SYSTEMATIC REVIEW

published: 31 January 2022

doi: 10.3389/fpsyg.2021.746217

Effectiveness of eHealth-Based
Psychological Interventions for
Depression Treatment in Patients
With Type 1 or Type 2 Diabetes
Mellitus: A Systematic Review
Esperanza Varela-Moreno 1,2,3 , Mónica Carreira Soler 1,3 , José Guzmán-Parra 2,3 ,
Francisco Jódar-Sánchez 4 , Fermín Mayoral-Cleries 2,3 and María Teresa Anarte-Ortíz 1,3*
1
Departamento de Personalidad, Evaluación y Tratamiento Psicológico, Facultad de Psicología, Universidad de Málaga,
Málaga, Spain, 2 Unidad de Gestión Clínica en Salud Mental, Hospital Regional Universitario de Málaga, Málaga, Spain,
3
Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain, 4 Departamento de Economía Aplicada, Facultad
de Ciencias Económicas, y Empresariales Universidad de Málaga, Málaga, Spain

Edited by: Background: Comorbidity between diabetes mellitus and depression is highly prevalent.
Eleni Petkari, The risk of depression in a person with diabetes is approximately twice that of a
Universidad Internacional de La
Rioja, Spain
person without this disease. Depression has a major impact on patient well-being
Reviewed by:
and control of diabetes. However, despite the availability of effective and specific
Rachael Frost, therapeutic interventions for the treatment of depression in people with diabetes, 50%
University College London, of patients do not receive psychological treatment due to insufficient and difficult
United Kingdom
Giorgia Varallo, accessibility to psychological therapies in health systems. The use of information and
Italian Auxological Institute communication technologies (ICTs) has therefore been proposed as a useful tool for the
(IRCCS), Italy
delivery of psychological interventions, but it continues to be a field in which scientific
*Correspondence:
María Teresa Anarte-Ortíz
evidence is recent and controversial. This systematic review aims to update the available
anarte@uma.es information on the efficacy of psychological interventions delivered through ICTs to
improve depressive symptomatology in patients with diabetes.
Specialty section:
This article was submitted to Methods: A systematic review of the literature was performed following the PRISMA
Psychology for Clinical Settings, guidelines and using MEDLINE, Embase, PubMed, Web of Science, PsycINFO, Scopus,
a section of the journal
Frontiers in Psychology
and Cochrane Library databases to search for randomized clinical trials of eHealth
Received: 26 July 2021
treatments for patients with diabetes and comorbid depression from 1995 through
Accepted: 20 December 2021 2020. In addition, studies related to follow-up appointments were identified. Inclusion
Published: 31 January 2022 criteria were as follows: (a) randomized clinical trials (RCTs); (b) patients with type 1 and
Citation: type 2 diabetes; (c) adult population over 18 years of age; (d) presence of depressive
Varela-Moreno E, Carreira Soler M,
Guzmán-Parra J, Jódar-Sánchez F, symptomatology assessed with standardized instruments; (e) treatments for depression
Mayoral-Cleries F and Anarte-Ortíz MT based on established psychotherapeutic techniques and principles; (f) delivered through
(2022) Effectiveness of eHealth-Based
Psychological Interventions for
eHealth technologies. We did not limit severity of depressive symptomatology, delivery
Depression Treatment in Patients With setting or comparison group (treatment as usual or other treatment). Two coauthors
Type 1 or Type 2 Diabetes Mellitus: A independently reviewed the publications identified for inclusion and extracted data from
Systematic Review.
Front. Psychol. 12:746217. the included studies. A third reviewer was involved to discuss discrepancies found.
doi: 10.3389/fpsyg.2021.746217 The PEDro scale was used to assess the quality of the RCTs. No meta-analysis of the

Frontiers in Psychology | www.frontiersin.org 1 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

results was performed. The protocol used for this review is available in PROSPERO
(Reg; CRD42020180405).
Results: The initial search identified 427 relevant scientific publications. After removing
duplicates and ineligible citations, a total of 201 articles were analyzed in full text.
Ten articles met the criteria of this review and were included, obtaining very good
scientific quality after evaluation with the PEDro scale. The main results show that
the eHealth psychological intervention for depression in patients with diabetes showed
beneficial effects both at the end of treatment and in the short (3 months) and long
term (6 and 12 months) for the improvement of depressive symptomatology. The
methodology used (type of diabetes, eHealth technology used, recruitment context,
implementation and follow-up) was very heterogeneous. However, all studies were based
on cognitive-behavioral tools and used standardized assessment instruments to evaluate
depressive symptomatology or diagnosis of MDD. Glycemic control was assessed by
glycosylated hemoglobin, but no benefits were found in improving glycemic control.
Only four studies included psychoeducational content on diabetes and depression,
but none used tools to improve or enhance adherence to medical prescriptions or
diabetes self-care.
Conclusions: ICT-based psychological interventions for the treatment of depression
in people with diabetes appear to be effective in reducing depressive symptomatology
but do not appear to provide significant results with regard to glycemic control.
Nonetheless, the scientific evidence reported to date is still very limited and the
methodology very diverse. In addition, no studies have implemented these systems in
routine clinical practice, and no studies are available on the economic analysis of these
interventions. Future research should focus on studying and including new tools to ensure
improvements in diabetes outcomes and not only on psychological well-being in order
to advance knowledge about these treatments. Economic evaluations should also be
undertaken to analyze whether these treatment programs implemented using eHealth
technologies are cost-effective.

Keywords: depression, diabetes mellitus, glycemic control, online, eHealth, telemedicine, psychological
treatment, systematic review

INTRODUCTION of all ages affected (Friedrich, 2017), and because it carries the
highest burden of disability among all mental disorders (Üstün
Depression is a major global public health problem both because et al., 2001). It is also responsible for the largest proportion of
of its high prevalence, with an estimated 300 million people the burden of comorbidity and morbidity attributable to non-
fatal health outcomes (Moussavi et al., 2007). The comorbidity
between depression and chronic disease, especially diabetes has
Abbreviations: AADQ, Acceptance and Action Diabetes Questionnaire; BAI, been widely reported in the literature (Khaledi et al., 2019). The
Beck Anxiety Inventory; BDI, Beck Depression Inventory; CES-D, Center risk of depression in a person with diabetes is approximately
for Epidemiological Studies Depression scale; CSQ-8, Client Satisfaction double that of a person without this disease (Anderson et al.,
Questionnaire; DDS, Diabetes Distress Scale; DSM-IV, Diagnostic and Statistical
Manual of Mental Disorders, 4th ed.; DSMQ, Diabetes Self-Management
2001; Semenkovich et al., 2015), generating a very negative
Questionnaire; GAD, Generalized Anxiety Disorder; GDS, Global Deterioration impact on emotional well-being, quality of life, and control of
Scale de Reisberg; HADS, Hospital Anxiety and Depression Scales; K-10, The the disease, resulting in poorer diabetes outcomes (Egede and
Kessler Psychological Distress Scale; MINI, Mini International Neuropsychiatric Ellis, 2010). A recent review (Khaledi et al., 2019) found that one
Interview 5.0.0; PAID, Diabetes Distress are the Problem Areas in Diabetes; PHQ-
in four adults with diabetes had depression and concluded that,
9, Patient Health Questionnaire-9 item; SF-12, Patient health-related quality of
life; SMP-T2D, Self-Management Profile for Type 2 Diabetes; WAS, Work and given the high prevalence of depressive disorders in patients with
Social Adjustment Scale; WHO CIDI-auto, World Health Organization Composite diabetes, screening for comorbid depression and its prevalent risk
International Diagnostic Interview. factors in this population is recommended.

