506 INTERNATIONAL JOURNAL OF PUBLIC OPINION RESEARCH

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1 International Journal of Public Opinion Research Vol. 19 No. 4 ß The Author Published by Oxford University Press on behalf of The World Association for Public Opinion Research. All rights reserved. doi: /ijpor/edm023 Advance Access publication 12 October 2007 TELEPHONE NUMBER PORTABILITY AND THE PREVALENCE OF CELL PHONE NUMBERS IN RANDOM DIGIT-DIALED TELEPHONE SURVEY SAMPLES Michael W. Link, Machell Town, and Ali H. Mokdad Telephone number portability is a feature of circuit switch telecommunication networks that allows people to port (i.e., permanently move or transfer) a telephone number from a landline to a wireless service, between two wireless services or, less frequently, from a wireless to a landline service. It was introduced in the United States as a means of improving competition among telecommunications companies and offering customers greater flexibility in telecommunications services (FCC, 2006). The problem for survey research is that telephone numbers thought to be landline numbers within a particular geographic area are sometimes later found to be associated with cell phones, which is problematic for more traditional random digitdialed (RDD) telephone surveys that tend to exclude cell phone numbers. Number portability is occurring globally, with regulations varying across countries. Singapore was the first to introduce number portability in Number portability is also provided in the European Union, as well as in countries such as Australia, Brazil, South Korea, Argentina, Colombia, and Taiwan. Canada, India, Japan, and several other countries have plans in place to offer number portability in the near future (Rembert, 2006). Since November 2003 in the United States, people in the 100 largest metropolitan statistical areas were able to port their numbers (FCC, 2006). Since May 2004, this service has been available nationwide. U.S. companies are required to offer number portability within the same geographic area. These companies, however, are not specifically prohibited from porting numbers across geographic areas, and many do. For survey researchers, telephone number portability erodes the efficiency and precision of the sampling frame for RDD landline telephone surveys when the ported number is used in a different geographic area. RDD sampling is built upon the premise that, in the absence of a complete registry of residential numbers as is available in some countries, the exchanges and area codes used in generating random samples of telephone numbers identify landline telephone numbers within defined geographic areas. Most RDD telephone surveys currently conducted in the USA exclude known cell phone numbers from their sampling frames because of cost, operational and, in some cases, ethical considerations. When landline numbers are ported to cell phones, the efficiency of the RDD landline sample frame decreases as additional calls are required to identify and remove these numbers from the sample. This leads to increased costs for data collection. Although a centralized database of ported numbers, maintained by the local number portability administrator NeuStar, can be used to pre-screen many of these numbers, the system is not fail-proof. For example, a delay may occur between when a number is transferred and when

2 RESEARCH NOTES 505 it appears in the database. Likewise, an unknown percentage of ported numbers may go unreported, particularly among smaller, more rural independent local exchange carriers. We provide one of the first empirical assessments of the potential problem of number portability for RDD landline surveys, using one of the world s largest ongoing RDD surveys, the Behavioral Risk Factor Surveillance System (BRFSS). With more than two million telephone numbers processed annually, the BRFSS allows us to (1) assess the degree to which cell phones are showing up in RDD landline samples and the percentage of ported numbers that can be identified through prescreening with the NeuStar database and during the interview process, (2) determine state and regional variations regarding number porting, and (3) explore other attributes associated with this activity. METHODS As one of the largest, ongoing RDD telephone surveys, the BRFSS collects information monthly on preventive health practices and risk behaviors that are linked to chronic diseases, injuries, and preventable infectious diseases in the adult population (Mokdad, Stroup, & Giles, 2003). More than 350,000 adults are interviewed annually in the 50 U.S. states, as well as the District of Columbia, Puerto Rico, and the Virgin Islands. Interviews are conducted by the individual state health departments with assistance from the Centers for Disease Control and Prevention. In 2005, 2,382,101 telephone numbers were drawn as part of the ongoing surveys in the states and District of Columbia (Puerto Rico and the Virgin Islands were excluded from this analysis). Cell phones within these state-based samples were identified using three methods. First, numbers were screened by the sample provider, Marketing Systems Group, using the NeuStar database. These numbers were flagged as cell phones and not called. Second, if a sample member volunteered at any point during the survey introduction that he or she was on a cell phone, the interviewer terminated the call by saying, Thank you very much, but we are only interviewing landline telephone users and those in private residences. The call was then given a final disposition code of ineligible cell phone. Third, sample members were asked as part of the introduction if they had been reached on a cell phone: Is this a cellular telephone? If the respondent answered yes, then the call was terminated and given a final disposition code. The cell phone question came after the interviewer had confirmed that the correct number had been dialed and that it was associated with a residence. Using this information, we were able to classify each cell phone number as such during the prescreening process, during the questionnaire introduction, or at the cell phone screening question. To better understand the types of numbers that are likely to be cell phones and the geographic distribution of these numbers, we used four pieces of information from the sample files. First, numbers were categorized as being listed or unlisted on published telephone directories. Second, numbers were categorized by exchange type as defined by Telcordia, which maintains a database of telephone number assignments for every telephone switch and central office in the North American telephone

