Appendix 1. Sampling Procedure.

Discussion In general, the goal of the sampling procedure was to select women for inclusion such that it would provide a representative cross-section of the target population within the Marz (region). Methodological concerns include selection criteria that might result in a biased selection of women such that their use/knowledge of family planning methods is different (higher or lower) than the target population or selects them from specific socio- demographic groups. Logistical considerations include the efficient use of limited personnel resources; limited time for implementation, and the availability of the required information/resources to carry out the process. Thus the two primary factors driving the decision for an acceptable sampling strategy are the methodological rigor and the feasibility/cost of implementation.

The methods used must assure sufficient sample size for detecting urban/rural differences, and differences among regions receiving the supplemental campaigns from those receiving only the national campaign. Sufficient numbers were sampled so as to allow for those declining to participate in the study, those selected but disqualified, and those lost to follow-up over the duration of the study.

In terms of sampling strategy, three basic approaches were considered: multi-stage cluster sampling (probability proportional to size/PPS), random digit dialing, and random household selection. After an assessment of the extant data underlying each of the approaches and reviewing methods used for similar rigorous studies in the country immediately prior to this project, cluster sampling was selected.

Cluster Sampling Cluster sampling is an efficient use of resources of particular utility when viable sampling frames for simple random sampling (SRS) are not available. Such is the case in where the population has undergone tremendous transition in recent years, including large-scale migration/emigration, further complicated by the renaming of

Appendix 1 streets and addresses at the time of independence, and the destruction of several towns and villages due to an earthquake in 1988.

Two extant data sources, both presumed to be equitably distributed throughout the population in question and thus suitable for use in selecting clusters, are medical rosters and administrative rosters. With the collapse of the Soviet Union and consequently the Armenian economy, the medical system remains largely in disarray. While adults may forgo medical treatment, the pediatric component of the medical system remains the most viable. Its rosters of children have been used as the basis for cluster sampling in the past with good success.

The administrative district roster, in theory, offers an advantage that it is geographically based. Each district headquarters has a record of each address (household) within the administrative district. This could provide a non-biased and non-medically influenced selection of households. The reality is, however, that these records are poorly maintained, are incomplete, and have not been updated to reflect the changes in street/village names or the destruction of some towns/ villages. This introduces unknown and potentially systematic biases in selection, which cannot be adjusted for. Therefore, this promising approach is not as desirable as the clinic rosters.

In opting to use the pediatric clinic rosters, the potential bias toward the selection of households forgoing family planning must be addressed. The very fact that the household has a child may imply a set of family planning practices different from the general population. Thus, selecting a household for inclusion in every cluster on this basis would bias the sample with respect to a key outcome of interest - family planning practices. To assure that the cluster selection criteria do not preferentially select for or against users of family planning methods, the cluster starting point was offset an Nth unit away from the address randomly selected from the children’s roster. The methodology still permitted the referent household to be included in the sample through the procedures for completing the cluster without introducing a bias or counter-bias with respect to the presence of young children in the home.

Appendix 1

In addition, the typical cluster sampling procedure of selecting adjacent households was further modified to assure that proximal households were not included as the literature clearly shows that neighbors can influence each other's use of health care and this may include family planning choices. The process used reflects a cluster sampling methodology that attempts to more closely mimic a simple random sample design by increasing the catchment area of the cluster. This approach presumably increasing the within-cluster heterogeneity and preserves the power of the sample size. Random Digit Dialing. Random Digit Dialing (RDD) has been used in with limited success. The poor condition of the phone system (such that it can be difficult to call/connect to certain parts/districts of the city where the phone system is extremely poor) as well as the socio- economic bias introduced by selecting for the presence of a phone introduce significant biases of concern for this study. Furthermore, this strategy is not feasible for the outlying regions where access to phone service is even more limited. It would not be prudent to mix sampling methodologies between Yerevan and the regions without some understanding of the differing biases that might be introduced. Additionally, RDD selection for a survey that requires a face-to-face interview would add a significant unnecessary administrative burden.

Random Selection While the gold standard for selection, simple random selection (SRS) is virtually impossible in Armenia, as no viable, unbiased, complete sampling frames currently exist. Attempts at approaching this ideal would be extremely costly and time consuming with little appreciable gain in analytic power over the PPS cluster sampling.

Sample size The use of PPS sampling in this case is based on several assumptions. 1. Patterns of emigration are uniform across Armenia. 2. A cluster size of 6 coupled with skipping adjacent households effectively minimizes heterogeneity bias.

