Reviewer ’s report  
 
Title: Factors influencing use of long -acting versus short -acting contraceptive methods among 
reproductive -age women in a resource -limited setting  
 
Version: 0 Date: 05 May 2016  
 
Reviewer: Brianna Magnusson  
 
Reviewer's report:  
 
Manuscript Review: Factors influencing use of long -term versus short -term modern 
contraceptive methods among reproductive -age women in a resource limited setting  
Overall: The manuscript is generally well written and the information regarding  women in this 
settings reasons for choosing their method of contraception has potential to influence further 
research and clinical practice.  The manuscript could benefit from some revisions as outlined 
below:  
 
Abstract:  
In the abstract and other places the word "commonest" is used.  This should be changed 
throughout to "most common"  
 
Introduction:  
A stronger start to the introduction would go a long way to strengthening the article. You may 
consider framing the problem first, some ideas:  
 Uganda has a high birth rate  
 Contraceptive use and access are low  
 Short term methods are used more commonly than long -term methods  
 Benefits of longer -term methods to women in this setting  
All of these are included in the introduction, but re -orderi ng them could strengthen the 
introduction.  
Page 4; Line 7 -12 - Not necessary to define the difference between short and long -term methods 
for this audience.  
Page 4; Line 19 - This sentence reads: "In these settings, long -term methods are more 
independe nt of user characteristics…" I believe this should be the effectiveness of long term 
methods is independent of user characteristics.  
Page 5: Line 9 - should be the prevalence of long and short -term contraceptive use  
 
Method:  
In the Study Design & Setting section it would be useful to have an overall statement explaining 
that the "mixed -methods" included individual interviews, focus groups and practitioner 
interviews.  
 
Study Population:  
 Do you have information about a response rate?   
 Is it likely tha t women who seek care outside the 8am to 2pm hours are different than women 
seeking care within those hours?  If so, please explain how this might have affected your 
sample.  
 
Measures:  
It would be useful to have more information on the types of questions asked.  The authors have 
given several sample questions, but some general information regarding the questionnaire would 
be useful.  For example:  
 How many total questions were asked?  
 What is the average length of the questionnaire?  
 How many questions were open or close -ended?  
It is stated that the survey was designed to assess knowledge, attitudes and practices of 
contraceptive use.  Please elaborate on each of these.  Specifically, contraceptive knowledge was 
assess by asking x number of close -ended questions…etc.  There is a good example of this in the 
manuscript on page 6; line 32. Under knowledge I would be specifically interested in 
understanding the questions related to "how do you think this method works?"  
For the attitudes questions page 6; li ne 25 it is stated that participants were asked if the agreed or 
disagreed?  What's this a Likert scaled or just the 2 response options?  
 
Data Analysis:  
Page 7; line 24 - Rather than stating "we summarized numeric and categorical characteristics as 
appropriate" please state how you summarized.  Based on your table I assume you used 
frequencies and percentages.  It's easier and clearer to simply state that.   
The authors used logistic regression analysis to predict the odds of long -term use.  As you note 
there were no significant findings in the adjusted regression models.  Given the small sample size 
and the low prevalence of long -term method use logistic r egression doesn't seem to add anything 
to the analysis.  Perhaps bi -variate comparisons are sufficient.  
Page 7; line 46 - States that missing data were obtained from client files.  I'm assuming this is 
related to demographic factors, please clarify what type of data was available in the health 
record.  
Please discuss how the logistic regression model was built. Is it just everything except 
education?  
 
Results:  
Throughout the results section there are several numbers that do not match was is displayed in  
the tables.  Please carefully check this section to ensure data presented in text, matches that 
present in the tables. Example page 8; line 42 states 42% still desired children. Table 1 would 
indicate that this should be about 67%.  
It would be useful to group the results section by table a little more strictly.  For example page 8; 
line 42 -47 the lines beginning "Up to 46%..." This data is not in table 1.  Yet what appears before 
and after in the text are found in Table 1.   
On the same sentence, it is n ot clear to me, what "up to 46%" means. Up to would indicate there 
was a range of estimates, but that doesn't seem to be the case.  
In several places there is reference to "Depot" injectables.  I was under the impression Depot 
Provera was a brand name.  I  believe it would be acceptable to simply refer to these as 
injectables.  
Page 8; line 52 - "All respondents know about at least one method."  Isn't this a given since all 
women had to be current or prior users?  What is meant by "know about".  Is this si mple 
awareness that the method exists or understanding of how it works?  
 Page 9; line 40 - The interpretation of the logistic regression results is inconsistent with your 
model.. If your model is predicting the odds of long -term use you should be talking about the 
odds of increased use of long -term methods.   
 
