ZION RESEARCH

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እንኳን ለትንሳኤ በዓል በሰላም አደረሳችሁ! በዓሉ የሰላም የፍቅር የደስታ እንዲሆንላችሁ እመኛለሁ።       መልካም   በዓል @zionresearch

እንኳን ለትንሳኤ በዓል በሰላም አደረሳችሁ! በዓሉ የሰላም የፍቅር የደስታ እንዲሆንላችሁ እመኛለሁ።       መልካም   በዓል @zionresearch

Brief Article Review Guideline Even though article review guidelines can vary across different situations, journals, institutions, and professors, we can use article review format as persented below. 1⃣ Citation: write the following information about the article you are going to review ➖Include full title, all authors (last name, initials), full journal title, year, volume number, and page numbers. 2⃣Summary: ➖Present summary of essential contents and main ideas 3⃣Study Titles, problem &purpose ➖is the title important? Self explanatory? ➖Was the purpose and/or research question stated clearly? ➖A clear statement of purpose or research questions helps you determine if the topic is important, relevant, and of interest to you. ➖Does the author clearly define a research problem or topic? ➖Is its significance explained? Are core issues or research variables identified? ➖Is specialized terminology usefully defined? 4⃣Was relevant background literature reviewed? ➖A review of the literature should be included in an article describing research to provide some background to the study. ➖Does the author provide an adequate literature review? ➖Does it discuss current research on the problem, and help to situate the authors own research? 5⃣Are the research objectives clearly stated? ➖Are hypotheses or specific research questions identified? 6⃣Methodology ➖Does the author clearly identify the research methodology and any associated limitations of the research design? ➖Are participants described, including the method of sample selection if appropriate? ➖Are instruments adequately described, including issues of appropriateness, validity and reliability? ➖Do any evident biases or ethical considerations arise in relation to the methodology? ➖Are the methods for measuring results clearly explained and appropriate? 7⃣Results ➖What are the author's major findings and conclusions? ➖Have these been supported by the author's analyses, arguments, findings or evidence? ➖Has the author overlooked anything? 8⃣Discussion & conclusion ➖Do the research results validate the authors conclusions and/or recommendations? ➖is the finding adquetly discussed and the author compared the finding with other similar studies?? ➖is the conclusion reported inline with its objectives?? 9⃣ Suggestion for future research: ➖Does the author suggest areas for further research or discussion? 🔟References ➖Are references given (footnotes or bibliography)? ➖What is the size of the reference section? ➖Are the references recent, important? ➖How are the references used: for support, rebuttal, etc.? Please #Share our channel to your friends and classmates and encourage us! @zionresearch Discussion group @researchers_room

The calculation of design effect (DEFF) depends on the specific sampling method used. Here's a breakdown for two common methods: 1. Stratified Sampling: For stratified sampling, where the population is divided into subgroups (strata), the DEFF can be estimated using the following formula: DEFF = 1 + [(n_h - 1) * ρ_h] / (N - n) Where: * DEFF: Design effect * n_h: Sample size from stratum h * ρ_h: Intraclass correlation coefficient within stratum h (measures how similar units within a stratum are) * N: Total population size * n: Total sample size (sum of n_h across all strata) 2. Cluster Sampling: In cluster sampling, where groups (clusters) are selected instead of individual units, the DEFF can be calculated with this formula: DEFF = 1 + (ICC * (average cluster size - 1)) Where: * DEFF: Design effect * ICC: Intraclass correlation coefficient (measures how similar units within a cluster are) * Average cluster size: The average number of units within a cluster If ✅DEFF = 1: your complex design is as efficient as SRS). ✅DEFF > 1: The variance increases, results might be less precise). You might need a bigger sample size to compensate. ✅DEFF < 1 (rare): The variance decreases, results might be more precise than SRS) - this can happen with some stratification techniques. Important points to remember: 📋 These formulas require specific values like intraclass correlation coefficient (ICC), which may need to be estimated from pilot studies or previous research. 📋There are more complex formulas for DEFF that account for weighting adjustments and other design features. ✅Software packages for statistical analysis often have built-in functions to calculate DEFF based on your sampling design. ✌️For more complex sampling designs or if you need help with specific calculations, consulting a statistician is recommended.

