The research presented here includes racial and ethnic groups less frequently reported in the scientific literature. This study does have limitations. Due to the sensitive nature of the subject, some bias in reporting due to perceived social desirability of behaviors would be expected. The survey question related to severe morning sickness during pregnancy was self-reported and non-validated, so variation may have existed with respect to maternal interpretation of nausea severity. There may also be some effects due to mode bias mail versus telephone , as mail respondents were more likely to report all three outcomes of interest than were phone respondents data not shown.
However, phone respondents tend to differ from mail respondents in multiple ways, some of which are thought to be at least partially addressed by PRAMS weighting for demographic characteristics. Without their willingness to share information about their experiences before, during, and after pregnancy, this research would not be possible.
National Center for Biotechnology Information , U. Hawaii J Med Public Health. This article has been cited by other articles in PMC. Abstract Recreational use of marijuana is relatively common in the United States, and medicinal use is gaining popular and legal support. Introduction Recreational use of marijuana is relatively common in the United States, 1 and medicinal use is increasingly gaining popular and legal support. Measures The following questions pertaining to severe nausea during pregnancy and marijuana use in the month before and during pregnancy were used for this analysis: Severe nausea, vomiting, or dehydration N Y.
Open in a separate window. Marijuana pot, bud or hashish hash N Y.
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Conflict of Interest None of the authors identify a conflict of interest. National Center for Health Statistics, author. Health, United States, The pharmacologic and clinical effects of medical cannabis. Medicinal use of marijuana—polling results. The New England Journal of Medicine.
National Survey on Drug Use and Health. Inter-university Consortium for Political and Social Research [distributor]; The good and the bad effects of - trans-deltatetrahydrocannabinol Delta 9-THC on humans. Official Journal of the International Society on Toxinology. Cannabis Treatments in Obstetrics and Genecology: Journal of Cannabis Therapeutics. Survey of medicinal cannabis use among childbearing women: Birth outcomes associated with cannabis use before and during pregnancy.
Alcohol, tobacco, cocaine, and marijuana use: Smoking and marijuana use in pregnancy. Clinical Obstetrics and Gynecology. Low birth weight and preterm births: Official Journal of the California Perinatal Association. Marijuana use and pregnancy: Illicit drug use and adverse birth outcomes: Journal of Urban Health: Bulletin of the New York Academy of Medicine.
Current Drug Abuse Reviews. United States Census Bureau, author. California Journal of Health Promotion. Department of Health and Human Services, author. All participants received an uploading pedometer the Omron HJITC, which stores 42 days of step-count data and has an embedded USB port [ 33 ] , along with general guidance on using the pedometer and instructions for logging onto and uploading data to the study website. To establish a baseline step count that was not influenced by use of the pedometer information, participants were instructed to wear their pedometer for 7 days with the display covered before completing their first upload.
After completing the baseline survey, uploading 7 days of useable pedometer data, and receiving medical clearance, each participant was randomly allocated in a 1: The program also generated an email message to inform participants about their group assignment Internet support or monthly upload and instructions to remove the sticker covering the pedometer display.
The study intervention, based on the Stepping Up to Health program [ 31 , 34 ], consisted of three primary components: The conceptual framework and more detailed description of the intervention components are published elsewhere [ 31 ]. Briefly, participants were instructed to wear their pedometer from the time they got up in the morning until they went to bed. Intervention participants then received weekly email reminders to upload their pedometer data, which was used to establish weekly individualized walking goals.
The step count goal was emailed to the participant each week and posted on the study website. The study website, which was fully accessible to intervention participants, also included graphical and written feedback about their progress toward their walking goals and contained pain- or activity-related motivational and informational messages. These messages included quick tips, which changed every other day, and weekly updates about topics in the news. Back class materials, which included handouts about topics such as body mechanics, use of cold packs, lumbar rolls, and good posture, as well as a video demonstrating specific strengthening and stretching exercises were also available on the website.
