score 8-15 (N=135) Harmful Drink=AUDIT score ≥ 16 (N=22) Psychosis=Current diagnosis (N=115) PTSD+AOD=Current AOD treatment (N=29)

SHADE study◉ No differences in therapeutic alliance or treatment

satisfaction for therapist-delivered versus SHADE treatment.

◉ No relationship between treatment preference and retention, alliance or perceptions.

◉ If no preference, significantly greater benefit for alcohol use from SHADE.

◉ Content and modality of SHADE delivery acceptable

• “Helped me take more control in my life”

Kay-Lambkin et al. (2012), J Dual Diagnosis 8(4):262-276

The vital piece in the puzzle….us!What concerns people about eHealth?

◉ Sample with psychosis

– Trust, credibility, accuracy of information

– Privacy concerns

– Impersonal

◉ Sample of General Population excl. psychosis

– Reliability and accuracy of information

– Confidentiality and anonymity

– ImpersonalCarroll & Rounsaville (2010) Current Psychiatry Reports 12: 426-

432Kay-Lambkin et al. (2011) BMC Public Health 11:277

How might we address this*?◉ Website/Promotion/Champion

– Provide evidence for efficacy– Expertise of developers– Transparency of sponsorship of site, ownership and

authorship of content– Last updated information– Quality seal of approval– Recommended by peers/family/professionals/other sites

◉ Internet treatment a useful step within a larger therapeutic process

◉ Appropriate marketing in non-Internet environments*Kay-Lambkin et al. (2011) BMC Public Health 11:277)

Klein et al. (2010) JMIR12 (5): e51p1-e51p12

Acknowledgements◉ Amanda Baker◉ Maree Teesson◉ David Kavanagh◉ Brian Kelly◉ Terry Lewin◉ Vaughan Carr

Funding◉ AERF◉ NHMRC◉ DoHA

Institutions

f.kaylambkin@unsw.edu.au