Appendix 1 3. The population is uniformly distributed across geographic areas with respect to key socio-demographic variables. Extant data and prior research indicate that these assumptions are reasonable for Armenia at this time.

The sample size of 1212 is comparable to similar studies and supported by simple sample size calculations (5), which indicate a minimum of 200 observations for each comparison unit [n= 2z2pq/d2 where z = 1.96, p=0.4 (based on prior research and erring toward a more conservative sample size estimate), q = 0.6, and d = 0.1 (minimal practically significant difference to detect)]. The methods used assured sufficient sample size for detecting urban/rural differences, and differences among regions receiving the supplemental campaigns from those receiving only the national campaign. Sufficient numbers were sampled so as to allow for those declining to participate in the study, those selected but disqualified, and those lost to follow-up over the duration of the study.

Sampling Procedures Preparatory Phase For this study, the cluster size was set at 6. This is a reasonably small cluster size (minimizes homogeneity bias) and represents the total number of interviews expected from one interviewer per full day.

1. For each region (city in the case of Yerevan), a list of all pediatric polyclinics (or equivalent) was compiled. The population served by each Polyclinic was tabulated in an ordered manner. A random starting point was selected and then cluster starting points systematically drawn from the ordered list (presented later in this Appendix). The number of clusters to be drawn form each policlinic was influenced by the size of the population served by the clinic. Thus, some polyclinics had more cluster starting points than others. Similarly, starting points near the geographic boundary of a polyclinic catchment area, could lead to a cluster drawn from households residing in several polyclinic catchment areas.

Appendix 1 2. When visiting the polyclinic for its records, those clinics selected more than once had that many of its districts randomly sampled. As districts (physician/nurse team) usually serve similar sized populations, the listing of districts were randomly selected in lieu of the more intensive process of weighted sampling described for the selection of polyclinics.

3. For each selected district, a random address was selected from the roster using a random number generator and the number of addresses in the roster. For purposes of this study, the roster of registered births for 1997 was used.

4. A list of the 84 cluster starting points was produced for Yerevan. A similar process was used to sample from the intervention regions (Lori & Vayots Dzor). Here, the organization was slightly different, with 2-6 shrjans (districts) in each region. Identification of the cities/regional centers/villages to be selected within each of these marzes was performed as the first level of selection. After that, the number of the clusters that should be taken from each city/regional center/village within the shrjan, based on the population, was enumerated. Smaller towns and villages did not have a polyclinic, but a smaller, comparable unit such as an ambulatory clinic or a FAP (see Table 1 in this Appendix).

5. A database of the starting addresses was created to facilitate administration of the survey.

Implementation Phase The interviewer proceeded to the cluster start address and then counted off the offset (5 houses/units to the right/up). The interviewers were working individually and were completing 6 surveys within the cluster following the protocol below.

1. If there was at least one eligible, willing respondent at the address, the interviewers completed the survey.

Appendix 1 2. Once a survey was completed or if the household yielded no respondents, the next household was selected as follows:

Direction of movement: Direction of movement for the cluster was decided by a coin toss (heads = right/up, tails = left/down). Magnitude of Movement: Last household resulted in: · Completed survey: skip 5 doors · Non-respondent/unwilling respondent: next household in the direction chosen by a coin toss. 3. Repeat the previous steps until a total of six households were surveyed in the cluster

Notes 1) If there were more than one eligible woman in the household, the interviewers had to make a random choice with help of the selection of the respondent table (see below) 2) In the absence of other eligible respondents in the household, incomplete interviews were considered equivalent to non-respondents and the next household was attempted. 2) In the absence of other eligible respondents in the household, for those interviews where it became clear during the interview that the respondent was incorrectly ruled as eligible and should have been excluded, the household was considered a non-respondent and the next household attempted. 3) If other eligible respondents were in the household of situations 1 or 2 above, selection from among the remaining respondents was attempted (as described in selection criteria) before declaring the household a non- respondent.

This technique of selection was slightly modified for rural villages where only 1 cluster was taken. In such cases because of organizational factors and in order to make the

Appendix 1 selection process well organized and less time-consuming, the interviewers worked in teams of two, each of them conducting three interviews in the cluster. For these cases the interviewers each moved in opposite directions from the referent address.

