Submissions

Author Guidelines

1. AUTHOR GUIDELINES

   Submission of Manuscripts
   Only original material in the manuscript will be considered for publication. Neither the manuscript nor essential substance of the manuscript should be submitted for publication elsewhere before appearing in this journal.
   Online submission
   On our website, the corresponding author must create an account or login to an existing account. Then he must complete a 5-step simple submission process. The manuscript must be blinded, with no indication of the authors' names, designations, departments, institutions, or towns. Author information should be included in metadata. If required, supplemental files such as data files, fee submission documents, and so on can be included.
   Language
   PJHS is published in English. Use of British English is preferred however American English can also be employed where convenient.
   Writing Style and format
   Please use Times New Roman, size 12, justified, with a line spacing of 1.0. Tables and illustrations (figure/ chart/ image) should be placed where specified, not at the conclusion of the document.
   Submission Format According to the type of Manuscript Review article: Maximum 3500 words excluding references.
   Original article: Maximum 2500 words excluding structured abstract of 250 words and 20 references (minimum).

   Case Report: Abstract; Introduction; Case Report; Discussion and Conclusion

   Short Report: Abstract; Introduction; Patients Methods and Result; and Conclusion

   Special Communication: Abstract; Introduction; Methods and Result; and Conclusion

   Short Reports / Short Communications / Special Communications / Case reports: Maximum 1250 words excluding title page and an unstructured abstract of 150 words with no more than two tables or figures and 10 references. It should not be signed by more than six authors.
   
   Letters to the Editor: Maximum 250 words if it is in reference to a recent journal article, or 400 words in all other cases. It must have no more than five references and one figure or table. It must not be signed by any more than three authors. Letters referring to a recent journal article must be received within four weeks of its publication.

   Title of the manuscript
   It must include the study's design, objectives, and variables. It should also include information about the characteristics and geographical location of the population of interest. Use of abbreviations should be avoided in title. Each manuscript should include five to ten key words. These should be included in the Medical Subject Headings (MeSH) of the United States National Library of Medicine, which may be found at: https://meshb.nlm.nih.gov/
   Abbreviations
   Only standard abbreviations should be used. For each abbreviation, the full term should be presented first, followed by the abbreviation in parenthesis. A well-known and widely used abbreviation may be used in this capacity.
   Tables and Illustrations
   1. There is no limit to the number of tables and illustrations (graphs/ charts/ images) that can be included. These should be in accordance with the manuscript's rational demand.
   2. Each table and illustration should stand alone, displaying all of its contents/meanings without referring to the text.
   3. Each table and illustration must have a legend below the table/illustration. The title of the table and picture should be a summary of the manuscript's tile.
   4. Illustrations must be of high quality. Graphs and charts should be editable.
   5. Where applicable, a legend should be included with the table or illustration.
   6. If a table or illustration is taken from a published work, the source must be cited.
   7. To reproduce a previously published illustration, the author must obtain permission from the author/publisher.
   References
   1. Vancouver style must be followed.
   2. References should be numbered serially and given in digits within the text, as in standard medical journals.
   3. Add authors. Give last/family/surname in full, then first letter of 1st and 2nd names as capital with no gap. Add six authors. In case of more than six authors, et al should be added after six authors.
   4. Journal titles should be written in full form followed by the issue and volume number.
   5. Add DOI where available; otherwise add online link.
   Here is an example for a journal article: Ishaq T, Khattak MI, Amin S, Haq NU. Frequency and risk factors for hepatitis C among pregnant women. Gomal J Med Sci 2011; 9:166-9.

   Units of Measurements
   Please use Systems International (SI) units, where possible.

   Drug Names

   Generic names of drugs are preferred. Where essential the brand names can be given in parenthesis.

   ORIGINAL ARTICLE

   Abstract: Word count should be within 250. It may be up to 350 in exceptional cases. It should have the following sub-headings: Background, Material & Methods, Results, and Conclusion. Background includes 1-3 sentences regarding the introduction of your problem/s of interest and objective/s. Material & Methods include study design, duration, setting, population & sampling, and data collection (variables and their attributes and types) and analysis plans (descriptive, estimation of parameters and hypotheses testing). Conclusion is the summary of your results in simple words.

   Text

   The main part of the original research article should follow IMRAD; to have the following sub- headings: Introduction, Material and Methods, Results, AND Discussion & Conclusion.

   A. INTRODUCTION: This section should have nearly all the following components.

   Bring here data in quantities (numbers & figures) regarding all your variables of interest as per your objectives. It may include prevalence and/or incidence of the disease of interest/ under investigation, its distribution by socio-demographic factors, its various determinants or its treatment. Instead of prevalence, distribution, determinant and treatment of a disease, the researcher may determine any health related event in a population, like level/ concentration/ score of some anthropometric measure/ biochemical parameter, like weight, height, blood pressure (BP), random blood sugar (RBS) etc. Here bring the level/ concentration/ score of your parameters of interest. The data is collected from global populations/ studies, then regional, then national and lastly local populations/ studies. The manuscript should clearly sate research problem, knowledge gap, research question, research objective, hypothesis and significance of the study.

