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. Author manuscript; available in PMC: 2015 Dec 16.
Published in final edited form as: Health Psychol. 2015 Dec;34(0):1296–1304. doi: 10.1037/hea0000307

Internet-based physical activity intervention for women with a family history of breast cancer

Sheri J Hartman 1,2,3, Shira I Dunsiger 3,6, Catherine R Marinac 2,4, Bess H Marcus 1,3, Rochelle K Rosen 3,6, Kim M Gans 5,6
PMCID: PMC4681398  NIHMSID: NIHMS735088  PMID: 26651471

Abstract

Objective

Physical inactivity is a modifiable risk factor for breast cancer. Physical activity interventions that can be delivered through the Internet have the potential to increase participant reach. The efficacy of an Internet-based physical activity intervention was tested in a sample of women at an elevated risk for breast cancer.

Methods

A total of 55 women with at least one first-degree relative with breast cancer (but no personal history of breast cancer) were randomized to a 3-month theoretically grounded Internet-based physical activity intervention or an active control arm. Minutes of moderate to vigorous physical activity, psychosocial mediators of physical activity adoption and maintenance, as well as worry and perceived risk of developing breast cancer were assessed at baseline, 3-month, and 5-month follow up.

Results

Participants were on average 46.2 (SD=11.4) years old with a BMI of 27.3 (SD=4.8) kg/m2. The intervention arm significantly increased minutes of moderate to vigorous physical activity compared to the active control arm at 3 months (213 vs. 129 min/week) and 5 months (208 vs. 119 min/week; both p<.001). Regression models indicated that participants in the intervention had significantly higher self-efficacy for physical activity at 3 months (p<.01) and borderline significantly higher self-efficacy at 5 months (p=0.05). Baseline breast cancer worry and perceived risk were not associated with physical activity.

Conclusions

Findings from this study suggest that an Internet-based physical activity intervention may substantially increase physical activity in women with a family history of breast cancer.

Keywords: Physical activity, Internet-based intervention, breast cancer risk

INTRODUCTION

Based on the current United States breast cancer incidence rates, roughly 12.4% of all women will develop breast cancer at some point in their lives (Howlader et al., 2012). This projection is significantly higher for women with a family history of the disease. According to two meta-analyses (Collaborative Group on Hormonal Factors in Breast, 2001; Pharoah, Day, Duffy, Easton, & Ponder, 1997), women with one first degree relative with breast cancer have approximately double the risk of developing breast cancer compared to women with no family history of the disease. Breast cancer incidence rates are projected to remain stable in years to come (Rahib et al., 2014); thus, targeted interventions are needed to reduce breast cancer risk among this high-risk subgroup of women.

Data from numerous observational studies in general populations of women (not specifically women with a family history of breast cancer) suggest that engaging in healthy lifestyle behaviors, such as being physically active, may lower breast cancer risk by 12–40% (McTiernan, 2003; Wu, Zhang, & Kang, 2013). Physical activity in the general population has been shown to be protective for both pre- and post-menopausal breast cancer, with some reviews of the literature finding a stronger relationship with pre-menopausal breast cancer (Wu et al., 2013) and others finding a stronger relationship with post-menopausal breast cancer (World Cancer Research Fund / American Institute for Cancer Research, 2007). Physical activity has also been shown to be more protective in women with a BMI less than 25 kg/m2, compared to women who are overweight or obese (BMI≥25kg/m2)(Wu et al., 2013).

Considering the evidence for the benefits of physical activity for reducing cancer risk, the American Cancer Society established physical activity recommendations for cancer prevention (Kushi et al., 2012). These recommendations include engaging in at least 150 minutes of moderate-vigorous intensity exercise, although higher amounts of physical activity may provide even greater reductions in breast cancer risk (Kushi et al., 2012). Despite the benefits on physical activity for the prevention of cancer and other chronic diseases, almost 60% of women in the United States do not meet these recommendations (US Department of Health and Human Services, 2008). These rates of physical activity engagement appear to be similarly low among women with a first-degree relative with breast cancer, although data is limited (Audrain, Schwartz, Herrera, Goldman, & Bush, 2001).

