This paper is in the following e-collection/theme issue:

Web-based and Mobile Health Interventions (3297) Diabetes Self-Management (484) Diabetes Reviews and Scoping Studies (32)

Published on in Vol 15, No 12 (2013): December

Use of Behavioral Change Techniques in Web-Based Self-Management Programs for Type 2 Diabetes Patients: Systematic Review

Use of Behavioral Change Techniques in Web-Based Self-Management Programs for Type 2 Diabetes Patients: Systematic Review

Use of Behavioral Change Techniques in Web-Based Self-Management Programs for Type 2 Diabetes Patients: Systematic Review

Authors of this article:

Michael van Vugt1, 2 ;   Maartje de Wit1, 2 ;   Wilmy HJJ Cleijne1 ;   Frank J Snoek1, 2
Article Authors Cited by (89) Tweetations (27) Metrics

    Review

    1Department of Medical Psychology, VU University Medical Centre, Amsterdam, Netherlands

    2EMGO+ Institute for Health and Care Research, VU University Medical Centre, Amsterdam, Netherlands

    Corresponding Author:

    Michael van Vugt, Ing, MSc

    Department of Medical Psychology

    VU University Medical Centre

    MF-D345

    Van der Boechorststraat 7

    Amsterdam, 1081 BT

    Netherlands

    Phone: 31 204446099

    Fax:31 204448230

    Email: m.vanvugt@vumc.nl


    Background: Type 2 diabetes mellitus (T2DM) is a highly prevalent chronic metabolic disease characterized by hyperglycemia and cardiovascular risks. Without proper treatment, T2DM can lead to long-term complications. Diabetes self-management is recognized as the cornerstone of overall diabetes management. Web-based self-management programs for T2DM patients can help to successfully improve patient health behaviors and health-related outcomes. Theories can help to specify key determinants of the target behaviors and behavior change strategies required to arrive at the desired health outcomes, which can then be translated into specific behavioral techniques or strategies that patients can learn to apply in their daily life. From previous reviews of a wide range of online diabetes self-management tools and programs, it appears that it is still unclear which behavioral change techniques (BCTs) are primarily used and are most effective when it comes to improving diabetes self-management behaviors and related health outcomes.

    Objective: We set out to identify which BCTs are being applied in online self-management programs for T2DM and whether there is indication of their effectiveness in relation to predefined health outcomes.

    Methods: Articles were systematically searched and screened on the mentioned use of 40 BCTs, which were then linked to reported statistically significant improvements in study outcomes.

    Results: We found 13 randomized controlled trials reporting on 8 online self-management interventions for T2DM. The BCTs used were feedback on performance, providing information on consequences of behavior, barrier identification/problem solving, and self-monitoring of behavior. These BCTs were also linked to positive outcomes for health behavior change, psychological well-being, or clinical parameters.

    Conclusions: A relatively small number of theory-based online self-management support programs for T2DM have been reported using only a select number of BCTs. The development of future online self-management interventions should be based on the use of theories and BCTs and should be reported accurately.

    J Med Internet Res 2013;15(12):e279

    doi:10.2196/jmir.2800

    Keywords

    Web-based; online; self-management; review; type 2 diabetes mellitus; behavioral change techniques 


    Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance and beta cell impairment [1]. The number of people with T2DM is rising exponentially and is estimated to reach 439 million patients worldwide in 2030 [2]. Without proper treatment, T2DM can lead to long-term complications, such as neuropathy, nephropathy, retinopathy, cardiovascular disease, and a lowered quality of life [3]. The treatment of T2DM patients is largely dependent on the patient’s daily self-care by means of lifestyle modification (diet and physical exercise) and taking oral blood glucose-lowering medication and/or insulin, often combined with medication to normalize blood pressure, cholesterol, and triglycerides [4,5]. Therefore, diabetes self-management is recognized as the cornerstone of overall diabetes management [6,7].

    Self-management enables patients to take control of their chronic disease, such as the treatment and the physical and psychological symptoms, by making their own decisions and performing self-chosen actions aimed at improving their health [8-10]. For T2DM, the Association of American Diabetes Educators (AADE) has defined 7 key self-management behaviors: (1) healthy eating, (2) being active, (3) monitoring, (4) taking medication, (5) problem solving, (6) reducing risks, and (7) healthy coping [11].