DESIGN EFFECT The design effect (DEFF) essentially tells you how much a particular sampling design impacts the variance of your results, compared to a simple random sample (SRS). The design effect (DEFF) is most relevant for complex sampling methods where the selection process deviates from a simple random sample (SRS). 📈 Here are some common sampling methods where DEFF is applied: ➡️ Stratified Sampling: This method divides the population into subgroups (strata) based on relevant characteristics. DEFF helps account for the increased variance within strata compared to SRS. ➡️ Cluster Sampling: Here, groups (clusters) are selected instead of individual units. DEFF reflects the impact of clustering on variance, which can be higher if units within clusters are similar. ➡️ Multistage Sampling: This involves selecting units at multiple stages, like counties then households within those counties. DEFF considers the combined effect of these stages on variance. ➡️ Unequal Probability Sampling: If some units have a higher chance of being selected, DEFF helps adjust for this by incorporating the selection probabilities. 🚫 As a rule of thumb the design effect of 1.5 and 2.0 are usually applied to adjust sample size in complex sampling, however DEFF has it's own estimation. It's important to note that DEFF calculations depend on the specific sampling design. There are different formulas for stratified sampling, cluster sampling, and so on. However, the core concept remains the same - comparing the variance under the chosen design to that of a hypothetical SRS. Let's look at some methods of calculation 👇👇👇

What is Design Effect? How can we calculate it? When do we apply it? @zionresearch

ኢድ ሙባረክ! ለመላው የእስልምና ተከታዮች በሙሉ መልካም በዓል ተመኘን! @zionresearch

IBM SPSS software If you need individual training on statistical models and software, feel free to contact us. We provide through online based on your need. @rreessss

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#ጥቆማ በወራቤ ኮምፕርሄንሲቭ ስፔሻላይዝድ ሆስፒታል በተፈጥሮ የላንቃና የከንፈር መሰንጠቅ ችግር ላለባቸው ህጻናት #ነፃ የቀዶ-ጥገና ህክምና ቅዳሜ መጋቢት 14 እና 15 2016 ዓ/ም ይሰጣል። ስለሆነም ተገልጋዮች አርብ ማታ ማለትም መጋቢት 13/07/2016 ዓ.ም ገብተዉ በማደር የአገልግሎቱ ተጠቃሚ እንዲሆኑ ሲጠቆም የታካሚውና የአስታማሚው የምግብ፣ የደርሶ መልስ ትራንስፖርት ወጪ መንግስታዊ ባልሆኑ ድርጅቾች በኩል እንደሚሸፈን ተገልጿል። ይህንን አገልግሎት መጠቀም የሚፈልጉ ተገልጋዮች በሚከተሉት ስልክ ቁጥሮች በመደወል ተጨማሪ መረጃ ማግኘት እንደምትችሉ ተጠቁሟል። +251911676748 ወይም +251912185515

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Theoretical vs conceptual framework 📋As a researcher, you need to understand the importance of establishing a solid theoretical and conceptual framework to guide the investigation and interpretation of research findings. 🅰 Theoretical Framework 📋A theoretical framework is a conceptual structure that outlines the fundamental principles, theories, and assumptions guiding a research study. 📋It provides a systematic understanding of the phenomena under investigation by integrating relevant theories from existing literature. 📋Theoretical frameworks help researchers contextualize their study within established knowledge and theoretical perspectives, guiding the formulation of hypotheses, interpretation of findings, and development of research methodologies. 🅱 Conceptual Framework 📋A conceptual framework is a set of interconnected concepts, constructs, and variables that form the foundation of a research study. 📋It translates theoretical principles into tangible elements that can be measured and analyzed. 📋Conceptual frameworks define key concepts, specify relationships between variables, and provide a framework for organizing and interpreting data. 📋They serve as a roadmap for researchers, guiding the selection of research methods, data collection techniques, and analytical approaches. 📋Conceptual frameworks help researchers operationalize abstract theories into empirical research designs, facilitating the investigation of complex phenomena and the generation of meaningful insights. @zionresearch @rreessss for assistance