The low rates of physical activity among women with a first-degree relative with breast cancer highlight the need for intervention. High reach interventions that minimize barriers to participation (e.g., transportation, childcare, high costs) may be effective for addressing this important public health issue. Internet-based interventions are a promising remote delivery channel for such interventions given that they can allow for interactive and tailored interventions. Furthermore, these interventions have the potential to be disseminated widely: an estimated 87% of US adults currently use the Internet (Pew Internet and American Life Project, 2014), and over 40% of breast cancer patients use the internet to access health-related information (Littlechild & Barr, 2013). Despite the advantages of Internet-based programs, existing interventions in the general population have yielded mixed results. A review of 72 studies found that only 61% reported significant improvements in physical activity (Joseph, Durant, Benitez, & Pekmezi, 2014), and a meta-analysis of 34 studies found a small but significant effect size (d=0.14, p < .001) for Internet-based physical activity interventions (Davies, Spence, Vandelanotte, Caperchione, & Mummery, 2012).

Developing targeted content may be one way to increase the effectiveness of Internet-based interventions (Abraham & Michie, 2008). For example, some first-degree relatives of breast cancer patients have high levels of cancer-related worry and distress (Boyer et al., 2002; Lindberg & Wellisch, 2004; Rabin et al., 2007; Zapka, Fisher, Lemon, Clemow, & Fletcher, 2006); therefore these women may be motivated to be physically active by interventions that target their concerns about familial risk of breast cancer. In addition, many first-degree relatives of breast cancer patients are not aware of risk factors for breast cancer. For example, a study of female first-degree relatives of breast cancer patients found that genetics, stress, and pollution were the most frequently reported causes of cancer (endorsed by 45–52% of participants) with risk factors including lack of exercise, hormone replacement treatment, alcohol consumption, and old age endorsed by only 13%, 13%, 6.5%, and 0% respectively (Rabin & Pinto, 2006). A qualitative study with sisters of breast cancer patients found that less than one third of the sisters identified lack of exercise as a risk factor. On the contrary, most felt that breast cancer was indiscriminate and occur in women who lead healthy lifestyles, as well as those who do not (Spector et al., 2009). Taken together, the above studies suggest that informing such women about the benefits of physical activity for reducing breast cancer risk (a personal health concern) could increase a woman’s motivation to become more physically active.

This concept of using knowledge and perceived risk to motivate behavior change is consistent with Social Cognitive Theory (SCT), which states that behaviors are determined by a dynamic interaction of personal factors, environmental influences, and behavioral attributes (Bandura, 1986; Painter, Borba, Hynes, Mays, & Glanz, 2008; Rosenstock, Strecher, & Becker, 1988). Informing women of modifiable risk factors can help to influence expectancies and incentives (value of the outcome), two major concepts of SCT (Rosenstock et al., 1988). For example, a woman who is concerned about getting breast cancer and feels that being sedentary increases her risk may be likely to increase her physical activity if she believes that: (a) physical activity would decrease her cancer risk (outcome expectations); and (b) that she is capable of increasing her physical activity (self-efficacy) (Rosenstock et al., 1988). The example outlined above demonstrates that a targeted intervention based on these theoretical constructs could be influential in promoting physical activity behavior change.

The primary objective of this pilot study was to test the efficacy of a 3-month SCT grounded Internet-based physical activity intervention targeting women at increased risk for breast cancer. Although previous studies have demonstrated that SCT-based interventions are effective at increasing PA most focusing on cancer have recruited cancer survivors and not those at increased risk for cancer ((Basen-Engquist et al., 2011; Hatchett, Hallam, & Ford, 2013; Stacey, James, Chapman, Courneya, & Lubans, 2015). In addition, other studies have required in-person assessments, and have used time-intensive and expensive delivery channels (e.g., group sessions, mail delivery)(Basen-Engquist et al., 2011; Muller & Khoo, 2014). The current study was completely non-face-to-face and used an Internet-based PA intervention, which has the potential to result in widespread diffusion of information. It was hypothesized that an Internet-based physical activity intervention would be more effective than the active control condition at increasing physical activity levels among first-degree relatives of breast cancer survivors. The secondary objective was to explore changes in theoretically relevant psychosocial mediators of physical activity adoption and maintenance (self-efficacy, decisional balance, cognitive processes, and behavioral processes). The tertiary objective was to explore whether breast cancer worry or perceived risk of breast cancer was associated with changes in physical activity.

