11th International Conference on Dementia and Dementia Care
February 22-23, 2021 | Vienna, Austria
2019 | Volume 3, Issue 1
1 Department of Medicine
Afiliation: , Email:
Extended Abstract Journal of Addiction and Clinical Research
Check your pattern-A development solution for a development problem
Patrick Moore
This paper is an update to Perception Development: The Cause of Substance
Use Disorders (Moore, 2018). In this follow up we examine the relationships
between the Affective Risk Response System (ARRS), Substance Abuse
Disorders (SUDs), autonomy and dependence. These relationships in
an empowerment model (Cummings, 2001) explain what works as well
as undesirable outcomes and suggest new objectives. If the method and
measurements discussed are accurate then we can identify and intervene
on SUDs before symptoms. If so, there is a tipping point at which SUDs
would cease to exist. Mistaking fear for faith will end. To understand the
relationships mentioned above a closer look at the ARRS as used in the
Prehab method is necessary.
In order to thrive in a risk filled world, humans continually change and
habituate. Recent research defines the ARRS as a built in, highly evolved
system responsible for this task. A whole new genre of literature exists
describing why we do the things we do, why we are not always rational. Titles
such as Fast and Slow, (Kahneman, 2011), The Blank Slate (Pinker, 2002),
The Science of Fear (Gardner, 2008 ), Sway (Brafman & Brafman, 2008 ),
and many others illustrate how our ARRS is either a powerful asset or tragic
liability. How can the ARRS be so powerful? It has to do with fear.
The power that Ropeik (2010, p. 67. ) attributes to the ARRS is hard to
overstate for one reason; the ARRS generates fear, or lack thereof. Fear
is no longer considered emotional or cognitive. Fear originates from the
ARRS. Ropeik further explains, when combined, these universal factors
compound their power and can combine with other biases becoming even
more powerful (2010, pp.65-133). The relationship between the ARRS and
SUDs is made possible by combining them in a model.
In the Prehab presentation (https://lnkd.in/gXs_vZz) and book (moore,
2016), some, but not all, risk response factors are arranged in a way
complimentary to a progressive addiction model called MAPP (Motivational
Assessment Prevention Program). The MAPP model has 5 stages of SUD
risk arranged from a low risk stage 0 to a severe risk stage 4. For the first
time, risk response factors are included with mental, physical and outcome
progression in a model for students to self-evaluate. The distribution of risk
factors and biases by stage is capitalized for the purpose of identification.
Stage 0: A low risk, stable, mature or developing Risk/Benefit process starts
here. Constructive Paranoia (Diamond, 2013) happens here. New risks are
encountered in the next stage.
Stage1: NEW gets attention. If students perceive the NEW as GOOD they
investigate. If others seem to BENEFIT with little RISK and they know more
(SOCIAL PROOF) than me; then students participate in the NEW. If NEW
behavior results in outcomes interpreted as HIGH BENEFIT and LOW
RISK and students believe they are in CONTROL then the behavior is
repeated.
Stage 2: VALUE ATTRIBUTION and GROUP POLARIZATION combine
to escalate behavior and students COMMIT to this behavior. Group
dynamics change here. Students become more significant members of
smaller groups in stage 2. There are usually some consequences which tend
to be ignored due to EUPHORIC RECALL.
Stage 3: At this point the behavior is no longer NEW, it is now FAMILIAR.
CONFIRMATORY bias reinforces the GOOD, increases BENEFIT and
reduces RISK, inspiring OPTIMISM in spite of overwhelming evidence to
the contrary. Groups are smaller in size and more extreme.
Stage 4: Desperate for change but clings to the FAMILIAR beyond all
reason. Anything NEW is feared. The inability to change, creates a lethal
cycle of PAIN AND SUFFERING and LOSS ACCEPTANCE. This cannot
be overstated. Loneliness, isolation, physical and mental dependence and
destructive paranoia happen here.
The relationship between the ARRS and SUDs is a natural fit. What we
do not know is how many students are at which stage and if they had this
information in a presentation would it do any good? A new assessment and
measurement became necessary.
Ignoring the conventional SUD attributes like quantity, frequency and drug
type created space for a new assessment. The MAPP assessment asks three
questions. What stage were you at? What stage are you at? What stage will
you be at? Combining these individual variables into one variable forms a
new variable named the Temporal Assessment Variable (TAV). The TAV is a
useful measurement for several reasons.
Whereas the generally accepted SUD assessments paint a picture of risk,
the TAV is more like a movie tracking both risk and benefit as affected by
other risk response factors back and forth over time and the entire SUD
continuum. In this way, direction, magnitude and velocity of change can
be seen. Another TAV advantage is that the first half of the measurement is
historical and behavioral as interpreted by the client in terms of the client’s
experience, not someone else’s interpretation. This measurement is called
the Student Type Variable (STV). The last half of the TAV reflects clinical
change or lack there in each client. This measurement is called the Student
Outcome Variable (SOV). Take for instance the TAV 320.
If a first semester college freshman self scores a TAV of 320 they are reporting
a drop in risk and behavior from a ( 3 ) to a ( 2 ) indicating some kind of
intervention. In the future they plan to be at Stage 0 indicating a change in
their interpretation of their own ARRS as result of the presentation. Cross
indexing the first half of the TAV with the second half of the TAV for data
analysis yields an amazing amount of epidemiological information. These
subjective interpretations of objective scores are supported by the frequency
distribution of the TAV and other measurements. The Alcohol Use Disorder
Identification Test (AUDIT) (Babor & Higgins-Biddle, 2001 ) is a decades
old, non equivalent and accepted measure that predicts nearly the exact
same frequency distribution. A correlation coefficient of r=.9999 is typical
between MAPP, AUDIT and eCHUG. The pattern remains the same,
MAPP and the TAV measurement are new. Only MAPP measures clinical
change over time before and after the intervention. The pattern is important
because it can be used as data to populate another model.
This is the risk pattern for random samples in Western Society in terms of
the TAV. 75% of a sample will be low risk. The TAV for these students ends
in a 0 or 1 following a 0 or 1. 20% of the sample will be high risk. The TAV
for these students ends in 0 or 1 down from a 1 or higher. 5% of the sample
is severe risk. The TAV for these students ends in 2 or higher. Direction
of risk, how fast and how far risk is taken can now be tracked by individual
or group.
Now we have data to further define relationships. The best way to see
relationships is in an elaboration model (Babbie, 2004, pp. 421-437), see
below.
High Benefit Low Benefit
Low Risk Stage 0 Stage 2,3
High Risk Stage 1 Stage 4