Finally, the website based e-community or forum allowed participants to post suggestions, ask questions, and share stories. Topics discussed included mental health concerns, such as depression, strategies for walking such as walking the dog or interesting hiking trails, walking during hot weather and cold weather, and use of alternative pain management strategies such as massage. Research staff participated in and monitored the forum posts as well as used the forum as a venue to generate competitions to encourage meeting walking goals. Usual care participants also received the uploading pedometer and monthly email reminders to upload their pedometer data.
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However, they did not receive any goals or feedback and their access to the study website was limited to completing surveys and reporting adverse events only. Both groups were encouraged to report any health problems via the website, email, or phone. Four weeks after randomization and every 8 weeks thereafter, participants were prompted to complete a survey that asked about specific adverse events eg, heart attack and symptoms such as shortness of breath. This information was closely monitored and participants with potentially serious health-related problems were contacted for further assessment and follow-up.
Outcomes were measured at baseline, 6 months, and 12 months using a survey administered through the study website, or by a mailed questionnaire if the participant could not complete the computerized instrument. The prespecified primary outcome was pain-related disability at 12 months, as measured using the back pain-specific Roland Morris Disability Questionnaire RDQ [ 35 ], and a generic pain-related function measure from the Medical Outcomes Study MOS [ 36 ].
The RDQ, a item scale with higher scores indicating greater disability, has been widely used in back pain studies as a measure of self-perceived disability [ 35 , 37 - 39 ]. The MOS measure assesses the effect of pain on mood and behaviors as well as pain severity, with higher scores also indicating greater functional interference [ 36 ].
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Walking, also a secondary outcome, was measured as the average number of steps per day over the past 7 days using step-count data collected through the pedometer uploads. Other secondary outcomes included pain-related fear-avoidance, measured using the Fear-Avoidance Beliefs Questionnaire physical activity subscale higher scores reflect higher levels of fear-avoidance [ 41 ], and self-efficacy for exercise, measured using the Exercise Regularly Scale, with higher scores indicating higher levels of self-efficacy [ 42 ]. Additional data collected at baseline included age, gender, race, employment status, education level, relationship status, average household income, body mass index, and use of narcotic medications for pain management.
An administrative interface to the website provided data on the number of pedometer uploads and website log-ins. Sample size was based on the RDQ score as the primary outcome with a minimally detectable and clinically meaningful effect size determined as a difference of 0. To detect a difference of 0. The analyst assessing final trial outcomes was blinded to study assignment. All analyses were conducted using an intent-to-treat approach with participants analyzed according to original group assignment. We conducted both complete and all case analyses to assess differences between groups in change in RDQ at 6 and 12 months.
The complete case analysis was conducted using multiple linear regression models with adjustment for baseline values of the RDQ. The all case analysis was conducted using linear mixed-effects models, allowing us to use data from all participants and provide an unbiased estimate of the outcome, assuming data are missing at random [ 45 ].
For example, for our month analysis, RDQ scores at baseline and 12 months were used as dependent variables, with the primary independent variables consisting of an indicator for the intervention group and an interaction term of time by intervention group. Adjustment for covariates was only planned if an imbalance was found between groups at baseline.
As a pragmatic trial we did not screen based on RDQ scores, and some participants had baseline scores that were very low or even 0. Analyses were conducted using Stata Over potential participants Figure 1 were assessed for eligibility.
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Of those determined to be eligible, completed all of the steps in the enrollment process, with randomly allocated to the Internet-mediated intervention and to enhanced usual care. Participants were predominantly male and white, with an average age of 51 years Table 1. The majority had completed some college, were either married or living with someone as a couple, and the mean body mass index was over None of the observed differences in baseline characteristics were statistically significant.
At baseline, mean RDQ scores were greater than 9 in both groups Table 1 , indicating moderately severe back pain-related disability. The mean RDQ score at 6 months was 7. RDQ scores continued to decline between 6 and 12 months in both groups and, while scores for the intervention group remained lower than for usual care, at 12 months these differences were no longer statistically significant.
