Scientific Study Designs for Research 2

KowalskiD pg. 1

Scientific Study Designs for research.

What Research is ... the systematic

process of collecting and analyzing

information (data) in order to increase our

understanding if phenomenon about

which we are concerned or interested.

Apa pentingnya penelitian? Contohnya

untuk mengetahui kontra indikasi kb?

Tidak boleh diberikan pada pendarahan

pervaginam yang gak diketahui

sebabnya/DisfUterinBleeding misalnya.

Mengetahui amannya bagaimana? Karena

SUDAH terbukti di penelitian. Seperti

merokok, hasil penelitian menunjukkan

ada efek sampingnya. Tanpa penelitian kita

tidak akan tahu bahwa penyebab ca serviks

adalah HPV dan karena penelitian juga

maka ada vaksinnya.

Jadi peran penelitian, ilmu makin maju dan

kesejahteraan manusia meningkat.

Penelitian itu mencari KEBENARAN. Untuk

mencari kebenaran harus menggunakan

metode yang benar, tata cara yang benar,

dll.

Kalau tidak penting tidak perlu diteliti,

begitu pun variabel yang di tanyakan

nantinya, yang di anggap penting saja.

Research Characteristics

1. Originates with a question or

problem.

2. Requires clear articulation of a

goal.

3. Follows a spesifik Plan or prosedur

(Scientifiec method)

4. Often divides main problem into

subproblems.

5. Guided by spesific problem,

question, or hypothesis.

6. Accepts certain critical

assumtions.

7. Requires collection and

interpretation of data.

8. Cyclical (helical) in nature.

Karakter/ ciri-ciri penelitian : (Contohnya akan

dilakukan penelitian tentang medical check up)

Berasal dari sebuah pertanyaan atau problem.

Contoh, seberapa banyak orang yang

melakukan medical checkup?

Ada Goal tujuannya. Apakah tujuannya hanya

mengetahui presentasi saja? Atau cari

penyebab atau pencegahannya.

Scientific method. Pendekatan atau prosedur

ilmiahnya seperti apa?

Contoh prosedur ilmiah : Riset problem >

penelusuran literatur > kerangka teoritisnya >

kerangka konsepnya > pengumpulan data dan

analisis > kesimpulannya apa.

Divides main problem kedalam subproblem.

Misalnya masalah medical checkup, fokus pada

checkup ca serviks (pap smear) saja misalnya.

Jadi bikin subproblem yang lebih spesifik dari

main problem yang umum. Guided by spesific

problem.

Bikin hipotesisnya. Hypotesis, misalnya biaya

mungkin menyebabkan kebiasaan medical

checkup. Nanti di buktikan hipotesisnya benar

atau tidak.

Question problem, misalnya apakah ada

hubungan dengan tingkat pendidikan atau

pengetahuan dengan kepatuhan pemeriksaan

pap smear (check up ca serviks)?

Critical assumtions,contohnya asumsi saya ibu

tidak punya biaya, alat gak ada, dll sehingga

tidak melakukan pap smear. Nanti asumsi ini

kemudian akan dibuktikan.

Collection dan interpretasi data. Harus punya

data, misalnya usia ibunya, pendidikan,

pengetahuan, usia menikah dsb.

Cyclical (helical) in nature. Secara siklus dalam

alamiah. Menggambarkan secara teoritis

masalah tersebut dan manfaatnya apa?

Kuliah Pertama Metodologi

Penelitian. Dr. Djap.

BOLD : SLIDE KULIAH Regular : Catatan

Rekomendasi bacaan ada di lampiran.

KowalskiD pg. 2

Asumsi tersebut bisa tidak di jelasan secara

teoritis. Kalau hasil penelitian telah keluar,

selanjutnya bagaimana?

Research Project.

Research begins with a problem.

o This problem need not be

Earth-shaking.

Identifying this problem can

actually be the hardest part of

research.

In general, good research projects

should :

o Address an important

question.

o Advance knowledge.

Mulai penelitian dengan hal-hal yang

sederhana saja. Penelitian harus mulai dari

problem yang muncul. Bukan harus

masalah yang besar.

Hubungan kopi dan maag > white coffee.

Contoh lainnya hubungan aktivitas fisik

dan hipertensi. Lalu di bikin subproblem,

hipertensi sistol, hipertensi diastol; lalu di

hubungkan dengan aktivitas fisik, apa yang

paling berpengaruh hipertensi sistol atau

diastol dengan aktivitas fisik.

Pertanyaan harus sederhana, operable,

dan pastinya peneliti harus memiliki

pengetahuan.

High-Quality Research

Good research requires :

The scope and limitations of the

work to be clearly defined.

The process to be clearly explained

so that it can be reproduced and

verified by other researchers.

A thoroughly planned design that

is objective as possible.

Highly ethical standards be

applied.

All limitations be documented.

Data be adequately analyzed and

explained.

All findings be presented

unambiguously and all conclusions

be justified by sufficient evidence.

Apa scope kita atau ruang lingkup

penelitian kita. Misalnya kesehatan kalau

begitu bahasa masalah kesehatan.

Kalau hendak melakukan sebuah

penelitian, metode penelitiann tersebut

harus benar sehingga bisa di gunakan oleh

orang lain pada tempat berbeda. Jadi harus

berlaku untuk semua orang. Misalnya

hubungan rokok dan kanker paru, sama

pada setiap individu dan di setiap tempat.

Ingat juga penelitian dilakukan pada orang

yang beresiko, contohnya penelitian

tentang ca serviks tidak mungkin dilakukan

pada laki.

Buatlah tujuan-tujuan penelitian yang yang

bisa dilaksanakan.