    To promote daily self-management for T2DM patients, educational and behavioral support programs have been developed and shown to be effective for behavioral and medical outcomes [7,12-15]. More recently, self-management programs for T2DM patients are also available on the Internet [16-19]. Web-based self-management programs for T2DM patients have been shown to increase the effectiveness and reach of clinical-based consultations [20]. Furthermore, these Web-based programs can help to improve patient health behaviors (eg, self-monitoring, physical activity, diet) and subsequent health outcomes (eg, weight, glycemic control, emotional distress) [21,22]. However, attrition can be problematic in Web-based interventions and should be considered during the creation process [23].

    It is recognized that theory-based self-management programs are more effective than non-theory-based programs; indeed, most self-management programs are informed by theory or elements of a behavior change model [10,24,25]. Theories can help to specify key determinants of the target behaviors and behavior change strategies required to arrive at the desired health outcomes, which can then be translated into specific behavioral techniques or strategies that patients can learn to apply in their daily life [8]. Abraham and Michie [26,27] have developed a taxonomy of behavioral change techniques (BCTs) for different health behaviors, such as healthy eating and physical exercise. Such taxonomy can help to identify successful BCTs and support the development of new online self-management programs for T2DM and other chronic diseases [25-27]. From previous reviews of a wide range of online diabetes self-management tools and programs, it would appear that it is still unclear which BCTs are most used and most effective when it comes to improving self-management behaviors and related health outcomes [21,22,28,29]. Therefore, we set out to: (1) systematically review the literature and identify which BCTs are being applied in online self-management programs for T2DM and how often, and (2) determine whether there is indication from randomized controlled trials (RCTs) for the effectiveness of applied BCTs in relation to particular health outcomes.


    Search

    On July 24, 2012, we searched within PubMed, EMBASE, Cochrane, PsycInfo, and Cinahl. Because of the size of the search term used, the search terms can be found in Multimedia Appendix 1. Some keywords used in the search were diabetes mellitus; diabetes mellitus, type 2; Internet; eHealth; online; and Web-based. The systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement where applicable [30].

    Inclusion Exclusion Criteria

    The retrieved articles were screened using the following inclusion criteria: written in English, published after 1994 (the introduction of the Internet), about T2DM, included patients aged 18 years or older, and concerned Web-based (online) self-management programs for which participants had to use the Internet to connect to the intervention. We only included RCTs to establish whether the BCTs used in the programs were associated with significant improvements. We defined self-management programs as systematic approaches to assist patients in their diabetes self-care, and where in some way or other patients were actively engaged and prompted to make decisions for themselves and have responsibility over their own actions [8,10]. Articles were excluded if they were not related to diabetes, reported only on technology testing, were not Web-based programs, did not target a self-management behavior, or only included type 1 diabetes mellitus (T1DM). Book chapters, abstracts, and pilot studies were not included.

    Study Selection and Data Extraction

    Two researchers (MvV, WHJJC) independently reviewed the articles and extracted data on demographics, care setting, type of study, duration, measurements, nature of the intervention and control condition, applied inclusion criteria, used theory or model, BCTs, target behavior(s), outcome parameters, results, limits, and adherence. The risk of bias was assessed for all included studies using a quality assessment tool as proposed by van Tulder et al [31] and can be found in the Multimedia Appendix 2. The BCTs were categorized based on the checklist as proposed by Michie et al [27] which can be found in Multimedia Appendix 3. Disagreements regarding defined BCTs between the researchers were resolved by discussion within the research group. The BCTs used and the statistically significant outcomes were uncovered for each study. For each study with an improved study outcome (health behaviors, clinical outcome measures, and psychological outcomes), we looked if a BCT was present in the intervention for improving that particular outcome. We used Microsoft Excel 2003 to cross-reference this data and generated a list of frequently used BCTs associated with significant improvements in defined behavioral, clinical, and psychological outcomes.