METHODS

Study design and sample

Eligible participants were women aged 21 to 65 with a mother or sister who had previously been diagnosed with breast cancer; proficient in English; sedentary (defined as engaging in less than 60 minutes of moderate-intensity physical activity each week); and self-reported eating 3 or less servings of fruits and vegetables per day. Women were excluded if they were pregnant or intended to become pregnant within 3 months of study enrollment; had a history of a severe psychiatric illness; had a previous diagnosis of cancer except basal cell carcinoma; or had a medical condition that, in the investigator’s judgment, would make it difficult or dangerous for them to exercise (e.g., CVD). Written informed consent was obtained, and the protocol was approved by the institutional review board of The Miriam Hospital, RI.

Participants were recruited through self-referral from posted advertisements on a variety of websites, including craiglist.org, in 10 cities throughout the eastern and central time zones. Eligibility was assessed via a telephone interview. Women who were eligible and interested were mailed (or emailed) an informed consent form and required to sign the form and mail, fax, or scan it back to the study team. After obtaining written informed consent, participants completed a series of initial assessments comprised of online questionnaires and a telephone-based assessment of current physical activity.

After completing the initial assessments, participants received another phone call where they were randomized in equal numbers to either the physical activity intervention or the active control arm via a computer-based program. After participants were randomized, they completed a goal-setting session and were given details of their group assignment. Subsequent study assessments including online psychosocial questionnaires and instruments and a telephone-administered 7-day Physical Activity Recall (PAR) (Blair et al., 1985), were conducted at month 3 and 5. Study staff who administered the 7-Day PAR were blinded to group assignment. In addition, participants completed a brief online questionnaire during months 1, 2, and 3. The purpose of these online questionnaires was to provide tailored intervention content. Participants in both arms were given a $10 incentive for completing monthly intervention tailoring questionnaires and $25 incentives for completing the 3-month and 5-month assessments.

Intervention Arm (Physical Activity Intervention)

Participants were enrolled in a 3-month physical activity intervention designed to motivate participants to increase their moderate intensity physical activity. This intervention was modified from an efficacious print-based physical activity intervention (Marcus, Napolitano, et al., 2007) and was targeted to the interests and needs of women at increased risk for breast cancer (Hartman, Dunsiger, & Marcus, 2013) through formative research. Specifically, 7 focus groups were conducted among women with a first-degree relative with breast cancer to identify needs and concerns of this target population (Hartman & Rosen, 2013). Information gathered from these focus groups was used to modify the existing intervention. For example, focus group participants reported a strong interest in a personalized discussion of their own breast cancer risk factors. They also wanted stories from other women like themselves incorporated into the intervention materials, and they wanted a way to communicate and talk with other participants. In addition, some of the women were interested in receiving more general breast cancer information because they felt they did not have current or accurate information. Each of these components: personalization, communication with other participants, and provision of current breast cancer risk information, were included in the current intervention.

The modified intervention used in the present study consisted of an Internet-based program with brief telephone counseling to allow for personalized discussion of risk factors. Participants in the physical activity intervention arm were given access to the exercise website and were introduced to its features during the goal setting call. Main features of the website included: self-monitoring of physical activity; message board to interact with other participants and study staff; graph to show the participant’s progress in comparison to other women in the study; personalized physical activity goal; a place to see all the emails sent from the study; and information and resources regarding physical activity and breast cancer. The breast cancer-related topics included evidence-based information on modifiable and non-modifiable risk factors for breast cancer, details on how physical activity may reduce breast cancer risk, as well as general information about breast cancer (e.g., the importance of breast cancer screening and myths and facts about breast cancer).

