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Transl Behav Med. 2016 June; 6(2): 285–294.
Published online 2015 August 25. doi:  10.1007/s13142-015-0339-7
PMCID: PMC4927440

Development and design of an intervention to improve physical activity in pregnant women using Text4baby


Text4baby is a free, mobile health information service for pregnant and post-partum women. This study aims to understand preferences of physical activity text messages (SMS), sequentially develop prototype SMS, and determine preferred dose of SMS to inform a future study utilizing Text4baby. This study had a user-centered design with three phases: (1) literature review and interviews with pregnant women for development of prototype SMS, (2) interviews with health care professionals and pregnant women for prototype SMS feedback, and (3) survey to determine preferred dose of SMS. Data from interviews identified knowledge and support as major themes. Prototypes were developed (N = 14) and informed 168 SMS. Pregnant women (N = 326) thought three SMS/week were about right (50.2 %) and preferred three SMS/week throughout pregnancy (71.9 %). There is a need for opportunities for behavioral scientists to incorporate evidence-based practices within scalable interventions. As such, this research will inform utilization of Text4baby to potentially improve physical activity participation.

Keywords: Pregnancy, Mobile health, Technology, SMS, Text messaging


Regular physical activity during pregnancy has many health benefits for both mother and fetus [13]. For the mother, benefits may include weight control [4] and reduced risk of early delivery and gestational diabetes [2, 3, 57], and for the fetus, benefits may include improved stress tolerance and a decrease in resting fetal heart rate [812]. Despite these benefits, only 15.8 % of pregnant women (as compared to 26 % of non-pregnant women) achieve recommendations for physical activity [6, 13, 14] (i.e., meeting physical activity recommendations of 150 min of moderate intensity activity per week) [1517].

Pregnancy may be an opportune time to promote the adoption of physical activity, as women may be more likely to adopt health behaviors because they are concerned with the healthy development of their baby and/or a quick return to pre-pregnancy body composition [1821]. However, women may not be receiving information they need from trusted sources such as physicians to make changes in their health behaviors (i.e., physical activity) [20, 22]. For example, research suggests that women may not receive adequate information about physical activity during physician visits because physicians are constrained by time and may lack knowledge about proper recommendations [20, 2225]. In our formative work, women reported using the internet for pregnancy-related information (94 % of respondents) and did this to add to the information their health care provider gave them (88 %) or wanted to find out more information on their own (99 % of those that responded). Approximately 44 % of women used the internet for information related specifically to physical activity/exercise. Interestingly, women in our study were concerned about the accuracy of the information they were accessing online (~65 % felt that they had been to a site that was wrong or misleading). Pregnant women have specifically requested current evidence-based recommendations for physical activity to help them to be more active [22]. However, studies have suggested that women may not know how to evaluate the accuracy of the information they receive and do not consistently check the source of information [26, 27]. Recent theories posit that improving the quality and precision of information about physical activity may be insufficient to change this behavior; the timing and dose of information over time may be important moderators of the specificity of information [28].

Of late, mHealth interventions (i.e., the use of mobile and wireless devices to improve health outcomes, health care services, and health research) have become increasingly popular as a means to motivate individuals for physical activity participation [2936]. Specifically, mobile phone text messaging (SMS) has been used to provide timely access to health advice, prompt self-monitoring, and educate individuals about preventive health [37]. SMS may be an effective channel to provide pregnant women with evidence-based information about physical activity and improve their physical activity participation during pregnancy. SMS interventions may be particularly useful because over 90 % of women in the USA own a mobile phone, 80 % of these send/receive text messages, and 60 % access the internet from their mobile phone [38].

Text4baby is a free, nationwide, mobile health information service that delivers health-related SMS to pregnant women and during the first year post-partum. Text4baby has been shown to be acceptable by low-income underserved pregnant women and new mothers with the potential to change health behavior [39, 40]. A prospective cohort study evaluating Text4baby reported that 88 % of their participants (n = 209) planned to continue using Text4baby (after an intervention) [39]. In one pilot study, Text4baby users were three times (OR = 2.73, p = .042) more likely to believe that they were prepared to be a new mother compared to the no exposure control group (N = 123) [40]. The standard Text4baby SMS set includes 267 messages addressing a wide range of maternal and child health topics (i.e., safety, nutrition, support, symptoms, screening, development) throughout pregnancy and up until the baby’s first birthday [41]. Currently, the standard Text4baby SMS set has limited (only two) content related to physical activity participation. The purpose of the current study was to (1) conduct formative research to understand SMS acceptable to pregnant women, (2) develop a pool of prototype physical activity text messages that include referrals to evidence-based physical activity websites, and (3) determine by survey the preferred dose (number per day or week) and timing of text messages (time of day, number per trimester). Information gathered from this study will inform the design of a larger randomized control trial [42, 43].


