The aims of the present review are to apply a recent risk factor approach (H. C. Kraemer et al., 1997) to putative risk factors for eating disorders, to order these along a timeline, and to deduce general taxonomic questions. Putative risk factors were classified according to risk factor type, outcome (anorexia nervosa, bulimia nervosa, binge-eating disorder, full vs. partial syndromes), and additional factor characteristics (specificity, potency, need for replication). Few of the putative risk factors were reported to precede the onset of the disorder. Many factors were general risk factors; only few differentiated between the 3 eating disorder syndromes. Common risk factors from longitudinal and cross-sectional studies were gender, ethnicity, early childhood eating and gastrointestinal problems, elevated weight and shape concerns, negative self-evaluation, sexual abuse and other adverse experiences, and general psychiatric morbidity. Suggestions are made for the conceptualization of future risk factor studies.

Coming to Terms With Risk Factors for Eating Disorders: Application of Risk Terminology and Suggestions for a General Taxonomy

Internet-based psychotherapeutic interventions have been used for more than a decade, but no comprehensive review and no extensive meta-analysis of their effectiveness have been conducted. We have collected all of the empirical articles published up to March 2006 (n = 64) that examine the effectiveness of online therapy of different forms and performed a meta-analysis of all the studies reported in them (n = 92). These studies involved a total of 9,764 clients who were treated through various Internet-based psychological interventions for a variety of problems, whose effectiveness was assessed by different types of measures. The overall mean weighted effect size was found to be 0.53 (medium effect), which is quite similar to the average effect size of traditional, face-to-face therapy. Next, we examined interacting effects of various possible relevant moderators of the effects of online therapy, including type of therapy (self-help web-based therapy versus online communication-based etherapy), ty...

/pdf/a-comprehensive-review-and-a-meta-analysis-of-the-23saazmujq.pdf

A Comprehensive Review and a Meta-Analysis of the Effectiveness of Internet-Based Psychotherapeutic Interventions

Scientific knowledge is increasingly being stored online. A large number of infrastructures that provide access to scientific knowledge are now available on the Internet. They range from online journals to collaboratories and logic servers. This article examines a variety of such infrastructures and derives implications for their further evolution. It assesses their impact on the way that scientists will create, organize and integrate knowledge. In parallel, the article illustrates how online content may become more adaptive and structured. The text consists of individually marked sections that are assembled dynamically to the needs of each reader on different levels of detail.

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=2525&context=cais

Web Based Knowledge Infrastructures for the Sciences: An Adaptive Document

BACKGROUND: A primary focus of self-care interventions for chronic illness is the encouragement of an individual's behavior change necessitating knowledge sharing, education, and understanding of the condition. The use of the Internet to deliver Web-based interventions to patients is increasing rapidly. In a 7-year period (1996 to 2003), there was a 12-fold increase in MEDLINE citations for “Web-based therapies.” The use and effectiveness of Web-based interventions to encourage an individual's change in behavior compared to non-Web-based interventions have not been substantially reviewed.

OBJECTIVE: This meta-analysis was undertaken to provide further information on patient/client knowledge and behavioral change outcomes after Web-based interventions as compared to outcomes seen after implementation of non-Web-based interventions.

METHODS: The MEDLINE, CINAHL, Cochrane Library, EMBASE, ERIC, and PSYCHInfo databases were searched for relevant citations between the years 1996 and 2003. Identified articles were retrieved, reviewed, and assessed according to established criteria for quality and inclusion/exclusion in the study. Twenty-two articles were deemed appropriate for the study and selected for analysis. Effect sizes were calculated to ascertain a standardized difference between the intervention (Web-based) and control (non-Web-based) groups by applying the appropriate meta-analytic technique. Homogeneity analysis, forest plot review, and sensitivity analyses were performed to ascertain the comparability of the studies.

