Published on 01.11.13 in Vol 15, No 11 (2013): November
MomMoodBooster Web-Based Intervention for Postpartum Depression: Feasibility Trial Results
Background: Postpartum depression (PPD)—the most common complication of childbirth—is a significant and prevalent public health problem that severely disrupts family interactions and can result in serious lasting consequences to the health of women and the healthy development of infants. These consequences increase in severity when left untreated; most women with PPD do not obtain help due to a range of logistical and attitudinal barriers.
Objective: This pilot study was designed to test the feasibility, acceptability, and potential efficacy of an innovative and interactive guided Web-based intervention for postpartum depression, MomMoodBooster (MMB).
Methods: A sample of 53 women who satisfied eligibility criteria (<9 months postpartum, ≥18 years of age, home Internet access and use of personal email, Edinburgh Postnatal Depression Survey score of 12-20 or Patient Health Questionnaire score from 10-19) were invited to use the MMB program. Assessments occurred at screening/pretest, posttest (3 months following enrollment), and at 6 months follow-up.
Results: All six sessions of the program were completed by 87% (46/53) of participants. Participants were engaged with the program: visit days (mean 15.2, SD 8.7), number of visits (mean 20.1, SD 12.2), total duration of visits in hours (mean 5.1, SD 1.3), and number of sessions viewed out of six (mean 5.6, SD 1.3) all support high usage. Posttest data were collected from 89% of participants (47/53) and 6-month follow-up data were collected from 87% of participants (46/53). At pretest, 55% (29/53) of participants met PHQ-9 criteria for minor or major depression. At posttest, 90% (26/29) no longer met criteria.
Conclusions: These findings support the expanded use and additional testing of the MMB program, including its implementation in a range of clinical and public health settings.
Trial Registration: Clinicaltrials.gov NCT00942721; http://clinicaltrials.gov/ct2/show/NCT00942721 (Archived by WebCite at http://www.webcitation.org/6KjYDvYkQ).
J Med Internet Res 2013;15(11):e242
Postpartum depression has been defined to include any major or subsyndromal depression present at any time during the first year after delivery , and it is the most common complication of childbirth [ ]. In terms of prevalence (10-20% of women) and severity, PPD lies between “baby blues” (less severe and quite common affecting 80% of women) and postpartum psychosis (more severe and less common affecting 0.1-0.2% of women) [ ]. Left untreated, PPD has serious consequences [ ]: for the mother, diminished well-being, feelings of failure, difficulties interacting with her infant, her family (partner’s mental health, relationship problems); and for her infant, compromised cognitive and psychosocial development [ - ] and increased risk of mental health difficulties even in adolescence [ ].
PPD is related to a range of biopsychosocial and cultural factors . Previous episodes especially during pregnancy [ ] or family history of mental health problems, low social and emotional support, drug and alcohol abuse, past or present abuse [ ], and major life stressors are all major risk factors for PPD [ ]. Less salient risk factors include marital relationship difficulties, low income, unemployment, and obstetric factors and complications [ ]. Issues encountered during the reproductive year also increase risk for PPD, premature birth, and subsequent hospitalization of the infant (including care in a neonatal intensive care unit) [ - ]. Culturally and linguistically diverse women, especially refugees, asylum seekers, and immigrants have increased risk [ ].
There are also significant economic and social costs (eg, loss of productivity for mother and father, health care costs, personal and broader social and economic costs) to the community. For example, Dagher et al  reported that PPD was related to increased health care services use, which translated into higher costs to providers. Research from the United Kingdom indicates that costs associated with PPD are higher in high-risk women [ ]. An Australian analysis estimated the cost of PPD and anxiety in mothers delivering in 2012 to be $500 million by the time the children reach 2 years of age [ ].
Given the limited empirical evidence supporting use of antidepressant medication with PPD [, ], there is a significant need to develop effective psychosocial treatment approaches. Recent meta-analyses of psychosocial interventions for PPD concluded that they have a moderate beneficial effect [ , ]. Treatment modalities have included counseling [ ], interpersonal psychotherapy (IPT) [ , ], and cognitive behavior therapy (CBT). A wealth of research supports the effectiveness of CBT interventions for depression in general [ , ], and perinatal depression specifically. About two-thirds of depressed individuals receiving CBT remit with treatment [ ] and also have a reduced risk of relapse [ ]. These benefits appear to accrue particularly in individuals with mild to moderate depression [ ]. Milgrom and her colleagues created and conducted a series of successful trials [ , ] using a face-to-face individual PPD treatment program based on an adaptation of the Coping with Depression course by Lewinsohn [ , ] that also included elements of IPT (provided content on interpersonal relationships, an opportunity for partners to become involved and provide input, and a focus on infants).
Although recent trials [, ] have demonstrated that, within a collaborative care model for depression, women suffering from PPD can be screened within a stepped-care treatment protocol during visits to their health care provider [ , ], the data indicate that, overall, fewer than 50% of postpartum women receive help for their depression [ - ]. Many of the available PPD treatment approaches are office-based, which reduces their practicality for new mothers. In addition, patient-level barriers to the uptake of treatment include travel requirements, childcare, stigma, feelings of failure, poor understanding of depression or what help is available, and safety concerns about using prescription medications [ - ]. Provider-level barriers that discourage physicians and medical/clinic staff from becoming more fully involved in PPD screening and treatment include their lack of knowledge and skills due to insufficient training regarding depression and mental health, their fear of liability, the dearth of mental health treatment resources and flexible referral systems, and inadequate reimbursement [ - ].
Web-based PPD treatment may reduce both patient- and provider-level barriers to treatment uptake and thus extend the reach of helpful treatments to underserved mothers suffering from depression. For example, Web-based treatments can reduce feelings of stigma because participation is relatively anonymous and can be completed in women’s homes (thus avoiding travel) at times of their choosing without requiring childcare arrangements. Providers can recommend that women use an evidence-based Web-based PPD treatment program thus alleviating their concerns about training deficits and/or time required to provide treatment.
An increasing number of Web-based depression interventions have emerged [, - ]. The efficacy of these interventions has been demonstrated relative to control conditions in populations with elevated symptoms and, increasingly, in clinically diagnosed groups [ - ]. Face-to-face CBT has also been compared with Web-based CBT treatment. For example, Spek et al [ ] found that both in-person and Web-based CBT interventions were superior to a waitlist control, that no significant differences were found between intervention modality, and that reductions in depressive symptoms were maintained at least 1 year after initiation of Web-delivered CBT. Similar results have emerged in other published comparisons [ , ]. Reviews of the available evidence [ , , , ] indicate that purely self-guided Web-based interventions benefit depressed individuals, but that effect sizes were enhanced when online programs were facilitated by a live coach [ ]. Trained coaches have been shown to enhance the therapeutic alliance of Internet programs by providing low-intensity support [ ] and increasing adherence to online mental health treatments [ , ].
Based on our review to date, there has been only one published report of the results of a Web-based depression intervention for postpartum women. In the randomized controlled trial (RCT) by O’Mahen et al based in England, 910 women with PPD symptoms (>12 on the Edinburgh Postnatal Depression Survey or EPDS ) were randomly assigned to either (1) a full-featured 11-sesssion Web-based behavioral activation intervention (N=462) contextualized for PPD (NetMums) that also included access to features of the popular NetMums website/online community, special chat access to parent-supporters and specialist health visitors, or (2) a treatment as usual condition (N=448) [ , ]. Although there was notable attrition at the 15-week follow-up (61% attrition in the intervention and 64% in the control), results showed significant benefits to the intervention versus the control condition. Among completers at follow-up, there was clinically significant improvement among 61% of women in intervention versus 41% in the control.
The present study reports on the Web-based MomMoodBooster (MMB) program based on Milgrom’s adaptation of the Coping With Depression Course (CWDC)  for postpartum depression [ , , ] as well as an adaptation of the CWDC for Web-based delivery [ ]. MMB was developed and pilot-tested by a multinational team from Oregon Research Institute (ORI), Parent-Infant Research Institute (PIRI) in Melbourne, Australia, and the Iowa Depression and Clinical Research Center (IDCRC). The Australian version of the program was localized for spelling (eg, it was rebranded to MumMoodBooster), word choices, and selected videos. We described the formative research foundation for this MMB in a previous paper [ ]. This report describes the outcome results of a feasibility trial of the MMB program.