This study included three phases and was based upon user center and an iterative design process. User-centered design considers the people who will ultimately be impacted by the intervention (i.e., the user) as the center of the intervention design process [44]. In phase 1, we used qualitative research methods (i.e., interviews) and the literature to understand the needs and opinions of the potential users of the intervention (i.e., pregnant women) to develop prototype text messages (N = 14). In phase 2, we gained insight about the prototype text messages using additional qualitative research methods (i.e., interviews) with health care professionals (e.g., physicians, midwives) and the target user group and then developed 168 additional text messages. Finally, in phase 3, we conducted a survey to determine the users preferred dose of text messages to inform the design of our intervention (currently being implemented). The following sections detail each phase of the process, and the final intervention design is also briefly described. An Institutional Review Board at a University in the Southwestern United States approved this study, and all participants consented to participate in the study.

Phase 1: interviews and prototype development

During phase 1, we conducted a literature review and interviews in active pregnant women (i.e., meeting physical activity recommendations of 150 min of moderate intensity activity per week) [1517] to identify potential themes for the text message prototypes (i.e., barriers, strategies). We interviewed active pregnant women due to their potential insight on overcoming barriers to physical activity during this time in addition to the limited research about facilitators to physical activity adherence in active pregnant women [45, 46]. Women were recruited for the interviews from local community physician clinics via fliers, social media (e.g., Facebook), and word of mouth. Physically active women were invited to participate in the interviews if they were (1) pregnant or had ever been pregnant, (2) ages 18 years and older, (3) able to speak English, (4) participated in at least 30 min of moderate activity 5 days week (more than 150 min) in the last week (self-reported), and (5) willing to participate in an interview for 30–60 min. Interested participants contacted the research team to volunteer to participate in the study. The research team confirmed eligibility (over the phone) and then scheduled a time for an interview. Interviews were conducted (N = 15) over the phone at a time convenient to the participant. Participants were provided a $25 incentive to participate. All interviews were audio recorded and transcribed verbatim. Interviews lasted less than 30 min and included questions about how active pregnant women fit in physical activity during their day, symptoms and/or fears related to being active during pregnancy and how they overcame those in order to remain active, reasons they chose to be active during pregnancy, strategies they used to be active (e.g., support, resources), and how they thought inactive pregnant women should be prompted to be active. Example interview questions are included in Table Table11.

Table 1
Sample survey and interview questions

Interviews were analyzed using a case study approach in QSR NVivo10 (Cambridge, MA, 2010). A case study approach allows the investigator to study multiple bounded systems (cases), through detailed, in-depth data collection involving interviews and reports a case description and case-based themes [47, 48]. Two coders, trained in qualitative data analysis (master’s and doctoral level training) coded the data and then met to discuss themes. Themes were then re-established, and the coders recoded data together, according to those themes. Discussion occurred until all conflicts were agreed upon related to themes and codes. Validation was conducted similar to peer debriefing to assure that the coders considered all aspects of inquiry for interpretation and evaluation of the data [49, 50]. Themes were developed based on the major topics of the interview questions [49]. Themes that emerged from the interviews were used to develop categories (N = 7) for text message prototype development.

Phase 2: prototype assessment with key informants to inform text message content

In phase 2, prototype text messages were developed. Two prototype text messages were developed for each of the seven categories identified in phase 1 (N = 14). Prototypes were limited to 160 characters or less and included a mobile-friendly link to a Health on the Net Code of Conduct (HON Code) [51] certified website (i.e., an ethical, reliable online source for health information). To be HON Code certified, a website must provide the qualifications of authors, cite all sources of information, ensure privacy, complement information provided by physicians, ensure privacy, provide accurate contact information, disclose financial conflicts, and has appropriate advertising [51].

