2 BVA_Call Center (B) Employing Statistical Methods

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Board of Veterans' Appeals - Veterans Information Office - Voice of the Veteran Call Center Survey

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B. COLLECTIONS OF INFORMATION EMPLOYING STATISTICAL METHODS


1. Provide a numerical estimate of the potential respondent universe and describe any sampling or other respondent selection method to be used. Data on the number of entities (e.g., households or persons) in the universe and the corresponding sample are to be provided in tabular format for the universe as a whole and for each stratum. Indicate expected response rates. If this has been conducted previously include actual response rates achieved.


The respective target population for this survey is as follows:


  • Survey of Satisfaction with the Board of Veterans’ Appeals (Board) Call Center Experience: gathers satisfaction data from Veterans (customers) who recently contacted the Board’s Veterans Information Office (VIO) Call Center.


This section describes the universe of respondents for the survey, and the sampling plan that will be employed to achieve a representative sample for each survey.


The Board’s VIO Call Center will forward a photocopy of caller data (name, phone number) manually collected during the course of routine business every third business day throughout the month for up to six days per month (with exception of holidays). A minimum of 1390 call records will be provided each month for the Board VIO Call Center in order to complete either 416 or 417 monthly interviews and ensure a representative random sample in the requisite 1250 total surveys quarterly. The Board VIO Call Center will be provided a list of days on which the sample will be collected and the number of call records for which data should be collected. A maximum of 7 attempts will be made on every number until the requisite number of surveys has been completed.


Call Center will submit all routinely collected samples to Contractor on a weekly basis. Contractor will randomly select needed records to complete minimum weekly quotas.


Table 5 displays the number of clients to be surveyed, the expected response rate, and the expected yield of completed call center satisfaction survey. The anticipated response rate is 37.037%.


TABLE 5:

CALL CENTER SATISFACTION SURVEY, EXPECTED RESPONSE RATE AND SURVEY YIELD

Number of Customers

Expected Response Rate

Completed Surveys Expected

13,502

37.037%

5,000


2. Describe the procedures for the collection of information, including: Statistical methodology for stratification and sample selection; the estimation procedure; the degree of accuracy needed for the purpose in the proposed justification; any unusual problems requiring specialized sampling procedures; and any use of periodic (less frequent than annual) data collection cycles to reduce burden.


The call center satisfaction survey will entail simple random sampling of 1390 client interactions from the Board Call Center. A 95% confidence interval for categorical variables for the survey is used. There are no unusual procedures that will be required to draw a representative sample meeting these criteria.


3. Describe methods used to maximize the response rate and to deal with issues of non-response. The accuracy and reliability of information collected must be shown to be adequate for intended uses. For collections based on sampling, a special justification must be provided for any collection that will not yield “reliable” data that can be generalized to the universe studied.


The Board will obtain the services of a Contractor to develop, administer, and analyze this survey.


Strategies to Maximize Response Rates


The Board will employ a variety of methods to minimize respondent burden and to maximize survey response rates. This section identified the strategies to be employed to reach these objectives. Each strategy is outlined below.


  • Strategy # 1 to Maximize Response Rates: Conduct Cognitive Labs/Pre-testing of Surveys


J.D. Power and Associates conducted cognitive tests of the same survey instrument used for the Veterans Benefits Administration (VBA) Call Center Satisfaction Study prior to fielding of that initial survey in 2010. The Board survey instrument is 99% the same as the VBA’s Call Center Satisfaction Study research instrument which is currently in field and associated with the Voice of the Veteran Contract No. GS-10F-0163X. Detail on the VBA tests can be found below in the response for Item 4.


  • Strategy # 2 to Maximize Response Rates: Maintaining a Toll-Free Survey Hotline


During the period that the survey is in the field, the Contractor will provide and maintain a toll-free telephone line to answer any questions respondents and regional office points of contact may have about the survey (e.g., how to interpret questions and response items, the purpose of the survey, how to get another survey if their copy has been lost/damaged). Project staff will be available to answer telephone calls during regular business hours (8:30 a.m. to 6 p.m. ET). A voice messaging system will be available to receive messages after regular business hours so after-hours calls can be responded to within 24 hours.


Strategy # 3 to Maximize Response Rates: Excluding Questions of a “Sensitive” Nature


None of the questions included in the survey are sensitive, or private in nature, which will encourage compliance.





Strategy # 4 to Maximize Response Rates: Assuring and Maintaining Confidentiality

Survey respondents will be assured that their personal anonymity will be maintained. Upon completion of the field period, the Contractor will undertake to destroy any customer information that it has in its possession, in order to ensure that all customer information is kept private to the extent of the law.


Strategy # 5 to Maximize Response Rates: Secure Networks and Systems


The Contractor will have a secure network infrastructure that will protect the integrity of the databases, the survey application, and all associated server resources. The servers must be protected by a strong firewall system and the operations center must be in a secure temperature-controlled environment with video surveillance, where network services are continually monitored by automated real-time programs to ensure the integrity and availability of all critical components. All key servers will be supported by a backup power supply that can continue to run the systems in the event of a power outage. Additionally, the Contractor must be immediately alerted if critical monitor thresholds are exceeded, so that they can proactively respond before outages occur.