Frontiers in Psychology | www.frontiersin.org 2 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

Scientific evidence on treatment for depression shows their patients. Recently, in response to the need to improve this
that depression can be successfully treated with a variety situation, non-face-to-face models of alternative psychological
of psychological and pharmacological interventions, often interventions have been proposed for implementation in medical
implemented through collaborative and stepped care care using new information and communication technologies
approaches (Cuijpers et al., 2008; Petrak and Herpertz, 2009; (ICTs), known as eHealth. However, although this is a rapidly
Baumeister, 2012). However, despite evidence recommending advancing field, the scientific evidence is not yet abundant.
the combination of both treatments, pharmacological treatments Effective online interventions for depression have been
remain the most common option in routine clinical practice. designed for the general population (Andrews et al., 2010;
Regarding psychological interventions for depression, those Montero-Marín et al., 2016; Karyotaki et al., 2021). However,
that implement behavioral therapy and cognitive techniques although eHealth programs to address depressive symptoms
have the highest efficacy and scientific evidence (Hofmann in the population with diabetes appear to show improvement
et al., 2012). On the other hand, treatment with antidepressant in depressive symptomatology and diabetes related distress
drugs is shown to be effective, but they differ substantially with (Franco et al., 2018), they are scarce and methodologically
respect to short- and long-term side effects (Hackett et al., 2008; diverse, offering no data on which aspects are the most effective.
Rayner et al., 2010; Moncrieff, 2011; Baumeister, 2012). For this Accordingly, this review aims to examine the information
reason, the National Institute for Health and Clinical Evidence published to date on the efficacy of psychological interventions
(NICE) guideline on depression recommends psychological delivered through eHealth to improve depressive symptoms in
interventions as first-line treatments for treating depressive patients with Type 1 diabetes (T1DM) or Type 2 Diabetes
symptoms (National Institute for Clinical Excellence, 2009; (T2DM) and to analyze the characteristics of each, in order to
Baumeister, 2012). contribute empirical evidence useful to professionals in their
The effective management of diabetes requires a complicated decision-making when developing, designing, or selecting future
and demanding treatment regimen where the patient must ICT-based interventions for depression in people with diabetes.
take an active role in his or her self-care, involving a high
degree of responsibility for his or her disease and constant OBJECTIVE
decision making about treatment. In addition, each type of
diabetes has certain distinct clinical and treatment characteristics. The aim of this study was to conduct a systematic review
Daily life with diabetes differentiates this disease from other of the effectiveness of eHealth programs designed to reduce
chronic conditions and can generate routines associated with depressive symptomatology in people with type 1 diabetes
high levels of stress, which can lead to the appearance of mellitus (T1DM) and type 2 diabetes mellitus (T2DM) compared
depressive symptoms and the need for treatment. The appearance to control groups (treatment as usual [TAU] or other modalities).
of such depressive symptomatology can also affect glycemic To do this, the main outcome evaluated was the change
control; however, the data reported to date suggest a mainly in depressive symptoms assessed by validated psychometric
indirect effect of depression on glycemic control due to poor instruments that evaluate depressive symptomatology after the
self-care behaviors (Snoek et al., 2015). Therefore, treatment of treatment and in the follow up. Secondary objectives were to
depression in people with diabetes should be oriented toward analyze the effectiveness of the treatments on glycemic control
improving both psychological and medical outcomes, according through glycosylated hemoglobin (HbA1c) or other measures of
to the recommendations of the American Diabetes Association diabetes monitoring.
(Americam Diabetes Association, 2021).
Psychological interventions aimed at the treatment of METHODS
depression in patients with diabetes are well-documented as
being effective in treating depressive symptoms (Van der Feltz- This systematic review was carried out according to the
Cornelis et al., 2010; Markowitz et al., 2011; Petrak et al., 2015). recommendations of the PRISMA statement (Urrútia
In contrast, studies on pharmacological treatment for depression and Bonfilll, 2013), and the protocol followed to
in people with diabetes report inconclusive results (Baumeister, develop this systematic review is available in PROSPERO
2012; Baumeister et al., 2012; Petrak et al., 2015) and sometimes (Reg: CRD42020180405).
negative results (Lustman et al., 1997). However, reviews on the
efficacy of both interventions on improving glycemic control Inclusion and Exclusion Criteria
obtained unsatisfactory results (Van der Feltz-Cornelis et al., The following inclusion criteria were considered for this review:
2010; Markowitz et al., 2011; Petrak et al., 2015). It is essential (a) randomized clinical trials (RCTs); (b) patients with a diagnosis
to take these data into account for the development of future of T1DM and T2DM according to ADA criteria (2021); (c)
research and interventions. presence of depressive symptomatology or Major Depressive
Despite the availability of effective therapeutic interventions Disorder (MDD) assessed with standardized instruments; (d)
for the treatment of depressive symptomatology, not all patients adult population over 18 years of age; (e) psychological treatment
can be treated with the resources available. It has been found that programs for depression based on established psychotherapeutic
50% of patients are not being treated (Egede and Ellis, 2010), and techniques and principles; (f) eHealth-based psychological
pharmacological treatment remains the treatment of choice, due intervention (mobile, web, etc.). There were no limits to the
to the high cost of face-to-face delivery of these treatments. As scope of the intervention or to the severity of depressive
a result, healthcare professionals are demanding alternatives for symptomatology. The inclusion criteria for the control group

Frontiers in Psychology | www.frontiersin.org 3 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

were as follows: (a) non-exposed control group: TAU or waiting Data Analysis
list; (b) comparisons with others equivalent treatments (e.g., Due to the paucity of studies conducted on eHealth treatments
face-to-face treatments). for depression in people with diabetes, the diverse methodology
Excluded from this review were all published uncontrolled and the insufficient data reported on the effectiveness of the
studies or any research that did not provide results on the programs provided by the different RCTs, we decided not to
effectiveness of these programs (e.g., protocols). We also conduct a meta-analysis of the results found. Consequently,
excluded studies focusing on other types of diabetes (e.g., we were unable to include a quantitative analysis of the
gestational diabetes), populations under 18 years of age, results; instead, we conducted a systematic review following the
those aimed at other chronic diseases or psychopathological recommendations of the PRISMA guidelines (Moher et al., 2009).
disorders, studies that did not implement eHealth-based
depression treatment programs, studies not aimed at the Evaluation of Studies Quality
treatment of depression (e.g., assessment studies, self-help, The PEDro scale (de Morton, 2009) was used to assess the
or psychoeducational treatments) and those that did not use quality of the clinical trials by means of 11 items rated 0–1,
validated assessment instruments. depending on whether the study does not meet the evaluated
criterion or meets it, respectively. It should be noted that the
Information Sources and Search Strategy first item is not considered for the final calculation, and thus the
The following databases were used in our search strategy: maximum score is 10 points. Those studies with a total score
MEDLINE, Embase, PubMed, Web of Science, PsycINFO, equal to or higher than 6 were considered high quality, those
Scopus, and Cochrane Library. Hand searches of reference with a total score of 4 or 5 were classified as moderate quality,
lists of studies and searches of Internet resources were also and those with a total score of <4 were considered low quality
performed (e.g., Google Scholar). Electronic searches were (Maher et al., 2003; de Morton, 2009). For the evaluation of
performed using various combinations of search terms such as the studies based on these criteria, two independent reviewers
diabetes; depression; depressive disorder; affective symptoms; (EV, MC) performed the analysis by verifying compliance with
internet; computer; online therapy; telehealth; telecare; web- the criteria. Any discrepancies found were resolved by a third
based; e-health intervention; blood glucose; glycosylated reviewer (MTA).
hemoglobin; glycemic load. The language was not limited,
and the years of publication were stipulated to be between RESULTS
1995 and 2020 (decision based on the recognition that the
Internet became a major source in 1995 with the launch of Search Results
Windows 95). The last search was conducted on December The electronic search yielded 423 potentially relevant articles.
15, 2020. For example, using PubMed, the specific search Four additional articles were identified that were not found in
strategy was as follows: (((diabetes[Title/Abstract]) AND the databases but obtained after manual searches of reference
(depression[Title/Abstract] OR “depressive disorder”[Mesh] OR lists of studies and searches of Internet resources. After removal
“affective symptoms”[Mesh])) AND (internet[Title/Abstract] of duplicates (n = 75) and ineligible studies (n = 151),
OR computer[Title/Abstract] OR “online therapy”[Mesh] a total of 201 articles were retained for full-text review.
OR “telehealth”[Mesh] OR “telecare”[Mesh] OR “web- Fifteen articles were eliminated because they did not focus
based”[Mesh] OR “e-health intervention”[Mesh])) on diabetes; 29 articles did not evaluate the effectiveness of
AND (blood glucose[Title/Abstract] OR glycosylated a psychological intervention; 30 articles did not address the
hemoglobin[Title/Abstract] OR “glycemic load”[Mesh]. treatment of depression; 32 were not based on established
psychotherapeutic techniques; 35 were not delivered using
eHealth tools; 46 were not aimed at an adult population over
Study Selection and Data Extraction 18 years of age; three articles addressed the protocol and
Process did not report clinical trial data; one article was excluded
The studies were selected through a two-stage process. First, two because it was not possible to access it. Finally, 10 articles were
independent reviewers (EV and MC) extracted the data from the selected for full-text evaluation. The flow diagram is presented
different databases and imported them into an application for in Figure 1.
the management of bibliographic references (Zotero), removing
duplicate citations. After obtaining the total number of records Quality of the Studies
or unique citations screened, both reviewers independently Regarding the quality of the included articles, all were of
examined the titles and abstracts of all the studies generated by moderate-high quality on the PEDro scale. Nine of these articles
the electronic searches. Second, they checked that the inclusion were considered high quality, scoring above six points on the
and exclusion criteria were met. Thus, if the abstract met the PEDro scale: Nobis et al. (2015), Clarke et al. (2019), Naik et al.
inclusion criteria, following the protocol for article selection, the (2019), and Baldwin et al. (2020) scored 9/10. Ebert et al. (2017)
full texts were obtained. A third reviewer intervened (MTA), achieved a score of 8/10, and in the articles by Piette et al.
after receiving both reviews, in order to resolve the discrepancies (2011), Van Bastelaar et al. (2011, 2012), and Newby et al. (2017)
found, and ten articles were finally included for qualitative the score was 7/10. Finally, the study by Egede et al. (2018)
analysis (see Figure 1). scored 5/10. The evaluation of the studies using the PEDro scale

