intervention studies

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Intervention Studies Sue Lindsay, Ph.D., MSW, MPH Division of Epidemiology and Biostatistics Institute for Public Health San Diego State University

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Intervention Studies. Sue Lindsay, Ph.D., MSW, MPH Division of Epidemiology and Biostatistics Institute for Public Health San Diego State University. What Causes this Disease?. Risk Factors Age Gender Bacteria or virus Exposure to toxins Diet Exercise/activity Genetics - PowerPoint PPT Presentation

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Page 1: Intervention Studies

Intervention Studies

Sue Lindsay, Ph.D., MSW, MPH

Division of Epidemiology and Biostatistics

Institute for Public Health

San Diego State University

Page 2: Intervention Studies

Risk Factors• Age• Gender• Bacteria or virus• Exposure to toxins• Diet• Exercise/activity• Genetics • Stress• Childhood trauma• Body mass index• Smoking/alcohol

What Causes this Disease?

Disease

Page 3: Intervention Studies

Interventions• New screening techniques• New medical technologies• Medication• Surgical interventions• Diet and exercise programs• Educational interventions• Stress reduction programs• Smoking cessation programs• Genetic screenings• Health promotion activities• Case management and support• Others?

How can we prevent,

detect, and treat this disease?

Disease

Page 4: Intervention Studies

Intervention Studies

Research designs that are utilizedto evaluate the impact of a therapy,intervention, or prevention strategy

Page 5: Intervention Studies

Types of Designs

• Observational Designs (4)

• Comparison Group Designs (4)

• Experimental designs (4) Clinical Trials (4)

Page 6: Intervention Studies

Comparison Groupvs.

Control Group

Page 7: Intervention Studies

Observational Designs

1. Before and after studies

2. Cross-sectional studies with non- uniform programs

3. Panel or Cohort Studies

4. Population-based time series

Page 8: Intervention Studies

Observational Designs

• Before and After Studies (pre-test, post-test)– Select persons to receive the intervention

– Measure outcome of interest before intervention

– Measure outcome of interest after intervention

Pre-test Post-testIntervention

Page 9: Intervention Studies

Observational Designs

• Cross-Sectional Studies for Non-Uniform Programs– Select persons to receive the intervention

– Carefully measure participation in the program

– Measure outcome of interest after intervention

Measureoutcome

High users

Intervention

Low users

Page 10: Intervention Studies

Observational Designs

• Panel or Cohort Studies – Select persons to receive the intervention

– Measure participation in the program at multiple points in time

– Measure outcome at multiple points in time

MeasureInitial

Measure6 months

Measure1 year

Intervention

Page 11: Intervention Studies

Observational Designs

• Population-based time series– Many cross-sectional measures of a population

– Track the exposure of the population to an intervention

– Compare cross-sectional results with exposure

InitialSurvey

1 yearSurvey

2 yearSurvey

Measure Intervention Measure Intervention Measure Intervention

Page 12: Intervention Studies

Comparison Group Designs

1. Historic or Generic Comparison Group

2. Concurrent Comparison Group

3. Matched Comparison Group

4. Comparison Cross-Over Designs

Page 13: Intervention Studies

Comparison Group Designs

• Historic or Generic Comparison Group– Select persons to receive the intervention

– Select historic control group or publicly available norms

– Measure outcome of interest after intervention

Measureoutcome

Intervention

Comparison group: Previous yearCounty, State, or National rates

Page 14: Intervention Studies

Comparison Group Designs

• Concurrent Comparison group– Select persons to receive the intervention

– Select another group that does not receive the intervention

– Measure outcome of interest before and after intervention

InitialMeasure

FinalMeasure

Intervention

Comparison GroupNo Intervention

Page 15: Intervention Studies

Comparison Group Designs

• Matched comparison group– Select persons to receive the intervention

– Select comparison group matched to intervention group

– Measure outcome of interest before and after intervention

InitialMeasure

FinalMeasure

Intervention

Matched comparison groupNo Intervention

Page 16: Intervention Studies

Comparison Group Designs

• Comparison Cross-Over Designs– Select persons to receive the intervention

– Select comparison group

– After some time, intervention group becomes comparison group,

and comparison group becomes intervention group.