Approach to Examine Non-Response Bias


Two types of non-response can affect the interpretation and generalization of survey data: item non-response and unit non-response. Item non-response occurs when one or more survey items are left blank in an otherwise completed, returned questionnaire. In most satisfaction surveys, however, missing data rates on satisfaction items need to be at or above 50% before item non-response negatively impacts the results. This is because satisfaction items (i.e., ratings of knowledge, courtesy, responsiveness, etc.) tend to be highly correlated (r >/=. 70) and therefore are collinear. Unit non-response is non-participation by an individual that was intended to be included in the survey sample and failed to respond to the survey. Unit non-response – the failure to return a questionnaire – is what generally is recognized as survey non-response bias.


Non-response bias refers to the error expected in estimating a population characteristic based on a sample of survey data that are not included or are under-represented within the resulting sample. Stated more technically, non-response bias is the difference between a survey estimate and the actual population value. Two factors determine the degree to which non-response bias will impact the accuracy and reliability of the resulting survey estimate. The first factor is the overall amount of non-response (e.g., overall response rate). Typically, response rates of 25% or better provide resulting survey estimates that are within an acceptable margin of error from which to generalize to the overall population. However, this is not always the case if the second factor is also present. That is, in cases where there are meaningful differences between those who respond and those that do not on the key outcome measures or on other measures that predict or explain the primary outcome measures, than high response rates may not adequately minimize non-response bias.


There are two approaches to tackling the effects of non-response. One is to minimize the chances of non-response at the data collection stage. This may involve introducing measures which aim to maximize the response rate. The other approach is to make statistical adjustments at a survey follow-up stage when all the data is collected. Both approaches are described in the next paragraphs of this section.


Since it is not always possible to measure the actual bias due to unit non-response, there are strategies for reducing non-response bias by maximizing response rates across all types of respondents. In the face of a long-standing trend of declining response rates in survey research (Steeh, 1981; Smith, 1995; Bradburn, 1992; De Leeuw & Heer, 2002; Curtin & Presser, 2005), these strategies include:


  • Contractor will attempt to contact respondents a maximum of 7 times over a 3-day period – varying the call time in the respondents’ time zone to increase the likelihood of completing the survey.

  • Use of an extended survey field-period to afford opportunities to respond for subgroups having a propensity to respond late (e.g., males, young, full-time employed).

  • Use of well-designed questionnaires and the promise of confidentiality.

  • Providing a contact name and telephone number for inquiries.

Employing these strategies to the administration of the survey will be crucial for maximizing high response rates across all respondent types (see Strategies 1-5).


Non-response follow-up analyses can help identify potential sources of bias and can help reassure data users, as well as the agency collecting and releasing the data, of the quality of the data collected. The approach to examining the presence of non-response bias will be conducted as follows:


  • Compare the Demographics of Respondents from the BVA Call Center Satisfaction Survey to the Demographics of Non-Respondents from the BVA Call Center Satisfaction Survey. To examine the presence of non-response bias, VA will compare the demographics of responders (i.e. those who responded to the BVA Call Center Satisfaction Survey) to the non-responders (i.e. those who did not respond to the BVA Call Center Satisfaction Survey).

  • The comparison between responders and non-responders will be made on the following variables for this survey:

    • Region – it is possible that participants from a certain part of the country (i.e., region) may respond to the survey at a higher rate than those who are from another part of the country. Contractor will analyze regions based on converting telephone numbers to zip codes and using those to map regional analysis. In the case of cell phones, (which can be identified by Contractor), respondents will be asked their zip code as part of the survey.

    • Gender – it is possible that participants from a certain gender (i.e., male) may respond at a higher rate than their counterpart. Gender will be recorded in the survey by interviewer. Respondents will only be asked to clarify their gender if interviewer cannot determine.

    • Degree and depth of interaction with Call Center – it is possible that respondents and non-respondents may differ with respect to the degree and depth of their interaction with BVA Call Center.


Based on the steps discussed above, the Board will identify issues with respect to non-response bias for the survey.


4. Describe any tests of procedures or methods to be undertaken. Testing is encouraged as an effective means of refining collections to minimize burden and improve utility. Tests must be approved if they call for answers to identical questions of 10 or more individuals.


Prior to fielding the VBA Call Center Customer Satisfaction Study, the Contractor together with the VBA conducted cognitive labs with three or more test users for the survey, to determine whether respondents understand the survey questions and answer choices, as intended. The Contractor worked closely with VBA, and Cognitive lab participants were drawn from the same population that were used for the main study. Cognitive lab sessions took place in the metropolitan Washington, DC, area in 2010.


Once the participants were selected, VA conducted cognitive lab sessions aimed at identifying needed additions or refinements to the questionnaire. Cognitive labs are one-on-one sessions with potential survey participants, in which respondents are asked to complete the questionnaire while thinking aloud. The primary purpose of these sessions was to gather feedback on survey questions and answer choices to ensure they are easily understood and correctly interpreted. Outcomes of cognitive labs include, but are not limited to: addition or omission of specific questions, changes to wording of questions, clarification of question response options, addition of response options, and changes to ordering of questions. Given that the VBA questionnaire has been in field since 2010, further Cognitive Lab testing will not be needed.


5. Provide the name and telephone number of individuals consulted on statistical aspects of the design and the name of the agency unit, contractor(s), grantee(s), or other person(s) who will actually collect and/or analyze the information for the agency.


For this survey, the Board contracted the services of J.D. Power and Associates to administer the survey. The following is a list of the persons involved in the survey.


  • Mrs. Gina Pingitore, PhD, J.D. Power and Associates, 805-418-8043

  • Mr. Greg Truex, MPP, J.D. Power and Associates, 202-383-3511

  • Ms. Tara Wutke, J.D. Power and Associates, 202-383-3707

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