The MOS function measure also suggested greater improvements in function for intervention compared to usual care participants at 6 months Figure 2 , but none of the adjusted differences were statistically significantly different. At baseline, pain severity was rated at approximately 6 on a scale by both intervention and usual care participants Table 1.
Reported pain levels decreased in both groups at 6 months and remained lower than baseline at 12 months. The greatest change occurred between baseline and 6 months among those in the intervention group 6. Average step counts of slightly more than steps per day at baseline in each group increased at 6 months for intervention patients, with an adjusted difference between groups of more than steps. By 12 months, however, the adjusted difference between groups was only steps. Exercise self-efficacy scores appeared to be the same or lower worse for both groups at 6 months, although the decrease was significantly less for those in the intervention compared to the control group, an adjusted difference of 0.
This difference did not persist at 12 months. There was no difference between groups in the physical activity fear-avoidance scale at any time point. During the study, approximately adverse events were reported by participants by those in usual care and nearly by those in the intervention. These events ranged from calluses to chest pain. However, no major study-related adverse events eg, heart attack were identified for either group. Improving management of chronic pain is a significant public health challenge and moral imperative according to a recent Institute of Medicine report [ 8 ].
More than 1 million adults in the United States have chronic pain, with low back pain being the most frequently reported condition [ 8 ].
Our findings show that an automated, Internet-mediated walking intervention may help to reduce back pain-related disability among patients with chronic back pain, although the benefits did not persist for the entire month study period. Improvement was greatest for those individuals reporting moderate to severe levels of pain-related disability at baseline. The functional results observed are generally similar to those found in other recent studies of non-invasive interventions, such as yoga and massage [ 46 , 47 ].
These studies also tend to show more rapid improvements for those receiving the intervention but with gradual improvements over time for those in usual care. Although we did not have a global health question and so are unable to isolate what proportion would qualify as definitely improved, this classification generally corresponds with other measures that suggest clinical improvement, such as return to work, less pain, improved function, and fewer physician visits [ 48 ].
Thus, we believe that our findings suggest that automated, remotely delivered interventions can be effectively used to promote a more rapid reduction in back pain-related disability and supplement care for patients with chronic low back pain. Further investigation is needed, however, to understand the characteristics of patients who had an early or enduring response to the intervention so that we may better target patients most likely to benefit and broaden the response.
Given the proven benefits of exercise for managing low back pain [ 19 ], a key component of the intervention focused on increasing daily step counts ie, walking. During the first 6 months of the study, we saw an increase of nearly more steps or one-third of a mile per day among intervention compared to usual care participants. Although not a statistically significant difference, we believe that even modest increases in activity can be beneficial. As one intervention participant noted: In fact, just up until recently when I had resumed walking.
Although we do not know specific reasons for this lack of participation, these data suggest that additional strategies to keep people active and engaged may be needed. This could include, for example, an online coaching component, which has been shown to improve adherence to other types of behavioral changes [ 47 - 49 ]. Our monitoring of adverse events showed a higher number of reported events by intervention participants.
This information was, however, collected solely through self-report and we expect that some of the difference in the overall number of events reported between groups could be due to our more frequent contact with intervention participants via email and through the website.
In addition, despite the higher level of musculoskeletal events reported by intervention participants, we found no evidence that the intervention led to excessive harms. Thus, even though more work to understand the circumstances for those reporting musculoskeletal problems or worsening back pain may be required, these findings add to the evidence base to support walking as a generally safe and potentially effective intervention for some patients with chronic low back pain [ 49 - 52 ].
Other potential mechanisms of action are less clear. Despite a marginally greater decrease in pain levels among intervention participants at 6 months, this effect did not persist at 12 months. In addition, while there was a significant difference between groups in self-efficacy for exercise at 6 months, rather than the hypothesized improvement for those in the intervention, both groups reported lower levels of self-efficacy. However, the decline was smaller for those receiving the intervention. The reason for the decrease is not entirely clear but may be largely due to an unrealistic assessment of self-efficacy at baseline [ 53 ].