Intervention

No Intervention

No Intervention

Intervention

InitialMeasure

MeasureAt Cross-Over

Final Measure

Page 17: Intervention Studies

Experimental Designs

Clinical Trials

1. Randomized Clinical Trial

2. Stratified Randomization

3. Experimental Cross-Over Designs

4. Factorial Designs

Page 18: Intervention Studies

Clinical Trial Study Designs

Improved Not Improved

Improved Not improved

Treatment

#1

Treatment

#2

Defined Population

Randomize

Page 19: Intervention Studies

Types of Clinical Trials(David E. Lilienfeld)

1. Therapeutic Trialsrelieve symptoms or improve survivorship

2. Intervention Trialsintervention to prevent disease with persons at risk

3. Preventive (Prophylactic) Trialsdetermine efficacy of a preventive agent

Page 20: Intervention Studies

Selection of Study Subjects

• Criteria for study subject selection must be very precise and written

• Avoid subjective decision-making concerning who will be in the study and who will not

Page 21: Intervention Studies

Randomization

• Assignment to either study or control group will not be predictable

• Elimination of investigator bias in the process of selecting patients for either the treatment or control group.

• Randomization increases the likelihood that groups will be comparable on known variables

• Randomization increases the likelihood that groups will be comparable on unknown variables

Page 22: Intervention Studies

Masking (Blinding)

• Subjects do not know whether they are in the study or control group (single blinding)

• Data collectors and analyzers do not know which patients are in the study or control group (double blinding)

Page 23: Intervention Studies

Clinical Trials

• Randomized Clinical Trial– Select persons to participate in study

– Randomize into intervention (“study”) or control group

– Measure outcome of interest after interventionMeasureoutcomeIntervention

Control

Measureoutcome

Randomize participantsinto intervention or control group

Frequently uses multiple arms of intervention

Page 24: Intervention Studies

Clinical Trials

• Stratified Randomization– Stratify variables of interest into subgroups

– Randomize each subgroup into intervention and control groups

– Measure outcome of interest after intervention

MeasureoutcomeIntervention

Control

Measureoutcome

Randomize Into intervention or control group

Page 25: Intervention Studies

Clinical Trials

• Experimental Cross-Over Designs– Select persons to receive the intervention

– Randomize them into two different intervention groups

– After some time, the two groups change interventions

Intervention

No Intervention

No Intervention

Intervention

InitialMeasure

MeasureAt Cross-Over

Final Measure

Ran

dom

ize

Page 26: Intervention Studies

Clinical Trials

• Factorial Designs – Studying the effects of two independent treatments (A & B)

– Randomize into one of four intervention groups

– Measure outcome of interest after interventions

Measureoutcome

Treatment A and B

Randomize participantsinto one of four groups

Treatment A only

Treatment B only

Neither A nor B

Measureoutcome

Measureoutcome

Measureoutcome

Page 27: Intervention Studies

Challenges to the Validity of

Clinical Trials

• Selection of subjects is not well-defined or well followed

• Improper randomization, failure of randomization procedures

• Data collection for study subjects and controls not standardized

• No masking or unintentional unmasking • Unintentional cross-over

• Lack of compliance of study or control subjects

• Differential drop-out rates

• Errors in analysis: • Intent to treat analysis: everyone randomized is analyzed

Page 28: Intervention Studies

Analysis of Clinical Trials

• Relative Risk

• Efficacy

• NNT: Number of patients who would need to be treated to prevent one adverse outcome

Page 29: Intervention Studies

Relative Risk in a Clinical Trial

a

Disease No Disease

Intervention (+)

Control (-)

b

c d

Risk

a

c

(a + b)*

(c + d)*

Relative Risk =a/(a+b)

c/(c+d)

* Denominator is often person-years in the study

Page 30: Intervention Studies

An Example

In a study to evaluate the efficacy of a new treatment for the common cold, 1,000 children 2-18 years old with newly diagnosed viral colds were recruited from pediatrician offices. 500 were randomly assigned to receive the new antiviral therapy and 500 were assigned to a control group. After five days, 200 of the study group had no cold symptoms, while only 100 of the control group had no cold symptoms. What is the relative risk of curing the common cold for the study group compared to the control group.