Once the prototype text messages were developed, informal interviews were conducted to determine the feasibility (perceived acceptability and demand) and the appropriateness (culturally and linguistically) of the material. Interviews were conducted with a convenient sample of physicians (N = 7), nurses/midwives (N = 5), and inactive (i.e., not meeting physical activity recommendations of 150 min of moderate intensity per week) pregnant women (N = 5). Participants for interviews were recruited through physician clinics and word of mouth and were included if they were (1) a physician, nurse/midwife, or pregnant patient at a local physician clinic, (2) able to read and speak English, (3) willing to participate in a 60-min interview, and (4) at least 18 years of age. All interviews took place in person at a place convenient for the participant (i.e., physician office, coffee shop) and were provided $25 for their participation. Participants were provided the two prototype text messages in each of the seven categories on a PowerPoint slide. The interviewer read the text messages to the participant and then asked the following questions: (1) “Could you please give us your gut reaction about these text messages?,” (2) “Do you think these would help women with their physical activity?,” (3) “How might we improve these messages?,” and (4) “Which one of these do you prefer and why?.” Figure Figure11 illustrates an example prototype provided in the interviews.

Fig 1
Example prototype

Phase 3: appropriate dose and informing of design

We conducted a survey to determine the acceptable dose (frequency and intensity) of messages and to inform the design of the intervention. Women were invited to participate if they were (1) pregnant or had ever been pregnant, (2) at least 18 years of age, (3) able to read and speak English, (4) and willing to complete a 5-min survey. A convenience sample of pregnant women (N = 326) was recruited from throughout the USA using word of mouth, fliers placed in places where pregnant women may be present (e.g., baby stores, maternity stores, physician clinics, WIC clinics), using email listservs (e.g., partnership with Text4baby and foundations related to pregnancy), and social media (e.g., Facebook, Twitter). Additionally, investigators recruited women from a WIC clinic in the Midwest to ensure participation from a diverse sample of women. The survey was free, voluntary, and available online and on hardcopy. There was no incentive to complete the survey. Women who chose to complete the survey clicked on an internet link provided on all recruitment materials. The survey was hosted by Qualtrics (Provo, Utah). Women recruited from the WIC clinics who did not have access to a computer completed the survey on paper, and research team members entered their survey online (N = 120).

The survey had 45 questions and assessed how often during the pregnancy (e.g., daily or weekly) and when during the pregnancy (e.g., time of day; first, second, third trimester, and/or throughout) women would want to receive text messages about physical activity participation. The survey also asked questions about the use of other automated services for health information via text or email and the frequency and intensity of those services. Example survey questions are listed in Table Table11.

Survey data was downloaded from Qualtrics and analyzed using Statistical Package for the Social Sciences (SPSS) software version 21 [52]. Data was reviewed for errors, missing values, and outliers. Frequencies were run to determine the distribution of variables. Age and current and pre-pregnancy BMIs were calculated to determine the mean and standard deviation of the sample.


Phase 1: interviews

Demographic information for interviews with active pregnant women (N = 15) are presented in Table Table2.2. Knowledge and support were the two major themes identified in the interviews. Categories and subcategories were then derived from the main themes. Knowledge included basic education and information (e.g., dispelling myths, activity ideas (i.e., modifications, lifestyle-based activity)), time (e.g., strategies to make time), safety, and benefits/consequences of activity. Related to knowledge, one woman said educating women would help them stay active during pregnancy, “…I think just even being educated on even the simplest things are going to help people better understand like how it will help and how important it is,” and another said that she liked to receive information, “I think a mixture of motivational and informative…I like information, I like little tips.”

Table 2
Demographic information of active pregnant women

Related to safety, a woman shared that she felt safe and overcame any fear about activity by modifying, “Modify, and do something that I am more comfortable doing.” Related to the benefits, one woman shared that she felt that helping inactive pregnant women understand the benefits of physical activity would encourage them to be active. “Helping women understand the benefits of being active, and it might be different for every woman, so I think highlighting the array of benefits. So maybe it’s that your labor is easier or maybe that you feel better while you are pregnant, but I think a lot of women are motivated by looking good…if you stay active during your pregnancy, it will be easier to lose the weight after you gift birth.” Another said, “…this is imperative for your child.”

Support included motivators (e.g., resources to help with motivation, accountability), social environments (e.g., activity with other pregnant women/moms), and praise (e.g., how to encourage activity). Women reported using the gym and group fitness classes and relying on instructors and significant others to motivate them. “…my husband is very supportive. He is not one for physical activity …but he is really good if I say, “will you walk with me”…and we will go for a walk together.” Another shared, “I do have a friend that we like to work out together. And I think that’s key when you have, like for yoga. When you have paid for something and you need to be there, that’s a good motivator.”

Sample text messages according to their respective themes and categories are presented in Table Table33.