    Article Selection

    Figure 1 shows a flowchart of the screening process. The search query resulted in 17,885 articles. After removing duplicated articles, titles and abstracts were screened for inclusion and exclusion criteria. After the first draft, 16,998 articles were excluded because they did not meet the inclusion criteria. We categorized the remaining 306 articles as: (1) studies on Web-based self-management programs, (2) reviews, (3) telehealth, telecare, or telemedicine studies [32-34], and (4) nonrelevant studies. This resulted in 13 articles reporting on 8 different Web-based self-management interventions for T2DM patients. These articles were individually read, screened for the BCTs used, and then discussed to reach consensus. Most articles provided only a short basic description of the intervention that was used. For 1 study [35], an additional article was consulted to uncover the content of the intervention [36].

    ‎
    Figure 1. Flowchart screening process of articles included in review.
    View this figure

    Study Characteristics

    Tables 1 and 2 provide an overview of the included studies and their results. Of the 13 RCT studies, 10 were performed in North America [37-46], 1 in Asia [47], and 2 in Europe [35,48]. The combined total patient sample size was 3813. Demographically, on average 54.8% of the participants were female and the average age was 57.2 years (SD 7.20). Average program completion rate was 81.7% (SD 15.2%). Four studies recruited their participants from the community by using flyers and newspapers [35,39,45,48]. Five studies recruited their participants from primary health care [37,42-44,46], 1 study recruited their participants from secondary health care [47], and 3 studies recruited their participants from primary and secondary health care [38,40,41]. All the studies included patients who had been diagnosed with T2DM for longer than a year. Five studies also included patients with T1DM [35,38,40,41,48] and 1 study also offered the intervention to people with diagnoses of chronic heart disease and chronic lung disease [45]. Average study duration was 6.69 months (SD 4.92). Adherence for all studies was high, which in itself contributes to the overall high quality of the included studies.

    Table 1. Characteristics of the studies.
    StudyStudy descriptionParticipants

    		QualityaCountrynGroups, nMeasurements, nSettingbInclusion criteriacDuration (months)EthnicityFemale, %Age, mean
    Glasgow et al (2012) [37]83%US463331T2DM, age 25-75, BMI >25 kg/m2, at least 1 other risk factor for heart disease, access to telephone and Internet, fluent in English or Spanish, ability to perform mild to moderate exercise12White, Latino5058.4
    Van Bastelaar et al (2011) [35]83%NL255231+2CESD>16, email address, access to Internet, no history of suicide, suicidal ideation, bipolar, psychotic, pregnancy, recent loss of significant other3White6150.0
    Bond et al (2010) [38]72%US62221+2T1DM or T2DM for at least 1 y, age ≥60, living independently, fluent in English6White4567.2
    Lorig et al (2010) [39]78%US761331+2T2DM, age ≥18, not pregnant or in care for cancer, access to the Internet18White, Native Indian, Alaska Native7354.3
    Glasgow et al (2010) [46]78%US463321T2DM, age 25-75,BMI>25 kg/m2, at least 1 other risk factor for heart disease, access to telephone and Internet, fluent in English or Spanish, ability to perform mild to moderate exercise4White5058.4
    Wangberg et al (2008) [48]67%NO61221+2T1DM or T2DM, access to Internet (no exclusion criteria)1White5740.1
    Bond et al (2007) [40]78%US62221+2T1DM or T2DM for ≥1 y, age ≥60, living independently, fluent in English6White4567.2
    Bond et al (2006) [41]50%US15221+2T1DM or T2DM for ≥1 y, age ≥60, living independently, fluent in English6White——
    Kim et al (2006) [47]72%KR73322T2DM <20 y, age ≥20, FBS <240 mg/dL and/or HbA1c less than 10.0%, no chronic complications, no evidence of heart disease, musculoskeletal disorders, or other disabling diseases that could restrict physical activity, no insulin administration3Asian4755.1
    Lorig et al (2006) [45]78%US958231+2Age ≥18, T2DM or COPD or CHF, no active treatment of cancer for 1 y, not participated in self-management program, access to Internet (email), agree to 1-2 h per week of log-on time over at least 3 sessions/w for 6 w, able to complete the online questionnaire12White7157.5
    Glasgow et al (2003) [42]67%US320321T2DM (Welborn criteria), age 40-75, have a telephone, fluent in English, live in local area and planning to remain in the area for year of study10White5359.0
    Barrera et al (2002) [43]72%US160411T2DM (Welborn criteria), age 40-75, have a telephone, fluent in English, live in local area and planning to remain in the area for year of study3White5359.0
    McKay et al (2002) [44]72%US160421T2DM (Welborn criteria), age: 40-75, have a telephone, fluent in English, live in local area and planning to remain in the area for year of study3White5359.3