200/500

100/500=

0.40

0.20= 2.0

Children with colds who took the antiviral medication were 2.0times more likely to by asymptomatic after 5 days than those who did not.

Page 31: Intervention Studies

Efficacy

Rate in the

Control Group__

The reduction in the risk of disease or outcome

because of the intervention.

X 100

Rate in the

Study Group

Rate in the

Control Group

Page 32: Intervention Studies

An Example

In a study to evaluate the efficacy of a new vaccine for the prevention of a viral respiratory disease (VRD), 1,000 health care workers who volunteered to work with VRD patients were recruited by participating hospitals, 500 were given the new vaccine, and 500 received a placebo. After one month’s time, researchers noted that 25 of the treated workers had acquired VRD, while 100 of the control workers contracted VRD. What is the efficacy of the new vaccine?

100/500 - 25/500

100/500=

0.20-0.05

0.20= 0.75

75% of VRD infections can be reduced with the vaccine

Page 33: Intervention Studies

NNT

The number of patients who would need to be

treated (NNT) to prevent one adverse outcome.

Rate in the

Untreated Group

1

_ Rate in the

Treated Group

Page 34: Intervention Studies

An Example

In a study to evaluate the effectiveness of a supervised diet and exercise routine to prevent the development of obesity in overweight children, 3,000 overweight children were enrolled by participating pediatricians. 1,500 were randomized to the diet and exercise plan while 1,500 were randomized to normal pediatric care and recommendations. After one year’s time, 375 of the normal care children had developed obesity, while 325 of the diet and exercise children were obese. Calculate the NNT

1

375/1,500=

1

0.25= 33

We would need to treat 33 overweight children to prevent one from becoming obese

325/1,500_

0.22_

Page 35: Intervention Studies

A mini quiz

Page 36: Intervention Studies

A pharmaceutical company has developed a new sunscreen and decides to evaluate it using lifeguards at Mission Beach. Lifeguards are recruited and randomly assigned to both an intervention and control group. Those in the intervention group are given a lotion that looks identical to the lotion given to control group. Both groups are asked to use the sunscreen daily and report to a spot on the beach each Friday afternoon to be measured for evidence of sun damage.

What is the study design?

Page 37: Intervention Studies

In an effort to reduce obesity and the potential for Type II diabetes, many schools are considering removing high sugar content soda machines from their campuses. Ten elementary schools in a school district volunteered to be part of a study to evaluate this approach and removed soda machines from their campus. These ten schools were then matched with schools of similar socioeconomic status and race/ethnicity with soda machines. Incoming first graders were weighed and measured at each school, and followed forward until sixth grade with measurements each year.

What is the study design?

Page 38: Intervention Studies

Between 1990 and 1995 bicycle safety helmet laws were enacted in all 50 states, requiring children to wear helmets at all times while riding bikes. A study was done using San Diego Trauma Center data to compare the rates of bicycle head trauma injuries in the years 1985, 1990, 1995, and 2000.

What is the study design?

Page 39: Intervention Studies

The hypothesis is that diet and exercise can both independently improve the risk of developing certain types of cancer. Women and men are recruited to participate in a long-term study of diet and exercise. Men and women separately are randomized into one of four groups: 1) a group educated only about the benefits of good eating habits, 2) a group educated only about the benefits of exercise, 3) a group educated about the benefits of both good eating habits and exercise, and 4) a group provided no specific intervention.

What is the study design?

Page 40: Intervention Studies

1,000 men being treated for mild hypertension were recruited to participate in a study of a new medication for the prevention of mild hypertension. 500 of the men were randomized to receive the new medication while 500 were randomized to continue with their current medications. Each month, blood pressure measurements were taken. After six months, those on the new medication were switched back to their old medication, while those on their old medication were switched to the new drug.

What is the study design?

Page 41: Intervention Studies

A study was designed to evaluate the use of home visiting by professional nurses and social workers for the prevention of family violence. Intact families reporting stress were assigned a home visitor who made weekly contacts and referrals for the family. Comprehensive initial assessments were performed, and the families were assessed at six month intervals for family functioning and evidence of violence.

What is the study design?