Appendix 1 Selection of Respondent

1. How many women between the ages of 18 and 35 live in this flat/house? __ __ females

2. For each of these women could you give me the following information:

LIST FROM OLDEST TO YOUNGEST

Line First name Age Marital status

1 ______

2 ______

3 ______

4 ______

5 ______

6 ______

Codes:

1 Married - Registered 2 Married - Unregistered 3 Married (Registered or unregistered) but living apart for more than 30 days 4 Divorced 5 Widowed 6 Single (Never married)

SELECTION OF INDIVIDUAL RESPONDENT: (Exclude women who are in Marital status categories 3-6)

LAST DIGIT OF THE VISIT NUMBER IN THE CLUSTER

Eligible Respondents 0 1 2 3 4 5 6 7 8 9

2 1 2 1 2 1 2 1 2 1 2

3 3 1 2 3 1 2 3 1 2 3

4 3 4 1 2 3 4 1 2 3 4

5 1 2 3 4 5 1 2 3 4 5

6 6 1 2 3 4 5 6 1 2 3

Appendix 1 2.4 Human Subjects: All participants were provided with and had explained to them a notice approved by the Human Subject Review committees of both the AUA and JHU outlining the purpose of the study, the uses of the data, and their right to choose not to participate. This notice was accompanied by endorsement letters/letters of introduction from the Ministry of Health and the AUA. As identifying information was needed in order to link pre and post intervention data, an explanation of the safeguards used to protect identities was included. The verbal consent form in English as approved by the relevant committees appears below.

VERBAL CONSENT FORM

Evaluation of IEC Impact under the Family Health Campaign Project, Armenia, 2000

Good Morning/afternoon/evening. My name is . Thank you for taking the time to talk with me. The American University of Armenia is conducting this study on behalf of the Ministry of Health. This study will address the knowledge of, attitudes about, and practices of family planning. Your responses will help support new programs for women’s health, so please be as truthful and complete as possible. This is not an exam or a test. The interview will last about 30 to 45 minutes.

In about six months, you may be visited again to talk about these issues and to see how you feel then. Any information you provide will remain anonymous. Your participation in this study is voluntary. Nothing will happen to you if you do not participate in the survey. You can stop whenever you want. Your responses will remain confidential and will not be available to anyone other than University’s research team.

You will be given a card with contact information for the research team. If you have any questions or problems please feel free to contact the office.

May I continue?

Appendix 1

Tables 1. Cluster sampling for Yerevan Yerevan Children Policlynics #chld (0-14) # of clusters "Manuk" CP 10964 3 Emerg.3 CP 21230 6 4th CP 11568 3 "Arabkir" CP 21838 6 1th CP 10760 3 2th CP 23944 6 3th CP 16123 5 4th CP 28823 7 5th CP 28806 8 6th CP 17590 5 7th CP 11220 3 8th CP 22980 6 9th CP 17061 5 5th pol.'s CD 4086 1 8th pol.'s CD 11910 3 17th pol.'s CD 10026 3 18th pol.'s CD 8845 2 20th pol.'s CD 11674 3 21th pol.'s CD 2950 1 22th pol.'s CD 10110 3 23th pol.'s CD 2794 1 Sari Taghi CP 5073 1 Total 310375 84

Appendix 1 2. Cluster sampling for regions

Lory/Vayots Dzor

Marz/areas #of clusters #of policlinics/HC LORI Vanadsor 32 5 1 1 1 1 Debet 1 1 1 1 Shahumian 1 1 / Spitak 4 1 Arevashogh 1 1 Lernatsk 1 1 1 1 1 1 Jrashen 1 1 Saramej 1 1 /Tashir 2 1 Artsni 1 1 1 1 1 1 Norashen 1 1 1 1 TUMANYAN/ Alaverdi 4 1 1 1 1 1 Akor 1 1 Katchatchakut 1 1 Pokr Airum 1 1 1 1 1 1 7 1 Vayots Dzor / Yeghegnadzor 2 1 1 1 Getap 1 1 1 1 1 1 Chiva 1 1 / 2 1 Vayk 2 1 1 1

Appendix 1 Sampling in # of Vanadsor CP-s Total # of children clusters

#1 Pol.'s CD 5470 5 #2 Pol.'s CD 6597 7 #3 CP 9166 8 #4 CP 5420 5 #5 Pol.'s CD 6339 7 Total 32992 32

Armavir # of clusters Armavir 5 Metzamor 1 Aygeshat 1 Armavir 1 Getashen 1 Lenukhi 1 Hatsik 1 1 Nalbandian 1 1 1 Ejmiatsin 7 1 Aragats 1 Artimed 1 Griboedov 1 Tsaqghkalanj 1 1 1 Jrarat 1 1 Bagaran 1 1 Qarakert 1 Total 34

Appendix 1