Participants and Procedures
Participants (N=53) were recruited from two different research sites (n=27 from our US site in Iowa and n=26 from our Australia site in greater Melbourne). Prospective participants were identified via birth records, nurse/health professional referrals, online advertisements, and news stories to local university and hospital settings.
Upon receipt of a referral or direct contact from a prospective participant, each woman was contacted by a member of the research team to explain the study and obtain informed consent for participation. During the initial contact, a preliminary check of eligibility criteria was conducted. Preliminary screening criteria included <9 months postpartum, ≥18 years of age, home Internet access and use of personal email, and an EPDS score  from 12-20 or a Personal Health Questionnaire (PHQ-9) score [ ] from 10-19. These ranges were chosen to identify women with mild to moderately severe depression. Women satisfying initial eligibility criteria were then mailed a Participant Information and Consent Form for their signature.
Women meeting initial screening criteria then completed a phone-administered Structured Clinical Interview for DSM-IV Disorders (SCID) [, ] and the Hamilton Rating Scale for Depression (HRSD) [ - ] to evaluate the following exclusion criteria: current diagnosis of substance abuse, bipolar disorder or psychotic depression, and/or current treatment for depressive symptoms including antidepressant medication or psychotherapy. A participant’s endorsement of suicidal statements on assessments or to project staff triggered a suicide risk management protocol designed to determine the presence of current plans for self-harm, resulting in an offer of assistance and exclusion from participation in the study. Women who satisfied all inclusion and exclusion criteria were invited to participate in the study and were asked to complete the pretest assessment by visiting the secure research website. Women who did not meet eligibility criteria were offered treatment through the Infant Clinic (Australian site) and/or referral to other services as appropriate (US site). The research protocol and related informed consent procedures were reviewed and approved by the Human Research Ethics Committee of Austin Health in Australia and the Institutional Review Boards of both ORI and the University of Iowa.
Following enrollment, participants worked through the MMB program and received weekly phone calls from a personal coach (psychologist or graduate research assistant at the Australian site or a research assistant at the US site) who encouraged participants to use the program, to practice the recommended strategies, and to report their mood levels on a PHQ-9 assessment. Every effort was made to use the same personal coach for each participant on each call. The program automatically sent email reminders to encourage participants to log into the program.
As described in, assessments occurred at screening/pretest (corresponding to enrollment), a posttest (3 months following pretest), and follow-up (6 months following pretest). At posttest and follow-up, participants were asked to complete questionnaires both by visiting the secure website and completing another assessment by phone. By using the same phone assessor, we hoped to obtain a more sensitive measure of change. Expert phone assessors from our US research site provided assessors in our Australia site with systematic training (videoconferencing and reliability training using audio test cases) in the use of the SCID and HRSD. All phone-based assessments were recorded and reviewed.
Structured Clinical Interview for DSM-IV Disorders
Trained diagnostic interviewers conducted phone-based SCID interviews [, ]. In order to minimize respondent burden, we used SCID Modules A-F, but we did not include the Somatoform, Eating Disorders, and Adjustment Disorder Modules.
Hamilton Rating Scale for Depression
Interviewers also administered the HRSD [, - ] by phone. Scoring is based on the sum of 24 items. The maximum overall score for the HRSD-24 is 69. For the current study, Cronbach alpha=.76.
Edinburgh Postnatal Depression Scale
During screening, participants were asked to complete the EPDS, a brief, simple self-rated, 10-item measure developed to screen for symptoms of postpartum depression [, ]. Responses are rated from 0 to 3 and summed to yield the score with a maximum overall score of 30.
We measured maternal age, delivery date and gestation, parity, education, history of previous treatment for depression, and household income.
Patient Health Questionnaire
Participants were asked to complete six separate PHQ-9 assessments from pretest, posttest, and follow-up. Personal coaches administered the PHQ-9 during phone calls that corresponded to Sessions 3 and 5 of the MMB program. These serial PHQ-9 assessments were used for program evaluation, to provide participants with a useful assessment of their status, and as an important safety check of participant status [, - ]. PHQ-9 scores showing a 5-point or greater escalation from pretest triggered a safety protocol, as did endorsement of the PHQ-9 suicidality item. The maximum overall score for the PHQ-9 is 27. For the current study, Cronbach alpha=.76. To evaluate the clinical significance of the intervention effects, we calculated the minimal clinically important difference (MCID [ ]) based on Lowe et al [ ], which represents a reduction in the PHQ-9 score of 5 points or greater. Thus, pretest-posttest changes on the PHQ-9 of ≥5 points represented a clinically important difference. For the current study, Cronbach alpha=.76.
Automatic Thoughts Questionnaire
Participants were asked to indicate how frequently over the previous week they had negative thoughts using the 30-item Automatic Thoughts Questionnaire (ATQ) [, ] (eg, “My life is a mess”). Value options range from 0 to 4 (0=Not at all to 4=All of the time) with a maximum score of 120. For the current study, Cronbach alpha=.92.
Behavioral Activation for Depression Scale
We used the 25-item Behavioral Activation for Depression Scale (BADS) to measure changes in activation, avoidance/rumination, work/school impairment, and social impairment (eg, “I stayed in bed for too long even though I had things to do”) . Value options range from 0 to 6 with a maximum score of 150. For the current study, Cronbach alpha=.83.
Dyadic Adjustment Scale
We assessed women’s relationships with their partners using the Dyadic Adjustment Scale-7 (DAS-7) , an abbreviated version of the Dyadic Adjustment Scale [ ]. The general satisfaction score was calculated as the sum of all scores (maximum score=36). For the current study, Cronbach alpha=.85
Parenting Sense of Competence
We included the Parenting Sense of Competence (PSOC) efficacy scale  that asks the participant to describe her extent of agreement with 7 items designed to assess whether she is knowledgeable and competent in being a mother [ ] (eg, “I honestly believe I have all the skills necessary to be a good mother to my baby”). Value options ranged from 1 to 6 (1=Strongly Disagree to 6=Strongly Agree) with a maximum score of 42. For the current study, Cronbach alpha=.90.
Based on the work of Bandura  and Maciejewski et al [ ], we used 8 items to assess participant self-efficacy or confidence in being able to work with the program to reduce feelings of depression at pretest and posttest. The question asked was, “During the past week, including today, how confident are you in your ability to… (1) increase your daily pleasant activities?; (2) control your negative thinking?; (3) increase your positive thinking?; (4) get support when you need it?; (5) keep track of your mood?; (6) reduce tension using relaxation?; (7) set realistic goals for yourself?; and (8) manage your mood?” Value options ranged from 1 to 5 (1=Not At All Confident to 5=Very Confident). Self-efficacy score was computed as the mean across 8 items. For the current study, Cronbach alpha=.88.
We used industry-standard website analytic tools and planned database flags recommended by Peterson  to track visit patterns including the date/time for each webpage viewed, which enabled us to unobtrusively measure visit frequency and duration. We also considered ways that participants were able to initiate interactions with the program (see ) that shared similar characteristics, as in initiate interaction only (eg, play a video or tutorial), enter personal data into an activity (eg, typed in reasons into a list, completed a drag and drop activity, completed online activities as part of recommended homework), and personalized features of the program (eg, set goals for daily pleasant activities, updated tracking of mood and activities, uploaded personal pictures).
Personal Coach Call Metrics
Personal coaches also tracked the number and duration of calls with participants. After each call, personal coaches provided an impression of their working alliance with the participant (response options: 1=minimal, 2=partial, 3=good, 4=excellent) and the level of distraction during the call (response option: 1=none/limited, 2=some, 3=a lot).
Program Helpfulness (Self-Report by Phone at Posttest)
We used open-ended items to ask participants to identify aspects of the program that were most helpful and least helpful. We also asked participants if they would recommend the program to other depressed postpartum women.
Program Usability (Self-Report Online at Posttest)
We obtained a quantitative measure of usability by asking participants to complete our adapted version of the System Usability Scale (SUS) [, ], a 10-item scale that asked the participant to rate the degree to which she agreed (1=Strongly Disagree to 5=Strongly Agree) with positive and negative descriptions of a Web-based program (eg, “I think that I would like to use this website frequently”) [ ]. The maximum score (indicating maximum usability) is 100. For the current study, Cronbach alpha=.80.