   B. MATERIALS AND METHODS

   This section should have nearly all the following components.
   
   1. Design, Setting & Duration
   Please mention the study design (cross-sectional/case-control/cohort/ trial) with name of the academic/ professional department and name of the academic/ professional institution with city and country. It shows ownership. Add duration of the study with day, month and year.

   2. Technical approval from the institutional research board and ethical approval from institutional ethical committee & patients’ consent.

   3. Population & sampling

   Research is a problem solving activity for a specified population; never for a sample. Please specify/ define your population by count, geographic location, socio-demographic and disease factors. Then tell how you calculated the sample size as required by the design of your study with formula/calculation or online calculator/software with reference/link. Then give sampling technique. Then give inclusion and exclusion criteria for one group or separately for each group in case of two or more groups.

   4. Equipment, procedure, intervention and follow up

   Please narrate here all the steps which you took from enrolment of a subject to its discharge from the study, including history, general & systemic examination, investigations and any intervention (health education, food, exercise, vaccine, drug, device, laser or surgery). Please give details of different equipment, instruments, appliances and tools used, giving the name, model, version, company name and its manufacturing city name in parenthesis.
   5. Data collection plan

   1. Data collection methods (physical procedures to collect data)
   a. Literature survey (secondary data; the data of other researchers collected, mostly qualitative)
   b. Questionnaire
   c. Interview
   d. Observation: clinical examination, laboratory & imaging tests, pre, per and post drug- treatment/ device-procedure/ operation notes/ findings as morbidities, disabilities, mortalities. (b, c and d give us primary & first hand data, the data which we generate ourselves from the sample, mostly quantitative). Tell which one or more methods of data collection are used by you.
   2. Questionnaire is framed from literature. The data on research variables is collected by questionnaire. Qualities are transformed into quantities (qualitative variable/data to quantitative variable/data) as in Knowledge, Attitude & Practice (KAP) Surveys. It gives us quantitative data. Its reliability is pretested by a pilot study by selecting sample from a sample and is shown as Cronbach’s alpha. It should be based on a 5-point Likert scale, with a range of 1-5 scores (strongly disagree, disagree, neutral, agree & strongly agree, respectively) respectively for each response. It includes respondent demographic. The questionnaire must not be on nominal or ordinal scale.
   3. Questionnaire; To-do list
   a. Items (questions) are extracted from literature (existing knowledge)
   b. Designed as per list of variables, their attributes & their relationship as per theoretical framework
   c. Items should be short & to the point
   
   4. Avoid in framing a questionnaire; Not-to-do list
   a. Double-Barrel items/questions (Qs)
   b. Putting words in mouth of respondent (leading Qs)
   c. Memory dependent Qs; should base on cash memory
   d. Emotional loaded Qs (positive emotion=happiness, negative are anger, fear, sadness & hatreness)
   e. Personal Qs (private, vary from culture to culture)
   f. Technical Jargons
   g. Too many
   h. Too long
   i. Negative Qs. I do not like computer. If negative are used, then reverse the scoring at analysis.

   5. Name the demographic variables: gender, age in years, age groups, education level, residence, experience, income etc.

   6. Name the research variables: pain in flank, category of pain in throat, level of knowledge, level of attitude, level of practice, weight in Kg, height in cm, volume in ml, RBS in mg/dL, T3 level in pcg/ml
   7. In case of categorical (nominal or ordinal) variable, tell the attributes (categories/ groups) of the variable
   a. Age grouping was; group 1 up to 50 years, group 2 more than 50 years in a study “prevalence of HTN in employees of a bank”
   b. Age in years was categorized as; group 1= 40-49, group 2 = 50-59, group 3 = 60-69, group 4
   = 70 and above years for a study “prevalence of DM in adult age shopkeepers”
   c. The two attributes of residence were urban and rural
   d. The five attributes of education level were: matric = group 1, graduation = group 2, masters
   = group 3, MPhil = group 4 and PhD = group 5
   e. Level of knowledge, level of attitude and level of practice (KAP) were determined by a questionnaire based on 5-point Likert Scale. There were so many questions for each of the three KAP variables with a range of 1-5 scores (strongly disagree, disagree, neutral, agree & strongly agree, respectively) for each question.