Literature review, penting untuk

mengetahui apakah penelitian yang akan

kita lakukan sudah di teliti atau belum oleh

orang lain. Selain itu penting juga untuk

mencari referensi pendukung yang

mungkin berhubungan dengan penelitian

yang akan kita lakukan.

Etika standar, perlu terutama untuk

eksperiment. Misalnya membuktikan obat

kanker baru untuk pengobatan pada

kanker. Pasien dibagi dua kelompok.

Kelompok satunya di beri obat yang akan

di uji, yang lain tidak mungkin di beri

plasebo sebagai kelompok kontrol, tidak

etis kalau orang kanker hanya diberikan

plasebo. Makanya kelompok kontrol tadi

tetap di berikan obat kanker yang standar.

KowalskiD pg. 3

Diliat mana yang lebih baik hasilnya. Jadi

penting keetisan.

Semua keterbatasan harus di

dokumentasikan, apapun yang

menghambat dalam penelitian. Semua

data di analisa dan di paparkan. Data yang

‘cacat’ atau kurang lengkap bisa di

eliminasi.

Sources of Research Problems.

Observation

Literature reviews

Professional conferences

Experts

o Media (new paper,

megazine ...)

o Internet ...

Sumber referensi penelitian berdasarkan

masalah yang akan di cari jawabannya.

Sumbernya dapat di liat di atas.

Stating the Research Problem

Once you’ve identified a research

problem:

State that problem clearly and

completely.

Determine the feasibility of the

research.

Identify subproblems:

Completely researchable units.

Small in number.

Add up the total problem.

Must be clearly tied to the

interpretation of the data.

Bagaimana merumuskan masalah

penelitian. Liat masalah dan what, who,

how much, when, and where. Itu yang

perlu di pertanyakan atas masalah yang

muncul. Kemudian tentukan apakah kita

bisa melaksanakan penelitian tersebut,

alat atau instrumen, dana, dll.

Subproblem jangan terlalu banyak.

Subproblem itu tujuan khusus, main

problem tujuan utamanya.

Datanya yang didapatkan harus dapat di

interpretasikan.

Literature Review

A literature review is a necessity.

Without this step, you won’t know

if your problem has been solved or

what related research is already

underway.

When performing the review:

Start searching professional

journals.

Begin with the most recent articles

you can find.

Keep track of relevant articles in a

bibliography.

Don’t be discouraged if work on

the topic is already underway.

Ketika sudah punya masalah penelitian,

kita harus cari literatur review. Melihat

masalah yang kita bahas itu. Apa sudah ada

pembahasan. Jangan2 masalah tersebut

sudah usang dan sudah di teliti oleh banyak

orang. Kalau masih belum, cari journal

yang relevan. Tapi jangan berkecil hati

kalau mungkin sudah di bahas, mungkin

saja kita bisa menemukan hal yang baru.

Yang tidak ada di penelitian sebelumnya

(suatu hal yang novelti/baru)

Literature Review Pitfalls (1 of 2)

Be very careful to check your sources

when doing your literature review.

Many trade megazines are not peer

reviewed.

KowalskiD pg. 4

Professional conferences and

journals often have each article

reviewed by multiple people

before it is even recommended for

publication.

The IEEE and ACM digital libraries

are good places to start looking for

legitimate research.

Harus di cek sumber bahan journal. Hati-

hati mengambil literatur. Journal yang

menjadi literatur kita itu harus telah

melewati peer review, melalui tahapan

pemeriksaan bahwa tulisan yang ada

dalam journal tersebut berkualitas dan

penting untuk di ketahui oleh khalayak

ramai.

Literature Review Pitfalls (1 of 2)

...sorry gak sempat fotoin, ketiduran. Zzzz

Internet bisa menjadi sumber yang bagus,

tetapi banyak juga yang pseudoscience dan

poor riset. Misalnya journal2 yang berasal

dari perusahaan obat. Yang di tampilkan

hanya yang bagusnya. Yang negatifnya

tidak di tampilkan dalam journal. Hal ini

disebut Bias Publication.

Jadi pastikan, harus verifikasi semua

dokumen dan sudah di peer reviewed.

Step 1: A Question Is Raised

A question occurs to or is posed to the

researcher for which that researcher has

no answer.

This doesn’t mean that someone

else doesn’t already have an

answer.

The question needs to be converted to an

appropriate problem statement like that

documented in a research proposal.

Ketika tidak ada jawaban, itu suatu

problem. Setiap pertanyaan akan problem

tersebut di konversi menjadi proposal

penelitian.

Step 2: Suggest Hypotheses

The researcher generates intermediate

hypotheses to describe a solution to the

problem.

This is at best a temporary solution

since there is as yet no evidence to

support either the acceptance or

rejection of these hypotheses.

Hipotesis inilah yang akan di uji dalam

penelitian. Diterima atau ditolak

ditentukan berdasarkan data hasil

penelitian.

Step 3: Literature Review

The available literature is reviewed to

determine if there is already a solution to

the problem.

Existing solutions do not always

explain new observations.

The existing solution might require

some revision or even be

discarded.

Proposal bisa di ubah/review yang kurang.

Tergantung literatur review. Kalau ada

yang kurang bisa di tambahkan pada

analisa data.

Step 4: Literature Evaluation

It’s possible that the literature review has

yielded a solution to the proposed

problem.

This means that you haven’t really

done research.

On the other hand, if the literature review

turns up nothing, then additional research

activities are justified.

KowalskiD pg. 5

Step 5: Acquire Data

The researcher now begins to gather data

relating to the research problem.

This means of data acquisition will

often change based on the type of

the research problem.

This might entail only data gathering, but

it could also require the creation of new

measurement instruments.