We developed the MMB program using an iterative formative research process that included focus groups and usability testing . A detailed description of this process and a schematic depiction of the MMB program is available in our earlier publication [ ]. The MMB program also includes three complementary websites: (1) a personal coach portal to enable coaches to review the progress each participant has made going through the program, (2) a simplified Partner Support website designed to provide participant partners with information about PPD and an overview of MMB, and (3) an administrative website that enabled research staff to monitor completion of the assessments and other elements of the research project. The MMB program was designed to be fully scalable and to run on PC and Mac computers using various current browsers without plugins or applications. Java scripting, HTML+CSS, and Dynamic HTML were used to deliver interactive content.
The program consisted of the following six sequential sessions with each successive session becoming available weekly. Sessions were as follows: (1) Getting Started, (2) Managing Mood, (3) Increasing Pleasant Activities, (4) Managing Negative Thoughts, (5) Increasing Positive Thoughts, and (6) Planning for the Future. Each session opened with an autoplay host video that introduces the session goals. Webpages delivered content using text, programmed interactions, animations, and videos to present program content. Tunnel architecture  was used to guide participants through the six sessions. While each successive program session could be accessed weekly, the schedule was flexible in that participants could take an additional week to complete any session. Coach calls corresponded to each program week. Thus, it was possible for the MMB program to be completed in 6-12 weeks with 6-12 coach calls.
The program includes a number of features designed to encourage participant engagement and behavior change (seeand - ). For example, each day the program encouraged participants to enter ratings of their mood and to note the number of pleasant activities they engaged in. They were also able to type in personal lists, view videos and animations, and access a library of relevant articles on communication skills, getting support, managing stress, managing time, solving problems, sleep and caring for baby, baby’s needs, and relationship with partner.
Because social isolation and stigma are common in this population, MMB includes a private peer-based Web forum in which mothers can post messages as well as read and interact with the messages of other program participants. Finally, the program could be used by participants to send an email invitation to their partner encouraging them to visit a separate MMB informational website that described postpartum depression, the MMB program, and the important role of partners play [, ].
As research shows, receiving email reminders can help to encourage greater adherence with Web-based interventions , MMB participants were sent automated email reminders to encourage their engagement with the Web-based program as well as to prompt them to complete the online assessments. Participants were able to access the online program for 6+ months following enrollment.
Personal Coach Calls
The entire program was facilitated by a series of phone calls with a personal coach. All coaches were graduate research assistants or research psychologists who had received training in the content of the MMB program, their roles as coaches versus therapists/counselors, and in their data collection responsibilities. Coach training started with a guided tour of the MMB program and its coach portal that summarized participant use of the features of each session. This was followed by a videoconference that included review of the coach manual that contained detailed scripts for each call, the coach data collection responsibilities, and a discussion of the role of the coach and the rationale for making calls (ie, to provide a human voice behind the automated program, to help each participant problem solve possible barriers to using the program, and to encourage program use). All coach calls were audiorecorded, and a subset was selected to monitor fidelity of implementation as well as reliability of phone-administered assessments.
Changes in PHQ-9 scores across time were evaluated using an unconditional growth model nesting repeated measures within individuals. This multilevel model includes time as the only predictor, coded as the number of weeks since the pretest assessment, and allows the number and spacing of measurement occasions to vary across persons . A self-efficacy score was computed as the mean across 8 items. Pretest to 3-month posttest and pretest to 6-month follow-up comparisons on the ATQ, BADS, DAS-7, PSOC, and self-efficacy were evaluated using paired samples t tests.
All analyses involved an intent-to-treat approach whereby missing data were addressed in one of two ways recommended by Schafer and Graham . We used a model-based maximum likelihood procedure in the analysis of PHQ-9 data in which parameter estimates were computed based on all available raw data. We used detailed data on participant engagement as person-level predictors of the linear and quadratic slope parameters specified in the unconditional PHQ-9 growth model. We also used the multiple imputation procedure in SPSS version 21 to account for missing data for our analysis of the ATQ, BADS, DAS-7, PSOC, and self-efficacy outcomes. Our multiple imputation procedure was fully conditional and used the iterative Markov chain Monte Carlo method to generate 20 complete datasets using all outcomes across time as predictors of missing values. The imputation model for each variable was a linear regression and included a constant term and main effects of predictor variables. Paired samples t tests were conducted for each measure across each of the 20 imputed datasets and reported pooled estimates in the results. To supplement tests of statistical significance, we computed partial point-biserial r as a measure of effect size in accordance with Rosenthal [ ]. Partial point-biserial r was defined as √(t2 / (t2 + df)); small effect size=0.14, medium effect size=0.36, and large effect size=0.51 [ ].
Participant Characteristics and Study Attrition
Of the women who started the study, two were withdrawn because of concerns regarding self-harm and one woman withdrew of her own volition because she reported that she was feeling better and no longer wanted to be in the study. The resulting sample of 53 study participants had a mean age of 31.9 years (SD 5.1), a mean of 39.1 weeks (SD 2.4) gestation when their baby was born, and a mean number of 2.0 (SD 1.1) children. Mean baby age at the pretest was 5.5 months (SD 2.9). Participants were relatively well educated (14/53, 26% reported having graduate or postgraduate degrees) and 59% (31/53) reported annual family income of at least $60,000. Based on the SCID at screening, 49% (26/53) met criteria for DSM-IV major depressive disorder. Pretest characteristics of participants are presented in.
Of the remaining participants, 87% (46/53) completed all six sessions in the program. Posttest data were collected from 89% (47/53) on all key measures with the exception of the HRSD (45/53, 85%). Follow-up data at 6 months were collected from 87% of women (46/53). The extent to which attrition threatened the external validity of the study was evaluated using contingency table analyses and t tests. Overall attrition was 13% (7/53) from pretest to 6-month follow-up. Attrition was not associated with demographic characteristics or pretest values on the outcome measures. Given the minimal rates of missing data and the low likelihood of bias due to attrition, maximum likelihood estimation and multiple imputation procedures were appropriate for modeling potential intervention effects. Note that imputation was used to handle both types of missing data (ie, fully missing and “present” but with partial data).
Primary Depression Outcomes
Patient Health Questionnaire Scores
As shown in, PHQ-9 scores decreased from pretest (mean 12.6, SD 4.1) to posttest (mean 5.0, SD 4.4) and the 6-month follow-up (mean 4.2, SD 3.9). Changes from pretest were statistically significant (P<.001) with large effects at posttest (partial r=.77) and 6-month follow-up (partial r=.82). In terms of clinical significance, at pretest, 55% (29/53) participants met PHQ-9 criteria for minor or major depression. At posttest, 90% (26/29) no longer met these PHQ-9 criteria. Results also indicated that 77% (36/47) of the participants experienced a minimal clinically important difference (ie, ≥5 point decrease) in their PHQ-9 depression scores from pretest to posttest.
depicts the observed and model-implied trajectory of PHQ-9 scores from pretest through the 6-month follow-up. A visual inspection of the data and a likelihood ratio (LR) test suggested that including a linear and quadratic growth parameter resulted in significantly better fit compared to a linear-only model (LR statistic with 2 degrees of freedom=36.79, P<.001). The statistical model that included linear and quadratic growth (-2 log-likelihood=1429.06, Akaike information criterion=1437.06, Bayesian information criterion=1451.25) implied an average pretest PHQ-9 score of 11.49 (SE 0.48), which decreased over time indicating a significant improvement in participant depression. Specifically, the model revealed a significant initial linear decrease (estimate=-0.79, SE 0.07, P<.001, partial r=.61) that significantly decelerated over time (estimate=0.02, SE 0.002, P<.001, partial r=.57). We also tested for differential trajectories in PHQ-9 scores between US and Australian participants by adding the main effect of region and the time by region interactions to the unconditional growth model described earlier. None of these parameters were statistically significant (P>.50), suggesting similar PHQ-9 trajectories between US and Australian participants.
As noted in, HRSD scores also decreased from pretest (mean 16.9, SD 6.9) to posttest (mean 7.0, SD 5.6) and the 6-month follow-up (mean 6.6, SD 6.8). Changes from pretest were statistically significant (P<.001) with large effects at posttest (partial r=.75) and 6-month follow-up (partial r=.71).