   8. Identify independent, dependent, confounding and matching variables, where required
   9. Tell the data types (nominal/ordinal/interval/ratio); gender, residence and pain in flank were nominal data. Age groups, education level, and category of pain in throat were ordinal data. Age in years, level of knowledge, level of attitude, level of practice (all three on Likert Scale), pain score (on visual analogue pain scale-VAPS), weight in Kg, height in cm, volume in ml, RBS in mg/dL, T3 level in pcg/ml were interval/ ratio/ numeric/ continuous data.
   10. Attach Performa and questionnaire. if any.
   11. Mention which calculator or software was used for data analysis

   6. Data analysis plan

   Research is for a specified population; never for a sample. It is ideal to observe the entire population, but it is not feasible. Statistics as a discipline helps us in collecting data for a sample, analyze it for the sample (descriptive statistics; describe the sample) and then infer it on to the population from which it was drawn (inferential statistics; describe the population
   
   based on the data collected from the sample). Inferential statistics includes estimation of parameter and hypothesis testing.
   Global literature is full of research articles which are restricted to sample, with no mention of the population. For us, it may be anything, but not research.
   Our authors have to give analysis plan for all the three components of the statistical analysis. It is widely stated and widely accepted narrative that the cross-sectional studies don’t require hypothesis. It is a miss-understanding. Cross-sectional studies do require hypothesis. There may be some one dozen cross-sectional studies, each with many hypotheses published in this journal from 2018 to 2021, regarding burden/ magnitude (prevalence/ distribution) of malaria, leishmaniasis, DS-TB, DR-TB etc.
   Data analysis is simply a process of converting data (un-organized facts & figures) into information (organized facts & figures). Both qualitative and quantitative data are organized as per requirements of the topic and end users of the findings. When analyzed (organized), qualitative and quantitative facts and figures are mixed together to form a single piece of information or knowledge.
   There are two types of analysis.

   Qualitative analysis

   Qualitative data includes text, picture, audio and video. This analysis is based on qualitative argumentation (not included here).

   Quantitative analysis

   Quantitative data includes nominal, ordinal, interval and ratio data. This analysis is based on statistical computations (included here).

   Descriptive analysis

   It is the analysis of data collected from the sample. Here each variable is described separately without talking about its difference between the groups or within the groups or its relationships to any other variable in the same population.
   Categorical (nominal and ordinal data) is analyzed by count and percentage. Numeric (interval and ratio) is subjected to tests of normality; Skewness, kurtosis, Kolmogoro-Smirnov test & histogram. If it is distributed normally; then it is analyzed by mean, minimum, maximum, range and SD. If it is distributed not normally (skewed); then it is analyzed by median (quartile 2), quartile 1 (Q1), quartile 3 (Q3) and Inter Quartile Range (IQR=Q3-Q1).
   Inferential analysis: Here the data for the sample is inferred on to population. It includes estimation of parameters and testing of hypotheses.

   Estimation of parameters

   Here an interval in constructed around a sample statistics to estimate a parameter i.e. mean or proportion for a population at certain level of confidence, usually 95%. It is represented as confidence interval of mean or proportion, both with lower and upper bounds.
   The mean RBS of the sample (n=350) was 110 (95% CL, 105.5-114.5) mg/dL. The frequency (%age) of diabetes mellitus in the sample (n=300) was 45 (15%, 95% CL, 12.5-17.5).
   
   C. RESULTS
   1. Preparing the sample for analysis; number of subjects
   1. Total number of participants/ respondents/ subjects/ cases/ patients/ controls/ animals/ specimens/ plants/ microorganisms enrolled/ included at inception/ start of the survey/ study/ trail
   2. Group wise number of participants/ subjects/ cases/ patients/ controls at inception
   3. Frequency (count) & percentage of responses of the respondents in case of questionnaire based survey
   4. Mention if any subject died?
   5. How many were dropped out & why? Mention different causes with numbers of subject separately i.e. due to which complications of the drugs/ devices/ laser/ surgical procedure etc.
   6. How many were lost to follow up?
   7. Mention the missing data at follow ups
   8. The rest of the subjects are the actual size of the sample/s to be analyzed
   2. Descriptive analysis: Please analyze and write here your findings as explained in data analysis plan.
   3. Estimation of parameters: Please analyze and write here your findings as explained in data analysis plan.
   4. Testing of hypotheses: Please analyze and write here your findings as explained in data analysis plan.
   D. DISCUSSION
   1. Put your findings for your first objective/ variable. Then add studies with similar findings from local, then national, then regional and lastly global studies/ literature/ populations. Then add studies with higher findings (higher prevalence/proportion/mean) and lastly with lower findings. Likewise go for your next objectives/ variables one by one.
   2. The comparison is to be based on estimation of parameters (indices of population) and not on sample statistics (sample indices). Further it should be based on hypotheses testing, but most studies lack both the estimation of parameters and hypotheses testing.
   3. The comparisons must be based on numbers/ indices (counts, percentages and means) from populations, not merely on theoretical/logical/philosophical statements/argumentation.
   4. Each study brought for comparison should have author name, city & country name, duration of study, sample size and relevant data for comparison.
   5. Better to bring those studies which are already cited in introduction.
   6. Other studies may have data for many more objectives/ variables. You have to bring only relevant data matching to your objective/ variables.
   7. Conclusion is the last part of the discussion. It is actually summary of your results. What you observed and analyzed in your study, bring those facts here in non-statistical language as statement in simple English. Do not bring conclusions from work of other authors.
   8. Recommendations may be added as separate heading or it may be the last paragraph of the conclusion. Here you may go beyond your own findings.
   
   E. CONCLUSION
   It should be based on the objective and principal findings. False ambiguous conclusion and speculations should be avoided.