    aAssessment of study quality as proposed by van Tulder et al [31] see Multimedia Appendix 2.

    b1=Primary care setting; 2=secondary care setting.

    cCESD: Center for Epidemiologic Studies Depression Scale; FBS: fasting blood sugar; HbA1c: glycated hemoglobin; COPD: chronic obstructive pulmonary disease; CHF: congestive heart failure; T2DM: type 2 diabetes mellitus; T1DM: type 1 diabetes mellitus.

    Table 2. Results of the studies.
    StudyResultsaCompletion rate (adherence)Power calculation
    Glasgow et al (2012) [37]Significant improvements in diet (fat intake), physical activity, and biological outcomes in both IGs vs baseline, and significant reduction in distress for both groups vs CG77%Yes
    Van Bastelaar et al (2011) [35]Significant improvements in depression and diabetes distress for IG68%Yes
    Bond et al (2010) [38]Significant improvements in quality of life, depression, social support, and self-efficacy for IG100%Yes
    Lorig et al (2010) [39]Significant improvements in HbA1c, patient activation, and self-efficacy for IGs vs CG82%Yes
    Glasgow et al (2010) [46]Significant improvements in diet (fat intake), physical activity, and biological outcomes in both IGs vs baseline, and significant reduction in distress for both groups vs CG83%Yes
    Wangberg et al (2008) [48]Significant improvements in self-care for high-efficacy group45%Yes (after)
    Bond et al (2007) [40]Significant improvements in HbA1c, weight, and HDL cholesterol for IG vs CG100%Yes
    Bond et al (2006) [41]Significant improvements in HbA1c and high comorbidities for IG vs CG—Yes
    Kim et al (2006) [47]Significant improvements in physical activity, FBS and HbA1c for both IGs vs CG100%Yes
    Lorig et al (2006) [45]Significant improvements in exercise, health distress, fatigue, pain, shortness of breath, reduction in disability for IG82%No
    Glasgow et al (2003) [42]Significant improvements in psychosocial and some biological outcomes for all IGs vs CG82%No
    Barrera et al (2002) [43]Significant improvements in diabetes-specific support measure and a general support scale for all IGs vs CG79%No
    McKay et al (2002) [44]Significant improvements in diet for all IGs vs CG, but no significant differences between conditions84%No

    aIG: intervention group; CG: control group; HDL: high-density lipoprotein; FBS: fasting blood sugar; HbA1c: glycated hemoglobin.

    The Interventions

    Tables 3 and 4 provide an overview of the interventions. Four of the 8 identified online interventions were developed by adapting existing (group) self-management programs into online self-management programs [35,39,45,47], and 4 interventions were newly created [37,38,40-44,46,48]. Two self-management interventions were developed as adjuncts to routine diabetes care, in which health care providers were able to have either online synchronous and asynchronous communication or telephone contact with the patient [38,40,41,47]. Six interventions were developed as standalone programs [35,37,39,42-46,48]. Five interventions were structured as sequential lessons [35,37,39,45-47] and 3 interventions allowed the participant to navigate freely through the program [38,40-44,48]. All 8 interventions offered some form of online coaching [35,37-48]. Seven of the 8 programs reported using a psychological theory or model as the basis for the self-management program, where some programs used multiple theories [37,42,46]. The theories and models used were: self-efficacy theory, [39,42,45], social support theory [42], transtheoretical model (TTM) [47], social cognitive theory [37,46,48], social-ecological model [37,46], and cognitive behavioral therapy [35].