Secondary Outcomes and Putative Mechanisms of Change
also provides descriptive statistics and the pretest to posttest and pretest to 6-month follow-up comparisons on the ATQ, BADS, DAS-7, PSOC, and self-efficacy measures. Statistically significant and large effects from pretest to posttest were obtained for the ATQ (partial r=.66), BADS (partial r=.77), PSOC (partial r=.62), and self-efficacy (partial r=.51). From pretest to 6-month follow-up, statistically significant and large effects were obtained on the ATQ (partial r=.57), BADS (partial r=.70), PSOC (partial r=.60), and self-efficacy (partial r=.68). Measures of the DAS from pretest to posttest and follow-up did not show significant change.
Website Engagement and Program Usability
Unobtrusive program use data indicated that mothers were engaged with the program: visit days (mean 15.2, SD 8.7); number of visits (mean 20.1, SD 12.2); total duration of visits in hours (mean 5.1, SD 1.3); and number of sessions viewed out of six (mean 5.6, SD 1.3). A total of 96% (51/53) of participants kept track of their daily mood ratings at least once (mean 38.1 days tracked, SD 25.6) and 92% (49/53) tracked the pleasant activities they wanted to accomplish each day (mean 29.2 days tracked, SD 23.7). The website forum provided the opportunity to post and view content; 38% (19/53) of mothers (mean 1.5, SD 2.9) posted forum content, and 74% (39/53) (mean 30.2, SD 26.8) viewed content. In addition, the MMB partner support website was accessed by 34% (18/53) of the participants’ partners. Results on the System Usability Scale [, ] administered at posttest provide a quantitative measure of program ease of use. The mean System Usability Scale score was 84.4 (SD 11.6, range 52.5-100), which translates to a usability grade of “A” for the MMB program.
We explored associations between engagement and trajectories of PHQ-9 scores within a series of conditional growth models. These models included program engagement indicators as a composite measure as well as separately. Overall, the statistical models implied that program engagement was associated with additional decreases in PHQ-9 from pretest through follow-up. Specifically, the composite measure of program engagement was significantly related to the PHQ-9 linear slope parameter (estimate=-0.24, P=.021, partial r=.37). The linear slope parameter was also significantly related to the number of visit days to the program (estimate=-0.02, P=.043, partial r=.31) and selected engagement activities (see): the proportion of list activities completed (estimate=-0.02, P=.006, partial r=.43) and the proportion of activities engaged in that involved entering personal data (estimate=-0.01, P=.008, partial r=.44). Interestingly, the overall duration of program use was not significantly associated with the trajectories of the PHQ-9 scores.
Personal Coach Calls
A total of 98% (52/53) of women agreed to receive personal coach calls. Coaches made a mean of 5.65 calls to each assigned participant (N=52; SD 1.58, Min=1; Max=9). Mean total contact duration per participant summed over all calls was 96.99 minutes (N=52; SD 49.21; Min=6.10; Max=212.07). Personal coaches reported, on average, that they had a good working alliance with participants (mean 3.07, SD 0.44) and reported low levels of distraction during the calls (mean 1.26, SD 0.35).
At posttest, participants reported being quite satisfied with MMB features (mean 3.3, SD 0.4 on a 4-point scale: Not at all satisfied to Very satisfied), and they rated personal coach calls as being helpful (mean 3.4, SD 0.9 on 4-point scale: Not at all helpful to Very helpful). Responses to open-ended questions about satisfaction are noted in.
Use of Other Programs
At posttest we also asked participants “Since you enrolled in the MomMoodBooster program 3 months ago, which of the following products or programs have you used to manage your mood?”. A total of 30 out of 48 participants reported as follows: 12 (25.0%) read self-help books, 7 (14.6%) took medication for depression, 6 (12.5%) participated in an individual treatment program, 3 (6.3%) used hypnosis or acupuncture, 1 (2.1%) participated in a group treatment program, 1 (2.1%) participated in another Internet treatment program, and 30 (62.5%) participants indicated they had not participated in any other programs/products. Use of other programs for mood management was not significantly associated with the trajectories of the PHQ-9 scores.
Pilot study results described in this report—when combined with results of our formative research —provide comprehensive evidence supporting MomMoodBooster, an innovative Web-based intervention for postpartum depression. Pilot study participants, a clinical sample of 53 women recruited from the United States and Australia, were very engaged with the MomMoodBooster program: 87% completed the 6-month follow-up assessment, they viewed an average of 5.6 out of the 6 sessions, spent an average of more than 5 hours using the program, and spent an average of more than 95 minutes on personal coach calls. Their average number of 20.1 program visits compares quite favorably to results reported for many other Web-based depression interventions [ ]. Participants also reported positive ratings regarding program usability, which was mirrored in their favorable ratings and comments regarding the program, including coach calls.
It is important to note that the relationship between participant engagement in the program and depression outcomes warrants further analysis as our measure of program use duration was not significantly associated with improvement in depression as measured by trajectories of the PHQ-9 scores. Elsewhere  we have recommended that there may not be simple dose:response relationships between engagement and outcome and that composite measures incorporating several dimensions of program usage need to be explored in this regard.
Over the course of the program, participants showed significant improvements on clinician-rated HRSD and self-reported PHQ-9 assessments, and they sustained those improvements over the 6-month follow-up period. Fully 77% reported experiencing clinically important improvement in their PHQ-9 scores. Putative mechanisms of change showed corresponding improvements.
Our 13% participant attrition is slightly higher than what has been reported for telephone-delivered therapies , and notably lower than the 25% to 50% reported in face-to-face psychotherapy and the sizable attrition rates reported in self-help Internet interventions [ ]. Importantly, attrition was much lower than the nearly 60% attrition rate reported in a published paper on a Web-based intervention with women with PPD [ ] and a third of that reported by Milgrom in her group-based CBT intervention for postpartum depression [ ], the treatment approach embodied in the MMB program.
We believe that the highly encouraging results for participants using the MMB program were associated with three factors: (1) our adaptation and contextualization to PPD of Lewinsohn’s Coping with Depression Course, as embodied in Milgrom’s work, (2) MMB’s online engagement activities that encouraged participants to be actively involved, to spend time, and to follow treatment recommendations, and (3) personal coach calls that provided a key element of supportive accountability, which encouraged engagement and follow-through.
There are several study limitations that should also be noted. For example, we used a quasi-experimental design without a randomized controlled condition, thus we were not able to control for potential threats to the internal validity such as biases due to selection or maturation effects. In addition, our relatively small sample size may limit the generalizability of the study findings. We also recruited a convenience sample, which may not be representative of depressed postpartum women, generally. In addition, participants were relatively well educated and had a relatively high socioeconomic status. Finally, we did not assess the maintenance of the treatment benefits beyond 6 months.
We agree with the conclusion expressed by Lewis et al : “Given the time, cost, and childcare constraints of traditional interventions for postpartum depression, evaluations of new and innovative interventions are needed.” Based upon the promising results of our pilot study, we believe that the Web-based MomMoodBooster program represents just such an innovative treatment option. Next steps worthy of consideration include additional research. For example, controlled research is needed to evaluate MMB compared to alternative approaches when implemented within extant treatment programs based in real-world settings, such as in telephone-administered treatment programs [ - ], depression care management programs [ ], nurse home visitations to pregnant and postpartum women [ ], and in depression treatment provided in physician offices [ , ]. MMB would seem to be particularly appropriate within a stepped-care model as it could offer a low-cost, high-reach option as a preliminary treatment step [ , ] and/or in conjunction with other, more intensive “high-touch” treatments. Additional research might also examine the role of the personal coach. For example, rather than using research staff as coaches, it would be useful to test the use of endogenous providers as coaches. And since the cost and feasibility of providing 6 scheduled personal coaching calls may limit implementation opportunities, additional research might consider ways to provide fewer coach calls or provide a stepped-care approach that would tailor calls to the expressed interests of the recipient.
It would also be helpful to determine how program content might be adapted and delivered to reach low-income and minority postpartum depressed women by accommodating cultural differences , learning styles, and preferences in terms of tools/platforms to access program content (eg, use of smartphones is closing the “digital divide” [ , ]).