Sample size calculation 📋 sample size for proportion (Cochran) Sample size for survey (Yemane) Sample size correction (finite population)

Purposive sampling is a non-probability sampling technique where researchers select participants based on specific criteria or characteristics relevant to the research question. This method is often used when researchers want to gather in-depth information from individuals who possess certain characteristics or experiences that are crucial to the study. There are several types of purposive sampling methods, including: 1. Maximum variation sampling: In this method, researchers select participants who represent a wide range of characteristics or experiences related to the research topic. This helps to ensure diversity in the sample and capture a broad spectrum of perspectives. 2. Homogeneous sampling: Researchers choose participants who share similar characteristics or experiences, such as age, gender, occupation, or education level. This method is useful when the research aims to explore specific patterns or themes within a particular group. 3. Expert sampling: Researchers select participants who are considered experts or knowledgeable in a particular field or topic of interest. This method is commonly used in studies that require specialized expertise or insights from individuals with specific qualifications. 4. Snowball sampling: This method involves selecting initial participants who meet the research criteria and then asking them to refer other potential participants. This technique is useful for identifying hard-to-reach populations or individuals with unique experiences. 5. Convenience sampling: While not strictly a purposive sampling method, convenience sampling involves selecting participants based on their availability and accessibility. Researchers may choose this method when time and resources are limited, but it may introduce bias into the sample. Overall, purposive sampling allows researchers to strategically select participants who can provide valuable insights and perspectives relevant to the research question, making it a useful tool in qualitative research.

types of purposive sampling

Why doesn’t correlation mean causation? There are two main reasons why correlation isn’t causation. These problems are important to identify for drawing sound scientific conclusions from research. 1. The third variable problem. It means that a confounding variable affects both variables to make them seem causally related when they are not. For example, ice cream sales and violent crime rates are closely correlated, but they are not causally linked with each other. Instead, hot temperatures, a third variable, affects both variables separately. Failing to account for third variables can lead research biases to creep into your work. 2. The directionality problem. This occurs when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other. For example, vitamin D levels are correlated with depression, but it’s not clear whether low vitamin D causes depression, or whether depression causes reduced vitamin D intake. 😀 Therefore, don't conclude that there is a causal relationship between variables using correlation analysis even if the analysis shows the correlation is significant. @zionresearch

Recent research findings in health related issues that you might be interested in. - Researchers 3D-print functional human brain tissue¹ that could help study and treat neurological disorders such as Alzheimer's and Parkinson's. - Scientists discover how to reprogram T cells to fight aging¹ by eliminating specific cells in mice that cause inflammation and tissue damage. - A new study explains how brain cells organize and connect¹ based on general principles of networking and self-organization, rather than the biological features of an individual cell. - Scientists grow human retinas in a petri dish¹ and reveal how vitamin A enables people to see millions of colors, unlike most mammals. - A new approach to tackling bacterial infections¹ is identified by researchers who found a way to turn on a vital bacterial defense mechanism to fight and manage infections. - A new analysis reveals that many excess deaths attributed to natural causes are actually uncounted COVID-19 deaths², highlighting the need for accurate reporting and testing. - A new study shows that the brain's ability to compensate for age-related cognitive decline is stronger than previously thought², and depends on the level of education and cognitive reserve of the individual. - Scientists uncover how T cells combat tuberculosis², the bacterium that causes one of the deadliest infectious diseases in the world. - A new anti-viral drug study aims to cure long COVID², the condition that affects many people who have recovered from COVID-19 but still experience symptoms such as fatigue, brain fog, and shortness of breath. - A study finds that listening to the sounds of nature² can improve mental health and well-being, especially for people who live in urban areas. - A breakthrough in synthetic biology allows researchers to create super-engineered vaccines² that can target multiple strains of polio and potentially eradicate the disease. - A new DNA map³ could lead to better treatments for diseases such as cancer, diabetes, and Alzheimer's by revealing how genes interact and influence each other. - A new test⁴ could speed up the diagnosis of endometriosis, a painful condition that affects millions of women and can cause infertility. - A new study⁴ suggests that taurine, an amino acid found in meat, fish, and dairy products, may extend life and health by protecting cells from oxidative stress and inflammation. I hope you find these topics interesting and informative. If you want to learn more about any of them, you can follow the links to the sources. 😊 Source: Conversation with Bing, 16/02/2024 (1) Health & Medicine News -- ScienceDaily. https://www.sciencedaily.com/news/health_medicine/. (2) Medical research - BBC News. https://www.bbc.co.uk/news/topics/c1038wnxy50t. (3) 2022 Research Highlights — Promising Medical Findings. https://www.nih.gov/news-events/nih-research-matters/2022-research-highlights-promising-medical-findings. (4) Current Topics in Public Health and related disciplines. https://academic.oup.com/journals/pages/current-topics-in-public-health.