3 506 INTERNATIONAL JOURNAL OF PUBLIC OPINION RESEARCH network. Numbers may be in banks designated for analog service lines only (sometimes referred to as plain old telephone service or POTS lines), or they may be in mixed-use banks, which can contain numbers associated with POTS lines or cellular, mobile, or paging services. Telephone numbers for the BRFSS were drawn from five different types of telephone banks: (1) regular or POTS-only lines, (2) POTS lines and cellular service, (3) POTS lines and paging service, (4) POTS lines and mobile service, and (5) three or more services, which could include POTS lines or cellular, mobile, or paging services. Third, to examine geographic dispersion of ported phone numbers, we combined data across states using the four regions specified by the U.S. Census: Northeast, Midwest, South, and West. Fourth, we used the Metropolitan Status Area (MSA) code assigned to each telephone number: (1) in the center city of an MSA, (2) outside of the center city of an MSA, but inside the county containing the center city, (3) inside a suburban county of the MSA, (4) inan MSA that has no center city, and (5) not in an MSA. SPSS Version 13 with Complex Samples module was used in the analyses to account for the complex sampling design and calculate the standard errors and 95 percent confidence intervals (SPSS Inc., 2004). FINDINGS The national average percentage of cell phones was 0.6 percent. The percentage varied considerably across states, from a low of 0.2 percent in Alabama and Michigan to a high of 2.8 percent in Kansas. The overall percentage of cell phones was 1 percent or higher in six additional states: Connecticut (1.0 percent), Nebraska (1.0 percent), Massachusetts (1.0 percent), Missouri (1.2 percent), Kentucky (1.5 percent), and Georgia (1.9 percent). Most cell phones tended to be identified at the point of the explicit cell phone question in the introduction (0.3 percent), followed by the prescreening against the NeuStar database (0.2 percent), and then through information volunteered by respondents (0.1 percent). The percentages across all three categories were all highest in Kansas: prescreening (0.8 percent), volunteered during question introduction (0.9 percent tied with Kentucky), and during the cell phone question (1.1 percent). The percentage of cell phones in the RDD samples also varied by region and type of area in which the numbers were assigned (Table 1). The prevalence of cell phone numbers was highest in the Midwest (0.9 percent) and lowest in the West (0.5 percent). The percentage of cell phones was relatively consistent across more urban and suburban areas (i.e., where the exchange was located in whole or in part in a metropolitan statistical area), but the percentage was higher (0.9 percent) in more rural areas (i.e., those areas where the telephone number was not located in a metropolitan statistical area). Cell phones were more prevalent among directory-listed telephone numbers (0.8 percent) than among numbers that were not listed (0.5 percent), with the difference between the two groups being attributed to the higher percentage of cell numbers identified by the cell phone question (0.5 vs. 0.2 percent; Table 2). Not surprisingly, cell phones were most prevalent (3.7 percent) among mixed-use exchanges, in which numbers can be assigned to either POTS lines or cell phones.

4 TABLE 1 Percentage of telephone numbers determined to be cell phone numbers, by census regions and metropolitan statistical area type n Total Point at which number was identified as a cell phone number Prescreening Questionnaire introduction Cell phone screening question Census regions Northeast 619, Midwest 426, South 778, West 615, Metropolitan statistical area (MSA) City center 864, Outside city, 484, in county Suburban 317, MSA with 34, no center Not in MSA 678, Source: Behavioral Risk Factor Surveillance System, RESEARCH NOTES 507 These types of exchanges were followed by banks where numbers could be assigned to three or more different services (2.8 percent), regular or POTS lines (0.6 percent), banks serving a combination of POTS and paging services (0.5 percent), and POTS and mobile services (0.5 percent). Looking at the prevalence of cell phones in the RDD samples across time, we find no evidence of trending over the course of the year (Table 2). Overall rates varied between 0.5 percent and 0.7 percent across the four quarters (roughly, winter, spring, summer, and fall). Finally, in order to evaluate the potential data collection costs incurred by having ported cell phone numbers in RDD landline samples, we looked at the mean number of call attempts made to numbers identified as cell phones either through the respondent volunteering the information or responding yes to the cell phone question. Cases prescreened through the NeuStar database were excluded from this analysis. On average, 4.1 calls were required to identify cases thought to be landline numbers but in which surveyors were reaching cell phone numbers. This was just under half of the 8.6 calls required, on average, to finalize all other cases not identified as cell phones and closer to the 5.3 calls required to screen out all other ineligible numbers. DISCUSSION Telephone number portability is one of a number of telecommunications issues, along with increased use of cell phones and Voice over Internet Protocol (VoIP,