Frontiers in Psychology | www.frontiersin.org 4 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

FIGURE 1 | Flow diagram based on PRISMA guidelines.

therefore shows values between 5/10 and 9/10. Thus, nine of the but three studies (Van Bastelaar et al., 2011, 2012; Egede et al.,
articles scored higher than 6/10, and were considered to be of 2018). Item 4 (the groups were similar at baseline in relation to
high quality. Only one article scored 5/10, indicating moderate the most important prognostic indicators) was satisfied by all the
quality. No study was rated as low quality. Consequently, we can articles. Item 5 (all subjects were blinded) was not met in three of
conclude that, according to this assessment, the articles included the articles (Piette et al., 2011; Van Bastelaar et al., 2011, 2012).
in this review are of high and moderate quality, with the majority Item 6 (all therapists administering treatment were blinded) was
being considered high quality (except one). With respect to the only met in six of the articles analyzed (Van Bastelaar et al., 2011,
analysis of each of the items of the PEDro scale, we note that 2012; Nobis et al., 2015; Ebert et al., 2017; Clarke et al., 2019;
item 1 (inclusion criteria were specified) and item 2 (subjects Baldwin et al., 2020). Item 7 (all evaluators who measured at
were randomly assigned to the groups) were satisfied by all the least one key outcome were blinded) was met in seven of the ten
articles analyzed (Piette et al., 2011; Van Bastelaar et al., 2011, articles (Van Bastelaar et al., 2011, 2012; Nobis et al., 2015; Ebert
2012; Nobis et al., 2015; Ebert et al., 2017; Newby et al., 2017; et al., 2017; Clarke et al., 2019; Naik et al., 2019; Baldwin et al.,
Egede et al., 2018; Clarke et al., 2019; Naik et al., 2019; Baldwin 2020). Item 8 (measures of at least one of the key outcomes were
et al., 2020). Item 3 (allocation was concealed) was satisfied by all obtained from more than 85% of the subjects initially assigned

Frontiers in Psychology | www.frontiersin.org 5 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

to the groups) was only satisfied in three of the articles (Piette Evaluation and Monitoring Instruments
et al., 2011; Nobis et al., 2015; Egede et al., 2018). Item 9 (results All the studies included standardized measures to assess
were presented for all subjects who received treatment or were the severity of depressive symptoms. Two studies addressed
assigned to the control group, or when this was not possible, treatment of mild-moderate depressive symptoms (Piette et al.,
data for at least one key outcome were analyzed by intention to 2011; Clarke et al., 2019); two had as inclusion criteria, patients
treat) was satisfied by seven of the articles (Van Bastelaar et al., with moderate-high severity depressive symptomatology (Van
2011, 2012; Ebert et al., 2017; Newby et al., 2017; Clarke et al., Bastelaar et al., 2011; Naik et al., 2019), and one focused on high
2019; Naik et al., 2019; Baldwin et al., 2020). Item 10 (results of severity depressive symptoms (Nobis et al., 2015). Lastly, two of
between-group statistical comparisons were reported for at least the studies aimed to evaluate the efficacy of treatment for patients
one key outcome) was not satisfied by one of the articles analyzed with MDD (Newby et al., 2017; Egede et al., 2018).
(Van Bastelaar et al., 2011). Finally, item 11 (study provides point The following were used to assess depressive symptomatology:
and variability measures for at least one key outcome) was not the Patient Health Questionnaire-9 item (PHQ-9) (Newby
satisfied by two of the articles analyzed (Van Bastelaar et al., 2011; et al., 2017; Clarke et al., 2019; Naik et al., 2019), the Beck
Egede et al., 2018). Depression Inventory (BDI) (Piette et al., 2011), and the Center
for Epidemiological Studies Depression scale (CES-D) (Van
Bastelaar et al., 2011; Nobis et al., 2015). In three of the studies,
MDD was diagnosed using either the World Health Organization
Characteristics of Included Studies and Composite International Diagnostic Interview (WHO CIDI-
Participants auto) (Van Bastelaar et al., 2012) or the diagnostic criteria of
Design the Diagnostic and Statistical Manual of Mental Disorders, 4th
The ten articles included (Piette et al., 2011; Van Bastelaar et al., ed. (DSM-IV) (Egede et al., 2018) or the Mini International
2011, 2012; Nobis et al., 2015; Ebert et al., 2017; Newby et al., Neuropsychiatric Interview 5.0.0 (Newby et al., 2017). Only
2017; Egede et al., 2018; Clarke et al., 2019; Naik et al., 2019; one study included, in addition to psychometric assessment
Baldwin et al., 2020) corresponded to a total of seven studies. For instruments, the DMS-IV structured clinical interview (SCID-I)
easier reading we allude to the first published article to refer to to confirm the diagnosis of depression according to the diagnostic
each study (Piette et al., 2011; Van Bastelaar et al., 2011; Nobis criteria of the DMS-IV. The secondary variables evaluated in each
et al., 2015; Newby et al., 2017; Egede et al., 2018; Clarke et al., of the studies are shown in Table 1.
2019; Naik et al., 2019). All the studies included in this review Glycemic control was analyzed by HbA1c in all the studies.
were RCTs published in scientific journals. The search did not The secondary variables evaluated in each of the studies are
yield any doctoral theses or conference proceedings. shown in Table 1.