Participants were informed of the study’s goal to help women work up to 45–60 minutes of moderate intensity physical activity most days of the week. With the guidance of a doctoral-level psychologist, participants set a personalized starting physical activity goal. A detailed plan to reach the goal was developed and then uploaded to the participant’s website. Participants also had a call at week 2 with the psychologist where progress and barriers were reviewed and where participants were taught how to set new goals as needed so they could work up to the study goal. The initial goal setting call was 30–45 minutes long and the week 2 call took between 5–10 minutes. In addition, participants received 2–3 emails per week for 3 months that were sent on an automated schedule that required no human involvement. These emails included brief tips and facts about physical activity and breast cancer as well motivational physical activity materials and individually tailored feedback reports. The feedback reports were based on questionnaires completed once a month, online, during months 1, 2, and 3. The reports were generated by a previously developed computerized expert system using data from the monthly online questionnaires completed by each participant (Marcus, Lewis, et al., 2007). The reports provided information consisting of preplanned counseling messages written by doctoral-level psychologists who have experience in health behavior change. The messages were tailored to each individual participant’s barriers to and expected benefits from physical activity. Messages also reinforced successful use of strategies for physical activity adoption. These materials were matched to the individual’s motivational readiness for physical activity adoption (Marcus, Lewis, et al., 2007).

Active Control Arm (Nutrition Intervention)

The nutrition intervention delivered to the active control arm was designed to encourage participants to increase their intake of fruits and vegetables. Similar to the physical activity intervention, participants in the active control arm had access to a study website designed specifically for that arm of the study. Components of the website were comparable to those of the intervention arm’s website: self-monitoring, message board, feedback on other participant’s progress; personalized goal information and resources; and way to see all emails sent. Emails were sent on the same schedule as the intervention arm and included information about fruits, vegetables, and breast cancer. Participants completed a questionnaire each month assessing their fruit and vegetable intake to keep contact time consistent with the intervention arm. They also received breast cancer related information like the intervention arm, except the web-page on physical activity and breast cancer risk was replaced by content about weight and breast cancer risk. Participants in the control arm had the same amount of contact with the psychologist as the intervention arm: 30–45 minute goal setting call at baseline and 5–10 minute call at week 2. For both arms, participants received emails for only the first 3 months but continued to have access to the website through 5 months.

Measures

Physical Activity

Physical activity was assessed with the 7-day physical activity recall (PAR) (Blair et al., 1985) which is a validated interviewer-administered measure of physical activity (Hayden-Wade, Coleman, Sallis, & Armstrong, 2003; Pereira et al., 1997; Prince et al., 2008; Sloane, Snyder, Demark-Wahnefried, Lobach, & Kraus, 2009), that has been demonstrated sensitivity to change over time (Dunn, Andersen, & Jakicic, 1998; Dunn et al., 1999). Number of minutes of moderate to vigorous intensity physical activity was the primary variable of interest and treated as a continuous variable in the primary analysis.

Psychosocial Measures

Participants’ current stage of change for physical activity (i.e., precontemplation, contemplation, preparation, action, maintenance) was assessed using the Stages of Change for Physical Activity (Marcus, Selby, Niaura, & Rossi, 1992). Self-Efficacy for Physical Activity was assessed with a 5-item measure that assesses confidence in resisting relapse, making time for physical activity, and overcoming negative affect (Marcus, Selby, et al., 1992). Decision Making for Physical Activity was assessed using a 16-item instrument with two sub-scales: one indicative of benefits (i.e., Pros) of exercise adoption and another of negative consequences (i.e., Cons)(Marcus, Rakowski, & Rossi, 1992). Cognitive and behavioral processes were measured with the Processes of Change for Physical Activity, a 40-item measure (Marcus, Rossi, Selby, Niaura, & Abrams, 1992).

Cancer worry was assessed with the Cancer Worry Scale (Lerman et al., 1991), which is a 4-item measure of the extent to which breast cancer-specific worry interferes with daily functioning rated on a 4-point Likert scale (1=not at all or rarely; 4=a lot)(Bowen et al., 2003; Rees, Fry, Cull, & Sutton, 2004). Perceived risk of developing breast cancer was assessed with two questions modeled from previous research (Brain, Norman, Gray, & Mansel, 1999; Rowe, Montgomery, Duberstein, & Bovbjerg, 2005) assessing absolute and relative risk.

Other Measures

Demographic information was obtained at baseline through a self-report questionnaire. Height and weight were also self-reported. For weight, each person was asked to weigh themselves twice on the day of the assessment call and report both weights to the study staff. The two weights were averaged for analyses. Fruit and vegetable intake was measured by the By Meal Screener, a brief fruit and vegetable screener (Thompson et al., 2002).

