Hostname: page-component-7c8c6479df-fqc5m Total loading time: 0 Render date: 2024-03-17T12:15:18.286Z Has data issue: false hasContentIssue false

Cognitive–behavioural therapy for depression in people with a somatic disease: meta-analysis of randomised controlled trials

Published online by Cambridge University Press:  02 January 2018

Matthijs W. Beltman*
Affiliation:
Radboud University Nijmegen Medical Centre, Department of Psychiatry, Nijmegen, The Netherlands
Richard C. Oude Voshaar
Affiliation:
Radboud University Nijmegen Medical Centre, Department of Psychiatry, Nijmegen, The Netherlands
Anne E. Speckens
Affiliation:
Radboud University Nijmegen Medical Centre, Department of Psychiatry, Nijmegen, The Netherlands
*
Matthijs W. Beltman, Radboud University Nijmegen Medical Centre, Department of Psychiatry (966), PO Box 9101, 6500 HB Nijmegen, The Netherlands. Email: mw.beltman@psy.umcn.nl
Rights & Permissions [Opens in a new window]

Abstract

Background

Meta-analyses on psychological treatment for depression in individuals with a somatic disease are limited to specific underlying somatic diseases, thereby neglecting the generalisability of the interventions.

Aims

To examine the effectiveness of cognitive–behavioural therapy (CBT) for depression in people with a diversity of somatic diseases.

Method

Meta-analysis of randomised controlled trials evaluating CBT for depression in people with a somatic disease. Severity of depressive symptoms was pooled using the standardised mean difference (SMD).

Results

Twenty-nine papers met inclusion criteria. Cognitive–behavioural therapy was superior to control conditions with larger effects in studies restricted to participants with depressive disorder (SMD =–0.83, 95% CI –1.36 to –0.31, P<0.001) than in studies of participants with depressive symptoms (SMD =–0.16, 95% CI –0.27 to –0.06, P = 0.001). Subgroup analyses showed that CBT was not superior to other psychotherapies.

Conclusions

Cognitive–behavioural therapy significantly reduces depressive symptoms in people with a somatic disease, especially in those who meet the criteria for a depressive disorder.

Type
Review Article
Copyright
Copyright © Royal College of Psychiatrists, 2010 

Major depression occurs in 6–14% of medical in-patients, Reference Katon and Schulberg1 with even higher percentages in specific populations such as people with type 1 or type 2 diabetes Reference Lustman, Griffith, Freedland, Kissel and Clouse2 or cancer. Reference Hotopf, Chidgey, Addington-Hall and Ly3 Irrespective of the underlying somatic disease, depression always dramatically decreases quality of life. In medical and surgical in-patients, depressive symptoms are associated with longer hospital stays, higher rates of rehospitalisation and increased hospital utilisation. Reference Saravay, Pollack, Steinberg, Weinschel and Habert4,Reference Henk, Katzelnick, Kobak, Greist and Jefferson5 In out-patients with chronic medical conditions such as diabetes and heart disease, comorbid depressive disorder has been associated with increased medical consumption, amplification of somatic symptoms and disability, poor self-care and adherence to treatment, and increased morbidity and mortality. Reference Katon and Sullivan6 Although both pharmacological and psychological therapy are effective for depressive disorder in the general population, 7 studies in individuals with somatic diseases have yielded mixed results. Reference Berkman, Blumenthal, Burg, Carney, Catellier and Cowan8,Reference Yohannes, Connolly and Baldwin9 As antidepressant medication may interfere with somatic diseases or their treatment, leading to high drop-out rates, Reference Himelhoch, Medoff and Oyeniyi10 psychological treatments might be more suitable in this population. Therefore, it is not surprising that in the past decades a considerable number of studies have focused on the psychological treatment of depression in people with a somatic disease. Reference Himelhoch, Medoff and Oyeniyi10Reference Meyer and Mark16 Recent meta-analyses on psychological treatment for depression in individuals with somatic diseases, however, were limited for the following reasons. First, previous meta-analyses focused on the treatment of depressive symptoms in people with specific somatic diseases such as cancer, rheumatoid arthritis or multiple sclerosis. However, as depressive symptoms occur in a variety of somatic diseases, this approach limits our knowledge about the generalisability of cognitive–behavioural therapy (CBT). Secondly, most meta-analyses included a wide range of psychological interventions, Reference Himelhoch, Medoff and Oyeniyi10,Reference Astin, Beckner, Soeken, Hochberg and Berman12Reference Meyer and Mark16 which might have diluted the effect of CBT, and CBT has been shown by previous research to be one of the most effective interventions for depression. 17,18 Finally, none of these meta-analyses applied the diagnostic criteria of depressive disorder as an inclusion criterion.