Finally, MMB could be expanded to include content on antenatal depression and/or content to enhance mother:infant interactions, two under-recognized and often untreated problems [, ] that have profound effects on maternal and infant well-being and health. In addition to being a risk factor for PPD, antenatal depression is related to more frequent pre-eclampsia [ ], preterm birth [ ], low birth-weight [ ], and adverse obstetric outcomes [ ]. It also diminishes capacity for maternal self-care as it can be accompanied by inadequate nutrition, drug and alcohol abuse, and poor prenatal clinic attendance, all of which can further compromise the health of mother and baby [ , ]. Because research shows that treating postpartum depression does not improve poor mother:infant interactions, which results in risk to maternal and infant well-being and health [ , , ], then additional program content might be included in MMB in order to address this important area.
The MomMoodBooster feasibility pilot study was supported by grant 5R01-MH084931 from the National Institute of Mental Health of the National Institutes of Health (Principal Investigators: Drs Brian G Danaher, Jeannette Milgrom, and Scott Stuart). MMB technology development was accomplished with assistance from Steve Christensen, Tom Jacobs, Ethan Sletteland, and Toan Tran from InterVision Media (Eugene, OR) and Timothy Woolley from IEQ Technology (Springfield, OR). We also acknowledge the important contributions of ORI colleagues: Edward Lichtenstein, Ryann Crowley, Coleen Hudkins, and Katie Clawson. Cartoons that enhanced the MomMoodBooster library articles and the Partner Support Program were drawn by Bev Aisbett.
Conflicts of Interest
- O'Hara MW, McCabe JE. Postpartum depression: current status and future directions. Annu Rev Clin Psychol 2013;9:379-407. [CrossRef] [Medline]
- Beck CT. State of the Science on postpartum depression: what nurse researchers have contributed--part 1. MCN Am J Matern Child Nurs 2008;33(2):121-126. [CrossRef] [Medline]
- Field T, Diego M, Hernandez-Reif M. Prenatal depression effects and interventions: a review. Infant Behav Dev 2010 Dec;33(4):409-418 [FREE Full text] [CrossRef] [Medline]
- Beck CT. The effects of postpartum depression on child development: a meta-analysis. Arch Psychiatr Nurs 1998 Feb;12(1):12-20. [Medline]
- Milgrom J, Westley D, Gemmill AW. The mediating role of maternal responsiveness in some longer term effects of postnatal depression on infant development. Infant Behavior and Development 2004 Dec;27(4):443-454. [CrossRef]
- Milgrom J, Ericksen J, McCarthy R, Gemmill AW. Stressful impact of depression on early mother–infant relations. Stress and Health 2006 Oct;22(4):229-238. [CrossRef]
- Kaplan PS, Danko CM, Diaz A, Kalinka CJ. An associative learning deficit in 1-year-old infants of depressed mothers: role of depression duration. Infant Behav Dev 2011 Feb;34(1):35-44. [CrossRef] [Medline]
- Goodman SH, Gotlib IH. Risk for psychopathology in the children of depressed mothers: a developmental model for understanding mechanisms of transmission. Psychol Rev 1999 Jul;106(3):458-490. [Medline]
- Pawlby S, Hay DF, Sharp D, Waters CS, O'Keane V. Antenatal depression predicts depression in adolescent offspring: prospective longitudinal community-based study. J Affect Disord 2009 Mar;113(3):236-243. [CrossRef] [Medline]
- Buultjens M, Murphy G, Robinson PH, Milgrom J. The perinatal period: A literature review from the biopsychosocial perspective. Clinical Nursing Studies 2013;1(3):19-31. [CrossRef]
- Leigh B, Milgrom J. Risk factors for antenatal depression, postnatal depression and parenting stress. BMC Psychiatry 2008;8:24 [FREE Full text] [CrossRef] [Medline]
- Howard LM, Oram S, Galley H, Trevillion K, Feder G. Domestic violence and perinatal mental disorders: a systematic review and meta-analysis. PLoS Med 2013;10(5):e1001452 [FREE Full text] [CrossRef] [Medline]
- Milgrom J, Gemmill AW, Bilszta JL, Hayes B, Barnett B, Brooks J, et al. Antenatal risk factors for postnatal depression: a large prospective study. J Affect Disord 2008 May;108(1-2):147-157. [CrossRef] [Medline]
- Robertson E, Grace S, Wallington T, Stewart DE. Antenatal risk factors for postpartum depression: a synthesis of recent literature. Gen Hosp Psychiatry 2004;26(4):289-295. [CrossRef] [Medline]
- Bergström E, Wallin L, Thomson G, Flacking R. Postpartum depression in mothers of infants cared for in a Neonatal Intensive Care Unit – Incidence and associated factors. Journal of Neonatal Nursing 2012 Aug;18(4):143-151. [CrossRef]
- Vigod SN, Villegas L, Dennis CL, Ross LE. Prevalence and risk factors for postpartum depression among women with preterm and low-birth-weight infants: a systematic review. BJOG 2010 Apr;117(5):540-550. [CrossRef] [Medline]
- Centers for Disease ControlPrevention (CDC). Prevalence of self-reported postpartum depressive symptoms--17 states, 2004-2005. MMWR Morb Mortal Wkly Rep 2008 Apr 11;57(14):361-366 [FREE Full text] [Medline]
- Collins CH, Zimmerman C, Howard LM. Refugee, asylum seeker, immigrant women and postnatal depression: rates and risk factors. Arch Womens Ment Health 2011 Feb;14(1):3-11. [CrossRef] [Medline]
- Dagher RK, McGovern PM, Dowd BE, Gjerdingen DK. Postpartum depression and health services expenditures among employed women. J Occup Environ Med 2012 Feb;54(2):210-215. [CrossRef] [Medline]
- Petrou S, Cooper P, Murray L, Davidson LL. Economic costs of post-natal depression in a high-risk British cohort. Br J Psychiatry 2002 Dec;181:505-512 [FREE Full text] [Medline]
- Beyondblue. Valuing perinatal health: The consequences of not treating perinatal depression and anxiety. 2012. URL: http://www.beyondblue.org.au/docs/default-source/8.-perinatal-documents/bw0079-report-valuing-perintal-health.pdf?sfvrsn=2 [accessed 2013-10-24] [WebCite Cache]
- Howard LM, Hoffbrand S, Henshaw C, Boath L, Bradley E. Antidepressant prevention of postnatal depression. Cochrane Database Syst Rev 2005(2):CD004363. [CrossRef] [Medline]
- Cuijpers P, Brännmark JG, van Straten A. Psychological treatment of postpartum depression: a meta-analysis. J Clin Psychol 2008 Jan;64(1):103-118. [CrossRef] [Medline]
- Dennis CL, Hodnett E. Psychosocial and psychological interventions for treating postpartum depression. Cochrane Database Syst Rev 2007(4):CD006116. [CrossRef] [Medline]
- MacArthur C, Winter HR, Bick DE, Lilford RJ, Lancashire RJ, Knowles H, et al. Redesigning postnatal care: a randomised controlled trial of protocol-based midwifery-led care focused on individual women's physical and psychological health needs. Health Technol Assess 2003;7(37):1-98 [FREE Full text] [Medline]
- Stuart S, O'Hara MW, Gorman LL. The prevention and psychotherapeutic treatment of postpartum depression. Arch Womens Ment Health 2003 Aug;6 Suppl 2:S57-S69. [CrossRef] [Medline]
- O'Hara MW, Stuart S, Gorman LL, Wenzel A. Efficacy of interpersonal psychotherapy for postpartum depression. Arch Gen Psychiatry 2000 Nov;57(11):1039-1045. [Medline]
- Elkin I, Shea MT, Watkins JT, Imber SD, Sotsky SM, Collins JF, et al. National Institute of Mental Health Treatment of Depression Collaborative Research Program. General effectiveness of treatments. Arch Gen Psychiatry 1989 Nov;46(11):971-82; discussion 983. [Medline]
- NIMH. Breaking ground, breaking through: The strategic plan for mood disorders research of the National Institute of Mental Health. 2003. URL: http://www.nimh.nih.gov/about/strategic-planning-reports/breaking-ground-breaking-through--the-strategic-plan-for-mood-disorders-research.pdf [accessed 2013-10-24] [WebCite Cache]
- Gloaguen V, Cottraux J, Cucherat M, Blackburn IM. A meta-analysis of the effects of cognitive therapy in depressed patients. J Affect Disord 1998 Apr;49(1):59-72. [Medline]
- Clarke G, Eubanks D, Reid E, Kelleher C, O'Connor E, DeBar LL, et al. Overcoming Depression on the Internet (ODIN) (2): a randomized trial of a self-help depression skills program with reminders. J Med Internet Res 2005;7(2):e16 [FREE Full text] [CrossRef] [Medline]
- Milgrom J, Martin PR, Negri LM. Treating postnatal depression: a psychological approach for health care practitioners. Chichester: Wiley; 1999.
