Guidelines for Authors

GENERAL

Peshawar Journal of Medical Sciences (PJMS) is published quarterly by the Peshawar Institute of Research, D.I.Khan, Pakistan. It follows the International Committee of Medical Journals Editors (ICMJE) guidelines as “Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals” available at: http://www.icmje.org/icmje-recommendations.pdf

Submission of Manuscripts

Manuscripts containing original material are accepted only. Neither the article nor any part of its essential substance should be submitted for publication elsewhere before appearing in this journal.

Online Submission

The corresponding author has to create an account or log in to an existing account on our website. Then he has to follow a 5-step easy submission process. The manuscript must be blinded, not showing authors' details; names, designations, departments, institutions, cities, etc. The details of the authors are to be uploaded in metadata. The supplementary files, including data files, fee submission documents, etc. may be added if desired.

Language

PJMS is published in English. Try to follow British English but do not hesitate to use American English where convenient.

Writing style & format

Please use Times New Roman, size 12, justified with 1.5 line spacing. Put tables and illustrations (figure/ chart/ image) where stated, not at the end of the document.

Title of the manuscript

It must show the design, objectives, and variables of the study. It should also show the attributes and geographical location of the population of interest. Don’t use abbreviations. For example;
1. Prevalence of diabetes mellitus and its distribution by sex, age groups and residence in the adult population of district Lahore, Pakistan: a cross-sectional inquiry

2. Hypertension, diabetes mellitus, and obesity as determinants of coronary artery disease in the adult population of Islamabad city, Pakistan: a case-control approach
3. Age groups, gravidity, parity, and place of delivery as predictors of postpartum hemorrhage in women of Riyadh city, Saudi Arabia through cohort approach
4. Urethrocutaneous fistula following Snodgrass versus two stages Aivar Bracka repair of distal penile hypospadias in male children of district Peshawar, Pakistan: a randomized control trial
5. Post-operative oral antibiotics in reducing the frequency of surgical site infection following non-perforated appendectomy in the population of South Waziristan Agency, Pakistan: a randomized control trial
Keywords

Five to ten keywords per manuscript should be given. These should be included in Medical Subject Headings (MeSH) of the U.S. National Library of Medicine, available at: https://meshb.nlm.nih.gov/search

Abbreviations

Standard abbreviations should be used only. For every abbreviation, the full word should be given first with the abbreviation in parenthesis. Well-known and frequently used abbreviations may be used as such.

Tables and Illustrations

1. There is no limit on the number of tables and illustrations (graphs/ charts/ images). These should be as per the rational demand of the manuscript.
2. Each table and illustration should stand by itself; showing all its contents/ meanings without going into the text.
3. Each table and illustration must have a serial number and a title; above the table and below the illustration. The title of the table and illustration should be a summary of the title of the manuscript.
4. Illustrations should be of good quality.
5. Where required, a table or illustration should have an accompanying legend.
6. If a table or an illustration has been reproduced from a published work, the source must be cited.
7. The author must submit permission from the author/ publisher to reproduce the previously published illustration.

References

1. Vancouver style must be followed.
2. References should be numbered serially and given in digits as superscripts within the text, as in standard medical journals.
3. Add authors. Give last/family/surname in full, then the 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 abbreviated as in Index Medicus/ Medline/ PubMed/ NLM Catalogue. If not in Index Medicus, then it should be abbreviated as by the journal itself.
5. Add DOI where available; otherwise add the online link.
6. Here is an example for a journal article: Frequency, distribution, and determinants of Helicobacter pylori infection in adults and adolescents with gastric symptoms: cross-sectional epidemiological inquiry in district Haripur, Pakistan. Awan AA, Khattak AA, Haq M, Saadia Z, Marwat M, Khalid S, et al. Braz J Biol 2022 Jun 17;84:e248913. https://doi.org/10.1590/1519-6984.248913

Units of Measurements

 Systems International (SI) units are recommended, where possible.