Tables/Other Notes  
Table 1 is generally too long.  As I read the author instructions there is no table limit, so I would 
suggest breaking table 1 into smaller more cohesive tables.  Demographic chara cteristics in 1 
table, contraceptive characteristics in another etc.  Further, the data here is not particularly 
complex, just frequencies and percentages, so variables that do not fit cohesively together to 
make a table can be presented in the text alone.   
The authors found the likely differences between urban and rural settings important enough to 
stratify the sampling.  Is there value/sufficient sample to present bivariate results stratified by 
urban vs. rural?  Since the logistic regression doesn't rea lly hold up given the sample size, 
perhaps bivariate results comparing knowledge, attitudes, demographics in urban vs. rural could 
be informative?  
In all tables, be careful of possible disclosure risks.  In table 1 you have 3 places where the n is 
<5.  I would recommend suppressing this data.  
Dividing up the tables will help with this, but be very clear about the denominators in your 
percentages.  For Current method among current users a footnote provides the modified n (101), 
but that sample denominator should be noted for the next two variabl es.   
For the question "What type of method is more effective?" in table 1. It appears the results only 
represent 82% of the sample…where is everyone else?  
Table formatting: Is there a reason for rounding all percentages to whole numbers?  Typically at 
least one decimal places is provided.  
It is not necessary to provide in the tables data that are part of your selection criteria.  For 
example ever use of contraceptives was a requirement for selection, reporting this as 100% 
doesn't add anything to the p aper.  
I was surprised to note that 35% of the sample reported that OCs were the least effective method 
(Table 1). Is this consistent with other studies in the region?  Can you provide some context for 
this?  This might be an important discussion point.  
 
Table 2: Given the percentages, I am assuming that women could choose several reasons for 
"Reasons for choosing long -term methods?"   It would be helpful to make this clear in the 
methods and in the tables.  Tables should be independent of the text.  
Table 2: Please provide n's in the column headers.  
Table 3: It is not necessary to provide both CI's and p -values.  Both are measures of random error 
and provide the same information.  Please remove the p -values.  
As mentioned earlier, since the sample size  does not allow the adjusted model to be estimated 
with precision, this should probably be eliminated.  I do wonder if the analysis becomes stronger 
by looking at bi -variate results only and perhaps comparing these in urban vs. rural or long -term 
vs. short  term users as opposed to trying to use a logistic regression model.  
 
Discussion Comments:  
In the qualitative results there were findings related to a desire to hide a method from a partner.  
This finding surprised me, given that in the quantitiative resu lts it is reported that 90% of 
partners were supportive of family planning.  I think this brings up a couple of points that should 
be discussed in the discussion section.  
1- How common is partner support of contraceptive methods in Uganda?  Does this vary  by 
education level or rural vs. urban etc.?   
2- Given the apparent need to hide methods are LTCs really beneficial in this setting?  Is 
pushing for LTCs really the right answer to unwanted pregnancy in this setting?  An implant 
is visible, IUDs may have  strings that can be felt by a partner.   
I think the 2nd question holds given some other factors that women report such as a desire to 
control the method herself and to be able to stop when she wants to.  I do believe that some of 
these things can be mit igated with education and that is an important discussion point.  If we can 
educate and reduce myths or relieve concerns than more women may choose to use LTCs.  
However, I also think we need to leave space in this discussion for the idea that LTCs may not  be 
the right choice for all women.  As providers our bias may be for LTCs, but women should be at 
liberty to choose contraceptive methods that are appropriate for her preferences and choices.   
 
Final Comments:  
Overall I think you have an interesting pape r that could benefit from some revision.  With some 
revision and perhaps a reconsideration of the analytic approach I do think this paper would add 
to the literature.   
 
 
Are the methods appropriate and well described?  
If not, please specify what is required in your comments to the authors.  
 
Yes 
 
Does the work include the necessary controls?  
If not, please specify which controls are required in your comments to the authors.  
 
Yes 
 
Are the conclusions drawn adequately supported by the data shown?  
If not, please explain in your comments to the authors.  
 
Yes 
 
Are you able to assess any statistics in the manuscript or would you recommend an  
additional statistical review?  
If an additional statistical review is recommended, please specify what aspects require further  
assessment in your comments to the editors.  
 
I am able to assess the statistics  
 
Quality of written English  
Please indicate the quality of language in the manuscript:  
 
Acceptable  
 
Declaration of competing interests  
Please complete a declaration of competing i nterests, considering the following questions:  
 
1. Have you in the past five years received reimbursements, fees, funding, or salary from an  
organisation that may in any way gain or lose financially from the publication of this  
manuscript, either now or in the future?  
 
2. Do you hold any stocks or shares in an organisation that may in any way gain or lose  
financially from the publication of this manuscript, either now or in the future?  
 
3. Do you hold or are you currently applying for any patents relating to t he content of the  
manuscript?  
 
4. Have you received reimbursements, fees, funding, or salary from an organization that 
holds  or has applied for patents relating to the content of the manuscript?  
 
5. Do you have any other financial competing interests?  
 
6. Do you have any non -financial competing interests in relation to this paper?  
 
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