This document provides an overview of key concepts for collecting and managing data in research studies. It discusses sampling methods, types of variables, data collection techniques including using existing records, observation, interviews and questionnaires. It also covers ensuring quality of data through accuracy, reliability, data handling, data processing including coding, data entry and verification. The goal is to choose appropriate methods to obtain high quality representative data for analysis and drawing valid conclusions.
In many different types of researches we are interested in learning about large groups of people who all have something in common that is called 'target population' Researchers commonly study traits or characteristics (parameters) of populations in their studies. It is more or less impossible to study the whole population therefore researches need to select a sample or sub-group of the population that is likely to be representative of the target population. Therefore, the researcher would select individuals from which to collect the data which is called sample. Sampling is the method of selecting individuals from the population. The method of sampling is a key factor for generalizing the results of sample into a population. There are two main methods of sampling including probable and non-probable sampling techniques. In probable sampling method the sample, should be as representative as possible of the population which leads to more confident to generalize the results to the target population.
Another important question that must be answered in all sample surveys is "How many participants should be chosen for a survey"? An under-sized study can be a waste of resources since it may not produce useful results while an over-sized study uses more resources than necessary. Determining the sample size should be based on type of research and its objectives as well as required statistical methods. There are different methods for determining the sample size applying various formulas to calculate a sample size.
In many different types of researches we are interested in learning about large groups of people who all have something in common that is called 'target population' Researchers commonly study traits or characteristics (parameters) of populations in their studies. It is more or less impossible to study the whole population therefore researches need to select a sample or sub-group of the population that is likely to be representative of the target population. Therefore, the researcher would select individuals from which to collect the data which is called sample. Sampling is the method of selecting individuals from the population. The method of sampling is a key factor for generalizing the results of sample into a population. There are two main methods of sampling including probable and non-probable sampling techniques. In probable sampling method the sample, should be as representative as possible of the population which leads to more confident to generalize the results to the target population.
Another important question that must be answered in all sample surveys is "How many participants should be chosen for a survey"? An under-sized study can be a waste of resources since it may not produce useful results while an over-sized study uses more resources than necessary. Determining the sample size should be based on type of research and its objectives as well as required statistical methods. There are different methods for determining the sample size applying various formulas to calculate a sample size.
Clinical Research Statistics for Non-StatisticiansBrook White, PMP
Through real-world examples, this presentation teaches strategies for choosing appropriate outcome measures, methods for analysis and randomization, and sample sizes as well as tips for collecting the right data to answer your scientific questions.
Dear viewers Check Out my other piece of works at___ https://healthkura.com
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Assessment of Qualitative Data, Qualitative & Quantitative Data, Data Processing
Presentation Contents:
- Introduction to data
- Classification of data
- Collection of data
- Methods of data collection
- Assessment of qualitative data
- Processing of data
- Editing
- Coding
- Tabulation
- Graphical representation
If anyone is really interested about research related topics particularly on data collection, this presentation will be the best reference.
For Further Reading
- Biostatistics by Prem P. Panta
- Fundamentals of Research Methodology and Statistics by Yogesh k. Singh
- Research Design by J. W. Creswell
- Internet
Validity and bias in epidemiological studyAbhijit Das
Validity and bias are essential aspects of any research—a brief description of internal and external validity and different types of bias related to the epidemiological study.
These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdfJim Jacob Roy
Cardiac conduction defects can occur due to various causes.
Atrioventricular conduction blocks ( AV blocks ) are classified into 3 types.
This document describes the acute management of AV block.
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
Dr Sujoy Dasgupta presented the study on "Couples presenting to the infertility clinic- Do they really have infertility? – The unexplored stories of non-consummation" in the 13th Congress of the Asia Pacific Initiative on Reproduction (ASPIRE 2024) at Manila on 24 May, 2024.
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
The hemodynamic and autonomic determinants of elevated blood pressure in obes...
Data collection & management
1. Medicine & Society II
Collecting & Managing
Data
Dr Azmi Mohd Tamil
Dept. of Community Health,
Faculty of Medicine,
UKM
notes partially based on a lecture by
Assc. Prof. Dr. Roslina Abd. Manap
2. Sampling
Choosing a relatively small subset such
that it can adequately represent the
entire spectrum of population subjects
Aim to extrapolate results back to a
substantially larger population
to save time, money, efficiency and
safety.
3. SAMPLING
PROBABILITY NON-
SAMPLING
equal chance of being
PROBABILITY
selected SAMPLING
• simple random, • convenience,
• systematic,
•
• quota,
stratified,
• multistage, • purposive.
• cluster
4. SAMPLING &
TYPE OF POPULATION
Selection representative of population
? sampling methods
- simple random sampling (may not be
practical in national study)
- stratified random sampling
(in heterogenous pop./stratum)
- multistage sampling
(national-state-district-sub district-village)
- cluster sampling
5. Data Collection
Data collection begins after
deciding on design of study and
the sampling strategy
6. Data Collection
Sample subjects are identified and the
required individual information is
obtained in an item-wise and structured
manner.
7. Data Collection
Information is collected on certain
characteristics, attributes and the
qualities of interest from the samples
These data may be quantitative or
qualitative in nature.
8. Types of Variables
Qualitative - categorised based on
characteristics which differentiate it e.g.
ethnic - Malay, Chinese, Indian etc.