Research design vs research approach Study design and research approach are two important concepts in research methodology. They are related but not the same. - Research approach refers to the overall strategy or plan for conducting a research study. It involves choosing between qualitative, quantitative, or mixed methods, depending on the research question, objectives, and assumptions. 📋Therefore, when stating research approach in your research you need to state either Quantitative, Quantitative or Mixed and the justification to use it. - Study design refers to the specific type of research design that is used to collect and analyze data within a chosen research approach. There are many types of study designs, such as experiments, surveys, case studies, explanatory , exploratory, phonological grounded theory, ethnographies, etc. 📋Therefore, when you explain your research design state either explanatory or exploratory or experimental if you use quantitative approach and state either phenomenologic or ethnographic etc if you use qualitative and provide the justification. 📋If you want to combine both qualitative and quantitative methods to address different aspects of the research problem, or to triangulate or complement the data, a mixed methods approach is useful. You can use study designs such as sequential, concurrent, or transformative designs. The choice of research approach and study design depends on various factors, such as: - The nature and scope of the research problem - The availability and quality of data sources - The feasibility and ethical issues of the research methods - The expected outcomes and implications of the research findings Use the following Source to read more. (1) What Is a Research Design | Types, Guide & Examples - Scribbr. https://www.scribbr.com/methodology/research-design/. (2) The Selection of a Research Approach - SAGE Publications Inc. https://us.sagepub.com/sites/default/files/upm-binaries/55588_Chapter_1_Sample_Creswell_Research_Design_4e.pdf. (3) Research Design | Step-by-Step Guide with Examples - Scribbr. https://www.scribbr.co.uk/research-methods/research-design/. (4) What Is a Research Design | Types, Guide & Examples - Scribbr. https://www.scribbr.com/methodology/research-design/. (5) Research Design | Step-by-Step Guide with Examples - Scribbr. https://www.scribbr.co.uk/research-methods/research-design/. (6) The Selection of a Research Approach - SAGE Publications Inc. https://us.sagepub.com/sites/default/files/upm-binaries/55588_Chapter_1_Sample_Creswell_Research_Design_4e.pdf. (7) Research Design vs. Research Methods - What's the Difference? | This vs .... https://thisvsthat.io/research-design-vs-research-methods. Http://t.me/zionresearch