Ada banyak cara untuk mendapatkan data.

Bisa dari KMS juga untuk mengetahui umur

kalau orangnya tidak ada di tempat

misalnya. Bisa lewat wawancara juga. Tapi

wawancara sering punya kelemahan,

karena orangnya harus jujur. Wawancara

juga memiliki kelemahan juga untuk

memori yang sangat lama. Misalnya tanya

riwayat imunisasi. Namanya bias recall.

Kalau untuk data yang baru, bisa di buat

alat ukur/intrumen penelitian yang baru.

Step 6: Data Analysis

The data that were gathered in the

previous step are analyzed as a first step

in ascertaining their meaning.

As before, the analysis of the data does

not constitute research.

This is basic number crunching.

Tergantung tujuan penelitiannya. Bisa

terjadi analisis data di sesuaikan dengan

keadaan data. Dan bisa di ubah tujuan

penelitian tergantung data yang

didapatkan.

Step 7: Data Interpretation

The researcher interprets the newly

analyzed data and suggests a conclusion.

This can be difficult.

Keep in mind that data analysis

that suggest a correlation between

two variables can’t automatically

be interpreted as suggesting

causality between those variables.

Interpretasikan data, tetapi bukan

membaca atau menulis ulang. Tahapan ini

biasanya yang paling susah. Jelaskan juga

korelasinya. Ingat korelasi antar data tidak

berarti berhubungan sebab-akibat

(kausalitas). Dikatakan Kausalitas misalnya

orang di sebut menderita tbc kalau di

temukan kuman tbc dalam tubuhnya.

Step 8: Hypothesis Support

The data will either support the

hypotheses or they won’t.

This may lead the researcher to

cycle back to an earlier step in the

process and begin again with a

new hypothesis.

This is one of the self-correcting

mechanisms associated with the

scientific method.

Common Methodologies

Methodologies are high-level approaches

to conducting research.

The individual steps within the

methodology might vary based on

the research being performed.

Two commonly used research

methodologies:

Quantitative

Qualitative

Kualitatif itu explanation atau

memprediksi.

KowalskiD pg. 6

Methodology Comparison

Quantitative Qualitative Explanation, prediction Explanation, description

Test theories Build theories

Kwon variables Unknown variables

Large sample Small sample

Standarized instuments Observations, interviews

Deductive Inductive

Deduktif, berarti suatu hal yang kecil tapi

bisa di generalisasikan.

Induktif, hal yang umum jadi khusus.

Misalnya tentang kemiskinan, kemiskinan

penyebabnya apa? (penyebab itulah yang

merupakan hal2 induktifnya)

Small sampel bisa 10-20 orang saja.

-Slide tabel gak jelas-

Type of study itu ada beberapa macam.

Cross-section, Kohort, case controls dll.

Timing penelitian bisa progresi,

longitudinal (berkali2), prospektif atau

retrospektif.

Kapan penelitian dimulai?

Cross-section, collect all information,

snapshot pada saat itu; dapat semua info

dalam satu waktu.

Kohort, bisa prosektif atau retrospektif.

Kohort di mulai pemaparan dulu. Contoh

studi Kohort kanker paru pada perokok,

orang yang merokok di follow-up sampai

ada kanker paru, orang yang tidak merokok

juga di follow-up apakah ada kanker paru

atau tidak. Ini yang prospektif. Kohort di

mulai dari yang explosure/terpapar.

Kalau case kontrol, di tentukan kasusnya,

lalu di assesment ke belakang apakah ada

paparan dengan faktor resiko atau tidak.

Misalnya pada ca paru, di asses ke

belakang siapa yang merokok siapa yang

tidak.

Experiment sifatnya pasti prospektif.

Contohnya makan obat tertentu lalu di

lihat sembuh atau tidak. Tidak bisa

retrospektif. Serta ada intervensinya, ada

yang di kasi obat, ada kelompok yang tidak

di kasi obat (Plasebo misalnya).

Apa tujuan penelitian?

Cross-section: mencari prevalensi,

mengetahui tentang masalah kesehatan,

perkembangan, change over time suatu

keadaan/penyakit.

Cohort: mencari etiologi, mencari

insidens, dll.

Case control : bisa melihat etiological tapi

sifatnya retrospektif.

Experiment : ingin melihat prospektif dari

suatu intervensi di bandingkan yang

kelompok kontrol.

Desain Dasar

Eksperimen; peneliti memiliki

‘kekuasaan’ untuk menentukan subyek

akan terpajan atau tidak.

Observasi; peneliti hanya melakukan

observasi saja.

Cross-sectional

Hal-hal yang harus diperhatikan pada x-

section.

- Keluaran dan pajanan di ukur pada

waktu yang sama, sehingga kurang

dapat melihat sebab-akibat (ada

antecendent)

- Banyak digunakan pada survei.

o Simple Random Sampling

umumnya sulit digunakan.

o Modifikasi sampel:

stratifikasi, klaster,

gabungan.

KowalskiD pg. 7

- Dapat digunakan untuk

menghitung prevalensi.

KOHORT

Hal-hal yang harus diperhatikan pada

Kohort.

- Sampel dimulai dengan adanya

pajanan atau tidak.

- Peneliti harus mengetahui status

keterpajanan subyek.

- Untuk memperoleh subyek

terpajan perlu memeriksa subyek,

yang banyaknya tergantung

proporsi pajanan di populasi.

- Kohort dapat dilakukan secara

retrospektif dengan menggunakan

rekam medis atau catatan yang

ada.

Rekomendasi bacaan :

1. Acharya AS, Prakash A, Nigam

A,Saxena P. Scientific study designs

for research: an overview. Indian J

Med Spec 2012;3:191-4.