    Table 3. Characteristics of interventions and control conditions of the intervention programs.
    StudyIntervention condition 1Intervention condition 2Intervention condition 3Control condition
    Glasgow et al (2012), Glasgow et al (2010) [37,46]Self-administered, Web-based diabetes self-management program with goal setting and action planning for medication adherence, physical activity, and diet; self-monitoring and feedback on progress, monitoring of blood glucose, blood pressure, and cholesterol results, a moderated forum with community resources, and barrier identificationSelf-administered, Web-based diabetes self-management program with goal setting and action planning on medication adherence, physical activity, and diet; self-monitoring and feedback on progress, monitoring of blood glucose, blood pressure, and cholesterol results; a moderated forum with community resources, and barrier identification; 2 follow-up calls from interventionist and invitation to attend 3 group sessions—Enhanced usual care (computer-based health risk appraisal feedback and recommended preventive care behaviors)
    van Bastelaar et al (2011) [35]Eight online lessons with cognitive behavioral therapy, coaching feedback, and mood diary——Waitlist control
    Bond et al (2010), Bond et al (2007), Bond et al (2006) [38,40,41]Online library, a personal electronic log of self-management activities, advice and counseling from a nurse via email, and weekly online problem-solving group discussions——Usual care
    Lorig et al (2010) [39]Web-based diabetes self-management program, 6 weekly sessions, bulletin board feedback on action planning, problem solving, difficult emotions, and celebrationsWeb-based diabetes self-management program, 6 weekly sessions, bulletin board feedback on action planning, problem solving, difficult emotions and celebrations,. listserve discussion group—Usual care
    Wangberg et al (2008) [48]Intervention tailored to high self-efficacy aimed at self-care: blood glucose monitoring, diet and physical activity, included T2DM information, barrier identification, quizzes with feedback, videos of peers, video lectures of professionalsIntervention tailored to low self-efficacy, aimed at self-care blood glucose monitoring, diet, and physical activity, including T2DM information, barrier identification, quizzes with feedback, videos of peers, video lectures of professionals—Usual care
    Kim et al (2006) [47]Web-based tailored physical activity counseling, based on participants’ assessed motivational stagePrinted-material physical activity intervention including the 5 stages of motivation change—Usual care
    Lorig et al (2006) [45]Web-based bulletin board discussion groups and a book, program contains individual exercise programs, emotion management, overview of medications, communication, healthy eating, fatigue management, action planning, feedback, and problem solving——Usual care
    Glasgow et al (2003), Barrera et al (2002), McKay et al (2002) [42-44]Goal setting with personalized feedback, barrier identification and problem solving, personalized self-management coach conditionGoal setting with personalized feedback, barrier identification and problem solving, peer support conditionCombined conditionOnly diabetes information online condition
    Table 4. Characteristics of the intervention programs.
    StudyTheory usedBCTsaHealth care professional includedEvolved or new interventionStandalone or embedded in care
    Glasgow et al (2012), Glasgow et al (2010) [37,46]Social cognitive theory, social-ecological model1,2,4,5,7-10,13,16,17,19,29,35NoNewStandalone
    van Bastelaar et al (2011) [35]Cognitive behavioral therapy1,2,4,8,12,13,15,16,19,21,22,24, 26,27,29,35,36,39,40NoEvolvedStandalone
    Bond et al (2010), Bond et al (2007), Bond et al (2006) [38,40,41]—1,2,5,6,8,10,11,16,17,19,21,23, 26,28,30,36NoNewEmbedded in care
    Lorig et al (2010) [39]Self-efficacy theory1-3,7,8,10,16,17,19,28,29,36NoEvolvedStandalone
    Wangberg et al (2008) [48]Social cognitive theory1,2,8,16,17,19,21,22,26,28NoNewStandalone
    Kim et al (2006) [47]Transtheoretical model5,6,7,17,19,20,21YesEvolvedEmbedded in care
    Lorig et al (2006) [45]Self-efficacy theory,1,4,7,8,19,21,22,27,28,29,33,34,36NoEvolvedStandalone
    Glasgow et al (2003), Barrera et al (2002), McKay et al (2002) [42-44]Self-efficacy theory, social support theory1,2,5,8,10,16,17,19,27-29YesNewStandalone

    aBCT: Behavioral change technique; see Multimedia Appendix 3.

