Over the recent years, a growing controversy has developed between conventional and complementary/alternative medicine. While complementary/alternative medicine has become increasingly popular, compensation packages have been reduced for lack of scientific evidence. Especially in areas where accepted treatments deliver insufficient results (often characterized by complex cause-and-effect relationships), we recognize patients/parents wanting convincing answers to questions such as:

• Why are therapies with strong indicators for better/breakthrough treatment results not scientifically researched with high priority? Doesn't the Hippocratic Oath "I will apply, for the benefit of the sick, all measures that are required..." ask for this research?
  
• When a therapy with strong indicators for better results isn't/can't be scientifically proved, what could be the reasons? What has been done to ensure these reasons have been sufficiently investigated and addressed?
• When accepted treatment delivers insufficient results, why is it made increasingly difficult for patients/parents to try alternative treatments?

The controversy:

Please observe: We also recognize different levels of public debates in different countries. In German-speaking countries, for example, the public debate demonstrates respect for complementary/alternative treatments.

Conclusion: A debate is needed. Here is our contribution to this debate:

1. Where can we find Guidance?

Undoubtedly, great thinkers like Einstein, Newton and Darwin delivered breakthrough results for daunting challenges. We admire them for what they achieved and we want to achieve similar breakthroughs.

Today, cost explosions within national health systems and an "explosion" in mental disorders demand breakthrough results. The obvious question becomes: How would Einstein, Newton and other great thinkers have approached this challenge?

Great thinkers are a special-interest research area of one of our advisors, Prof. Michael Fitzgerald. According to his research, Einstein, Newton and numerous other great thinkers show common characteristics. Please compare their common characteristics with today's thinking and working practices.

With these characteristics in mind: Do we continue to build on today's practices or do we follow the lead of Einstein, Newton, Darwin and other great thinkers? For On Mental Health, the answer is obvious:

With this guidance in mind, following is a list of emerging patterns.

Emerging Patterns from Unconventional/Alternative Treatment

• Hype - Some want to get rich; false hope is created
• Natural treatment - traditional Chinese medicine (TCM), Reiki and other ancient treatments (body- and brain-related)
  • Their long history - It can't be all "hocus-pocus" or only to fill pockets.
  • Many indicators of good to breakthrough treatment results and partial scientific acceptance (such as acupuncture)
• Universities researching TCM and other ancient treatments; clinics with scientifically trained doctors offering natural treatment and TCM in Germany.
• Some of those treatments approaching the body and the brain as single system (versus science-based Western medicine focusing on "cause and effect," the individual organs and discipline), in particular balance - stimulating the body's self-healing mechanisms
• Some of the treatments for mental matters that apply capacity management techniques (see capacity bottleneck component in the menu).
• Too many indicators of good to breakthrough results from certain treatments
• "Black sheep" attention dominating the media – Media attention has become more balanced in some countries, such as Germany.

Emerging Patterns from Brain Research

• A talk by John Lawson (University of Cambridge) at the Innovative Research in Autism (IRIA) Conference, April 2009, Tours, France - Treatment results for autism are disappointing; today's main research models for autism appear to be too limited. Those can be characterized as closed models or "if x then y"-type models. There is a need for open research models ("if x then perhaps not y").
• A conflict: exact research models (cause and effect based, "if x then y") versus phenomena that have far too many or no direct cause-and-effect relationships but are common in complex dynamic systems: capacity bottlenecks and the butterfly effect
• Exact research methods (mathematics, "if x then y") and linear methods (prior research) being applied versus the brain being a complex and dynamic system. - Is there a limit to the effectiveness of these methods?
• New research is normally based on prior research. - What if prior research is too limited due to research gaps?
  • Reasonably certain gaps: implications of capacity bottlenecks; use of capacity management techniques
  • Where is the attention to the butterfly effect in the research reports?
  • Where is the discipline that addresses the brain as a single complex and dynamic system?
• The number of resources put into brain research – From five scientific conferences in 2008/2009:
  • More than 26,000 scientists attended.
  • More than 17,000 abstracts were submitted (one abstract represents roughly one research project).
  • Status of brain research: It remains unknown how the brain operates; causes of mental disorders remain unknown.
• Treatments are improving but there is a lack of breakthrough treatments (from the patient's perspective).

Emerging Patterns - General

• The main challenge: Is there something that isn't working as it should?
• The media in Germany are talking about a boom in alternative treatments.
• Officials believe that treatments need to be scientifically proved; many patients/parents do not require proof if the risks are equal to or lower than officially accepted treatment.
• All that matters is the treatment result.

2. What is the Root Cause of the Challenge?

Emerging root cause: When too many pieces, dependencies (direct and indirect) and changes come together, solution approaches are initially effective, but then become ineffective.

Some of the pieces and dependencies:

Research gaps - exact research models - butterfly effects - capacity bottlenecks - knowledge gaps - prior research requirements - cause and effect relationship requirements - speed of treatment advancement - strict requirements for research funding - time needed until proof is generally accepted - politics - missing research discipline - standards - working practices

3. How can the Challenge be resolved?