2. Saxena P, Prakash A, Acharya AS,

Nigam A. Selecting a study design

for research. Indian J Med Spec

2013;4(2):334-9.

Scientific study designs for research: an overview Anita S Acharya*, Anupam Prakash** Aruna Nigam#, Pikee Saxena#

Symposium

Departments of *Community Medicine, **Medicine, and #Obstetrics & Gynaecology. Lady Hardinge Medical College, New Delhi-110001. India.Corresponding Author: Dr. Anita S Acharya, Associate Professor, Dept. of Community Medicine, Lady Hardinge Medical College, New Delhi-110001. India. E-mail: [email protected]: 11-08-2012 | Accepted: 13-08-2012 | Published Online: 26-08-2012This is an Open Access article distributed under the terms of the Creative Commons Attribution License (creativecommons.org/licenses/by/3.0)Conflict of interest: None declared Source of funding: Nil

Abstract

Research is a scientific, well planned methodical attempt to answer questions with valid data. “The rules that govern the process of collecting and arranging the data for analysis are called research designs”. They are broadly classified into “Observational” and “Experimental” study designs. In observational study design, the researcher simply observes and does not intervene in any way whereas in the latter, some kind of intervention/manipulation is done. Descriptive, observational study designs are useful for only generating hypothesis whereas, analytical, observational study designs are helpful for both generating and testing hypothesis. Randomised controlled trials are the “Gold Standard” for determining the strongest evidence for concluding causation. However, no study design is perfect. Each has its own inherent advantages and disadvantages. Depending on the type of research question, practicability, and resources in terms of manpower, money and time, the investigator has to choose the appropriate study design which will answer the research question in the most scientific manner. This article gives a brief overview of the various study designs commonly used in research.

Key words: Research design; cross-sectional; case-control; cohort; randomised controlled trial.

Research is derived from “re-search”. Search refers to “seek”, “investigate” or “explore” and in typical Hindi parlance it means “khoj”. Research may be a new search or an old thing being again investigated (re-search).

Once a research question is in place, what kind of study should be planned is important and this is primarily the focus of this article.

A study design is a specific plan or protocol for conducting the study, which allows the investigator to translate the conceptual hypothesis into an operational one. In other words “The rules that govern the process of collecting and arranging the data for analysis are called research designs” [1] which we shall be discussing in brief along with their advantages and dis-advantages.

It is very important to realise that “a poor design cannot be salvaged by good statistics”. A good study

design should be sound and scientific and planned very methodically. Therefore, an epidemiologist and statistician should be on board from the start of the study.

The epidemiologic study designs are broadly classified into “Observational” and “Experimental” study designs. Further classifications of various types of studies is outlined in Table 1.

A. OBSERVATIONAL STUDY DESIGNS

In an observational study design, the researcher or the investigator simply observes the individuals in the study and does not intervene in any way. They are further classified into “Descriptive” and “Analytical” studies.

DESCRIPTIVE STUDIES- These describe certain observations and could be in form of case reports or case series. Descriptive studies can be used

INDIAN JOURNAL OF MEDICAL SPECIALITIES 2012;3(2):191-194

Indian Journal of Medical Specialities, Vol. 3, No. 2, Jul - Dec 2012 191

for hypothesis generation and can also suggest associations. However, they cannot be used for testing the hypothesis.

ANALYTICAL STUDIES

Ecological studies- are usually undertaken to study the prevalence or incidence of diseases in populations or groups wherein the unit of study is population group rather than the individual [2]. For example, if we study the frequency of a characteristic (e.g. Alcohol intake) and some outcome of interest (e.g. Cirrhosis of Liver) occurring in the same geographic location (e.g. a city, state or a country). These studies can be used for generating hypotheses but not to draw causal conclusions because we do not have information as to whether people who consumed alcohol are the same people who developed cirrhosis of liver.

Cross-sectional study- In a cross-sectional study, data is collected at a single point in time or in a time frame. It is helpful to describe associations and determine prevalence. An example of a cross-sectional study is “Prevalence of Hypertension in Adults in a community” as shown in Figure 1.

The strengths of cross-sectional studies are that they can be performed quickly, are relatively inexpensive, provide the prevalence of a disease/risk factor and are useful to formulate a hypothesis. In spite of these salutary advantages, it has its

inherent weaknesses viz. cross-sectional studies cannot establish cause-effect relationship and cannot be used to test a hypothesis.

Case-Control Study- In a case-control study, one starts with people who have disease (cases) and then matches them with controls that do not have the disease. Then the researcher looks back and assesses the exposures in both the groups (cases as well as controls). A diagrammatic representation of a case control study is depicted in Figure 2.

The strengths of case-control studies are that they can be done in a short-period of time, are relatively inexpensive, are good for rare outcomes like cancer and can examine many exposures. Besides, they are useful to generate hypothesis and also are helpful in providing the odds ratio. The weak points include, that they cannot be used to determine the incidence, prevalence or the relative risk. Besides, they can only study one outcome and have a high susceptibility to bias.

CROSS-SECTIONAL STUDY

Sample of Population

Time Frame = Present

Obese Adults Prevalence of Hypertension

Non-obese Adults Prevalence of Hypertension

Figure 1- Depiction of a cross-sectional study

High E2 exposure

Low E2 exposure

High E2 exposure

Low E2 exposure

Patients with Uterine cancer (Cases)

Patients without Uterine cancer (Controls)

PAST PRESENT

Figure 2- Example of a Case-Control Study- Are those with uterine cancer more likely to have consumed Estrogen (E2)?