Qualitative variables can be classed into
nominal & ordinal.
Quantitative - numerical values collected
by observation, by measurement or by
counting. Can either be discrete or
continuous.
9. Variable
Classification
Quantitative
Qualitative
discrete - from
Nominal - no rank
counting ie no of
nor specific order
children/wives
e.g. ethnic; M, C, I &
continuous - can be in
O.
Ordinal - has
fractions, from
measurement e.g.
rank/order between
blood pressure,
categories but the
haemoglobin level.
difference cannot be
measured.
10. Types of Data
Table 1.1 Exam ples of types of data
Quantitative
Continuous Discrete
Blood pressure, height, w eight, age Number of children
Number of attacks of asthma per w eek
Categorical
Ordinal (Ordered categories) Nom inal (Unordered categories)
Grade of breast cancer Sex (male/female)
Better, same, w orse Alive or dead
Disagree, neutral, agree Blood group O, A, B, AB
http://www.bmj.com/collections/statsbk/
13. Type of Data Dictates Type of
Analysis - Quantitative
14. Data Collection Techniques
Use available information
Observation
Interviews
Questionnaires
Focus group discussion
15. Using Available
Information
Existing Records
• Hospital records - case notes
• National registry of births & deaths
• Census data
• Data from other surveys
16. Disadvantages of using
existing records
Incomplete records
Cause of death may not be verified by a
physician/MD
Missing vital information
Difficult to decipher
May not be representative of the target
group - only severe cases go to hosital
17. Disadvantages of using
existing records
Delayed publication - obsolete data
Different method of data recording
between institutions, states, countries,
making comparison & pooling of data
incompatible
Comparisons across time difficult due to
difference in classification, diagnostic
tools etc
18. Advantages of using
existing records
Cheap
convenient
in some situations, it is the only data
source i.e. accidents & suicides
19. Observation
Involves systematically selecting,
watching & recording behaviour and
characteristics of living beings, objects
or phenomena
Done using defined scales
Participant observation e.g. PEF and
asthma symptom diary
Non-participant observation e.g.
cholesterol levels
20. Interviews
Oral questioning of respondents either
individually or as a group.
Can be done loosely or highly structured
using a questionnaire
21. Administering Written
Questionnaires
Self-administered
via mail
by gathering them in one place and
getting them to fill it up
hand-delivering and collecting them later
Large non-response can distort results
22. Questionnaires
Influenced by education & attitude of
respondent esp. for self-administered
Interviewers need to be trained
open ended vs close ended
the need for pre-testing or pilot study
27. Focus group discussion
Selecting relevant parties to the
research questions at hand and
discussing with them in focus groups
examples in your own field of interest?
28. Source of biases during
data collection
Defective instruments
• close ended questions with poor choice of
options
• open ended questions with no guidelines
• vaguely-phrased questions
• illogical sequences of questions
• weighing scales that are not standardised
29. Source of biases during
data collection
Observer bias
• reporting of radiographs
Effect of interview on respondent
Attitude of respondent
• cough may be ignored by a smoker
• stigmatised diseases may not be disclosed
30. Plan for data collection
Permission to proceed
Logistics - who will collect what, when
and with what resources
Quality control
31. Quality of Data
How well do the variables designed for
the study represent the phenomena of
interest?
E.g. How well does FBS represent
control of diabetes
32.
33. Accuracy & Reliability
Accuracy - the degree which a
measurement actually measures the
measures the characteristic it is
supposed to measure
Reliability is the consistency of replicate
measures
36. Accuracy & Reliability
Both are reduced by random error and
systematic error from the same sources
of variability;
• the data collectors
• the respondents
• the instrument
37. Strategies to enhance
accuracy & reliability
Standardise procedures and
measurement methods
training & certifying the data collectors
Repetition
Blinding
38. Data handling
Check the data gathered
storing of data - backup, backup &
backup some more!
39. Data Management
Data processing
• Categorising
• Coding
• Data entry
• Verification/validation
41. Variable Labels
• Unique
• Not more than 8 characters
• Consists of letters and numbers only
• Begins with a letter instead of a number.
• Try to give a label that means something
42. Coding
• Determine the coding to be used for each
variable.
• For qualitative variables, it is recommended
to use numerical-codes to represent the
groups; eg. 1 = male and 2 = female, this
will also simplify the data entry process.
The “danger” of using string/text is that a
small “male” is different from a big “Male”,
• see Table I.
43.
44. Coding for Dichotomus
Variable
It is advisable to use
1=present, 0=absent.
Or 1=higher risk, 0=lower risk
45. Coding for Missing Value
@ blank responses
Usually required only for qualitative
variables
Conventionally coded using a value that
is not part of a valid response. For
example;
• Gender; M=1, F=2, MV=9
• Ethnic in East Malaysia; Codes 1 till 14 for
races, MV=99
46. Advantage of Coding
Reduce time for “data entry”.
Make analysis possible e.g. SPSS wont
analyse string responses of more than 8
characters
Need a proper coding manual
How to define variables and coding for
application such as SPSS and Excel are
available at the dept website
http://161.142.92.104/spss/
http://161.142.92.104/excel/
49. Data Entry
Independent operator verification
Random check of data entered against
the original
<5% error by convention
Some checks are built-in by the
software i.e. EpiInfo