5 508 INTERNATIONAL JOURNAL OF PUBLIC OPINION RESEARCH TABLE 2 Percentage of telephone numbers determined to be cell phone numbers, by type of phone number and yearly quarter when number was sampled n Total Point at which number was identified as a cell phone number Prescreening Questionnaire introduction Cell phone screening question Directory listing status Listed 927, Unlisted 1,454, Telcordia technologies exchange type: Regular 2,332, POTS and paging 20, POTS and cellular 15, þ services 10, POTS and mobile Quarter of year number was sampled January March 667, April June 714, July September 665, October December 393, Source: Behavioral Risk Factor Surveillance System, sometimes referred to as digital telephones), facing traditional RDD telephone surveys. RDD approaches in the U.S that have tended to focus on landline numbers exclusively have yet to adapt in any standardized way to keep up with these changes. Most RDD study protocols currently disallow survey calls to cell phones for operational, burden, or ethical reasons. Those that do allow such calls face the challenge of determining how to incorporate the cell phone-based respondents into the survey estimates since not all cell phone users (particularly those who are cell only ) are included in the survey and population data on cell phone use for postsurvey adjustments are currently exceedingly limited and often only national in scope (for example, see Blumberg, Luke, & Cynamon, 2006). There are no published studies on how VoIP phones, particularly those not based on standard telephone numbering systems, should be treated in RDD surveys. Portability of landline numbers has added yet another wrinkle to this mix. Because a person can now port his or her telephone number from a landline to a cell phone, the efficiency of RDD samples in identifying landline household phones and the geographic specificity of the numbers is slowly eroding. The findings from the 2005 BRFSS indicate that in the United States, the problem of ported numbers in RDD samples is minimal and did not appear to be growing during These numbers are most prevalent in only a few geographic areas and in mixed-use exchanges serving POTS and cellular numbers.

6 RESEARCH NOTES 509 These findings need to be viewed in the context of other trends in telecommunications, particularly the growth of cell phone-only households. For the first six months of 2006, approximately 10.5 percent of households in the USA were reported to be cell phone-only (Blumberg & Luke, 2007). Given the relatively low percentage of telephone numbers being ported from landlines to cell phones, it is probable that many of these cell phone-only household members are choosing to either obtain new cell service with a new telephone number or simply keep their previous cell phone number and dropping their landline number. Given the increasing concerns in the USA about telemarketers, identity theft, and privacy, choosing not to port a landline number (and its associated calls) to a cell phone would have the effect of allowing an individual to start fresh with their cell number. That is, the number would likely not be as readily available in commercial databases or published directories in the same way as most landline phones, thereby reducing the number of unwanted calls (at least until the new cell number was more widely used and distributed by the respondent). This supposition is buttressed by the finding that a higher percentage of ported numbers are directory listed. This would support the notion that those who want to stay connected are probably more likely to port their existing number to a cell phone than to obtain a new number. Why did the NeuStar database apparently fail to capture a majority of the numbers reported to be cell phones? There are two likely explanations. First, there may be delays or discrepancies in reporting these numbers by the local telecommunication carriers who are distributing the numbers. Second, the question used to determine if the number reached was a cell phone did not verify if any of the respondents had temporarily forwarded their landline telephone numbers to their cell phones. The questions preceding the cell phone question do verify the number called and that a household has been reached. It is still likely, however, that some portion of the telephone numbers reached were actually landline numbers that were forwarded to and answered on the respondent s cell phone. Similarly, the wording of the screener question did not specifically define what was meant by a cell phone. As a result, some respondents may have confused cordless landline phones with cellular phones, thereby misreporting that the phone was a cell phone. The 2006 BRFSS addresses this shortcoming by adding the following probe to the cell phone question: By cellular telephone, we mean a telephone that is mobile and usable outside of your neighborhood. Both temporary forwarding of landlines to cell phones and misreporting cordless phones as cellular phones would bias the estimates presented here higher. Inclusion of cell numbers in RDD landline samples does have some real associated costs, including the costs for sampling and contacting these numbers. These costs, however, are likely to be minimal in most instances. For instance, if after screening for known businesses, not-in-service numbers, and known cell phone numbers, it requires approximately four telephone numbers to be selected for every completed interview obtained (based on the 2005 BRFSS experience) and if we assume that 0.6 percent of these numbers are cell phones requiring, on average, four calls per number to screen them as cell phones, then we would expect to make approximately 100 calls per 1,000 completed interviews obtained to screen out cell phones. For a study of 1,000 completed interviews, this would likely translate into 2.5 h of