Recruitment Context Intervention Characteristics

With regard to recruitment, two of the studies analyzed used Psychotherapeutic Tools
advertisements and healthcare settings to recruit the sample All the studies included in this review were based on established
(Newby et al., 2017; Clarke et al., 2019). Two studies exclusively cognitive and/or behavioral psychological tools for the treatment
used advertisements as recruitment methods (Van Bastelaar et al., of depression. The intervention characteristics are listed in
2011; Nobis et al., 2015), and three used only the healthcare Table 2. In four studies, the intervention involved cognitive
setting as the recruitment method (Piette et al., 2011; Egede et al., behavioral therapy (CBT) (Piette et al., 2011; Van Bastelaar et al.,
2018; Naik et al., 2019). None used a primary healthcare system 2011; Newby et al., 2017; Clarke et al., 2019), and three studies
for recruitment. used a proprietary package that included both cognitive and
behavioral strategies: HOPE (Naik et al., 2019), GET.ON Mood
Enhancer Diabetes (Nobis et al., 2015), and Behavior Activation
Participants Treatment (Egede et al., 2018).
The sample size of the studies was 1960 patients (Piette et al., Psychoeducational content pertaining to diabetes and
2011; Van Bastelaar et al., 2011; Nobis et al., 2015; Newby et al., depression was addressed in four of the studies included in
2017; Egede et al., 2018; Clarke et al., 2019; Naik et al., 2019). this review (Piette et al., 2011; Van Bastelaar et al., 2011;
The characteristics of the included studies and the information Nobis et al., 2015; Naik et al., 2019), while three studies did
extracted are summarized in Table 1. not include this aspect (Newby et al., 2017; Egede et al.,
All the studies focused on patients with T2DM, and only three 2018; Clarke et al., 2019). Naik et al. (2019) also included
also included patients with T1DM (Van Bastelaar et al., 2011; management of diet-related thoughts, physical activity, and
Nobis et al., 2015; Newby et al., 2017). The mean age of the people medication management.
included in the studies in this review was 52.2 years. Most studies
reported that 44.5% of their sample were women (Piette et al., Comparison Group
2011; Van Bastelaar et al., 2011; Nobis et al., 2015; Newby et al., In the studies analyzed in this review, the treatment group
2017; Clarke et al., 2019), except two studies that reported that was compared with different group formats: one study
93.8% of the sample were men (Egede et al., 2018; Naik et al., compared their intervention vs. waiting list (Van Bastelaar
2019). et al., 2011), three studies used enhanced usual care

Frontiers in Psychology | www.frontiersin.org 6 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

TABLE 1 | Characteristics of the included studies according to the type of eHealth application.

References Country Sample (N) Type of Type of app Age (M, SD) Gender (% Sample Depression Glycemic Other variables
DM eHealth female sex) recruitment assessment control
TG (n) CG (n)
and criteria

Nobis et al. Germany 256 T2DM or Web-based 51 (12) 63% Online and offline CES-D ≥23 HbA1c PAID, HADS,
(2015) and T1DM advertisement SCID-I AADQ, DSMQ,
Ebert et al. CSQ-8
(2017) 129 127
Newby et al. Australia 90 T2DM or Web-based 46.7 (12.6) 64% Online MDD PHQ HbA1c PAID, K-10,
(2017) T1DM advertisements (5–23) SF-12, GAD-7,
and flyers in PHQ-15, MINI
41 49 medical settings
Clarke et al. Australia 723 T2DM Web-based 57.7 (10.6) 60.4% Online PHQ< 19 HbA1c WAS, DDS, GAD,
(2019) and advertisements, SMP-T2D
Baldwin et al. community
(2020) organizations,
health
368 355 professionals
Van Bastelaar Netherlands 255 T2DM or Web-based 50 (12) 61% Advertisements CES-D ≥16 HbA1c PAID
et al. (2011, T1DM
2012) 125 130
Piette et al. United States 291 T2DM Telephone 56 (10.1) 51.1% Community- BDI ≥14 HbA1c Blood pressure,
(2011) university-and VA physical activity
healthcare system (pedometer), Brief
Cope, Perceived
Competence
Scale, Morisky
medication
adherence scale y
145 146 SF-12
Naik et al. United States 255 T2DM Telephone 61.9 (8.3) 10.2% Health care PHQ-9 ≥10 HbA1c
(2019) system
(MEDVAMC) and
136 89 outpatient clinics
Egede et al. United States 90 T2DM Videocall 63.1 (4.2) 2.2% Health care MDD HbA1c BAI, GDS
(2018) system (DSM-IV)
(MEDVAMC) and
43 47 outpatient clinics

TG, Treatment Group; CG, Control/Comparison Group; M, Mean; SD, Standard Deviation; T1DM or T2DM, Type 1 and 2 Diabetes Mellitus; HbA1c, glycosylated hemoglobin; MDD,
Major Depressive Disorder. For measurement acronym’s meaning, see the List of nomenclatures section.

(Piette et al., 2011; Newby et al., 2017; Naik et al., 2019), Follow-Up
one study compared the intervention with a treatment-as-usual The results of this review indicate that patient follow-up was
group plus online psychoeducation for depression (Nobis et al., very diverse. One study evaluated efficacy in the short term
2015), another study with a placebo intervention group on (3 months) (Newby et al., 2017), other studies in the medium
healthy lifestyles (Clarke et al., 2019), and one study compared and long term (6 and 12 months) (Nobis et al., 2015; Clarke
the same intervention but with different formats: video call vs. et al., 2019; Naik et al., 2019), and three of them (Piette et al.,
same-room (Egede et al., 2018). None of the studies reported the 2011; Van Bastelaar et al., 2011; Egede et al., 2018) reported no
specifics of TAU. follow-up evaluation data for the variables studied, as shown in
Table 2.
Type of eHealth Delivery
The eHealth delivery method most commonly used to Efficacy of Intervention on Depressive
implement the intervention was based on web tools (Van Symptomatology and Glycemic Control
Bastelaar et al., 2011; Nobis et al., 2015; Newby et al., Depressive Symptomatology
2017; Clarke et al., 2019). A further two studies used the After reviewing the efficacy results of the various
telephone (Piette et al., 2011; Naik et al., 2019), and only eHealth treatment programs for the improvement
one study used a video call format (Egede et al., 2018). The of depressive symptomatology and MDD in people
duration of the intervention and participant follow-up was with T1DM and T2DM in the studies included in
also different in each of the studies analyzed, as can be seen this review, we found that all the studies report
in Table 2. improvements in depressive symptoms following treatment

Frontiers in Psychology | www.frontiersin.org 7 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

TABLE 2 | Characteristics of the intervention and efficacy results in depression and HbA1c.

Author and type of app Psychotherapeutic Group Follow-up Diabetes Efficacy results
comparison content

Nobis et al. (2015) and Systematic Treatment as usual 6 months Yes The TG had significantly lower depressive symptoms
Ebert et al. (2017) behavioral + online than the CG at both post-treatment (d = 0.89; p <
web-based activation and psychoeducation 0.001) and 6-month follow-up (d = 0.83; p < 0.0001)
problem solving about depression but there were no significant differences with respect to
glycemic control.
Newby et al. (2017) CBT Treatment as usual 3 months No The TG showed statistically significant improvements on
web-based the PHQ-9 both at post-treatment (g = 0.78) and at
3-month follow-up vs. the CG. No significant differences
were found in self-reported HbA1c levels (g = 0.14).
Clarke et al. (2019) and CBT Placebo 6 and 12 No All participants showed improvements in depressive
Baldwin et al. (2020) intervention on months symptomatology assessed by the PHQ-9 at
web-based healthy lifestyles post-treatment, but no statistically significant differences
were detected between groups (p = 0.74) or in HbA1c
levels. Efficacy analyses at follow-up report significant
improvements at 6 months (p < 0.001) and 12 months
(p < 0.001) between the TG and CG. HbA1c decreased
significantly between baseline in the TG and CG and at 6
months (p = 0.01) but not at 12 months (p = 0.12)
between the two groups.
Van Bastelaar et al. (2011, CBT Waiting list No follow-up Yes Web-based CBT was effective in reducing depressive
2012) web-based symptoms by intention-to-treat analysis (d = 0.29; p <
0.001) but had no beneficial effect on glycemic control (p
> 0.05) or in patients with Major Depressive Disorders.
Piette et al. (2011) telephone CBT Enhanced Usual No follow-up Yes The results show statistically significant improvements
Care between groups (p < 0.0001) after the intervention in
depression assessed by the BDI. However, no significant
improvements in HbA1c (p = 0.7) were observed
between groups.
Naik et al. (2019) telephone HOPE Enhanced Usual 12 months Yes The differences in PHQ-9 between HOPE and GC were
Care statistically significant after intervention (p = 0.03) and at
12 months (p = 0.03) but were not significant for HbA1c
between groups at either post-treatment (p = 0.08) or
12 months (p = 0.83).
Egede et al. (2018) videocall BAT Same-room No follow-up No No statistically significant differences were found
treatment between BAT and same-room therapy. No significant
differences were obtained in either depression scores or
HbA1c after 12 months of follow-up between the two
groups.