Table 3
Sample text messages

Phase 2: text message content

Demographic information of the 17 participants who completed prototype interviews are presented in Table Table4.4. Content for the SMS curriculum (168 texts) was guided by the most preferred prototype (of the two presented during prototype interviews) for each category (i.e., educational, benefits/consequences, time scheduling, motivational, social, safety, and praise). The preferred prototype also guided the linguistics for the content of the other text messages in that category. Additionally, reasons that the prototype was preferred (i.e., “like the way it sounds,” “it explains stuff”) were used to further inform content. Example of the text message revision process and two sample final text messages (in the benefits/consequences and safety categories) are illustrated in Table Table55.

Table 4
Demographic information of prototype interview participants
Table 5
Example of text message revision process and sample final text messages

Phase 3: dose for intervention and final design

Descriptive characteristics for women who completed the survey are presented in Table Table6.6. A total of 326 women (mean age 30.51 ± 5.83) completed the survey. Seventy percent were Caucasian, and 17 % were African American. Approximately 73 % were married or living with a partner, and a third of the women had an income of less than $20,000 a year. A little over 30 % were currently pregnant, and 61 % reported regular engagement in physical activity. Almost all women (94 %) used text messaging with 45 % receiving 0–10 text messages per day. Almost half of the women had/were currently participated in a text message-based service (e.g., Text4baby, Babycenter, Whattoexpect). Most women (86.5 %) read the text messages, and 84 % found them somewhat valued or highly valued. Participants thought that three texts per week, each week, for an automated service were about right (50.2 %) or too many (47.3 %). When asked about preference for the time during pregnancy (i.e., trimester) to receive three text messages per week, 71.9 % preferred a similar number throughout their pregnancy. Fifty percent of women reported that they could use physical activity messages during pregnancy (past or current) and felt that this information would be acceptable (39.4 %) or very acceptable (21.3 %). Results from the pregnancy text message survey questions are presented in Table Table66.

Table 6
Descriptive characteristics and survey responses


There is a need for SMS interventions that not only include evidence-based recommendations but are also designed appropriately for the target users to ensure the messages are both useful and usable (i.e., fit into a person’s life) [20]. This study used a mixed methods approach that utilized a team of experts in a variety of disciplines (e.g., physical activity, psychology, epidemiology, public health) and incorporated interviews, iterative prototyping, and surveys among key stakeholders (e.g., pregnant women, physicians) to glean insights about how physical activity messages could be incorporated into Text4baby in the future.

The research presented in this paper adds to the emerging literature supporting the need for formative research to design mHealth interventions and the opportunities for behavioral scientists to incorporate evidence-based practices within scalable interventions. Specifically, the intervention designed from the formative research reported here can be used to inform how physical activity messaging is incorporated into Text4baby in the future. The current Text4baby curriculum has limited SMS about physical activity, and because the evidence supporting participation in physical activity as part of a healthy pregnancy is ample [112], there is a need to modify standard Text4baby physical activity SMS in light of these findings.

During phase 1, our review of the literature and interviews in active pregnant women were essential to identify the areas of focus for SMS content that may help women overcome challenges to regular physical activity participation during pregnancy. Notably, women need education about physical activity benefits, ways in which to be safe and modify physical activity participation (i.e., intensity), and resources for support to help them be successful at physical activity participation [53]. Especially because some of these factors have been linked to increased physical activity participation in pregnant women [45].

During phase 2, we were able to gather feedback about our prototype SMS from key informants such as physicians and nurses in obstetrics and gynecology, in addition to our target population for the feasibility intervention (inactive pregnant women). Other formative work suggests that involving the target population and key informants can provide important information to help guide the development of program and messaging for interventions [54, 55]. This information helped guide the development of the physical activity curriculum SMS that will be tested in our feasibility intervention as well as what could be incorporated into Text4baby in the future. Satisfaction of the SMS content will also be explored in our next study.

Finally, phase 3 was particularly useful for informing the dose of our feasibility intervention. SMS frequency has been shown to moderate intervention effectiveness [56]. Specifically, interventions that allow participants to set their own schedule or those in which the frequency decreases over the course of the study may be more effective than those that have fixed frequency (e.g., once per month). The current Text4baby curriculum is provided 3 days per week (M, W, F) at noon. However, the dose of the Text4baby curriculum has had limited evaluation in relation to its acceptance (i.e., satisfaction) and/or its effectiveness in changing health behaviors (i.e., physical activity). We used phase 3 to not only determine if the SMS would be accepted 3 days a week but also if it would be accepted 7 days a week and/or if there are higher or lower dropout rates based on the frequency of text messages. Specifically, this phase contributes to the knowledge gap about balancing pragmatic requirements of usability/acceptability with the likely dosage necessary to achieve changes in physical activity behavior in pregnant women [56, 57].