Statistical Analysis

Descriptive statistics characterized the study population. A single longitudinal mixed effects model was used to simultaneously assessed treatment effects on 7-day PAR outcomes at 3 and 5 months, controlling for baseline. Models included a subject-specific intercept (to account for repeated measures within individual) and controlled for baseline physical activity, race and education (covariates chosen apriori). A longitudinal logistic regression model assessed differences in the probability of meeting the study’s goal of engaging in 45 min at least 5 days per week (i.e., 225min/week) at 3 and 5 months by treatment arm. This model was implemented with Generalized Estimating Equations and robust standard errors that assumed the same effect of intervention at 3 and 5 months. A series of longitudinal mixed effects models assessed differences in psychosocial outcomes over between intervention treatment groups at months 3 and 5 months. Psychosocial outcomes of interest included decisional balance, self-efficacy, cognitive processes, and behavioral processes. All models included a random intercept and controlled for baseline value, race and education. Subsequent models also considered controlling for variables not balanced by randomization (e.g., race, education); however including these variables in the models did not impact the study results or conclusions rendered. In addition, baseline cancer worry and perceived risk of breast cancer were tested as moderators of the intervention effects on change in physical activity at 3 and 5 months. All analyses were conducted in SAS version 9.3 (Carey, N.C.).

RESULTS

A total of 314 calls were received from interested people. Of those, 246 were assessed for eligibility; 68 were unable to be contacted; and 126 women did not meet eligibility criteria. The main reasons women were ineligible were: too active (n=34); no first-degree relative diagnosed with breast cancer (n=20); eating too many fruits and vegetables per day (n=20); and medical contraindication (n=19). Of the 99 eligible women, reasons for not being randomized included: not completing the orientation phone call (n=12); not sending back the signed informed consent (n=30); or not completing the baseline measurement phone call (n=1). A total of 28 women were randomized to the physical activity intervention and 28 to the active control arm. One participant in the active control arm was diagnosed with breast cancer by the 2nd week of the study and was withdrawn (no longer eligible). Baseline data corresponding to this participant were subsequently removed from analyses. At the end of the intervention (3 months) and at the 5-month follow-up, 4 participants in the intervention and 2 participants in the active control group were lost to follow-up (91% retention rate). See Figure 1 for CONSORT diagram.

Figure 1.

Figure 1

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CONSORT Flow Diagram

As shown in Table 1, participants were a mean age of 42.6 years old (SD=11.4), were predominantly white (93%), and had a mean BMI of 27.3 kg/m2 (SD=4.8). There were minimal differences in demographic characteristics between participants enrolled in the physical activity and active control arms; however participants randomized to the intervention were less active than participants in the active control arm (F=6.177, p=0.016). This was controlled for in all subsequent analyses of physical activity outcomes. In terms of intervention dose, 93% of the 2 week phone calls were completed (only 2 participants from each arm missed this call). Participant posts on the message board averaged 4.75 times (range 1–29) for the intervention arm and 8.07 times (range 1–30) for the active control arm.

Table 1.

Baseline Characteristics by Intervention Group in a Sample of Women with a First Degree Relative Diagnosed with Breast Cancer

Intervention (n=28) Active Control (n=27) All (n=55)
Age, years 42.4 (11.0) 42.7 (12.0) 42.6 (11.4)
Attended College 86% 100% 93%
Married 50% 37% 44%
White 96% 82% 91%
Non-Hispanic Latino 89% 93% 91%
BMI 27.6 (5.1) 26.9 (4.5) 27.3 (4.8)
Number of Children in Home 1.0 (1.1) 1.6 (3.8) 1.3 (2.8)
Physical Activity (min/week)* 14.1(22.5) 30.2(25.5) 22.0(25.2)
Decisional Balance Pros (range 2.5–5) 3.97(0.63) 4.25(0.60) 4.11(0.62)
Decisional Balance Cons (range 1–4.8) 2.65(0.91) 2.71(0.81) 2.68(0.85)
Self-Efficacy (range 1–5) 2.18(0.85) 2.24(0.86) 2.21(0.85)
Cognitive Processes (range 1–5)* 2.84(0.65) 3.23(0.72) 3.03(0.71)
Behavioral Processes (range 1–5) 2.47(0.61) 2.71(0.62) 2.59(0.62)
Breast Cancer Worry (range 4–12) 6.68(2.16) 6.21(1.69) 6.4(2.0)
Perceived Risk (range 11–60) 38.93(11.02) 39.25(8.42) 38.8 (9.5)
Fruit and Vegetable intake 1.44 (2.18) 5.73 (4.45 4.80 (3.49)
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*