Table 1- Types of scientific study designs

A) OBSERVATIONAL - DESCRIPTIVE o Case Reports o Case Series

- ANALYTICAL o Ecological studies o Cross-sectional o Case-control o Cohort

B) EXPERIMENTAL o Randomised controlled clinical trial (RCCT) o Randomised controlled field trial (RCFT)

C) META ANALYSIS/SYSTEMATIC REVIEWS

Anita S Acharya and others

192 Indian Journal of Medical Specialities, Vol. 3, No. 2, Jul - Dec 2012

The third type of analytical observational studies commonly planned are the Cohort studies. Cohort studies are the most difficult ones; they begin with disease-free patients/subjects and classify them as exposed/unexposed. After, this the outcomes are recorded in both the groups and the outcomes are compared using relative risk.

Example of a Cohort Study is- “To determine the effects of smoking on lung Cancer mortality in a population”.

In a prospective cohort study, exposure may or may not have occurred at study entry, but outcome definitely has not occurred at time of study entry. The subjects are followed up for a fixed period of time or till the disease occurs. In a retrospective (historical) cohort study, both the disease and exposure have already occurred at the time of study.

The advantages of cohort studies are that they provide incidence data, help in establishing time sequence for causality, eliminate recall bias, can study rare exposures and allow for accurate measurement of exposure variables.

Cohort studies can measure multiple outcomes and can adjust for confounding variables and can also calculate relative risk. Despite the several advantages, there are weaknesses as well and these include- cohort studies are expensive, time-consuming, cannot study rare outcomes and require a relatively large sample size. Besides, exposure may change over a period of time, there is attrition of study population over time and diseases which have a long pre-clinical phase can be problematic to study as well.

B. EXPERIMENTAL STUDIES

Analytical experimental/interventional studies are studies in which an intervention is performed and hence, also are referred to as “clinical trials”. Clinical trials provide the “gold standard” for determining the strongest evidence for concluding causation. Various instruments which are employed during clinical trials include- - Randomisation - Blinding o Placebo-controlled or o Standard treatment

Randomisation literally means to toss a coin to decide the assignment of the patient to a study group. The most critical element in randomisation is the unpredictability of the next assignment which essentially ensures elimination of selection bias [3].

Blinding or masking involves many components. The subjects should not know to which group they are assigned to. This can be either done by using a “placebo” or where standard treatments are available they should be given. For example, to study a new drug against HIV/AIDS in a study group, standard treatment should be provided to the control group as it would be unethical to give a placebo to the control group.

When the study subjects are only blinded, it is termed as “Single Blind study” whereas when both the study subjects as well as data collectors are blinded, it is a “Double-blind” study.

There are two types of randomised trials: (1) Randomised Controlled Clinical Trial (RCCT) (2) Randomised Controlled Field Trial (RCFT)

Example of a Randomised Controlled Clinical Trial (RCCT) is depicted in Figure 3- To study the association between garlic consumption and cardiovascular disease prevention in a city.

Randomised Controlled Field Trial (RCFT): It is similar to an RCCT except that the intervention is preventive and not therapeutic. These are usually preventive trials in which the efficacy of a preventive

Study Population

Randomise to two groups

Control Group (Placebo)

Outcomes (CAD or no CAD)

Treatment group(Garlic pill)

Outcomes (CAD or no CAD)

Figure 3- Example of a Randomised Controlled Clinical Trial

Scientific study designs

Indian Journal of Medical Specialities, Vol. 3, No. 2, Jul - Dec 2012 193

intervention such as a new vaccine is tested in one study group and the other group receives a placebo or standard. As they are usually conducted in the community, the term used is Randomised Controlled Field Trial (RCFT).

The advantages and disadvantages of a RCCT and RCFT are similar. The strengths are that they are the best measure of a causal relationship, are the best design for controlling bias and can measure multiple outcomes. The weaknesses include the high cost, compliance issues and at times, ethical issues may be a problem. Sometimes, it may take a long time to obtain results. Another disadvantage of both is “External Validity” which is the ability to generalise the findings to other groups of population [1].

C. META ANALYSIS/SYSTEMATIC REVIEWS

It is analysis of multiple studies including statistical techniques for merging and contrasting results across studies [4]. The need for a meta-analysis or a systematic review arises when there are conflicting evidences available from different studies addressing the same research question. However a number of biases can occur like publication bias, aggregation bias, and bias in exclusion of studies. Detailed description is beyond the purview of this article.

Table 2 provides a tabulated summary of the characteristics of various study designs.

References

1. Jekel JF, Katz DL, Elmore JG, Wild DMG. Epidemiology, Bio-statistics and Preventive Medicine. Saunders Elsevier, Philadelphia, 2007 3rd edn; pp. 77-89.

2. Das R, Das PN. Biomedical Research Methodology including Biostatistical Applications, Jaypee Brothers Medical Publishers, 2011 1st edn; pp. 19.

3. Leon G. Epidemiology. Saunders Elsevier, Philadelphia, 2009 4th edn; pp. 135.

4. Greenland S, O’Rourke K. Meta-analysis. In: Rothman KJ, Greenland S, Lash TL (eds). Modern Epidemiology. Lippincott Williams & Wilkins, Philadelphia, 2008 3rd edn; pp.652-82.

Cross- Case- Cohort RCT sectional control

Cost + ++ +++ ++++

Duration + ++ +++ +++

Sample Size Varies Small Large Varies

Incidence/ Prevalence None Incidence IncidencePrevalence

Multiple Yes No Yes Yes Outcomes

Bias prone Yes Yes No No

Causality No No No Yes

Table 2- Salient features of various study designs.

Key Points

• Choosing an appropriate study design to address a research question is very critical to obtain valid results.

