Importance of This Time-Series Research

Briefly describe a time series design that you would use to investigate the impact of the
effectiveness of substance abuse treatment, and explain how you would collect and
record the additional data. Be Specific.
2) Select a method for graphically representing the provided data. Use the method to
create a graph.
3). Analyze the data and provide a narrative description of your analysis.
4) Conclusion.

Conducting Time Series Research

Importance of This Time-Series Research
Substance abuse is a serious problem and stakeholders are continually doing all they
can to curb the effects. One of the key pillars of fighting this vice is a concept referred to as
Treatment-on-Demand (TOD). According to Sisko (1995) TOD avails various treatment
options from which drug users can choose. It is at the backdrop of this idea that this time-
series research was conducted. 
This study was designed as an effort to investigate the effects of a TOD Program for
marijuana users in the County. This program was started by a local NGO to try raising the
number of patients seeking medical help from government clinics. On data, this time series
research relied on data from the health promotion department within the ministry of public
health. This secondary data ranged from year 2008 to 2011. In this analysis, the dependent
variables were type of treatment, number of admissions per week and characteristics of the
patients. The TOD and time were the independent variables.
Experimental Data Collection
In recording the data, admissions were solely for those patients who enrolled for the
TOD program by having their details entered in the admission form. On patient

Time series research 2

characteristics, the research dwelt on age, information about previous drug use, sex, and race.
The research also highlighted the kind of treatment each patient received from the clinic and
this recorded using a special number. The County governor’s office furnished the research
with information about the programs funding.
To create a graphical representation of the data, the analysis worked with data on
patients’ admissions and annual funding for the TOD program during the fiscal years from
2008 to 2011. To steer away from the usual problems of conventional linear regression, this
time-series analysis relied on the auto-regressive integrated moving average techniques,
otherwise referred to as ARIMA.

Graph 40
600 30

400 Million $ Funding 20

Admissions monthly
200 10

2008 2009 2010 2011


Figure 1: Graphs Of Monthly Admissions And Funding In Millions Against Time In

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Interpretation of the data
From the graph, there are some depictions. From phase value, the number of
admissions to the program remained constant for 1 year, only to start increasing in the 2 nd
year. This is shown by the smooth graph of monthly admissions against time in years. This
suggests that it took at least 1 year for the effects of the TOD program to be felt on the
The second graph indicated through steps represents the annual funding in terms of
million dollars from the NGO funders. Funding for the program was increased on annual
basis (Sisko, 1995). 
Argument and Conclusion
This analysis is based on the effects of the TOD program for marijuana users in the
County. This program was associated in the observed increase in number of people being
admitted to the government clinic. Though there was some delay in realizing this increase in
admissions, this was attributed to the lag in funding the program.
The main aim of the County TOD program was to encourage marijuana users to use
the government’s comprehensive care units. This program was linked with a decrease in the
target group’s use of front-end alternatives. Not to say that frond-end solutions are bad, but
they act as pathways to treatments that are more comprehensive. In addition, there was a
significant increase in the number of admissions for marijuana users. From these findings, it
is concluded that initiatives such as the TOD in the County are effective in enhancing
comprehensive care for substance abusers in the society.

Time series research 4


Sisko B., (1995). Treatment On Demand: Realistic goal or impossible dream?. The Ninth
International Conference On Drug Policy Reform, Loews Santa Monica Beach Hotel

Santa Monica, California.