    Behavioral Change Techniques Used

    Only 3 studies explicitly mentioned the BCTs applied [36,37,39]. For the other studies, information on BCTs was extracted from the program description. The frequency of used BCT’s found in the articles is shown in Table 5. The most commonly applied BCT’s were: provide feedback on performance, provide information on consequences of behavior in general, barrier identification/problem solving, provide information on consequences of behavior to the individual, and prompt self-monitoring of behavior. Some of the unused BCTs were shaping, prompting focus on past success, agree behavioral contract, and fear arousal.

    Behavioral Change Techniques Linked to Improved Outcomes

    Seven of 13 RCTs reported statistically significant improvements in health behaviors (diet, physical activity/exercise, medication use, smoking) [37,42,44-48]. Nine studies reported statistically significant improvements in clinical outcomes measures, such as glycated hemoglobin (HbA1c), fasting blood glucose, cholesterol, and triglycerides [37,39-43,45-47]. Nine studies reported statistically significant improvements in psychological outcomes, such as depression, diabetes distress, psychosocial well-being, self-efficacy, stress, and communication [35,37-39,42-45,48]. Table 6 provides an overview of the frequency of applied BCTs found to be associated with the statistically significant improvement of study outcomes.

    The BCTs provide feedback on performance, provide information on consequences of behavior in general, barrier identification/problem solving, prompt self-monitoring of behavioral outcome, provide information on consequences of behavior to the individual, prompt self-monitoring of behavior, and plan social support/social change were all linked with improvements in health behaviors, clinical outcome measures, and psychological outcomes. Additionally, goal setting (behavior) was linked to improvements in clinical outcomes and facilitate social comparison was associated with improvements in psychological outcomes.

    Table 5. Frequencies of behavioral change techniques (BCTs) used in the interventions discussed in the articles (n=8).
    #BCTn%
    1Provide feedback on performance8100
    2Provide information on consequences of behavior in general788
    3Barrier identification/problem solving788
    4Provide information on consequences of behavior to the individual675
    5Prompt self-monitoring of behavior675
    6Prompt self-monitoring of behavioral outcome675
    7Provide instruction on how to perform the behavior563
    8Facilitate social comparison563
    9Plan social support/social change563
    10Goal setting (behavior)450
    11Action planning450
    12Prompt review of behavioral goals450
    13Stress management/emotional control training450
    14Provide normative information about others’ behavior338
    15Model/Demonstrate the behavior338
    16Prompt practice338
    17Use of follow-up prompts338
    18Goal setting (outcome)225
    19Provide rewards contingent on successful behavior225
    20Relapse prevention/coping planning225
    21Provide information about others’ approval113
    22Set graded tasks113
    23Prompt review of outcome goals113
    24Prompt rewards contingent on effort or progress toward behavior113
    25Prompting generalization of a target behavior113
    26Provide information on where and when to perform the behavior113
    27Teach to use prompts/cues113
    28Environmental restructuring113
    29Prompt identification as role model/position advocate113
    30Prompt self-talk113
    31Prompt use of imagery113
    32General communication skills training113
    33Stimulate anticipation of future rewards113
    34Shaping00
    35Prompting focus on past success00
    36Agree behavioral contract00
    37Prompt anticipated regret00
    38Fear arousal00
    39Motivational interviewing00
    40Time management00
    Table 6. Frequency of behavioral change techniques (BCTs) per improved study outcome.
    BCTImproved health behavior outcomes (n=7)Improved clinical outcome measures (n=9)Improved psychological outcomes (n=9)Combined average percentage