• For hypothesis generation, observational, descriptive studies are generally used whereas for generation as well as hypothesis testing, observational, analytic studies like case-control, cohort studies are commonly employed.

• Randomised controlled trials are the “Gold Standard” for determining the strongest evidence for concluding causation.

The above treatise should help clarify the doubts of scientific personnel and help them in planning what study design they require to achieve their respective research questions.

Anita S Acharya and others

194 Indian Journal of Medical Specialities, Vol. 3, No. 2, Jul - Dec 2012

Symposium

Selecting a study design for researchPikee Saxena*, Anupam Prakash**, Anita S Acharya#, Aruna Nigam##

Departments of *Obs. & Gynae., **Medicine and #Community Medicine, Lady Hardinge Medical College & SSK Hospital, New Delhi-110001. ##Department of Obs. & Gynae., HIMSR & HAH Centenary hospital, New Delhi, India.Corresponding author: Dr. Pikee Saxena, Associate Professor, Department of Obs. & Gynae., Lady Hardinge Medical College & SSK Hospital, New Delhi-110001. India. Email- [email protected]: 11-06-2013 | Accepted: 26-06-2013 | Published Online: 07-07-2013This is an Open Access article distributed under the terms of the Creative Commons Attribution License (creativecommons.org/licenses/by/3.0)Conflict of interest: None declared | Source of funding: Nil | DOI: http://dx.doi.org/10.7713/ijms.2013.0033

Abstract

Study design forms the backbone of good research. It determines the methods and frequency of data collection, statistical tests to be applied and also helps in correct interpretation of data. Choosing a study design depends on several factors like research question, experience of the researcher, cost, time duration, latency and frequency of a disease. Study designs can be broadly categorised into observational studies where the investigator just observes the course that nature is taking without any manipulation; while experimental studies involve some intervention by the investigators in order to test the research hypothesis.

Observational studies could be descriptive or analytical. Descriptive studies help to generate a hypothesis like a case study or case series while analytical studies not only generate but also test hypothesis like a cross-sectional, case-control or cohort study. Experimental studies test the hypothesis and help to determine the cause of a disease. Each study design has its own merits and demerits which will be discussed in this article.

Key words: Case-control studies; cohort studies; cross-sectional studies; research.

Introduction

Epidemiology is a systematic study of the patterns, causes, and effects of disease conditions in a defined population. The primary goal of epidemiology is to identify causes of disease, investigate how outbreaks occur and explore ways to control and prevent diseases. Most epidemiological studies result in either formation of hypothesis or test the strength of association of this hypothesis in an unbiased manner. In simpler words, these study designs help to determine if the exposure is related to the disease.

What is a study design?

Design is the pattern, scheme or plan to collect evidence. Study design is a tool on which the credibility of research findings depends. Epidemiological studies are aimed at examining relationships between exposures like alcohol or smoking, biological agents, stress, or chemicals

to disease outcome. The identification of causal relationships between these exposures and outcomes is an important aspect of epidemiology. They also help to determine whether the results obtained are scientifically sound and unbiased.

Study design depends on a multitude of factors [1] like research question and goal, skills of the researcher, availability of funds, time duration during which a study is to be conducted, existing knowledge about the research question/disease, duration of latency of a disease and on whether it is a rare or common disease.

On the basis of any intervention done by the investigator, study designs can be divided into two broad categories (Table 1) [2,3]-

1. Observational studies are those where the investigator studies people or exposure as they exist or occur in nature. These do not involve any intervention or experiment by the investigator.

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It is of two types-

A. Descriptive studies are used to formulate hypothesis or association. They describe the frequency or characteristics of an outcome. They commonly answer the questions- who, when, what and where of a disease occurrence [2]. Examples include case-studies and cross-sectional studies.

B. Analytical studies are used to test hypotheses or the relationship between exposure and outcome. They commonly answer the question how a disease occurs? Examples are cross-sectional, case-control, cohort studies.

2. Experimental studies involve manipulation or intervention by the investigators in order to test the hypothesis through experiment. Examples are the randomised control trial (often used for new drug or comparing drug therapies), field trial (conducted on those at a high risk of contracting a disease) and community trial (research on social diseases).

In order to identify the aetiologic factors or exposure responsible for an outcome, each step in the epidemiologic framework provides new and important information. Depending on the increasing knowledge of disease or exposure and generating evidence, they can be classified in to a hierarchy as-

Cross-sectional studies –Help to develop hypothesis↓

Case Control study– Investigate relationship of exposure to outcome

↓Cohort study- Defines strength of association between exposure and outcome

↓Control Trial-Tests associations experimentally

Observation tools for data collection in a study:

• Selected units could be either individuals or a defined group of individuals/population.

• Based on whether single or multiple observations are to be made studies could be categorised as:

a. Cross-sectional study where only single or one set of observations are made, at a certain point in time.

b. Longitudinal study where at least two or more sets of observations are collected at different points of time.

• Based on data collection timing:

a. Prospective study looks forward in time and involves follow up. Example: In a prospective cohort, study is started with a cohort of disease free individuals who are followed up in time to observe how many of them develop a disease.

b. Retrospective study looks backwards in time. Example: Case control study, retrospective cohort study.

• Based on data collection methods:

a. Primary data is where the investigator is collecting the data. Sources include medical examinations, interviews, etc. Advantages of collection of primary data are that there is less measurement error and it suits objectives of the study better. The disadvantage is that it is costly or it may not be feasible.

b. Secondary data is where the data is collected by others and has not been collected for the purpose of the study. Sources include census data, vital statistics.