- Milgrom J, Negri LM, Gemmill AW, McNeil M, Martin PR. A randomized controlled trial of psychological interventions for postnatal depression. Br J Clin Psychol 2005 Nov;44(Pt 4):529-542. [CrossRef] [Medline]
- Cuijpers P, Muñoz RF, Clarke GN, Lewinsohn PM. Psychoeducational treatment and prevention of depression: the "Coping with Depression" course thirty years later. Clin Psychol Rev 2009 Jul;29(5):449-458. [CrossRef] [Medline]
- Yawn BP, Dietrich AJ, Wollan P, Bertram S, Graham D, Huff J, TRIPPD practices. TRIPPD: a practice-based network effectiveness study of postpartum depression screening and management. Ann Fam Med 2012 Jul;10(4):320-329 [FREE Full text] [CrossRef] [Medline]
- Gjerdingen D, Katon W, Rich DE. Stepped care treatment of postpartum depression: a primary care-based management model. Womens Health Issues 2008 Jan;18(1):44-52. [CrossRef] [Medline]
- Pollack LO, Segre LS, O'Hara MW, Stuart S. Postpartum depression: the distribution of severity in a community sample. Arch Womens Ment Health 2011 Aug;14(4):363-364 [FREE Full text] [CrossRef] [Medline]
- Cox J, Holden J. Perinatal Mental Health: A Guide to the Edinburgh Postnatal Depression Scale. London: The Royal College of Psychiatrists; 2003.
- Austin MP, Frilingos M, Lumley J, Hadzi-Pavlovic D, Roncolato W, Acland S, et al. Brief antenatal cognitive behaviour therapy group intervention for the prevention of postnatal depression and anxiety: a randomised controlled trial. J Affect Disord 2008 Jan;105(1-3):35-44. [CrossRef] [Medline]
- Watt S, Sword W, Krueger P, Sheehan D, Ontario Mother & Infant Survey. A cross-sectional study of early identification of postpartum depression: implications for primary care providers from The Ontario Mother & Infant Survey. BMC Fam Pract 2002 Apr 11;3:5 [FREE Full text] [Medline]
- Gentile S. Use of contemporary antidepressants during breastfeeding: a proposal for a specific safety index. Drug Saf 2007;30(2):107-121. [Medline]
- Bilszta J, Ericksen J, Buist A, Milgrom J. Women's experience of postnatal depression - beliefs and attitudes as barriers to care. Aust J Adv Nurs 2010;27(3):44-54.
- Murray L, Woolgar M, Murray J, Cooper P. Self-exclusion from health care in women at high risk for postpartum depression. Journal of Public Health 2003 Jun 01;25(2):131-137. [CrossRef]
- Byatt N, Biebel K, Friedman L, Debordes-Jackson G, Ziedonis D. Women's perspectives on postpartum depression screening in pediatric settings: a preliminary study. Arch Womens Ment Health 2013 Oct;16(5):429-432. [CrossRef] [Medline]
- Byatt N, Biebel K, Debordes-Jackson G, Lundquist RS, Moore Simas TA, Weinreb L, et al. Community mental health provider reluctance to provide pharmacotherapy may be a barrier to addressing perinatal depression: a preliminary study. Psychiatr Q 2013 Jun;84(2):169-174. [CrossRef] [Medline]
- Byatt N, Biebel K, Friedman L, Debordes-Jackson G, Ziedonis D, Pbert L. Patient's views on depression care in obstetric settings: how do they compare to the views of perinatal health care professionals? Gen Hosp Psychiatry 2013 Aug 19:436-449. [CrossRef] [Medline]
- Byatt N, Simas TA, Lundquist RS, Johnson JV, Ziedonis DM. Strategies for improving perinatal depression treatment in North American outpatient obstetric settings. J Psychosom Obstet Gynaecol 2012 Dec;33(4):143-161. [CrossRef] [Medline]
- Olson AL, Kemper KJ, Kelleher KJ, Hammond CS, Zuckerman BS, Dietrich AJ. Primary care pediatricians' roles and perceived responsibilities in the identification and management of maternal depression. Pediatrics 2002 Dec;110(6):1169-1176. [Medline]
- Chaudron LH, Szilagyi PG, Campbell AT, Mounts KO, McInerny TK. Legal and ethical considerations: risks and benefits of postpartum depression screening at well-child visits. Pediatrics 2007 Jan;119(1):123-128 [FREE Full text] [CrossRef] [Medline]
- Leiferman JA, Dauber SE, Scott K, Heisler K, Paulson JF. Predictors of maternal depression management among primary care physicians. Depress Res Treat 2010;2010:671279 [FREE Full text] [CrossRef] [Medline]
- Christensen H, Griffiths KM, Jorm AF. Delivering interventions for depression by using the internet: randomised controlled trial. BMJ 2004 Jan 31;328(7434):265 [FREE Full text] [CrossRef] [Medline]
- Christensen H, Griffiths KM, Mackinnon AJ, Brittliffe K. Online randomized controlled trial of brief and full cognitive behaviour therapy for depression. Psychol Med 2006 Dec;36(12):1737-1746. [CrossRef] [Medline]
- Clarke G, Reid E, Eubanks D, O'Connor E, DeBar LL, Kelleher C, et al. Overcoming depression on the Internet (ODIN): a randomized controlled trial of an Internet depression skills intervention program. J Med Internet Res 2002 Dec;4(3):E14 [FREE Full text] [CrossRef] [Medline]
- Galler JR, Harrison RH, Ramsey F, Forde V, Butler SC. Maternal depressive symptoms affect infant cognitive development in Barbados. J Child Psychol Psychiatry 2000 Sep;41(6):747-757. [Medline]
- Griffiths KM, Christensen H. Internet-based mental health programs: a powerful tool in the rural medical kit. Aust J Rural Health 2007 Apr;15(2):81-87. [CrossRef] [Medline]
- Farrer L, Christensen H, Griffiths KM, Mackinnon A. Web-based cognitive behavior therapy for depression with and without telephone tracking in a national helpline: secondary outcomes from a randomized controlled trial. J Med Internet Res 2012 Jun;14(3):e68 [FREE Full text] [CrossRef] [Medline]
- Spek V, Nyklícek I, Smits N, Cuijpers P, Riper H, Keyzer J, et al. Internet-based cognitive behavioural therapy for subthreshold depression in people over 50 years old: a randomized controlled clinical trial. Psychol Med 2007 Dec;37(12):1797-1806. [CrossRef] [Medline]
- Spek V, Cuijpers P, Nyklícek I, Riper H, Keyzer J, Pop V. Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a meta-analysis. Psychol Med 2007 Mar;37(3):319-328. [CrossRef] [Medline]
- Spek V, Nyklícek I, Cuijpers P, Pop V. Predictors of outcome of group and internet-based cognitive behavior therapy. J Affect Disord 2008 Jan;105(1-3):137-145. [CrossRef] [Medline]
- Spek V, Cuijpers P, Nyklícek I, Smits N, Riper H, Keyzer J, et al. One-year follow-up results of a randomized controlled clinical trial on internet-based cognitive behavioural therapy for subthreshold depression in people over 50 years. Psychol Med 2008 May;38(5):635-639. [CrossRef] [Medline]
- van Straten A, Cuijpers P, Smits N. Effectiveness of a web-based self-help intervention for symptoms of depression, anxiety, and stress: randomized controlled trial. J Med Internet Res 2008 Mar;10(1):e7 [FREE Full text] [CrossRef] [Medline]
- Perini S, Titov N, Andrews G. Clinician-assisted Internet-based treatment is effective for depression: randomized controlled trial. Aust N Z J Psychiatry 2009 Jun;43(6):571-578. [CrossRef] [Medline]
- Vernmark K, Lenndin J, Bjärehed J, Carlsson M, Karlsson J, Oberg J, et al. Internet administered guided self-help versus individualized e-mail therapy: A randomized trial of two versions of CBT for major depression. Behav Res Ther 2010 May;48(5):368-376. [CrossRef] [Medline]
- Titov N. Internet-delivered psychotherapy for depression in adults. Curr Opin Psychiatry 2011 Jan;24(1):18-23. [CrossRef] [Medline]