RESULTS: Aggregation of participant data revealed a total of 11,754 participants (5,841 women and 5,729 men). The average age of participants was 41.5 years. In those studies reporting attrition rates, the average drop out rate was 21% for both the intervention and control groups. For the five Web-based studies that reported usage statistics, time spent/session/person ranged from 4.5 to 45 minutes. Session logons/person/week ranged from 2.6 logons/person over 32 weeks to 1008 logons/person over 36 weeks. The intervention designs included one-time Web-participant health outcome studies compared to non-Web participant health outcomes, self-paced interventions, and longitudinal, repeated measure intervention studies. Longitudinal studies ranged from 3 weeks to 78 weeks in duration. The effect sizes for the studied outcomes ranged from -.01 to .75. Broad variability in the focus of the studied outcomes precluded the calculation of an overall effect size for the compared outcome variables in the Web-based compared to the non-Web-based interventions. Homogeneity statistic estimation also revealed widely differing study parameters (Qw16 = 49.993, P ≤ .001). There was no significant difference between study length and effect size. Sixteen of the 17 studied effect outcomes revealed improved knowledge and/or improved behavioral outcomes for participants using the Web-based interventions. Five studies provided group information to compare the validity of Web-based vs. non-Web-based instruments using one-time cross-sectional studies. These studies revealed effect sizes ranging from -.25 to +.29. Homogeneity statistic estimation again revealed widely differing study parameters (Qw4 = 18.238, P ≤ .001).

CONCLUSIONS: The effect size comparisons in the use of Web-based interventions compared to non-Web-based interventions showed an improvement in outcomes for individuals using Web-based interventions to achieve the specified knowledge and/or behavior change for the studied outcome variables. These outcomes included increased exercise time, increased knowledge of nutritional status, increased knowledge of asthma treatment, increased participation in healthcare, slower health decline, improved body shape perception, and 18-month weight loss maintenance.

 [J Med Internet Res 2004;6(4):e40]

The effectiveness of Web-based vs. non-Web-based interventions: a meta-analysis of behavioral change outcomes

Background: As Internet use grows, health interventions are increasingly being delivered online. Pioneering researchers are using the networking potential of the Internet, and several of them have evaluated these interventions. Objective: The objective was to review the reasons why health interventions have been delivered on the Internet and to reflect on the work of the pioneers in this field in order to inform future research. Methods: We conducted a qualitative systematic review of peer-reviewed evaluations of health interventions delivered to a known client/patient group using networked features of the Internet. Papers were reviewed for the reasons given for using the Internet, and these reasons were categorized. Results: We included studies evaluating 28 interventions plus 9 interventions that were evaluated in pilot studies. The interventions were aimed at a range of health conditions. Reasons for Internet delivery included low cost and resource implications due to the nature of the technology; reducing cost and increasing convenience for users; reduction of health service costs; overcoming isolation of users; the need for timely information; stigma reduction; and increased user and supplier control of the intervention. A small number of studies gave the existence of Internet interventions as the only reason for undertaking an evaluation of this mode of delivery. Conclusions: One must remain alert for the unintended effects of Internet delivery of health interventions due to the potential for reinforcing the problems that the intervention was designed to help. Internet delivery overcomes isolation of time, mobility, and geography, but it may not be a substitute for face-to-face contact. Future evaluations need to incorporate the evaluation of cost, not only to the health service but also to users and their social networks. When researchers report the outcomes of Internet-delivered health care interventions, it is important that they clearly state why they chose to use the Internet, preferably backing up their decision with theoretical models and exploratory work. Evaluation of the effectiveness of a health care intervention delivered by the Internet needs to include comparison with more traditional modes of delivery to answer the following question: What are the added benefits or disadvantages of Internet use that are particular to this mode of delivery? © Griffiths, Frances, Lindenmeyer, Antje, Powell, John, Thorogood, Margaret.

/pdf/why-are-health-care-interventions-delivered-over-the-1jrp3d5g0o.pdf

Why Are Health Care Interventions Delivered Over the Internet? A Systematic Review of the Published Literature

This study evaluated an Internet-delivered computer-assisted health education (CAHE) program designed to improve body satisfaction and reduce weight/shape concerns--concerns that have been shown to be risk factors for the development of eating disorders in young women. Participants were 60 women at a public university randomly assigned to either an intervention or control condition. Intervention participants completed the CAHE program Student Bodies. Measures of body image and disordered eating attitudes were assessed at baseline, postintervention, and 3-month follow-up. At follow-up, intervention participants, compared with controls, reported a significant improvement in body image and a decrease in drive for thinness. This program provides evidence for the feasibility and effectiveness of providing health education by means of the Internet.

Effectiveness of an Internet-based program for reducing risk factors for eating disorders.

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Effectiveness of an Internet-based program for reducing risk factors for eating disorders.