significant between group differences, p<.05

At 3 months, the intervention arm had significantly greater increases in minutes of moderate to vigorous intensity physical activity from 14.11 min/week to 213.13 min/week compared to the active control arm which increased from 30.22 min/week to 129.04 min/week (B = 100.39; SE = 30.25, p =.0013). This significant difference was maintained at 5 months (207.92 min/week vs. 118.70 min/week; B=105.86; SE= 29.89; p = .0006; See Figure 2). Individuals in the intervention arm engaged in an estimated 97.8 more minutes of moderate to vigorous physical activity at 3 months (p=0.0005) and 103.2 more minutes at the 5-month follow-up interval (p=0.0002) than the active control arm. In terms of between-group differences in meeting the study’s goal of 225 min/week, analyses suggest a borderline significant effect of intervention (p=0.05) such that the odds of meeting the physical activity guidelines were roughly 3-fold higher amongst those randomized to the physical activity intervention (OR=2.97, 95% CI:1.00–8.93).

Figure 2.

Figure 2

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Unadjusted Mean Minutes per Week of Physical Activity at Baseline, 3-Months, and 5-Months, in a sample of 55 Women Participating in a Physical Activity Intervention (n=28 Intervention; n=27 Active Control).

*p-value determined via Analysis of Variance (ANOVA)

Estimated mean differences in psychosocial outcomes between the intervention and active control group at 3 and 5 months are presented in Table 2. Results suggest a treatment effect for higher self-efficacy in the intervention arm at both 3 and 5 months. Specifically, individuals in the physical activity intervention had an estimated 0.72-point higher self-efficacy score for physical activity at 3 months (p<0.01) and 0.51 higher self-efficacy at 5 months (p=0.05). No statistically significant differences were observed between groups at either time point for any other psychosocial outcomes assessed in this study. Furthermore, baseline breast cancer worry and baseline perceived risk of breast cancer were not significantly associated with physical activity at 3 or 5 months (p>0.30, data not shown).

Table 2.

Estimated Mean Differences in Psychosocial Outcomes Between Physical Activity Intervention and Active Control at 3-Months and 5-Months.

Differences at 3-Months (Intervention-Control) Differences at 5-Months (Intervention-Control)
Estimate p-value Estimate p-value
Decisional Balance −0.11 0.74 0.07 0.84
Self-Efficacy 0.72 <0.01 0.51 0.05
Cognitive Processes −0.04 0.84 −0.18 0.40
Behavioral Processes 0.36 0.08 0.11 0.60
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Discussion

These findings suggest that an Internet-based, individually tailored theory-based intervention can be effective for helping women at risk for breast cancer increase their physical activity. Participants randomized to the intervention arm had significantly greater increases in moderate to vigorous intensity physical activity than the active control arm. The intervention arm also increased physical activity by roughly15-fold from baseline to month 3 and maintained that increase at the 5-month follow-up. While there are a growing number of Internet-based physical activity interventions, many have not shown sustained increases at follow-up or shown improvement over a control group as observed in the current study. For example Joseph and colleagues (2014) found that only 6 out of 16 Internet-based physical activity interventions had significant effects at follow-up and La Plante & Peng (2011) found that only 4 out of 7 interventions had significantly greater increases in physical activity than the control. Our intervention was associated with increased self-efficacy, which appeared to be sustained at both 3- and 5-month time points. These findings build upon the accumulating evidence that self-efficacy can be important for physical activity behavior change (Anderson-Bill, Winett, & Wojcik, 2011; Burke, Beilin, Cutt, Mansour, & Mori, 2008; Darker, French, Eves, & Sniehotta, 2010). Our finding suggests that utilizing individually tailored Internet-based interventions that target self-efficacy may be an effective way to increase physical activity.