TG, Treatment Group; CG, Control/Comparison Group; CBT, Cognitive Behavioral Therapy; HOPE, Healthy Outcomes Through Patient Empowerment; BAT, Behavioral Activation
Treatment; HbA1c, glycosylated hemoglobin. Articles sorted by year of publication and type of eHealth application. For measurement acronym’s meaning, see the List of
nomenclatures section.

(Piette et al., 2011; Van Bastelaar et al., 2011; Nobis et al., 2015; psychoeducational interventions in addition to TAU (Nobis et al.,
Newby et al., 2017; Egede et al., 2018; Clarke et al., 2019; Naik 2015), or compared to healthy lifestyles (Clarke et al., 2019),
et al., 2019) using cognitive-behavioral toolkits and different waiting list (Van Bastelaar et al., 2011) or face-to-face treatment
eHealth formats. Regarding follow-up, only four studies reported (Egede et al., 2018) (Table 3). Likewise, all eHealth treatment
efficacy analyses (Nobis et al., 2015; Newby et al., 2017; Clarke programs were effective in improving symptomatology that was
et al., 2019; Naik et al., 2019), showing that these results were mild-moderate (Piette et al., 2011; Clarke et al., 2019), moderate-
maintained in the short (3 months) (Newby et al., 2017), medium severe (Van Bastelaar et al., 2011; Naik et al., 2019), and severe
(6 months) (Nobis et al., 2015; Clarke et al., 2019), and long term (Nobis et al., 2015), as well as in patients with diabetes and
(12 months) (Clarke et al., 2019; Naik et al., 2019). These data are diagnosis of MDD (Newby et al., 2017; Egede et al., 2018).
provided in more detail in Tables 2, 3. However, none of the studies compared their treatment regimen
Regarding the method of administration, all programs based in patients of varying depressive severity. None of the studies
on ICT formats (web, telephone, and video call) were shown reviewed compared different types of eHealth delivery nor did
to be effective in reducing depressive symptomatology after they report cost-effectiveness analyses of each type of delivery
intervention compared to TAU (Piette et al., 2011; Nobis et al., in order to report results on which type of eHealth delivery
2015; Newby et al., 2017; Naik et al., 2019), compared to small might be more cost-effective in routine clinical practice. Only

Frontiers in Psychology | www.frontiersin.org 8 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

TABLE 3 | Results of depression and HbA1c baseline, post-treatment, and follow-up.

Author and type of app Depression Depression Depression HbA1c HbA1c post- HbA1c follow-up M
baseline M post- follow-up M (SD) baseline M treatment M (SD)
(SD) treatment M (SD) (SD)
(SD)

TG CG TG CG Time TG CG TG CG TG CG Time TG CG

Nobis et al. (2015) and Ebert 32.2 31.5 21.1 28.9 6 months 19.8 26.8 7.6% 7.4% – – 6 months 7.6% 7.4%
et al. (2017): web-based (7.0) (7.5) (8.8) (8.7) (9.6) (9.4) (1.6%) (1.3%) (1.6%) (1.4%)
Newby et al. (2017): 15.9 14.3 7.7 11.7 3 months 11.0 NR 7.9% 7.7% NR NR 3 months NR NR
web-based (5.2) (5.2) (5.0) (5.2) (4.5) (1.8%) (1.8%)
Clarke et al. (2019) and 11.3 10.7 8.7 8.2 6 months 8.3 8.4 NR NR NR NR 6 months 7.4% 7.2%
Baldwin et al. (2020): (4.0) (4.1) (5.6) (5.5) (0.3) (0.3) (0.1%) (0.1%)
web-based 12 8.4 8.0 12 7.5% 7.2%
months (0.3) (0.3) months (0.1%) (0.1%)
Van Bastelaar et al. (2011, 29 28 NR NR No – – 7.4% 7.3% NR NR No – –
2012): web-based (7) (7) follow-up (1.6%) (1.6%) follow-up
Piette et al. (2011): 26.7 26.5 14.2 18.6 No – – 7.5% 7.7% 7.7% 7.7% No – –
telephone (7.7) (9.9) (10.3) (10.7) follow-up (1.7%) (1.7%) (1.8%) (1.7%) follow-up
Naik et al. (2019): telephone 15.8 16.2 10.9 12.4 12 10.1 12.6 9.2% 9.3% 9.1% 8.7% 12 8.7% 8.9%
(4.2) (4.0) (6.1) (6.0) months (6.9) (6.5) (1.4%) (1.5%) (1.7%) (1.7%) months (1.6%) (2.0%)
Egede et al. (2018): 27.8 28.4 NR NR No – – 6.9% 7.3% NR NR No – –
videocall (9.6) (10.2) follow-up (1.1%) (2.0%) follow-up

TG, Treatment Group; CG, Control/Comparison Group; M, Mean; SD, Standard Deviation; HbA1c, glycosylated hemoglobin; NR, not reported. Articles sorted by year of publication
and type of eHealth application.

one study (Egede et al., 2018) compared the effectiveness of the difficulty in accessing face-to-face interventions (Lehtinen
the same treatment program for depression for people with et al., 1997). We also found a great deal of heterogeneity
diabetes using cognitive-behavioral tools implemented through in the methodology used by the studies analyzed: type of
ICTs (video call) versus the traditional face-to-face format, diabetes, severity of depressive symptomatology, recruitment
finding no significant differences between these two formats. and intervention context, treatment content, type of eHealth
It was not possible to report data on the efficacy of these delivery, comparison group, and follow-up, which makes
interventions for each type of diabetes, since none of the studies it difficult to generalize the results and draw conclusions.
analyzed made comparisons between these two populations However, this finding is consistent with that reported by
(T1DM and T2DM). other reviews (Petrak and Herpertz, 2009; Markowitz et al.,
2011) on the implementation of these treatments in the
Glycemic Control usual format. Nevertheless, their methodological quality
The mean baseline HbA1c levels found were 6.64% mmHg. was very good, a basic result that is very favorable for
None of the studies indicated, in their inclusion criteria, specific scientific quality.
HbA1c levels for participation in their programs. Regarding An important consideration is that three of the reviewed
the effect of the eHealth intervention on glycemic control, no studies (Van Bastelaar et al., 2011; Nobis et al., 2015;
significant improvements were found in any of the studies Newby et al., 2017) included patients with T1DM and
reviewed (Tables 2, 3). T2DM. This is relevant because although both conditions
belong to the same endocrine disease, they are categorized
DISCUSSION by the American Diabetes Association (Americam Diabetes
Association, 2021), as different etiopathogenetic categories with
The aim of this study was to conduct a systematic review distinct characteristics and treatments. In the case of T2DM,
of the current evidence on eHealth programs available for the main objectives of medical treatment focus on lifestyle
the treatment of depression in people with diabetes, and to modification and administration of oral antidiabetic drugs
discuss the procedures and findings extracted, since this is (Knowler et al., 2009; Americam Diabetes Association, 2021).
a current and rapidly growing topic in the field of mental In contrast, T1DM involves a complicated treatment regimen
health and chronic diseases. Our main findings indicate that, that additionally requires daily self-monitoring of blood glucose,
although psychological intervention programs are effective insulin administration, carbohydrate counting, management
in reducing depressive symptomatology in patients with of hyperglycemia and hypoglycemia, etc. (Americam Diabetes
diabetes, the evidence reported thus far on their delivery Association, 2021). These differences between the two types
through eHealth formats is scarce despite the high incidence of diabetes have important implications for the individual
of depression in this population (Anderson et al., 2001) and (differentiated sources of distress), as well as for the design and