There are still many questions about whether SMS for physical activity will increase physical activity participation during pregnancy. Further, it is not known whether the low dosage of messaging will be effective. However, based on information from all three phases, the research team finalized the design for the Text4baby study and this larger ongoing study (currently being conducted) will test the impact of various doses and timings of physical activity-based text messages. The study has a quasi-experimental design with four groups: (1) standard Text4baby approach (three Text4baby general curriculum text messages per week (M, W, F) at noon), (2) intervention (three text messages (one physical activity and two Text4baby) per week (M, W, F) at noon), (3) intervention +1 (seven text messages (six physical activity, one Text4baby) per week (Su-Sa) at noon), and (4) intervention +2 (seven text messages (six physical activity, one Text4baby) per week (Su-Sa) at the time of day they choose). Outcomes being assessed are feasibility, satisfaction, and physical activity levels.

Although this study adds to the literature, there were some limitations. All of the women that were interviewed in phase 1 were Caucasian, limiting the information we obtained from a more diverse sample to guide the themes and categories for the SMS curriculum content. However, phase 2 helped to guide the specific language for the text messages and three of the five women who were interviewed in this phase classified themselves as African American or other. Additionally, the physicians and nurses that were interviewed have a diverse sample of patients in which they provide care. We also had challenges recruiting racial/ethnic minorities to participate in the survey in phase 3. However, research team members actively recruited participants from a WIC clinic in the Midwest to help further engage low income and minority women who may not be normally interested or able (e.g., no internet access, no home computer) to participate in the survey. The survey was provided to these women in a hardcopy form, and the research team members later entered the data into Qualtrics. As a result, in the phase 3 survey, approximately 26 % of the women were non-White and 31 % had a household income below $20,000.

The formative study conducted here contributes to our knowledge about SMS for physical activity among pregnant women and helps to inform future research. The physical activity SMS curriculum can be added to an already existing service (i.e., Text4baby) and then examined for feasibility and initial effectiveness for significantly improving physical activity behavior during pregnancy. More importantly, the physical activity SMS has the potential to reach a large number of women across many socio-demographics. Future research should explore the effectiveness of Text4baby to improve health behaviors during pregnancy, namely physical activity. Additionally, minimal dose necessary to improve behaviors needs to be explored. Finally, targeting messages within special population groups (i.e., those with history of miscarriage, overweight/obese women) and the dose necessary to change behaviors in these groups specifically would significantly add to the literature. More research using Text4baby is warranted.


This paper was supported by the Virginia G. Piper Charitable Trust.

Conflict of interest

The authors declare that they have no conflict of interests.

Adherence to ethical standards

All procedures were conducted in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000.



Practice: To use an already existing, free, mobile health service, Text4baby, as an opportunity to disseminate physical activity messages to pregnant and post-partum women.

Policy: Health care providers could easily, with little resources (i.e., time, money) use Text4baby to refer patients to evidence-based information about physical activity during and after pregnancy.

Research: Research to determine the optimal dose of physical activity text messages within the Text4baby curriculum to improve physical activity participation in pregnant women is needed.

Contributor Information

Jennifer Huberty, ude.usa@ytrebuhJ.

Lacey Rowedder, ude.usa@reddewoR.yecaL.

Eric Hekler, ude.usa@relkehe.

Marc Adams, ude.usa@smadA.craM.

Emily Hanigan, moc.liamg@enaginah.

Darya McClain, ude.usa@nialCcM.ayraD.

Mary Balluff, vog.en-ytnuocsalguod@ffullab.yram.

Matt Buman, ude.usa@namuB.wehttaM.

Jessica Bushar, gro.bhmh@rahsubj.