Previous studies in similar populations of women at risk for breast cancer have noted associations between individual perceptions of breast cancer risk and physical activity engagement (Hartman et al., 2013). An interesting and unexpected finding in the present study was that worry about breast cancer and perceived risk of breast cancer were not associated with physical activity outcomes at any time point. These findings contradicted our expectation that targeting concerns about breast cancer would increase the efficacy of the intervention; however the lack of association between breast cancer worry/perceived risk and physical activity outcomes suggests that our targeted intervention may be effective for broad populations of women (i.e., those who might not have heightened concerns about breast cancer). Future research should examine the applicability and effectiveness of this targeted intervention in diverse populations of individuals.

Our results also demonstrate that combining a webpage with emails and minimal phone contact can be a powerful channel for health promotion. The Internet and automated emails are low cost intervention tools (following initial development) that can be used in the widespread diffusion of information about physical activity and other health behaviors. For example, the current study was delivered remotely from our facilities in Providence, Rhode Island to women throughout the eastern and central time zones in the United States. Since the intervention was Internet-based, a completely non-face-to-face format was used that allowed for much greater reach of the intervention and higher potential for successful dissemination. Furthermore, the intervention is consistent with the National Physical Activity Plan, which highlights the Internet as a strategy for delivering evidence-based physical activity interventions aimed at improving public health (Coordinating Committee and Working Groups for the Physical Activity Plan, 2010).

Strengths of this pilot study include the randomized group assignment with a contact control group, two follow-up assessments and the use of a non-face-to-face intervention poised for dissemination. In addition, the study used formative research methods to develop the intervention components and content of interest to our target population. Our study also had a very high retention rate with over 90% completing the 3 and 5 month assessments. This retention rate is considerably higher than has been seen in other Internet-based interventions (Mathieu, McGeechan, Barratt, & Herbert, 2013). It is possible that using an intervention that was targeted towards a specific population, women at increased risk for breast cancer, and incorporating materials directly related to breast cancer may have increased engagement in the study and helped to retain participants. Alternatively, the $25 incentives at the 3 and 5 month follow-up may have also played a role in increased retention, although many studies with similar incentives have lower retention rates. Limitations include the small and homogenous self-referred sample and restricting enrollment to participants with low levels of physical activity, thus limiting the generalizability of our findings. We were also required by our IRB to obtain written-informed consents from each participant, instead of a less-burdensome web-based consent. This consenting process could have limited generalizability of study findings as the study sample likely reflects a motived population of women. Furthermore, self-report measures were used to assess physical activity, and the physical activity intervention was tested across a relatively short time period and short follow-up. The study may have also been impacted by seasonality, as evidenced by the increase in physical activity in the control group from month 3 to 5. Recruitment was completed in three months, all of which were during the winter in Providence, RI (January – March); the 3 month follow-ups were in the spring (April – June) and the 5 month follow-ups took place in the summer (June – August). However seasonality would not have impacted the differences between the intervention and control groups. In addition the study used multiple channels of intervention delivery (Internet, email, and phone); therefore the contributions of these channels individually were not able to be assessed. Future research should examine which channel of delivery or combination of channels is more impactful. In addition, future research could incorporate wearable physical activity trackers, objective measurement of physical activity, a longer follow-up, and recruit a more diverse population.

Internet-based physical activity interventions show promise as a tool to increase physical activity and putatively reduce breast cancer risk. For women with a first-degree relative of breast cancer, an Internet-based physical activity intervention that incorporated information about breast cancer was associated with increased engagement in physical activity and increased self-efficacy. Given the potential for reaching a wide audience through a scalable intervention channel, more research is needed to determine the effectiveness of targeted interventions that will help women at risk for breast cancer to engage in healthy lifestyle behaviors.

Supplementary Material

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Acknowledgments

Research support was provided by funding from the National Cancer Institute (R25CA087972). Dr. Hartman is now supported by grant 1K07CA181323 from the National Cancer Institute. Ms. Marinac is a recipient of a Ruth L. Kirschstein National Research Service Award (NRSA) Individual Predoctoral Fellowship (1F31CA183125-01A1).

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NIHMS735088-supplement-1.pdf (221.6KB, pdf)
2
NIHMS735088-supplement-2.pdf (162.7KB, pdf)

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