7 510 INTERNATIONAL JOURNAL OF PUBLIC OPINION RESEARCH interviewer time (assuming 1.5 min per call on average) not a substantial sum. For a study such as BRFSS, however, the costs are significantly greater. For screening cell phone numbers in a sample large enough to yield 350,000 completed interviews, the estimated amount of interviewer time would be approximately 840 h(33,600 calls at 1.5 min each). If number portability does reach the level of becoming a significant problem for survey researchers, the data examined here point to a potential strategy to minimize the burden and costs of screening out these calls. Currently, mixed-use exchanges serving POTS lines and cellular exchanges and, to a lesser degree, those serving three or more telecommunications services have the largest proportion of cell phones within the exchanges. It would be possible to subsample from these exchanges, adding a post-survey adjustment to account for the subsampling. This would have the effect of reducing the number of cell phones encountered. The approach may also increase variance in the final weights; however, such an approach would need to be evaluated thoroughly before being implemented. It is highly unlikely that RDD surveys based on landline sampling alone will continue unchanged for the foreseeable future. Rather, the approach can and should evolve to account for the growing use of other technologies, like cell phones and VoIP, and changes in the geographic specificity of landlines in the face of number portability. It is difficult at this juncture to speculate on how widespread the use of number portability will be in the coming years. The study presented here provides a baseline against which to measure future trends in the USA. As communications technology continues to evolve, however, it is likely that the geographic anchoring of telephone numbers will continue to erode. For this reason, researchers interested in extending the longevity and validity of telephone surveys would be well advised to develop more standardized approaches to incorporating cell phone and VoIP numbers into RDD sampling and weighting schemes, while also determining how to handle the geographic indeterminacy of ported landline numbers. REFERENCES Blumberg, S. J., Luke, J. V., & Cynamon, M. L. (2006). Telephone coverage and health survey estimates: Evaluating the need for concern about wireless substitution. American Journal of Public Health, 96, Blumberg, S. J., & Luke, J. V. (2007). Wireless substitution: Preliminary data from the January-June 2006 National Health Interview Survey. Internet report. Retrieved February 15, 2007, from wireless2006/wireless2006.htm Federal Communications Commission (FCC). (2006). Wireless local number portability. Internet report. Retrieved September 12, 2006, from fcc.gov/wlnp Mokdad, A., Stroup, D., & Giles, W. (2003). Public health surveillance for behavioral risk factors in a changing environment: Recommendations from the behavioral risk factor surveillance team. Morbidity and Mortality Weekly Report, 52 (No. RR-9), 1 12.

8 RESEARCH NOTES 511 Rembert, L. (2006). Number portability: FCC issues a wireless safe harbor. Internet report. Retrieved September 12, 2006, from article.cfm?aid¼116 SPSS Inc. (2004). SPSS Complex Samples 13.0 [Computer software]. Chicago, IL: SPSS. BIOGRAPHICAL NOTES Michael W. Link, PhD is Chief Methodologist for Nielsen Media Research in Atlanta, GA, USA. At the time this research was conducted he was a Senior Survey Methodologist at the Centers for Disease Control and Prevention in Atlanta, GA, USA, where he was responsible for leading research and development efforts to enhance the Behavioral Risk Factor Surveillance System (BRFSS) with respect to survey methodology, research design, and information management. His current research focuses on methods for improving survey participation, use of mixed-modes for data collection, and address-based sampling. Machell Town, MS is a Mathematical Statistician at the Centers for Disease Control and Prevention. She is in charge of the sample design and weighting for the BRFSS. She worked previously at the U.S. Census Bureau for nine years where she specialized in survey design, imputation, small area estimation, and variance estimators. She received her Masters in Statistics from the University of Georgia and is currently pursuing a PhD in Epidemiology. Ali H. Mokdad, PhD is the chief of the Behavioral Surveillance Branch at the Centers for Disease Control and Prevention. Dr Mokdad has published numerous articles related to chronic diseases and their outcomes in journals such as the Journal of the American Medical Association and the American Journal of Preventive Medicine. He also manages the BRFSS to enable the CDC, state health departments, and other health and education agencies to monitor risk behaviors related to chronic diseases, injuries, and death in the USA. Address correspondence to Michael W. Link, Nielsen Media Research, 1145 Sanctuary Parkway, Suite 100, Alpharetta, GA 30004, Michael.Link@ Nielsen.com