1. Clapp JF, III, Lopez B, Harcar-Sevcik R. Neonatal behavioral profile of the offspring of women who continued to exercise regularly throughout pregnancy. Am J Obstet Gynecol. 1999;180(1):91–94. doi: 10.1016/S0002-9378(99)70155-9. [PubMed] [Cross Ref]
2. Dempsey JC, Butler CL, Williams MA. No need for a pregnant pause: physical activity may reduce the occurrence of gestational diabetes mellitus and preeclampsia. Exerc Sport Sci Rev. 2005;33(3):141–149. doi: 10.1097/00003677-200507000-00007. [PubMed] [Cross Ref]
3. Melzer K, Schutz Y, Boulvain M, et al. Physical activity and pregnancy. J Sports Med. 2010;40(6):493–507. doi: 10.2165/11532290-000000000-00000. [PubMed] [Cross Ref]
4. Doran F, Davis K. Factors that influence physical activity for pregnant and postpartum women and implications for primary care. Aust J Prim Health. 2011;17(1):79–85. doi: 10.1071/PY10036. [PubMed] [Cross Ref]
5. Chu SY, Callaghan WM, Kim SY, et al. Maternal obesity and risk of gestational diabetes mellitus. Diabetes Care. 2007;30(8):2070–2076. doi: 10.2337/dc06-2559a. [PubMed] [Cross Ref]
6. Evenson KR, Savitz DA, Huston SL. Leisure time physical activity among pregnant women in the US. Paediatr Perinat Epidemiol. 2004;18(6):400–407. doi: 10.1111/j.1365-3016.2004.00595.x. [PubMed] [Cross Ref]
7. Melzer K, Schutz Y, Soehnchen N, et al. Effects of recommended levels of physical activity on pregnancy outcomes. Am J Obstet Gynecol. 2010;202(3):266-e1. doi: 10.1016/j.ajog.2009.10.876. [PubMed] [Cross Ref]
8. Brenner IK, Wolfe LA, Monga M, et al. Physical conditioning effects on fetal heart rate responses to graded maternal exercise. Med Sci Sports Exerc. 1999;31(6):792–799. doi: 10.1097/00005768-199906000-00006. [PubMed] [Cross Ref]
9. Clapp JF, III, Kim H, Burciu B, et al. Beginning regular exercise in early pregnancy: effect on fetoplacental growth. Am J Obstet Gynecol. 2000;183(6):1484–1488. doi: 10.1067/mob.2000.107096. [PubMed] [Cross Ref]
10. Gustafson KM, May LE, Yeh HW, et al. Fetal cardiac autonomic control during breathing and non-breathing epochs: the effect of maternal exercise. Early Hum Dev. 2012;88(7):539–546. doi: 10.1016/j.earlhumdev.2011.12.017. [PMC free article] [PubMed] [Cross Ref]
11. May LE, Glaros A, Yeh HW, et al. Aerobic exercise during pregnancy influences fetal cardiac autonomic control of heart rate and heart rate variability. Early Hum Dev. 2010;86(4):213–217. doi: 10.1016/j.earlhumdev.2010.03.002. [PubMed] [Cross Ref]
12. May LE, Suminski RR, Langaker MD, et al. Regular maternal exercise dose and fetal heart outcome. Med Sci Sports Exerc. 2012;44(7):1252–1258. doi: 10.1249/MSS.0b013e318247b324. [PubMed] [Cross Ref]
13. Fell DB, Armson KS, Dodds L. The impact of pregnancy on physical activity level. Matern Child Health J. 2009;13(5):597–603. doi: 10.1007/s10995-008-0404-7. [PubMed] [Cross Ref]
14. Gaston A, Cramp A. Exercise during pregnancy: a review of patterns and determinants. J Sports Sci Med. 2011;14(4):299–305. doi: 10.1016/j.jsams.2011.02.006. [PubMed] [Cross Ref]
15. American College of Obstetricians and Gynecologists (ACOG) Committee on Obstetric Practice Committee opinion #267: exercise during pregnancy and the postpartum period. Obstet Gynecol. 2002;99(1):171–173. doi: 10.1016/S0029-7844(01)01749-5. [PubMed] [Cross Ref]
16. American College of Sports Medicine (ACSM). About ACSM: News Releases: PA Recommendations. Updated in 2011. Retrieved from on August 16, 2013.
17. Center for Disease Control and Prevention (CDC). How much physical activity do adults need? Updated in 2011. Retrieved from on August 16, 2013.
18. Campbell F, Johnson M, Messina J, et al. Behavioural interventions for weight management in pregnancy: a systematic review of quantitative and qualitative data. BMC Public Health. 2011;22(11):491–514. doi: 10.1186/1471-2458-11-491. [PMC free article] [PubMed] [Cross Ref]
19. Chang MW, Nitzke S, Guilford E, et al. Motivators and barriers to healthful eating and physical activity among low-income overweight and obese mothers. J Am Diet Assoc. 2008;108(6):1023–1028. doi: 10.1016/j.jada.2008.03.004. [PubMed] [Cross Ref]