Descriptive Studies

1. Case Reports or case series are detailed presentation of a single or a group of cases having unusual symptom or response. In many ways they are “sentinel events” which may lead to testable

Table 1- An overview of the various types of study designs

Observational Study Experimental Study

A. Descriptive study Randomised Control Trial Case study Field Trial Case Series Community trial

B. Analytical study Cross-sectional study Case-control study Cohort study

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Research study designs

hypothesis. The case is described along with the help of radiological, pathological, biochemical or/and haematological investigations. Case studies generally report a new or unique finding e.g. previous undescribed disease, unexpected link between diseases, unexpected new therapeutic effect or unexpected adverse events. A large number of case reports are indexed on Medline (www.pubmed.com) which provide a useful reminder about rare conditions, diagnoses, etc.

Advantages of case series are that they are useful for hypothesis generation and they provide information about rare diseases with few established risk factors. However, they cannot study cause and effect relationships and cannot assess disease frequency.

Examples of case report-

Generalised lymphadenopathy- an unusual aetiology;

A case report of a live, intrahepatic pregnancy;

Sudden death after administration of oral azithromycin.

Analytical Studies

1. Cross-sectional study represents a “Snapshot” of health problems of a population at a particular time. Both the exposure and disease are measured at the same time. These studies can be done quickly, are less expensive and do not require any follow up. They describe associations & measure point prevalence i.e. they determine the total number of persons suffering from a disease including both new and old cases at a particular time. They are useful for estimating population burden, health planning and priority setting of health problems. They are not useful for studying rare diseases. As compared to longitudinal studies there is no risk of individuals being lost to follow up.

Cross-sectional study calculates odds ratio (OR) which is a measure of association between an exposure and an outcome [4].

OR=1 Implies that exposure does not affect odds of outcome.OR>1 Implies that exposure is risky and is associated

with higher odds of outcome. OR<1 Implies that exposure is protective and is associated with lower odds of outcome.

The limitations of a cross-sectional study are that they have comparatively weaker observational design as they measure prevalence and not the incidence (new cases) of a disease. Another problem is that they consider only survivors and do not take into account the persons who have died due to the disease. They cannot determine the temporal relationship between the exposure and the disease and therefore cause-effect relationship cannot be established.

Examples of Cross-Sectional Studies-

• Is there any association between oat consumption and coronary artery disease (CAD)? (Figure 1)

• To determine height and weight pattern of students of class VIII.

• To assess prevalence of infertility amongst women attending Gynaecological OPD

2. Case control study is a retrospective study where the starting point is the identification of ‘cases’ with disease and suitable ‘controls’ without that disease. Both the cases and controls are selected ideally from the same population. Cases and controls are then compared to assess whether there were any differences in their past exposure. They are useful for generating hypothesis. These studies are most suitable for rare diseases or diseases with long latent period. The statistic generated to measure

Figure 1- Diagrammatic depiction of a cross-sectional study design


Pikee Saxena and others

association is the odds ratio, which is the ratio of the odds of exposure in the cases to the odds of exposure in the controls. Case control studies provide low cost answers to health questions. They are frequently used for investigating outbreak of a disease. The other advantages of these studies are that they are less expensive, consume less time. They can examine many exposures at one time.

The limitations of these studies are that they cannot measure incidence, prevalence or relative risk of exposure. These studies can only evaluate one outcome at a time. They are liable to recall & selection bias.

Examples of Case-Control Studies-

• Are individuals suffering from coronary artery disease less likely to have consumed oats as compared to controls? (Figure 2)

• To investigate the role of diet in breast cancer.• To assess whether hepatitis B infection played a

role in the aetiology of primary hepatocellular cancer?

3. Cohort Studies include a group of people who have something in common which may be a similar characteristic or exposure e.g. all people who attended a cricket match or all persons in a hospital who died due to a heart attack. This selected population is called a cohort. The study is initiated with disease-free patients who are followed up prospectively or retrospectively in time. The patients are then classified as exposed or unexposed. Data is collected at multiple points in time to identify new cases or incidence of a disease. These studies calculate relative risk which compares outcome in the exposed and unexposed group. Cohort studies are used to establish causation of a disease or to evaluate the outcome or impact of treatment. They are also useful for defining the spectrum of a disease.

In prospective cohort studies, exposure factors are identified at the beginning of a study and a defined population is followed into the future. In retrospective or historical cohort studies, past medical records for the defined population are used to identify exposure factors. In a retrospective (historical) cohort study, both the disease and exposure have already occurred at the time of study.Cohort studies provide incidence data and can

establish time sequence for causality of a disease outcome. They eliminate recall bias as the individuals are being observed directly and can measure multiple outcomes. Confounders can also be controlled more easily. They calculate relative risk (RR) or risk ratio which determines whether a disease is associated with exposure and also determines the strength of association. The RR is a more powerful effect measure than the OR, as the OR is just an estimation of the RR, since true incidence cannot be calculated in a case-control study where subjects are selected based on disease status. As with the OR, a RR=1 shows that there is no association between the exposure and disease, RR > 1 shows risky or positive association while RR <1 indicates negative or protective association.

Cohort studies are expensive and time consuming as the individuals are followed over a long period of time. They are not suitable for studying rare diseases or diseases with a long latent period and cannot prove causation. Other limitations are that due to long study duration, exposure may change over time and individuals may be lost during follow up.

Figure 2- Diagrammatic depiction of Case-control study design

Figure 3- Diagrammatic depiction of a prospective cohort study

Study population

Case control design

Oat eaters

Oat eaters

Oat non eaters

Oat non eaters

CAD (disease)

Controls (no disease)

}}

}

Study begins here

Time

Study population

free of disease

Cohortdesign Oat eaters

Oat non eaters

CAD

CAD

(no disease)

(no disease)

}}

}

timeStudy begins here

futurepresent



Examples of Cohort Studies-

• To study the effects of oat consumption as compared to oat non-consumption on CAD in a population? (Figutre 3)

• To investigate the association between hepatitis B virus infection and the development of primary hepatocellular carcinoma?