Frontiers in Psychology | www.frontiersin.org 9 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

content of the treatment programs implemented. We therefore scientific evidence that psychotherapy achieves superior long-
recommend that this aspect be considered in future research term results and lower relapse rates (Cuijpers et al., 2019).
when designing intervention programs, as it may influence However, due to this high prevalence, the economic resources
their effectiveness. required to meet the psychological treatment needs of this
There was higher percentage of women than men was population in PC are not feasible (Bower and Gilbody, 2005). For
observed, which again demonstrates the higher prevalence rate this reason, innovative cost-effective alternatives using ICTs for
of women with depressive symptomatology (Carreira et al., 2010; the treatment of depression in PC (Whiteside et al., 2014; Castro
Snoek et al., 2015). It was also noted that the different studies et al., 2015; Montero-Marín et al., 2016; Rodriguez-Pulido et al.,
report high percentages of the population with a high educational 2020) that minimally involve mental health services are being
level (university studies), but no data is analyzed or reported proposed. Nonetheless, it is not possible to draw conclusions
regarding this variable, which could influence the effectiveness of from this review with respect to the intervention settings because,
and adherence to web-based treatment programs for depression. although ICTs were used for the treatment of depression in
Therefore, it would be of interest for future research to take people with diabetes, none of the studies were carried out
this variable into account and report efficacy data comparing directly in the PC environment. These data are important
groups with different educational levels, in order to advance our factors to consider for future interventions in order to study the
understanding of this type of intervention. possible barriers to implementation of these treatments in PC
Regarding the analysis of the results that were the main focus health systems.
of this review, we found that treatment programs for depression Stepped care models have also been proposed in PC
in people with diabetes implemented using eHealth technology (Bower and Gilbody, 2005), whereby a large proportion of
appear to be effective in reducing depressive symptomatology. patients are treated first with low-intensity interventions, with
Nevertheless, it is not possible to draw conclusions regarding significant clinical benefits (García-Herrera et al., 2011). These
which format of eHealth technology is most effective in treating interventions involve a simpler and easier approach than formal
depression for the following reasons. The first is the paucity psychotherapies. The contact with patients is shorter, and
of studies (only seven included studies) and variability of the methods such as the Internet or mobile telephony can be
formats used (web, mobile phone and video call). Second, no used. In the case of depression, low-intensity interventions
studies have been found comparing different eHealth formats are offered to those patients who present mild or moderate
implementing the same treatment program. Only the study by depressive symptomatology. In addition, interventions that
Egede et al. (2018) compared an eHealth format (video call) require less interaction time with the therapist than face-to-
with face-to-face interventions, finding no significant differences face psychotherapy (guided self-help approach) or even no
between the two formats. Third, and although it was not the interaction at all (unguided self-help approach) seem to provide
subject under study in this review, none of the studies reported very positive results at low cost (Spek et al., 2007; Tate et al., 2009).
economic assessments that indicate whether these programs In this review, we found that only two of the studies analyzed
are cost-effective, possibly because they were not performed in focused on the treatment of mild-moderate depression (Piette
routine clinical practice. This would be an important aspect to et al., 2011; Clarke et al., 2019), two focused on the treatment of
include in future research. moderate-severe symptoms (Van Bastelaar et al., 2011; Naik et al.,
As a positive feature, we found that the treatment programs 2019), one on severe depressive symptoms (Nobis et al., 2015),
had in common the use of cognitive-behavioral tools, which and three were directed at treatment for MDD (Van Bastelaar
constitute the psychological treatment for depression that has et al., 2012; Newby et al., 2017; Egede et al., 2018). However,
been shown to be the most effective in the scientific literature the different intervention studies examined by this review
(Markowitz et al., 2011; Petrak et al., 2015) and clinical report good results following the intervention, regardless of the
guidelines (National Institute for Clinical Excellence, 2009), with severity of depressive symptomatology. Accordingly, the findings
good results. None of the studies included pharmacological appear to indicate that treatment programs for depression in
therapy, and the psychoeducational content varied among the people with diabetes implemented through eHealth formats are
different studies. effective in improving depressive symptomatology regardless of
Concerning the trial setting and recruitment of participants, severity. These results are very promising because many more
we found great diversity in the studies analyzed. Recruitment patients could benefit. Nevertheless, further research is needed
ranged from the use of advertisements in social networks to in this regard. In addition, it will be important to include
healthcare settings based on patient lists or only brochures. diagnostic interviews based on DSM-5 criteria and not only
However, no studies were identified that recruited the sample psychometric instruments, since clinical guidelines recommend
from primary care (PC), carrying out the intervention in the that the assessment of depression should not be based only on a
manner most similar to how such interventions would be carried mere symptom count (National Institute for Clinical Excellence,
out in the health care setting. In PC, the prevalence of depression 2009).
is very high at around 29% (Roca et al., 2009), has a high These results therefore suggest that this technology is effective
comorbidity with chronic diseases such as diabetes (Anderson for the treatment of depression in people with diabetes and has
et al., 2001), and is associated with poorer glycemic control the benefit of providing greater reach and care to a broader
(Egede and Ellis, 2010). Moreover, pharmacotherapy remains patient population. These are very important findings given the
the treatment of choice in PC for this population, despite scarcity of mental health resources (Bower and Gilbody, 2005).

Frontiers in Psychology | www.frontiersin.org 10 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

However, scientific evidence indicates that depression in people between the two types, use various eHealth formats, and do not
with diabetes not only has an adverse effect on the person’s include strategies aimed at improving adherence and diabetes
well-being but also on the clinical outcomes of the disease (Petrak self-care in their programs. Finally, the present systematic
et al., 2015), so treatment should be geared toward improving review only concentrated on ehealth depression treatment in
both psychological and medical outcomes (Petrak and Herpertz, adults with diabetes. Other meaningful indicators, such as
2009). Nonetheless, the results of this review indicate that these distress, anxiety, and quality of life, were not analyzed, which
treatments are not effective for improving control of diabetes. limited the examination of the overall effects of technology-
These results are similar to those reported by other reviews (Van based interventions. In addition, although other terms such as
der Feltz-Cornelis et al., 2010; Markowitz et al., 2011; Baumeister “technologies” or “telemedicine” could have been used, these
et al., 2012; Petrak et al., 2015), so it may be necessary to review terms did not meet the objectives set out in this review, as they
the treatments used in order to provide comprehensive patient were more general. Therefore, in order to focus our search on
management. Considering these results, we asked ourselves the articles that specifically target ehealth-delivered treatments, we
following question: what do these treatments bring to the diabetes chose to limit the terms used in the review.
setting and how do they differ from those developed for people
with depression without diabetes? This answer is key for future CONCLUSIONS
research to advance existing knowledge. The scientific literature
reports that depression appears to exert its effect on glycemic eHealth interventions have great potential to impact public
control in an indirect manner, through poor adherence and health. The rising use of the Internet and mobile devices across
self-care behaviors in diabetes (Snoek et al., 2015). However, the world has made these interventions increasingly common.
none of the studies included interventions addressed this aspect However, the scientific evidence in this field is very limited
in their programs. Therefore, it may be essential for the and recent. In order to draw conclusions, further studies that
treatment of depression in people with diabetes to include tools integrate these treatments into clinical practice are needed, as
aimed at improving adherence and diabetes self-management well as economic analyses of this type of intervention versus the
together with cognitive-behavioral strategies for the reduction of traditional face-to-face model.
depressive symptomatology.
DATA AVAILABILITY STATEMENT
Practical Implications
The results of the present review provide evidence of the The original contributions presented in the study are included
beneficial effect of eHealth cognitive-behavioral psychological in the article/supplementary material, further inquiries can be
interventions compared with usual care on the reduction directed to the corresponding author.
of depressive symptomatology. The evidence regarding
glycemic control was heterogeneous and inconclusive AUTHOR CONTRIBUTIONS
across the studies reviewed. We recommend that future
trials and clinical intervention in patients with diabetes EV-M and MC performed the independently searching process
and depressive symptoms consider these results and and organized the databases. MA-O intervened in order to
investigate the inclusion in their programs of tools for resolve the discrepancies found after the search in the databases.
self-care and adherence to diabetes treatment to improve EV-M wrote the first draft of the manuscript and was reviewed
not only the results for psychological well-being but also by MA-O and MC. All authors contributed to conception, design
for medical outcomes. It is also important to distinguish of the study, revised the manuscript, read, and approved the
between the two types of diabetes in order to develop submitted version.
specific content for each group as well as cost-effective
implementation and evaluation of these programs in routine FUNDING
clinical practice.
The translation of this article was carried out with funding from
Study Limitations the Puente Project (B.4) of the University of Malaga, entitled
This review collected data from a limited number of very Efficacy and Cost-Effectiveness of a Web Application to treat
heterogeneous studies on patients with diabetes receiving Depressive symptoms in adults with type 1 Diabetes: A controlled
treatment to reduce depressive symptoms using eHealth clinical trial (20-02-2021 /28-02-2022).
technologies, which made it difficult to perform a meta-analysis.
The review summarizes the evidence regarding treatments ACKNOWLEDGMENTS
for depression in a variety of settings, but none conducted
in PC systems. The included trials comprise samples with We would like to thank Laura Torreblanca Murillo for her
patients with type 1 and type 2 diabetes, do not differentiate collaboration in the first phase of the preparation of this work.