20. Huberty J, Dinkel D, Beets MW, et al. Describing the use of the internet for health, physical activity, and nutrition information in pregnant women. Matern Child Health J. 2013;17(8):1363–1372. doi: 10.1007/s10995-012-1160-2. [PubMed] [Cross Ref]
21. Szwajcer EM, Hiddink GJ, Maas L, et al. Nutrition-related information-seeking behaviours of women trying to conceive and pregnant women: evidence for the life course perspective. Fam Pract. 2008;25(Suppl 1):i99–i104. doi: 10.1093/fampra/cmn077. [PubMed] [Cross Ref]
22. Leiferman J, Sinatra E, Huberty J. Pregnant women’s perceptions of patient-provider communication for health behavior change during pregnancy. Open J Obstet Gynecol. 2014; 4(11): 672-684.
23. Cannella D, Lobel M, Monheit A. Knowing is believing: information and attitudes towards physical activity during pregnancy. J Psychosom Obstet Gynaecol. 2010;31(4):236–242. doi: 10.3109/0167482X.2010.525269. [PubMed] [Cross Ref]
24. Cheyney M, Moreno-Black G. Nutritional counseling in midwifery and obstetric practice. Ecol Food Nutr. 2010;49(1):1–29. doi: 10.1080/03670240903170491. [PubMed] [Cross Ref]
25. Kivits J. Informed patients and the internet: a mediated context for consultations with health professionals. J Health Psychol. 2006;11(2):269–282. doi: 10.1177/1359105306061186. [PubMed] [Cross Ref]
26. Cummins CO, Prochaska JO, Driskell MM, et al. Development of review criteria to evaluate health behavior change websites. J Health Psychol. 2003;8(1):55–62. doi: 10.1177/1359105303008001434. [PubMed] [Cross Ref]
27. Eysenbach G, Kohler C. How do consumers search for and appraise health information on the world wide web? Qualitative study using focus groups, usability tests, and in-depth interviews. BMJ. 2002;324(7337):573–577. doi: 10.1136/bmj.324.7337.573. [PMC free article] [PubMed] [Cross Ref]
28. Spruijt-Metz D, Nilsen W. Dynamic models of behavior for just-in-time adaptive interventions. IEEE Pervasive Comput. 2014;13(3):13–17. doi: 10.1109/MPRV.2014.46. [Cross Ref]
29. Cohall A, Hyden C. Rx for a healthy practice. Get the message? Text messaging in primary care settings. Contemp Pediatr. 2008;25(11):57–61.
30. Cole-Lewis H, Kershaw T. Text messaging as a tool for behavior change in disease prevention and management. Epidemiol Rev. 2010;32(1):56–69. doi: 10.1093/epirev/mxq004. [PMC free article] [PubMed] [Cross Ref]
31. Fjeldsoe BS, Miller YD, Marshall AL. MobileMums: a randomized controlled trial of an SMS-based physical activity intervention. Ann Behav Med. 2010;39(2):101–111. doi: 10.1007/s12160-010-9170-z. [PubMed] [Cross Ref]
32. Gerber BS, Stolley MR, Thompson AL, et al. Mobile phone text messaging to promote healthy behaviors and weight loss maintenance: a feasibility study. Health Informatics J. 2009;15(1):17–25. doi: 10.1177/1460458208099865. [PMC free article] [PubMed] [Cross Ref]
33. Haller D, Sanci L, Sawyer S, et al. R U OK 2 TXT 4 Research? Feasibility of text messaging communication in primary care research. Aust Fam Physician. 2006;35(5):175–176. [PubMed]
34. Hurling R, Catt M, Boni MD, et al. Using internet and mobile phone technology to deliver an automated physical activity program: randomized controlled trial. J Med Internet Res. 2007;9(2):e7. doi: 10.2196/jmir.9.2.e7. [PMC free article] [PubMed] [Cross Ref]
35. Krishna S, Boren S, Balas EA. Healthcare via cell phones: a systematic review. Telemed J E Health. 2009;15(3):231–240. doi: 10.1089/tmj.2008.0099. [PubMed] [Cross Ref]
36. Rice R, Katz J. Comparing internet and mobile phone usage: digital divides of usage, adoption and dropouts. Telecommun Policy. 2003;27(8):597–623. doi: 10.1016/S0308-5961(03)00068-5. [Cross Ref]
37. Demiris G, Afrin LB, Speedie S, et al. Patient-centered applications: use of information technology to promote disease management and wellness. A white paper by the AMIA knowledge in motion working group. J Am Med Inform Assoc. 2008;15(1):8–13. doi: 10.1197/jamia.M2492. [PMC free article] [PubMed] [Cross Ref]