    		n%n%n%%
    Provide feedback on performance710091009100100
    Provide information on consequences of behavior in general686889910092
    Barrier identification/problem solving686889910092
    Prompt self-monitoring of behavioral outcome68688977884
    Provide information on consequences of behavior to the individual57177888979
    Prompt self-monitoring of behavior57177888979
    Plan social support/social change57166777872
    Goal setting (behavior)57177855668
    Prompt review of behavioral goals45777866767
    Facilitate social comparison45766777867
    Action planning45755633349
    Use of follow-up prompts34333355644
    Provide instruction on how to perform the behavior34344444444
    Provide normative information about others’ behavior34333333336
    Stress management/emotional control training11444444434
    Provide rewards contingent on successful behavior22922222224
    Model/Demonstrate the behavior22911133324
    Relapse prevention/coping planning22922222224
    Prompt practice11422233323
    Set graded tasks22922211121
    Goal setting (outcome)11433311119
    Prompt self-talk11411111112
    Prompt use of imagery114.11111112
    Prompt review of outcome goals0022211111
    Teach to use prompts/cues0022211111
    Prompt identification as role model/position advocate0022211111
    Provide information on where and when to perform the behavior114111008
    Provide information about others’ approval001111117
    Prompt rewards contingent on effort or progress toward behavior00001113
    Prompting generalization of a target behavior00001113
    Environmental restructuring00001113
    General communication skills training00001113
    Stimulate anticipation of future rewards00001113
    Shaping0000000
    Prompting focus on past success0000000
    Agree behavioral contract0000000
    Prompt anticipated regret0000000
    Fear arousal0000000
    Motivational interviewing0000000
    Time management0000000

    Overall Findings

    To the best of our knowledge, this is the first review of BCT use in online diabetes self-management support programs. This information should prove helpful in designing effective online self-management programs for people with T2DM. We identified 13 RCT studies reporting on 8 different online self-management interventions of which 4 pre-existed as group-based programs. Despite the introduction of the Internet in 1994, only a relatively small number of Internet-based self-management interventions for T2DM patients have been studied. We did find 143 studies on various forms of diabetes telehealth and telecare interventions. These studies were excluded from our review because they did not qualify for our definition of self-management programs. Rather these programs stimulated patients to self-monitor their blood glucose, followed by professional feedback and advice. To our knowledge, these programs do not explicitly prompt or support patients to make decisions [32-34,49].

    The majority of the included studies that reported on self-management interventions only gave a very basic description of the program and its background. Indeed, it has been noted before that very few studies provide a detailed description of the actual behavioral change intervention [50-52]. This could be caused by the limited space authors have to describe the intervention in certain journals, making it difficult to replicate the study or allocate an effect size to specific parts of the intervention.

    The Use of Theories and Behavioral Change Techniques

    We observed that 7 of 8 interventions were grounded in a theoretical model, of which one of the used models (TTM), although popular, had limited evidence to support its assumptions [53,54]. Self-regulation theory with monitoring, action planning, and evaluating as its key features [55], and social learning theory, characterized by learning in social context [56], were most commonly used to inform development of the online interventions. However, only 3 studies specifically substantiated their choice for the use of specific BCTs to support their intervention [35,37,39]. After distilling the BCTs from the articles, the BCTs feedback on performance, providing information on consequences of behavior, barrier identification/problem solving, and self-monitoring of behavior and outcomes seemed to contribute the most to the effectiveness of the online self-management programs. These techniques also seemed to be key components for healthy eating and increasing physical activity [57], and were also commonly found in offline T2DM self-management programs [14,58]. However, being used frequently is in itself not a guarantee that these BCTs will actually contribute to the improvement of patients’ self-management in a particular domain. Nor does it mean that these BCTs fit the theory that was chosen to guide the intervention [59]. To further the development of effective online self-management interventions for T2DM and other chronic conditions, it is important to understand the underlying learning process [59]. Appropriate use of theories and supporting BCTs can prevent future interventions to be wrongly interpreted or executed by participants thereby improving treatment fidelity. This is particularly important for online programs, where confusion and misinterpretation on the part of the participant is more difficult to detect and address than in a group setting, for example, because of the more distant and static nature of the Web-based intervention. Therefore, it is crucial that the theoretical framework and BCTs are carefully chosen before a Web-based self-management intervention is created [60].