We conducted a meta-analysis of the effectiveness of CBT for depression in people with an underlying somatic disease. As we hypothesised that we would find higher efficacy in people who met predefined criteria for depression, we conducted separate meta-analyses for studies restricted to participants with depressive disorder and from those with depressive symptoms.

Method

Identification of studies

To identify relevant studies, we conducted a search of the Cochrane Central Register of Controlled Trials, PubMed and PsycINFO up to October 2008. We used the text keywords depressive disorder, depression, major depressive disorder or depressive sympto* combined with the keywords psychotherapy, cognitive therapy, behavi* therapy or CBT. We did not include any terms related to underlying somatic diseases to prevent the exclusion of any possible relevant study. This search strategy was repeated using the MESH-terms depressive disorder (exploded), depression (exploded), depressive disorder, major (exploded) AND psychotherapy (exploded), limited to humans, clinical trial or randomised controlled trial. Articles were retrieved for further assessment if the title or abstract suggested that a CBT (broadly defined) was used in a population with a somatic disease. Subsequently, the search was extended by a manual search of the reference lists of all resulting randomised controlled trials (RCTs).

Inclusion criteria

Manuscripts were included if they met the following criteria:

  1. (a) use of a randomised controlled research design;

  2. (b) inclusion of participants with an underlying somatic disease;

  3. (c) inclusion of a treatment arm with CBT, defined as a protocol-based psychological treatment including at least cognitive restructuring and behavioural activation procedures for depression for a minimum of six sessions. We also included problem-solving therapy and cognitive–behavioural stress management on the prerequisite that these interventions met our definition of CBT;

  4. (d) results for depressive symptoms were presented separately for each treatment arm at pre- and post-treatment;

  5. (e) use of a valid outcome measure (validated self-report questionnaire or clinical interview).

The first two authors (M.W.B. and R.C.O.V.) independently checked the inclusion and exclusion criteria of the identified studies. Disagreement over inclusion was resolved through discussion. When no consensus could be reached, a third investigator (A.E.S.) decided. Excluded were outcome studies without a randomised controlled design (e.g. open trials, case series and case reports), review papers, studies examining depression associated with unexplained somatic symptoms (e.g. fibromyalgia, chronic fatigue syndrome, irritable bowel syndrome, chronic pain), studies of individuals aged 18 years and under, studies in which the CBT could not be distinguished from other elements of the intervention (e.g. depression care management), studies including people with dementia or severe cognitive impairment, and studies limited to a specific psychiatric disorder with depressive symptoms as a second outcome measure. The language of publication was not an exclusion criteria.

Data extraction, selection procedure and quality assessment

The first two authors subsequently coded the selected studies separately on a coding form consisting of the following items: year of publication, total number of patients included, number of completers and number who dropped out, underlying somatic disease, setting (in- or out-patient clinic), age, gender, type of CBT intervention, delivery of treatment (face-to-face, telephone, internet), individual or group treatment, number of sessions, type of control condition (classified as either treatment as usual, a waiting list or other psychotherapy), outcome measures, whether depressive symptoms were the primary or secondary outcome measure, completer or intent-to-treat analysis, the results on post-treatment measures of interest (see Statistical analysis), and finally the psychiatric diagnostic criteria used at the time of inclusion (depressive disorder or depressive symptoms). Depressive disorder was defined as meeting DSM–IV 19 criteria or scoring above a predefined cut-off level on a screening questionnaire for depression. Depressive symptoms were used to indicate the dimensional score on a self-report questionnaire for depressive symptoms. Discrepancies in the two coding forms were resolved by discussion between both authors (M.W.B. and R.C.O.V.), and when no consensus could be reached the third author decided (A.E.S.).