Drug Names

Generic names of drugs are recommended. Where essential, the brand names should be added in parentheses.

ORIGINAL ARTICLE

Abstract: The word count should be within 250. It may be up to 350 in exceptional cases. It should have the following sub-headings: Background, Materials & Methods, Results, and Conclusion. Background includes 1-3 sentences regarding the introduction of your problem/s of interest and objective/s. Materials & 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). The conclusion is the summary of your results in simple words.

Text

It should usually be around 2500 words. It may exceed in certain cases with more objectives. The main part of the original research article should follow IMRAD; to have the following sub-headings: Introduction, Materials and Methods, Results, AND Discussion & Conclusion.

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

1. Background: Bring here data in quantities (numbers & figures) regarding all your variables of interest as per your objectives. It may include the 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, 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.

2. Research Problems (RPs): Unawareness of any aspect of a disease like prevalence, distribution, determinants (causes/ risk factors) or its treatment, or unawareness of level/ concentration/ score of some parameter in a specified population in a specified period of time is a research problem. State your problem here;
i. Unawareness regarding the prevalence of diabetes mellitus in the adult population of district Kohat, Pakistan for the year 2020 was our RP.
ii. Unawareness regarding the level of random blood sugar (RBS) in the adult population of district Kohat, Pakistan for the year 2020 was our RP.

3. Knowledge Gaps (KGs): Search different search engines and databases for your research problem. If you find the required study/ data, there is no KG and this problem is not a researchable title. If it was not found, the KG is identified and you may go ahead.
i. As no studies/ data were available regarding the prevalence of diabetes mellitus in the adult population of district Kohat, Pakistan for the year 2020, our KG was confirmed.
ii. As no studies/ data were available regarding the level of RBS in the adult population of district Kohat, Pakistan for the year 2020, our KG was confirmed.

4. Research Questions (RQs): Convert your problems to questions:
i. What is the prevalence of diabetes mellitus in the adult population of district Kohat, Pakistan for the year 2020?
ii. What is the level of RBS in the adult population of district Kohat, Pakistan for the year 2020?

5. Research objectives (RQs): Now state your intents in measurable terms;
i. The objective of this study was to determine the prevalence of diabetes mellitus in the adult population of district Kohat, Pakistan for the year 2020.
ii. The objective of this study was to determine the level of RBS in adult population of district Kohat, Pakistan for the year 2020.

6. Research (null) hypotheses: Here you bring a tentative answer to your research question from the literature. From the background given above you know the prevalence of diabetes mellitus and level of RBS in the adult population from global, regional, national, and local populations/ studies, including previous studies regarding district Kohat. Now you can formulate the hypothesis.

H₀₁: The observed prevalence of diabetes mellitus in the adult population of district Kohat, Pakistan for the year 2020 is same as expected.

H₀₂: The observed level of RBS in the adult population of district Kohat, Pakistan for the year 2020 is same as expected.

7. Operational definitions: Please tell how you will label a person as having a specified disease. Give biochemical level or scoring system as applied.

8. Significance of the study: Please tell how your findings will help the concerned stakeholders to improve the health status of the population. How the patients or healthy individuals will benefit from your findings?

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 the name of the academic/ professional department and institution with city and country. It shows ownership. Add the duration of the study with day, month, and year.

2. Technical approval from the institutional research board and ethical approval from the 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 the 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 enrollment 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 manufacturing city name in parentheses.