Frontiers in Psychology | www.frontiersin.org 11 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

REFERENCES Hackett, M. L., Anderson, C. S., House, A., and Xia, J. (2008). Interventions
for treating depression after stroke. Cochrane Database Syst. Rev. CD003437.
Americam Diabetes Association (2021). Classification and Diagnosis of Diabetes: doi: 10.1002/14651858.CD003437.pub3
Standards of Medical Care in Diabetes–2021. Diabetes Care 44(Suppl. 1), Hofmann, S. G., Asnaani, A., Vonk, I. J., Sawyer, A. T., and Fang, A. (2012). The
S15–S33. doi: 10.2337/dc21-S002 efficacy of cognitive behavioral therapy: a review of meta-analyses. Cognit. Ther.
Anderson, R. J., Freedland, K. E., Clouse, R. E., and Lustman, P. J. (2001). The Res. 36, 427–440. doi: 10.1007/s10608-012-9476-1
prevalence of comorbid depression in adults with diabetes: a meta-analysis. Karyotaki, E., Efthimiou, O., Miguel, C., Bermpohl, F. M. G., Furukawa, T.
Diabetes Care 24, 1069–1078. doi: 10.2337/diacare.24.6.1069 A., Cuijpers, P., et al. (2021). Internet-based cognitive behavioral therapy
Andrews, G., Cuijpers, P., Craske, M. G., McEvoy, P., and Titov, N. (2010). for depression: a systematic review and individual patient data network
Computer therapy for the anxiety and depressive disorders is effective, meta-analysis. JAMA Psychiatry 4, 361–371. doi: 10.1001/jamapsychiatry.20
acceptable and practical health care: a meta-analysis. PLoS ONE 10:e13196. 20.4364
doi: 10.1371/journal.pone.0013196 Khaledi, M., Haghighatdoost, F., Feizi, A., and Aminorroaya, A. (2019). The
Baldwin, P. A., Sanatkar, S., Clarke, J., Fletcher, S., Gunn, J., Wilhelm, K., prevalence of comorbid depression in patients with type 2 diabetes: an updated
et al. (2020). A web-based mental health intervention to improve social and systematic review and meta-analysis on huge number of observational studies.
occupational functioning in adults with type 2 diabetes (the springboard trial): Acta Diabetol. 6, 631–650. doi: 10.1007/s00592-019-01295-9
12-month outcomes of a randomized controlled trial. J. Med. Internet Res. Knowler, W. C., Fowler, S. E., and Hamman, R. F. (2009). Diabetes prevention
22:e16729. doi: 10.2196/16729 program research program. 10-year follow-up of diabetes incidence and
Baumeister, H. (2012). Inappropriate prescriptions of antidepressant drugs in weight loss in the diabetes prevention program outcomes study. Lancet 372,
patients with subthreshold to mild depression: Time for the evidence to become 1677–1686. doi: 10.1016/S0140-6736(09)61457-4
practice. J. Affect. Disord. 139, 240–243. doi: 10.1016/j.jad.2011.05.025 Lehtinen, V., Riikonen, E., and Lahtinen, E. (1997). Promotion of Mental Health on
Baumeister, H., Hutter, N., and Bengel, J. (2012). Psychological and the European Agenda. Helsinki: STAKES.
pharmacological interventions for depression in patients with diabetes Lustman, P. J., Griffith, L. S., Clouse, R. E., Freedland, K. E., Eisen, S. A., Rubin,
mellitus and depression. Cochrane Database Syst. Rev. 12:CD008381. E. H., et al. (1997). Effects of nortriptyline on depression and glycemic control
doi: 10.1002/14651858.CD008381.pub2 in diabetes: results of a double-blind, placebo-controlled trial. Psychosom. Med.
Bower, P., and Gilbody, S. (2005). Stepped care in psychological therapies: access, 59, 241–250. doi: 10.1097/00006842-199705000-00007
effectiveness and efficiency: narrative literature review. Br. J. Psychiatry 186, Maher, C. G., Sherrington, C., Herbert, R. D., Moseley, A. M., and Elkins,
11–17. doi: 10.1192/bjp.186.1.11 M. (2003). Reliability of the PEDro scale for rating quality of randomized
Carreira, M., Anarte, M. T., Ruiz De Adana, M. S., Félix Caballero, F., MacHado, controlled trials. Phys. Ther. 83, 713–721. doi: 10.1093/ptj/83.8.713
A., Domínguez-López, M., et al. (2010). Depresión en la diabetes mellitus tipo 1 Markowitz, S. M., Gonzalez, J. S., Wilkinson, J. L., and Safren, S. A. (2011). A review
y factores asociados. Med. Clin. 135, 151–155. doi: 10.1016/j.medcli.2010.02.027 of treating depression in diabetes: emerging findings. Psychosomatics 52, 1–18.
Castro, A., García-Palacios, A., García-Campayo, J., Mayoral, F., Botella, C., doi: 10.1016/j.psym.2010.11.007
García-Herrera, J. M., et al. (2015). Efficacy of low-intensity psychological Moher, D., Liberati, A., Tetzlaff, J., and Altman, D. G. (2009). PRISMA
intervention applied by ICTs for the treatment of depression in primary care: a group, preferred reporting items for systematic reviews and meta-
controlled trial. BMC Psychiatry 15:106. doi: 10.1186/s12888-015-0475-0 analyses: the PRISMA statement. Ann. Int. Med. 151, 264–269.
Clarke, J., Sanatkar, S., Baldwin, P. A., Fletcher, S., Gunn, J., Wilhelm, K., et al. doi: 10.7326/0003-4819-151-4-200908180-00135
(2019). A web-based cognitive behavior therapy intervention to improve Moncrieff, J. (2011). “The myth of the antidepressant: an historical analysis,”
social and occupational functioning in adults with type 2 diabetes (the in De-Medicalizing Misery (London: Palgrave Macmillan), 174–188.
SpringboarD trial): randomized controlled trial. J. Med. Internet Res. 21, 1–17. doi: 10.1057/9780230342507_13
doi: 10.2196/12246 Montero-Marín, J., Araya, R., Pérez-Yus, M. C., Mayoral, F., Gili, M., Botella,
Cuijpers, P., Quero, S., Dowrick, C., and Arroll, B. (2019). Psychological treatment C., et al. (2016). An internet-based intervention for depression in primary
of depression in primary care: recent developments. Curr. Psychiatry Rep. 21, care in Spain: a randomized controlled trial. J. Med. Internet Res.18:e5695.
1–10. doi: 10.1007/s11920-019-1117-x doi: 10.2196/jmir.5695
Cuijpers, P., Van Straten, A., Andersson, G., and Van Oppen, P. (2008). Moussavi, S., Chatterji, S., Verdes, E., Tandon, A., Patel, V., and Ustun, B. (2007).
Psychotherapy for depression in adults: a meta-analysis of comparative Depression, chronic diseases, and decrements in health: results from the World
outcome studies. J. Consult. Clin. Psychol. 76:909. doi: 10.1037/a0013075 Health Surveys. Lancet 370, 851–858. doi: 10.1016/S0140-6736(07)61415-9
de Morton, N. A. (2009). The PEDro scale is a valid measure of the methodological Naik, A. D., Hundt, N. E., Vaughan, E. M., Petersen, N. J., Zeno, D., Kunik,
quality of clinical trials: a demographic study. Aust. J. Physiother. 55, 129–133. M. E., et al. (2019). Effect of telephone-delivered collaborative goal setting
doi: 10.1016/S0004-9514(09)70043-1 and behavioral activation vs enhanced usual care for depression among adults
Ebert, D. D., Nobis, S., Lehr, D., Baumeister, H., Riper, H., Auerbach, R. P., with uncontrolled diabetes: a randomized clinical trial. JAMA Netw. Open.
et al. (2017). The 6-month effectiveness of Internet-based guided self-help for 2:e198634. doi: 10.1001/jamanetworkopen.2019.8634
depression in adults with Type 1 and 2 diabetes mellitus. Diabet. Med. 34, National Institute for Clinical Excellence (2009). Depression in Adults: Recognition
99–107. doi: 10.1111/dme.13173 and Management. Clinical Guideline [CG90]. National Institute for Health and
Egede, L. E., and Ellis, C. (2010). Diabetes and depression: global perspectives. Clinical Excellence.
Diabetes Res. Clin. Pract. 3, 302–312. doi: 10.1016/j.diabres.2010.01.024 Newby, J., Robins, L., Wilhelm, K., Smith, J., Fletcher, T., Gillis, I., et al.
Egede, L. E., Walker, R. J., Payne, E. H., Knapp, R. G., Acierno, R., and Frueh, B. C. (2017). Web-based cognitive behavior therapy for depression in people with
(2018). Effect of psychotherapy for depression via home telehealth on glycemic diabetes mellitus: a randomized controlled trial. J. Med. Internet Res.19:e157.
control in adults with type 2 diabetes: Subgroup analysis of a randomized doi: 10.2196/jmir.7274
clinical trial. J. Telemed. Telecare. 24, 596–602. doi: 10.1177/1357633X17730419 Nobis, S., Lehr, D., Ebert, D. D., Baumeister, H., Snoek, F., Riper, H., et al. (2015).
Franco, P., Gallardo, A. M., and Urtubey, X. (2018). Web-based interventions for Efficacy of a web-based intervention with mobile phone support in treating
depression in individuals with diabetes: review and discussion. JMIR Diabetes depressive symptoms in adults with type 1 and type 2 diabetes: a randomized
9:e9694. doi: 10.2196/preprints.9694 controlled trial. Diabetes Care 38, 776–783. doi: 10.2337/dc14-1728
Friedrich, M. J. (2017). Depression is the leading cause of disability around the Petrak, F., Baumeister, H., Skinner, T. C., Brown, A., and Holt, R. I. G. (2015).
world. JAMA. 317, 1517–1517. Depression and diabetes: treatment and health-care delivery. Lancet Diabetes
García-Herrera, J. M., Nogueras, E. V., Muñoz, F., and Morales, J. M. (2011). Endocrinol. 3, 472–485. doi: 10.1016/S2213-8587(15)00045-5
Guía de Práctica Clínica para el tratamiento de la depresión en Atención Petrak, F., and Herpertz, S. (2009). Treatment of depression in diabetes: an
Primaria. UGC Salud Mental Hospital Regional Universitario “Carlos Haya”. update. Curr. Opin. Psychiatry 22, 211–217. doi: 10.1097/YCO.0b013e32832
Málaga: GAEDAP. 07b45