የካንሰር ክትባት የሩሲያው ፕሬዝዳንት ቭላዲሚር ፑቲን የሩሲያ ተመራማሪዎች በቅርቡ ለካንሰር ታማሚዎች የሚቀርብ የካንሰር ክትባት ለማግኘት መቃረባቸውን አስታውቀዋል። ፑቲን በሞስኮ በተደረገው የቴክኖሎጂ ፎረም ላይ ቀርበው በሰጡት አስተያየት የካንሰር ክትባት እና የካንሰር በሽታን ለመከላከል የሚረዱ የመከላከያ መድሃኒቶችን ለመስራት መቃረባቸውን ገልፀዋል። ፑቲን ክትባቶቹ እና መድሃኒቶቹ በቅርብ ጊዜአት ተመርተው ለግለሰብ በሚደረጉ ሕክምናዎች ውጤታማ በሆነ መንገድ ጥቅም ላይ እንደሚውሉ ተስፋ የሚያደርጉ መሆኑንም ነው የጠቆሙት። ክትባቶቹ ለየትኛው የካንሰር አይነት እንደሚውሉ እና እንዴት እንደሚሰሩ ፕሬዝዳንት ፑቲን ለይተው  አለመናገራቸው የተገለፀ ሲሆን በርካታ ሀገራት እና ኩባንያዎች ለካሰር መከላከያ ክትባት ለመስራት ጥረት በማድረግ ላይ መሆናቸው ተመላክቷል። በሳለፍነው ዓመት በፈረንጆቹ 2030 ለ10 ሺህ ታካሚዎች የሚደረርስ የግል የካንሰር ህክምናዎች ላይ የክሊኒካል ሙከራ ለማድረግ የሚያስችል ስምምነት በብሪታኒያ እና በጀርመኑ ባዮኤንቴክ ኩባያ ጋር ስምምነት መደረጉ ተዘግቧል። በአሁኑ ወቅት የማህጸን በር ጫፍ ካንሰርን ጨምሮ በሰው ልጅ ላይ ካንሰርን የሚያስከትሉ በሂዩማን ፓፒሎማ ቫይረስ (HPV) የሚከላሉ እውቅና የተሰጣቸው ስድስት ክትባቶች እንዳሉ የዓለም ጤና ድርጅት ማሳወቁን የዘገበው ሮይተርስ ነው። @zionresearch

Key data on Maternal and child death status in Ethiopia Maternal Mortality Rate (MMR): 2019 estimate: 384 deaths per 100,000 live births (World Health Organization) Significant decrease: This represents a 67% decline from the 2000 level of 1,180 deaths per 100,000 live births. However, Ethiopia still faces a high burden of maternal mortality compared to the global average (211 deaths per 100,000 live births). Under-Five Mortality Rate (U5MR): 2019 estimate: 47 deaths per 1,000 live births (UNICEF) Steady decline: This shows a 71% decrease compared to the 1990 baseline of 204 deaths per 1,000 live births. However, it remains above the global average of 39 deaths per 1,000 live births. Infant Mortality Rate (IMR): 2019 estimate: 34 deaths per 1,000 live births (UNICEF) Progress with disparities: This represents a significant reduction from 124 deaths per 1,000 live births in 2000. However, there are disparities between rural and urban areas, with higher rates in rural areas. Neonatal Death Rate (NMR): 2019 estimate: 26 deaths per 1,000 live births (UNICEF) Slow progress: While some reduction has been achieved from 58 deaths per 1,000 live births in 2000, progress in reducing neonatal mortality has been slower compared to other child mortality indicators. @zionresearch

Some recent economic data about Ethiopia: Real GDP growth fell to 5.3% in 2022 from 5.6% in 2021 but remained above East Africa’s averag. Inflation rose to 34% in 2022 from 26.6% in 2021 due to internal conflict, drought, and the effects of Russia’s invasion of Ukraine on commodity prices. The fiscal deficit widened to 4.2% of GDP in 2022 from 2.8% in 2021 due to higher defense spending and weak revenue performance. The current account deficit deteriorated to 4.0% of GDP in 2022 from 3.2% in 2021 due to higher prices for commodity imports. Public and publicly guaranteed debt declined to 50.1% of GDP (with external debt at 23.6% of GDP) in 2022 from 51.0% in 20211.

Sampling techniques in research Types of sampling 1⃣Probability sampling 🔰ይህ sampling መንገድ በquantitative Research method ላይ የምንጠቀመው ነው፣ 🔰ሁሉም ሰዎች በጥናቱ ላይ የመሳታፍ እኩል እድል አላቸው ። ➖Simple random ➖Systematic random ➖Stratified ➖Cluster ➖Multi-stage 2⃣Non probability sampling 🔰ይህ መንገድ ለqualitative study የምንጠቀመው ነው፣ 🔰ሁሉም ሰዎች በጥናቱ የመሳታፍ እኩል እድል አይኖራቻውም። ➖Quota sampling ➖Purposive sampling ➖snowball sampling ➖convenience sampling T.me/zionresearch @rreessss or @zion_helper for assistance #share