- Wiersma JE, Titov N, Van Schaik DJ, Van Oppen P, Beekman AT, Cuijpers P, et al. Treating chronic symptoms of depression in the virtual clinic: findings on chronicity of depression in patients treated with internet-based computerized cognitive behaviour therapy for depression. Psychother Psychosom 2011;80(5):313-315. [CrossRef] [Medline]
- Griffiths KM, Farrer L, Christensen H. The efficacy of internet interventions for depression and anxiety disorders: a review of randomised controlled trials. Med J Aust 2010 Jun 7;192(11 Suppl):S4-11. [Medline]
- Hedman E, Andersson G, Andersson E, Ljótsson B, Rück C, Asmundson GJ, et al. Internet-based cognitive-behavioural therapy for severe health anxiety: randomised controlled trial. Br J Psychiatry 2011 Mar;198(3):230-236 [FREE Full text] [CrossRef] [Medline]
- Andrews G, Davies M, Titov N. Effectiveness randomized controlled trial of face to face versus Internet cognitive behaviour therapy for social phobia. Aust N Z J Psychiatry 2011 Apr;45(4):337-340. [CrossRef] [Medline]
- Andersson G, Cuijpers P. Internet-based and other computerized psychological treatments for adult depression: a meta-analysis. Cogn Behav Ther 2009 Dec;38(4):196-205. [CrossRef] [Medline]
- Mohr DC, Cuijpers P, Lehman K. Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions. J Med Internet Res 2011 Mar;13(1):e30 [FREE Full text] [CrossRef] [Medline]
- Titov N, Andrews G, Davies M, McIntyre K, Robinson E, Solley K. Internet treatment for depression: a randomized controlled trial comparing clinician vs. technician assistance. PLoS One 2010 Jun;5(6):e10939 [FREE Full text] [CrossRef] [Medline]
- Carroll KM, Ball SA, Martino S, Nich C, Babuscio TA, Rounsaville BJ. Enduring effects of a computer-assisted training program for cognitive behavioral therapy: a 6-month follow-up of CBT4CBT. Drug Alcohol Depend 2009 Feb 1;100(1-2):178-181 [FREE Full text] [CrossRef] [Medline]
- Cox JL, Holden JM, Sagovsky R. Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry 1987 Jun;150:782-786. [Medline]
- O'Mahen HA, Woodford J, McGinley J, Warren FC, Richards DA, Lynch TR, et al. Internet-based behavioral activation-treatment for postnatal depression (Netmums): a randomized controlled trial. J Affect Disord 2013 Sep 25;150(3):814-822. [CrossRef] [Medline]
- O'Mahen H, Himle JA, Fedock G, Henshaw E, Flynn H. A pilot randomized controlled trial of cognitive behavioral therapy for perinatal depression adapted for women with low incomes. Depress Anxiety 2013 Jul;30(7):679-687. [CrossRef] [Medline]
- Lewinsohn PM. Control your depression. New York: Simon and Schuster; 1992.
- Milgrom J, McCloud P. Parenting stress and postnatal depression. Stress Medicine 1996;12(3):177-186.
- Sheeber LB, Seeley JR, Feil EG, Davis B, Sorensen E, Kosty DB, et al. Development and pilot evaluation of an Internet-facilitated cognitive-behavioral intervention for maternal depression. J Consult Clin Psychol 2012 Oct;80(5):739-749. [CrossRef] [Medline]
- Danaher BG, Milgrom J, Seeley JR, Stuart S, Schembri C, Tyler MS, et al. Web-based intervention for postpartum depression: Formative research and design of the MomMoodBooster Program. JMIR Res Protoc 2012 Nov;1(2):e18. [CrossRef] [Medline]
- Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001 Sep;16(9):606-613 [FREE Full text] [Medline]
- Spitzer RL, Williams JB, Gibbon M, First MB. The Structured Clinical Interview for DSM-III-R (SCID). I: History, rationale, and description. Arch Gen Psychiatry 1992 Aug;49(8):624-629. [Medline]
- First MB. Structured clinical interview for DSM-IV axis I disorders SCID-I: clinician version, administration booklet. Washington, DC: American Psychiatric Press; 1997.
- Hamilton M. Hamilton depression scale. In: Guy W, editor. ECDEU assessment manual for psychopharmacology. Rockville, MD: National Institute of Mental Health; 1976:179-192.
- Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol 1967 Dec;6(4):278-296. [Medline]
- Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960 Feb;23:56-62 [FREE Full text] [Medline]
- Farabaugh AH, Bitran S, Witte J, Alpert J, Chuzi S, Clain AJ, et al. Anxious depression and early changes in the HAMD-17 anxiety-somatization factor items and antidepressant treatment outcome. Int Clin Psychopharmacol 2010 Jul;25(4):214-217 [FREE Full text] [CrossRef] [Medline]
- Milgrom J, Ericksen J, Negri L, Gemmill AW. Screening for postnatal depression in routine primary care: properties of the Edinburgh Postnatal Depression Scale in an Australian sample. Aust N Z J Psychiatry 2005 Sep;39(9):833-839. [CrossRef] [Medline]
- Cuijpers P, Donker T, van Straten A, Li J, Andersson G. Is guided self-help as effective as face-to-face psychotherapy for depression and anxiety disorders? A systematic review and meta-analysis of comparative outcome studies. Psychol Med 2010 Dec;40(12):1943-1957. [CrossRef] [Medline]
- Löwe B, Kroenke K, Herzog W, Gräfe K. Measuring depression outcome with a brief self-report instrument: sensitivity to change of the Patient Health Questionnaire (PHQ-9). Journal of Affective Disorders 2004 Jul;81(1):61-66. [CrossRef]
- Sidebottom AC, Harrison PA, Godecker A, Kim H. Validation of the Patient Health Questionnaire (PHQ)-9 for prenatal depression screening. Arch Womens Ment Health 2012 Oct;15(5):367-374. [CrossRef] [Medline]
- Jaeschke R, Singer J, Guyatt GH. Measurement of health status. Ascertaining the minimal clinically important difference. Control Clin Trials 1989 Dec;10(4):407-415. [Medline]
- Hollon SD, Kendall PC. Cognitive self-statements in depression: development of an automatic thoughts questionnaire. Cognit Ther Res 1980;4:383-395.
- Kaufman NK, Rohde P, Seeley JR, Clarke GN, Stice E. Potential mediators of cognitive-behavioral therapy for adolescents with comorbid major depression and conduct disorder. J Consult Clin Psychol 2005 Feb;73(1):38-46. [CrossRef] [Medline]
- Kanter JW, Mulick PS, Busch AM, Berlin KS, Martell CR. The Behavioral Activation for Depression Scale (BADS): psychometric properties and factor structure. J Psychopathol Behav Assess 2006 Oct 25;29(3):191-202. [CrossRef]
- Hunsley M, Best M, Lefebvre D, Vito J. The Seven-Item Short Form of the Dyadic Adjustment Scale: further evidence for construct validity. The American Journal of Family Therapy 2001 Oct;29(4):325-335. [CrossRef]
- Spanier GB. Measuring dyadic adjustment: new scales for assessing the quality of marriage and similar dyads. Journal of Marriage and the Family 1976 Feb;38(1):15-28. [CrossRef]
- Johnston C, Mash EJ. A measure of parenting satisfaction and efficacy. Journal of Clinical Child Psychology 1989 Jun;18(2):167-175. [CrossRef]
- Gilmore L, Cuskelly M. Factor structure of the Parenting Sense of Competence scale using a normative sample. Child Care Health Dev 2009 Jan;35(1):48-55. [CrossRef] [Medline]
- Bandura A. Health promotion by social cognitive means. Health Educ Behav 2004 Apr;31(2):143-164. [CrossRef] [Medline]
- Maciejewski PK, Prigerson HG, Mazure CM. Self-efficacy as a mediator between stressful life events and depressive symptoms. Differences based on history of prior depression. Br J Psychiatry 2000 Apr;176:373-378 [FREE Full text] [Medline]
- Peterson ET. Web site measurement hacks. Sebastopol, California: O'Reilly; 2005.