38. Fox S, Duggan M. (2012). Mobile health 2012. Pew Research Center’s Internet x0026 American Life Project [Internet]. Retrieved from: on January 23rd, 2015.
39. Gazmararian JA, Elon L, Yang B, et al. Text4baby program: an opportunity to reach underserved pregnant and postpartum women? Matern Child Health J. 2014;18:223–232. doi: 10.1007/s10995-013-1258-1. [PubMed] [Cross Ref]
40. Evans WD, Wallace JL, Snider J. Pilot evaluation of the text4baby mobile health program. BMC Public Health. 2012;12:1031. doi: 10.1186/1471-2458-12-1031. [PMC free article] [PubMed] [Cross Ref]
41. Text4Baby Enrollment Data. Text4Baby Website. Published February 2nd, 2010. Updated January 17th, 2015. Accessed January 22nd, 2015.
42. Bowen DJ, Kreuter M, Spring B, et al. How we design feasibility studies. Am J Prev Med. 2009;36(5):452–457. doi: 10.1016/j.amepre.2009.02.002. [PMC free article] [PubMed] [Cross Ref]
43. Leon AC, Davis LL, Kraemer HC. The role and interpretation of pilot studies in clinical research. J Psychiatr Res. 2011;45(5):626–629. doi: 10.1016/j.jpsychires.2010.10.008. [PMC free article] [PubMed] [Cross Ref]
44. McClain AD, Hekler EB, Gardner C. Incorporating prototyping and iteration into intervention development: a case study of a dining hall-based intervention. J Am Coll Heal. 2013;61(2):122–131. doi: 10.1080/07448481.2012.755189. [PMC free article] [PubMed] [Cross Ref]
45. Fieril KP, Olsén MF, Glantz A, Larsson M. Experiences of exercise during pregnancy among women who perform regular resistance training: a qualitative study. Phys Ther. 2014; 94(8): 1135-43. [PubMed]
46. Leiferman J, Swibas T, Koiness K, et al. My baby, my move: examination of perceived barriers and motivating factors related to antenatal physical activity. J Midwifery Womens Health. 2011;56(1):33–40. doi: 10.1111/j.1542-2011.2010.00004.x. [PubMed] [Cross Ref]
47. Creswell JW. Qualitative inquiry and research design: choosing among five approaches. London: Sage publications; 2012.
48. Miles MB, Huberman AM. Qualitative data analysis: an expanded sourcebook. Thousand Oaks: Sage publications; 1994.
49. Creswell JW. Qualitative inquiry and research design: choosing among five approaches. Thousand Oaks: SAGE Publications Inc; 2007.
50. Cooper J, Brandon P, Lindberg M. Using peer debriefing in the final stage of evaluation with implications for qualitative research: three impressionist tales. Paper presented at: Annual meeting of the American Educational Research Association; March 1997; Chicago Illinois.
51. The HON code of conduct for medical and health web sites. Health On the Net Code. Published April 1997. Updated September 19th, 2013. Accessed January 22nd, 2015.
52. Corp IBM. IBM SPSS Statistics for Windows, Version 21.0. IBM Corp.: Armonk, NY; 2012.
53. White JL, Randsdell LB, Vener J, et al. Factors related to physical activity adherence in women: review and suggestions for future research. Women Health. 2005;41(4):123–148. doi: 10.1300/J013v41n04_07. [PubMed] [Cross Ref]
54. Perry C, Hoffman B. Assessing tribal youth physical activity and programming using a community-based participatory research approach. Public Health Nurs. 2010;27(2):104–114. doi: 10.1111/j.1525-1446.2010.00833.x. [PMC free article] [PubMed] [Cross Ref]
55. Wen K, Miller S, Kilby L, Fleisher L, Belton T, Roy G, et al. Preventing postpartum smoking relapse among inner city women: development of a theory-based and evidence-guided text messaging intervention. J Med Internet Res. 2014; 3(2). [PMC free article] [PubMed]
56. Head KJ, Noar SM, Iannarino NT, Grant-Harrington N. Efficacy of text messaging-based interventions for health promotion: a meta-analysis. Soc Sci Med. 2013; 97: 41-48. [PubMed]
57. Cole-lewis H, Kershaw T. Text messaging as a tool for behavior change in disease prevention and management. Epidemiol Rev. 2008;32(1):56–69. doi: 10.1093/epirev/mxq004. [PMC free article] [PubMed] [Cross Ref]

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