    A number of potentially effective BCTs appear to be used rarely or never in online self-management programs for T2DM despite a good theoretical basis. For instance, only a selection of BCTs derived from social theories, which have a great influence on the self-management of T2DM [61], were represented in the reviewed studies that claimed to use these social theories. Although planning social support and having some form of coaching to provide feedback are frequently used, other BCTs that seem to affiliate with social cognitive theories, such as identification of a role model, model/demonstrate the behavior, and provide information about others’ approval, were not frequently used. The same is true for BCTs such as coping planning and use of imagery that have been shown to be effective in stimulating self-management of T2DM in an offline program [62]. Similarly BCTs that seem to be based in the classical and operant conditioning theories (characterized by associations and rewards), such as prompt rewards contingent on effort or progress toward behavior and teach to use prompts/cues, were also barely used, but have shown to be associated with improving physical activity [63]. Just because these theories and BCTs were not used in the reviewed interventions does not mean that they are of no value to an online self-management program.

    The question then arises why researchers only use a limited number of BCTs and why the chosen BCTs do not always match the theories underlying their intervention. One explanation could be that current online interventions are being copied from published successful online or offline interventions based on a selection of theories and BCTs. By copying existing self-management programs, other relevant theories and BCTs are slowly phased out, narrowing the spectrum of BCTs used. Another obvious reason why certain BCTs are not being used could be that they are too complex or too technologically demanding and, therefore, too costly to integrate into an online environment. For instance, integrating elements of social support into the intervention, such as a forum, email messaging, and chatting functionality, demands large databases and continuous moderator involvement. The maintenance costs of these parts could influence the choice of using these elements. Finally, another reason for underuse of effective BCTs may be that the development of Web-based interventions for T2DM patients are driven primarily by technological advancements rather than being based on a BCT [64].

    Limitations

    The number of articles uncovered in this review was limited to 13 RCTs, covering 8 different diabetes self-management interventions. By only including English studies there is a possibility we limited the amount of available interventions for this review. This, in combination with multiple BCTs used and a variety of outcome measures, made it difficult to allocate an effect size to a specific BCT. Furthermore, because of the fact that self-management interventions contain multiple modules with interactive components, it is difficult to attribute an improvement in a particular study outcome to one specific BCT.

    Conclusions/Future Recommendations

    The development of online self-management interventions for T2DM patients brings with it a responsibility of correctly constructing and choosing the working components to specifically target diabetes self-management goals and outcomes. To avoid a further narrowing of applied BCTs, we recommend developers of online self-management programs to not only copy existing successful programs, but also critically review and consider less frequently used BCTs in the context of their theoretical background and the chosen target behaviors.

    Ideally, the creation process should follow the order of choosing a theory first, then matching BCTs, and lastly the technology to support the intervention. BCTs can be selected from the taxonomy of 40 BCTs as proposed by Michie et al [27]. By using this strategy, online theory-based self-management programs for T2DM patients can be developed without making unnecessary compromises or biased choices caused by existing technology. Furthermore, reporting detailed information on used theories and BCTs in research protocols and articles will benefit researchers in the creation and understanding of new effective Web-based self-management interventions for T2DM and other chronic disorders.

    Conflicts of Interest

    None declared.

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    Multimedia Appendix 1

    Search terms.

    PDF File (Adobe PDF File), 27KB
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    Multimedia Appendix 2

    Study quality assessment.

    PDF File (Adobe PDF File), 23KB
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    Multimedia Appendix 3

    Behavioral change techniques proposed by Michie et al (2011).

    PDF File (Adobe PDF File), 19KB
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    ‎
    AADE: Association of American Diabetes Educators
    BCT: behavioral change technique
    CG: control group
    IG: intervention group
    RCT: randomized controlled trial
    T1DM: type 1 diabetes mellitus
    T2DM: type 2 diabetes mellitus
    TTM: transtheoretical model

    Edited by G Eysenbach; submitted 28.06.13; peer-reviewed by R Kok, T Fuller, S Langrial, A Conway; comments to author 29.07.13; revised version received 12.08.13; accepted 15.09.13; published 13.12.13

    Copyright

    ©Michael van Vugt, Maartje de Wit, Wilmy HJJ Cleijne, Frank J Snoek. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.12.2013.

    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.