| Literature DB >> 26919558 |
Eleonora Dal Grande1, Catherine Ruth Chittleborough2, Stefano Campostrini1,3, Maureen Dollard4, Anne Winifred Taylor1.
Abstract
Mobile telephone numbers are increasingly being included in household surveys samples. As approach letters cannot be sent because many do not have address details, alternatives approaches have been considered. This study assesses the effectiveness of sending a short message service (SMS) to a random sample of mobile telephone numbers to increase response rates. A simple random sample of 9000 Australian mobile telephone numbers: 4500 were randomly assigned to be sent a pre-notification SMS, and the remaining 4500 did not have a SMS sent. Adults aged 18 years and over, and currently in paid employment, were eligible to participate. American Association for Public Opinion Research formulas were used to calculated response cooperation and refusal rates. Response and cooperation rate were higher for the SMS groups (12.4% and 28.6% respectively) than the group with no SMS (7.7% and 16.0%). Refusal rates were lower for the SMS group (27.3%) than the group with no SMS (35.9%). When asked, 85.8% of the pre-notification group indicated they remembered receiving a SMS about the study. Sending a pre-notification SMS is effective in improving participation in population-based surveys. Response rates were increased by 60% and cooperation rates by 79%.Entities:
Mesh:
Year: 2016 PMID: 26919558 PMCID: PMC4769066 DOI: 10.1371/journal.pone.0150231
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
AWB Response rates: mobile telephone sample [using American Association for Public Opinion Research standards][30].
| No pre-notification SMS | Pre-notification SMS | P value | |
|---|---|---|---|
| Complete | 203 | 317 | |
| Refusal and breakoff (terminated) | 15 | 15 | |
| Refusal | 928 | 685 | |
| Non-contact | |||
| Respondent never available | 1 | 2 | |
| Answering machine household-message left | 27 | 9 | |
| Other, non-refusals | |||
| Physically or mentally unable/incompetent | 10 | 9 | |
| Language problem | 113 | 84 | |
| Always busy | 2 | 0 | |
| No answer | 1326 | 1445 | |
| Fax/data line | 9 | 14 | |
| Disconnected number | 891 | 864 | |
| Special technological circumstances | |||
| Pager | 95 | 96 | |
| Non-residential number | 60 | 42 | |
| No eligible respondent | 820 | 918 | |
| 4500 | 4500 | ||
| I = Complete Interviews (1.1) | 203 | 317 | |
| P = Partial Interviews (1.2) | 0 | 0 | |
| R = Refusal and break off (2.1) | 943 | 700 | |
| NC = Non Contact (2.2) | 28 | 11 | |
| O = Other (2.0, 2.3) | 123 | 93 | |
| Calculating e: | 0.41 | 0.37 | |
| UH = Unknown Household (3.1) | 1328 | 1445 | |
| UO = Unknown other (3.2–3.9) | 0 | 0 | |
| 7.7 | 12.4 | <0.001 | |
| 11.0 | 19.2 | <0.001 | |
| 16.0 | 28.6 | <0.001 | |
| 17.7 | 31.2 | <0.001 | |
| 35.9 | 27.3 | <0.001 | |
| 51.2 | 42.4 | <0.001 | |
| 72.7 | 62.4 | <0.001 | |
| 48.3 | 43.3 | <0.001 | |
| 69.0 | 67.2 | 0.27 | |
| 97.8 | 99.0 | 0.02 |
e is the estimated proportion of cases of unknown eligibility that are eligible.[30] Enter a different value or accept the estimate in this line as a default. This estimate is based on the proportion of eligible units among all units in the sample for which a definitive determination of status was obtained (a conservative estimate).
Demographic profile by pre-notification SMS mobile telephone groups.
| ABS Censusemployed | No pre-notification SMS | Pre-notification SMS | ||||
|---|---|---|---|---|---|---|
| % | n | % | n | % | P value | |
| Male | 50.1 | 104 | 51.2 (44.4–58.0) | 160 | 50.5 (45.0–55.9) | 0.87 |
| Female | 49.9 | 99 | 48.8 (42.0–55.6) | 157 | 49.5 (44.1–55.0) | |
| 18–24 years | 15.2 | 32 | 15.9 (11.5–21.6) | 41 | 12.9 (9.7–17.1) | 0.22 |
| 25–34 years | 24.4 | 41 | 20.4 (15.4–26.5) | 81 | 25.6 (21.1–30.6) | |
| 35–44 years | 23.3 | 47 | 23.4 (18.1–29.7) | 57 | 18.0 (14.1–22.6) | |
| 45–54 years | 21.9 | 53 | 26.4 (20.8–32.9) | 79 | 24.9 (20.5–30.0) | |
| 55–64 years | 13.1 | 19 | 9.5 (6.1–14.3) | 47 | 14.8 (11.3–19.2) | |
| 65+ | 2.1 | 9 | 4.5 (2.4–8.3) | 12 | 3.8 (2.2–6.5) | |
| Bachelor degree or higher | 23.8 | 83 | 40.9 (34.4–47.8) | 115 | 36.3 (31.2–41.7) | 0.29 |
| Below bachelor level | 76.2 | 120 | 59.1 (52.2–65.6) | 202 | 63.7 (58.3–68.8) | |
| Australia | 72.4 | 132 | 65.3 (58.6–71.6) | 218 | 68.8 (63.5–73.6) | 0.42 |
| Outside Australia | 27.6 | 70 | 34.7 (28.4–41.4) | 99 | 31.2 (26.4–36.5) | |
| Full time | 70.4 | 120 | 60.9 (54.0–67.5) | 220 | 70.7 (65.5–75.5) | 0.02 |
| Part time | 29.6 | 77 | 39.1 (32.5–46.0) | 91 | 29.3 (24.5–34.5) | |
ABS: Australian Bureau of Statistics [31]