Among the strengths of our study are the high rate of participant follow-up and our collection of detailed adverse event information. This study also has several limitations. First, patients were recruited from only 1 medical center and the sample was predominantly male. However, based on trials of similar types of interventions, we expect this approach could be even more effective among women [ 54 ].
Second, we are not able to directly compare our results to other types of back pain interventions eg, yoga , although as previously noted the general trajectory of our primary outcome RDQ score appears consistent with recent trials in this area. Third, although a consistent data collection format is generally recommended [ 55 ], we used both Internet-based and paper surveys. However, prior research has demonstrated similar psychometric properties between Internet and paper-and-pencil questionnaires [ 55 ] and specifically equivalence for our primary outcome [ 56 ].
We also believe that using both modes helped to ensure a high follow-up rate. Finally, as a multifaceted intervention, we are not able to determine which elements were most effective and can only draw conclusions about the program as a whole. Nonetheless, our results highlight the importance of providing active support eg, goal setting and feedback to encourage walking as compared with simply giving someone a pedometer to track step counts. In sum, our findings indicate that a facilitated walking intervention that uses an uploading pedometer and the Internet may help to reduce back pain-related disability among patients with chronic back pain, at least in the short term.
Additional support, however, is likely needed to ensure continuing improvements long term. Nevertheless, this type of primarily automated intervention can be used to deliver care with broad reach and could be an efficient way of delivering or supplementing care provided through traditional facility-based programs. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the US government. The study sponsors had no role in the design or conduct of the study; the collection, management, analysis, and interpretation of the data; or the preparation, review, or approval of the manuscript.
Development of the Stepping Up to Health intervention platform was supported by pilot grant funding from the following University of Michigan centers: Technical development of the Stepping Up to Health website could not have been accomplished without the expertise of our Web developers, Michael Hess, with assistance from Elizabeth Wilson and Adrienne Janney.
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Thanks also to Jill Bowdler for assistance with manuscript preparation. RK and MH were involved in study data collection. All authors were involved in drafting the manuscript and revising it for critically important content. All authors have read and approved the final manuscript. National Center for Biotechnology Information , U. J Med Internet Res. Published online Aug Reviewed by Monica Buhrman and Prawit Janwantanakul.
Sarah L Krein ude. Originally published in the Journal of Medical Internet Research http: This is an open-access article distributed under the terms of the Creative Commons Attribution License http: The complete bibliographic information, a link to the original publication on http: This article has been cited by other articles in PMC. Abstract Background Chronic pain, especially back pain, is a prevalent condition that is associated with disability, poor health status, anxiety and depression, decreased quality of life, and increased health services use and costs.
Objective The objective of the study was to determine whether a pedometer-based, Internet-mediated intervention can reduce chronic back pain-related disability. Methods A parallel group randomized controlled trial was conducted with 1: Results Baseline mean RDQ scores were greater than 9 in both groups.
Conclusions Intervention participants, compared with those receiving usual care, reported a greater decrease in back pain-related disability in the 6 months following study enrollment. Introduction Low back pain is a significant health problem with approximately one-half of adults reporting back pain during a given year [ 1 - 3 ]. Methods Design Overview We conducted a parallel group randomized controlled trial with participants allocated in a 1: Randomization After completing the baseline survey, uploading 7 days of useable pedometer data, and receiving medical clearance, each participant was randomly allocated in a 1: Intervention The study intervention, based on the Stepping Up to Health program [ 31 , 34 ], consisted of three primary components: Enhanced Usual Care Usual care participants also received the uploading pedometer and monthly email reminders to upload their pedometer data.
Monitoring of Adverse Events Both groups were encouraged to report any health problems via the website, email, or phone.