- Bangor A, Kortum PT, Miller JT. An empirical evaluation of the System Usability Scale. International Journal of Human-Computer Interaction 2008 Jul 29;24(6):574-594. [CrossRef]
- Tullis T, Albert W. Measuring the user experience: Collecting, analyzing, and presenting usability metrics. Boston: Elsevier/Morgan Kaufmann; 2008.
- Danaher BG, McKay HG, Seeley JR. The information architecture of behavior change websites. J Med Internet Res 2005 May;7(2):e12 [FREE Full text] [CrossRef] [Medline]
- Wee KY, Skouteris H, Pier C, Richardson B, Milgrom J. Correlates of ante- and postnatal depression in fathers: a systematic review. J Affect Disord 2011 May;130(3):358-377. [CrossRef] [Medline]
- Solantaus T, Salo S. Paternal postnatal depression: fathers emerge from the wings. The Lancet 2005 Jun;365(9478):2158-2159. [CrossRef]
- Raudenbush SW, Bryk AS. Hierarchical linear models: Applications and data analysis methods, 2nd edn. Thousand Oaks, CA: Sage; 2002.
- Schafer JL, Graham JW. Missing data: Our view of the state of the art. Psychological Methods 2002;7(2):147-177. [CrossRef]
- Rosenthal R. Meta-analytic procedures for social research. Newbury Park: Sage Publications; 1991.
- Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale, N.J: L. Erlbaum Associates; 1988.
- Sauro J. A Practical Guide to the System Usability Scale: Background, Benchmarks & Best Practices. Denver, CO: Measuring Usability LLC; 2011.
- Sauro J, Lewis JR. Quantifying the User Experience: Practical Statistics for User Research. Waltham, MA: Morgan Kaufmann; 2012.
- Mohr DC, Duffecy J, Jin L, Ludman EJ, Lewis A, Begale M, et al. Multimodal e-mental health treatment for depression: a feasibility trial. J Med Internet Res 2010;12(5):e48 [FREE Full text] [CrossRef] [Medline]
- Danaher BG, Seeley JR. Methodological issues in research on web-based behavioral interventions. Ann Behav Med 2009 Aug;38(1):28-39. [CrossRef] [Medline]
- Christensen H, Griffiths KM, Farrer L. Adherence in internet interventions for anxiety and depression. J Med Internet Res 2009;11(2):e13 [FREE Full text] [CrossRef] [Medline]
- Lewis BA, Gjerdingen DK, Avery MD, Guo H, Sirard JR, Bonikowske AR, et al. Examination of a telephone-based exercise intervention for the prevention of postpartum depression: design, methodology, and baseline data from The Healthy Mom study. Contemp Clin Trials 2012 Nov;33(6):1150-1158. [CrossRef] [Medline]
- Mohr DC, Burns MN, Schueller SM, Clarke G, Klinkman M. Behavioral Intervention Technologies: evidence review and recommendations for future research in mental health. Gen Hosp Psychiatry 2013 Jul;35(4):332-338. [CrossRef] [Medline]
- Mohr DC, Ho J, Duffecy J, Reifler D, Sokol L, Burns MN, et al. Effect of telephone-administered vs face-to-face cognitive behavioral therapy on adherence to therapy and depression outcomes among primary care patients: a randomized trial. JAMA 2012 Jun 6;307(21):2278-2285. [CrossRef] [Medline]
- Baker-Ericzén MJ, Connelly CD, Hazen AL, Dueñas C, Landsverk JA, Horwitz SM. A collaborative care telemedicine intervention to overcome treatment barriers for Latina women with depression during the perinatal period. Fam Syst Health 2012 Sep;30(3):224-240. [CrossRef] [Medline]
- Logsdon MC, Foltz MP, Stein B, Usui W, Josephson A. Adapting and testing telephone-based depression care management intervention for adolescent mothers. Arch Womens Ment Health 2010 Aug;13(4):307-317 [FREE Full text] [CrossRef] [Medline]
- Izzo CV, Eckenrode JJ, Smith EG, Henderson CR, Cole R, Kitzman H, et al. Reducing the impact of uncontrollable stressful life events through a program of nurse home visitation for new parents. Prev Sci 2005 Dec;6(4):269-274. [CrossRef] [Medline]
- Lopez MH, Gonzalez-Barrera A, Patten E. Pew Hispanic Center. 2013. Closing the Digital Divide: Latinos and technology adoption URL: http://www.pewhispanic.org/files/2013/03/Latinos_Social_Media_and_Mobile_Tech_03-2013_final.pdf [accessed 2013-10-24] [WebCite Cache]
- Smith A. Pew Research Center. 2013. Smartphone ownership: 2013 Update URL: http://www.pewinternet.org/~/media/Files/Reports/2013/PIP_Smartphone_adoption_2013.pdf [accessed 2013-10-25] [WebCite Cache]
- Kurki T, Hiilesmaa V, Raitasalo R, Mattila H, Ylikorkala O. Depression and anxiety in early pregnancy and risk for preeclampsia. Obstet Gynecol 2000 Apr;95(4):487-490. [Medline]
- Dayan J, Creveuil C, Marks MN, Conroy S, Herlicoviez M, Dreyfus M, et al. Prenatal depression, prenatal anxiety, and spontaneous preterm birth: a prospective cohort study among women with early and regular care. Psychosom Med 2006 Nov;68(6):938-946 [FREE Full text] [CrossRef] [Medline]
- Orr ST, James SA, Blackmore Prince C. Maternal prenatal depressive symptoms and spontaneous preterm births among African-American women in Baltimore, Maryland. Am J Epidemiol 2002 Nov 1;156(9):797-802 [FREE Full text] [Medline]
- Chung TK, Lau TK, Yip AS, Chiu HF, Lee DT. Antepartum depressive symptomatology is associated with adverse obstetric and neonatal outcomes. Psychosom Med 2001;63(5):830-834 [FREE Full text] [Medline]
- Austin MP. Psychosocial assessment and management of depression and anxiety in pregnancy. Key aspects of antenatal care for general practice. Aust Fam Physician 2003 Mar;32(3):119-126. [Medline]
- Coverdale JH, McCullough LB, Chervenak FA, Bayer T. Clinical implications and management strategies when depression occurs during pregnancy. Aust N Z J Obstet Gynaecol 1996 Nov;36(4):424-429. [Medline]
- Milgrom J, Ericksen J, McCarthy R, Gemmill AW. Stressful impact of depression on early mother–infant relations. Stress and Health 2006 Oct;22(4):229-238. [CrossRef]
- Milgrom J, Newnham C, Anderson PJ, Doyle LW, Gemmill AW, Lee K, et al. Early sensitivity training for parents of preterm infants: impact on the developing brain. Pediatr Res 2010 Mar;67(3):330-335. [CrossRef] [Medline]
|ATQ: Automatic Thoughts Questionnaire|
|BADS: Behavioral Activation for Depression Scale|
|CBT: cognitive behavioral therapy|
|CWDC: Coping With Depression Course|
|DAS-7: Dyadic Adjustment Scale (7-item version)|
|EPDS: Edinburgh Postnatal Depression Survey|
|HRSD: Hamilton Rating Scale for Depression|
|IDCRC: Iowa Depression and Clinical Research Center|
|IPT: interpersonal psychotherapy|
|MMB: MomMoodBooster (MumMoodBooster)|
|NHMRC: National Health and Medical Research Council (Australia)|
|ORI: Oregon Research Institute|
|PHQ-9: Patient Health Questionnaire (9-item version)|
|PIRI: Parent-Infant Research Institute (University of Melbourne)|
|PPD: postpartum depression|
|PSOC: Parenting Sense of Competence scale|
|SUS: System Usability Scale|
|SCID: Structured Clinical Interview for DSM-IV Disorders|
Edited by G Eysenbach; submitted 14.08.13; peer-reviewed by L Walekr, D Linares; comments to author 19.09.13; accepted 08.10.13; published 01.11.13
©Brian G Danaher, Jeannette Milgrom, John R Seeley, Scott Stuart, Charlene Schembri, Milagra S Tyler, Jennifer Ericksen, Whitney Lester, Alan W Gemmill, Derek B Kosty, Peter Lewinsohn. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 01.11.2013.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.