Frontiers in Psychology | www.frontiersin.org 12 January 2022 | Volume 12 | Article 746217

Varela-Moreno et al. eHealth, Depression and Diabetes: Systematic Review

Piette, J. D., Richardson, C., Himle, J., Duffy, S., Torres, T., Vogel, M., et al. (2011). diabetic patients: a randomized, controlled trial. Diabetes Care 34, 320–325.
A randomized trial of telephonic counseling plus walking for depressed diabetes doi: 10.2337/dc10-1248
patients. Med. Care 49, 641–648. doi: 10.1097/MLR.0b013e318215d0c9 Van Bastelaar, K. M. P., Pouwer, F., Cuijpers, P., Riper, H., Twisk, J. W. R.,
Rayner, L., Price, A., Evans, A., Valsraj, K., Higginson, I. J., and Hotopf, M. (2010). and Snoek, F. J. (2012). Is a severe clinical profile an effect modifier in a
Antidepressants for depression in physically ill people. Cochrane Database Syst. Web-based depression treatment for adults with type 1 or type 2 diabetes?
Rev. CD007503. doi: 10.1002/14651858.CD007503.pub2 Secondary analyses from a randomized controlled trial. J Med Internet Res.
Roca, M., Gili, M., Garcia-Garcia, M., Salva, J., Vives, M., Garcia Campayo, J., et al. 14:e2. doi: 10.2196/jmir.1657
(2009). Prevalence and comorbidity of common mental disorders in primary Van der Feltz-Cornelis, C. M., Nuyen, J., Stoop, C., Chan, J., Jacobson, A.
care. J. Affect. Disord. 119, 52–58. doi: 10.1016/j.jad.2009.03.014 M., Katon, W., et al. (2010). Effect of interventions for major depressive
Rodriguez-Pulido, F., Castillo, G., Hamrioui, S., Martin, L. D., Vazquez-Beltrán, P., disorder and significant depressive symptoms in patients with diabetes mellitus:
de la Torre-Díez, I., et al. (2020). Treatment of depression in primary care with a systematic review and meta-analysis. Gen. Hosp. Psychiatry 32, 380–395.
computerized psychological therapies: systematic reviews. J. Med. Syst. 44, 1–8. doi: 10.1016/j.genhosppsych.2010.03.011
doi: 10.1007/s10916-020-1543-7 Whiteside, U., Richards, J., Steinfeld, B., Simon, G., Caka, S., Tachibana, C.,
Semenkovich, K., Brown, M. E., Svrakic, D. M., and Lustman, P. J. (2015). et al. (2014). Online cognitive behavioral therapy for depressed primary care
Depression in type 2 diabetes mellitus: prevalence, impact, and treatment. patients: a pilot feasibility project. Perm. J. 18, 21–27. doi: 10.7812/TPP/13-155
Drugs 75, 577–587. doi: 10.1007/s40265-015-0347-4
Snoek, F. J., Bremmer, M. A., and Hermanns, N. (2015). Constructs of depression Conflict of Interest: The authors declare that the research was conducted in the
and distress in diabetes: time for an appraisal. Lancet Diabetes Endo. 6, 450–460. absence of any commercial or financial relationships that could be construed as a
doi: 10.1016/S2213-8587(15)00135-7 potential conflict of interest.
Spek, V., Cuijpers, P., NykIíček, I., Riper, H., Keyzer, J., and Pop, V.
(2007). Internet-based cognitive behaviour therapy for symptoms of
Publisher’s Note: All claims expressed in this article are solely those of the authors
depression and anxiety: a meta-analysis. Psychol Med. 3, 319–328.
doi: 10.1017/S0033291706008944 and do not necessarily represent those of their affiliated organizations, or those of
Tate, D. F., Finkelstein, E. A., Khavjou, O., and Gustafson, A. (2009). Cost the publisher, the editors and the reviewers. Any product that may be evaluated in
effectiveness of internet interventions: Review and recommendations. Ann. this article, or claim that may be made by its manufacturer, is not guaranteed or
Behav. Med. 1, 40–45. doi: 10.1007/s12160-009-9131-6 endorsed by the publisher.
Urrútia, G., and Bonfilll, X. (2013). La declaración prisma: Un paso adelante en la
mejora de las publicaciones de la revista Española de salud pública. Rev Esp de Copyright © 2022 Varela-Moreno, Carreira Soler, Guzmán-Parra, Jódar-Sánchez,
Salud Publica. 2, 99–102. doi: 10.4321/S1135-57272013000200001 Mayoral-Cleries and Anarte-Ortíz. This is an open-access article distributed under
Üstün, T. B., Chatterji, S., Villanueva, M., Bendib, L., Çelik, C., Sadana, R., the terms of the Creative Commons Attribution License (CC BY). The use,
et al. (2001). WHO Multi-Country Survey Study on Health and Responsiveness. distribution or reproduction in other forums is permitted, provided the original
Geneva: World Health Organization. author(s) and the copyright owner(s) are credited and that the original publication
Van Bastelaar, K. M. P., Pouwer, F., Cuijpers, P., Riper, H., and Snoek, in this journal is cited, in accordance with accepted academic practice. No use,
F. J. (2011). Web-based depression treatment for type 1 and type 2 distribution or reproduction is permitted which does not comply with these terms.

Frontiers in Psychology | www.frontiersin.org 13 January 2022 | Volume 12 | Article 746217