5. Data collection plan

1. Data collection methods are 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. The questionnaire is framed from the literature. The data on research variables are 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 a 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 the respondent demographic variables. The questionnaire must not be on a nominal or an ordinal scale.
3. Questionnaire; To-do list.
a. Items (questions) are extracted from literature (existing knowledge)
b. Designed as per the list of variables, their attributes & their relationship as per theoretical framework
c. Items should be short & to the point
4. Avoid framing a questionnaire; Not-to-do list.
a. Double-Barrel items/ questions (Qs)
b. Putting words in the mouth of the 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 items/ Qs. I do not like computers. If negatives 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 the case of a 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 hypertension in employees of banks”
b. Age in years was categorized as; group 1= 40-49, group 2= 50-59, group 3= 60-69, and 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 a 5-point Likert Scale. There were so many items for each of the three KAP variables with a range of 1-5 scores (strongly disagree, disagree, neutral, agree & strongly agree, respectively) for each item.

8. Identify independent, dependent, confounding, and matching variables, where required
9. Tell the data types (nominal/ ordinal/ interval/ ratio); gender, residence, and pain in the flank were nominal data. Age groups, education level, and category of pain in the 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 analog 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 to the population from which it was drawn (inferential statistics; describe the population based on the data collected from the sample). Inferential statistics includes the estimation of parameters and hypothesis testing.
Global literature is full of research articles that are restricted to the sample, with no mention of the population. For us, it may be anything, but not research.
Our authors have to give an analysis plan for all three components of the statistical analysis. It is widely stated and widely accepted narrative that cross-sectional studies don’t require a hypothesis. It is a misunderstanding. Cross-sectional studies do require a hypothesis.
Data analysis is simply a process of converting data (unorganized facts & figures) into information (organized facts & figures). Both qualitative and quantitative data are organized as per the requirements of the topic and the 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 include text, pictures, audio, and video. This analysis is based on qualitative argumentation (not included here).

Quantitative analysis: Quantitative data include 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 to the population. It includes the estimation of parameters and testing of hypotheses.

Estimation of parameters: Here an interval in constructed around sample statistics to estimate a parameter i.e. mean or proportion for a population at a certain level of confidence, usually 95%. It is represented as a 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).

Testing of hypotheses

Tests for significance of difference: Table 1 shows tests of statistical significance of difference of means or proportions between the groups.

Table 1: Tests for statistical significance of difference of means or proportions between the groups

Data	Numeric with normal distribution			Numeric with not normal distribution			Nominal data
Groups	1	2	>2	1	2	>2	2
Test	1-sample t	Unpaired t	1-way ANOVA	1-sample signed rank	Mann-Whitney	Kruskal-Wallis	McNemar chi-square
Parametric Tests				Non-Parametric Tests

Table 2 shows tests of statistical significance of differences of means within the groups. 

Table 2: Tests for statistical significance of difference of means within the groups

Type of data	Numeric data with Normal distribution		Numeric data  with not Normal distribution
Groups	2 groups	>2 groups	2 groups	>2 groups
Type of tests	Paired samples t test	Repeated-measures ANOVA	Wilcoxon test	Friedman test
	Parametric Tests		Non Parametric Tests

 

Tests for the significance of the relationship

The relationship between two categorical variables is verified through the chi-square test of association. The relationship between two or more numeric variables is verified through correlation and regression analysis.

C. RESULTS

1. Preparing the sample for analysis; the 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 a questionnaire-based survey
4. Mention if any subject died in follow-ups?
5. How many were dropped out & why in follow-ups? Mention different causes with numbers of subjects 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 the data analysis plan.
3. Estimation of parameters: Please analyze and write here your findings as explained in the data analysis plan.
4. Testing of hypotheses: Please analyze and write here your findings as explained in the 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 the estimation of parameters (indices of the 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 the author name, city & country name, duration of the study, sample size, and relevant data for comparison.
5. Better to bring those studies which you have already cited in your introduction.
6. Other studies may have data for many more objectives/ variables. You have to bring only relevant data matching your objective/ variables.
7. Conclusion is the last part of the discussion. It is actually a summary of your results. What you observed and analyzed in your study, bring those facts here in non-statistical language as statements in simple English. Do not bring conclusions from the work of other authors.
8. Recommendations may be added as a separate heading or it may be the last paragraph of the conclusion. Here you may go beyond your own findings.