• Whether family income affects educational achievement?

4. Randomised control trial (RCT) is an experimental study which is considered to be the “Gold Standard” in determining the relationship between exposure and outcome and generates Level 1 evidence [5]. It is used in clinical trials to evaluate whether an intervention or treatment works or to establish the efficacy and safety of medical technologies and health services.

Special characteristics of RCT are that the subjects are randomly assigned to “treatment or study” and “control” groups. Both these groups are similar to each other except for the intervention being tested. Randomisation helps to avoid the bias in choice of patients for treatment by a physician. This increases the probability that differences between the groups can be attributed to the treatment under study. After randomisation, allocation concealment is done for protecting randomisation process so that the treatment to be allocated is not revealed to the investigators before the patient is entered into the study, in order to avoid selection and confounder bias. Methods used for allocation concealment are sequentially numbered, opaque, sealed envelopes; pharmacy controlled or centrally controlled randomisation. This is followed by blinding procedures which are done to prevent participants, care-givers, or outcome assessors from knowing which intervention was received to

eliminate bias in outcome measurement. CONSORT 2010 statement recommends that it should be specified if participants, care providers or analysers were blinded rather than just mentioning “single-blind,” “double-blind,” and “triple-blind’ depending on whether one or two or all three parties were blinded.

An RCT is the best measure of causal relationship and is most effective design for controlling bias. Multiple outcomes can be evaluated in a RCT. However, RCTs are energy and time consuming. They are relatively costly and may not be feasible for all interventions or settings. They are mostly able to address one question at a time as studying multiple variables at one time may lead to errors. There is also an ethical concern of not giving intervention to the control group patients. RCTs are not practical for studying rare events. As RCTs are conducted in controlled conditions there is a limitation of external validity or generalisation of the results [6].

Examples of RCT-

• Does oat consumption reduce CAD as compared to those who are not exposed to oat intake? (Figure 4)

• The Women’s Health Initiative is a randomised trial in the USA to determine whether a sustained low-fat diet will reduce the incidence of breast cancer.

• Before and after measurements in a clinical trial for a new therapy, laboratory experiments, field trials.

Conclusions

There may be an overlap in the conceptual basis of quantitative study designs. If the cross-sectional study is repeated and the same sample is studied for a second time, the original cross-sectional study will become a cohort study. If, during a cohort study, the investigator evaluates an intervention, it becomes a trial. Cohort study also may change to case-control studies, using cases evolving during the course of the study (nested case control study). Cases of a case-series in a fixed population, may initiate a case-control study or a trial. It should be remembered that every epidemiological study may not fit neatly into one of the basic designs.

Figure 4- Experimental design of an RCT


Pikee Saxena and others

References

1. Acharya AS, Prakash A, Nigam A, Saxena P. Scientific study designs for research: an overview. Indian J Med Spec 2012;3:191-4.

2. Das R, Das PN. Biomedical Research Methodology including Biostatistical Applications. Jaypee Brothers Medical Publishers, New Delhi 1st edition, 2011; pp.19.

3. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. Types of epidemiologic studies: clinical trials. Lippincott Williams & Wilkins, Philadelphia, 3rd edition, 2008; pp. 89–92.

4. Prakash J, Nigam A, Saxena P, Acharya AS. Statistical tests of significance: an overview of the basic concepts. Indian J Med Spec 2012;3:203-6.

5. http://www.cebm.net/index.aspx?o=1025. Centre for Evidence-based Medicine. Levels of evidence. Last updated 12 July, 2012. Accessed on August 10, 2012.

6. Saxena P, Prakash A, Acharaya AS, Nigam A. How to design and conduct a randomised controlled trial? Indian J Med Spec 2012;3:198-202.

Key Points

• Study design is the basic framework of research and should be carefully selected before initiation of the study as it is the most essential tool on which the credibility of the study depends.

• Descriptive studies like case study and case series help to generate hypothesis.

• Cross-sectional study is a snapshot of a health outcome at a particular point in time. It helps to calculate point prevalence of a disease. Odds ratio can be calculated.

• Case-control study is a retrospective study which measures prevalence of risk factors in diseased and non-diseased individuals. It is useful for rare diseases. Odds ratio can be calculated.

• Cohort study could be prospective or retrospective where a group of individuals with a common characteristic are followed either into future or backwards into time. They test the hypothesis and calculate incidence, prevalence and relative risk. However, they cannot prove causality.

• Experimental studies include randomised

Table 2- A comparison of various study designs

Cross sectional Case control Cohort RCT

Comparative Cost Least Less More Most

Duration of study Relatively Less Relatively Most time- Relatively More consuming More

Sample size Variable Small Large Variable

Incidence/Prevalence Determine None Determine Determine Prevalence Incidence Incidence

Multiple outcomes Yes No Yes Yes

Bias prone Yes Yes Yes No

Causality No No No Yes

Different study designs answer different clinical questions. Each study design has its own characteristic strengths and limitations. The various study designs have been compared in Table 2. No single study is perfect and clinical decisions should be based on consistent findings from several studies that use similar design and methodology.

control trials which test the hypothesis experimentally and prove causality. They include special measures like randomisation, blinding, allocation concealment and are carried out under controlled conditions. They are the “Gold Standard” in determining the relationship between exposure and outcome and generate Level 1 evidence.



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Scientific Study Designs for Research 2