When data on means, standard deviations or number of participants in the experimental or control groups at the end of the treatment were missing, we contacted the trial authors. Where standard deviations were not available from trial authors, they were calculated from t-tests, confidence intervals or standard errors, where reported in articles. Reference Deeks20,Reference Deeks21 If these additional data were not available, the study data were not included in the meta-analysis.

The methodological quality of the included studies was assessed using the Amsterdam–Maastricht consensus list ranging from 0 (poor quality) to 19 (excellent quality). The Amsterdam–Maastricht consensus list is accepted by the Cochrane Review Group Reference van Tulder, Assendelft, Koes and Bouter22 and has been used previously in systematic reviews of RCTs in psychiatric disorders. Reference van Boeijen, van Balkom, van Oppen, Blankenstein, Cherpanath and van Dyck23,Reference Oude Voshaar, Couvée, Van Balkom, Mulder and Zitman24 It covers the Chalmers criteria usually applied in the assessment of study quality. Reference van Tulder, Assendelft, Koes and Bouter22,Reference Chalmers, Smith, Blackburn, Silverman, Schroeder and Reitman25

Statistical analysis

For the main analyses, studies were subdivided in studies restricted to participants with depressive disorder according to predefined criteria and studies of participants with depressive symptoms. The primary outcome measure for both categories was the severity of depressive symptoms. We a priori decided to use the Beck Depression Inventory (BDI) Reference Beck, Ward, Mendelson, Mock and Erbaugh26 or Beck Depression Inventory–II (BDI–II) Reference Beck, Steer and Brown27 as the primary outcome measure and, if not available (in order of preference), the Hamilton Depression Rating Scale (HDRS) Reference Hamilton28 or the Center for Epidemiological Studies – Depression Scale (CES–D). Reference Radloff29 If a separate measure of depressive symptoms was lacking, a subscale of a validated generic psychiatric instrument was used (in order of preference): the depression subscale of the Hospital Anxiety and Depression Scale (HADS), Reference Zigmond and Snaith30 the Profile of Mood Symptoms (POMS), Reference McNair, Lorr and Drappelman31 the Symptom Checklist 90-item version (SCL–90–R) Reference Derogatis32 or the Impact of Rheumatic Diseases on Health and Lifestyle (IRGL). Reference Huiskes, Kraaimaat and Bijlsma33

Data were analysed with Review Manager (RevMan) version 5.0.17 for Windows. At the moment, Cochrane methodology is widely advised and accepted as the preferred method in meta-analytic studies. We used the standardised mean difference (SMD) as the summary statistic in our meta-analysis, which expresses the size of the treatment effect in each trial relative to the variability observed in that trial, enabling us to pool different scales assessing one outcome measure. The SMD thus reflects the difference in the mean outcome between groups divided by the standard deviation of outcomes among participants. We applied the chi-squared test for heterogeneity. Since the chi-squared test has low power to assess heterogeneity where a small number of participants or trials are included, the P-value was conservatively set at 0.10. Reference Higgins and Green34 We used a fixed-effects model if homogeneity was found and a random-effects model if not (although the latter model slightly compromised the statistical power of our analysis). Summary statistics were based on intention-to-treat data and when missing, on available case analyses. It is generally assumed to be more realistic to include papers based on their completer data than excluding papers by not providing intention-to-treat data, on the prerequisite that potential difference between studies will be discussed and taken into account as a source of heterogeneity. Reference Higgins and Green34

The following subgroup analyses were performed to examine whether specific characteristics of the studies were related to the effect sizes:

  1. (a) type of CBT condition, classified as classic CBT, problem-solving therapy and cognitive–behavioural stress management;

  2. (b) control condition, classified as treatment as usual, waiting-list control condition and other psychotherapy;

  3. (c) treatment delivery in group versus individual format.

Sensitivity analyses were undertaken to assess whether the quality of the studies was related to the magnitude of the observed effect sizes. Studies were limited to those of higher quality as determined by risk of: drop-out rate lower than 20%, studies providing intention-to-treat data, outcome assessment by validated questionnaire (excluding subscales) or whether depressive symptoms was the primary or secondary outcome measure. Publication bias was explored by preparing funnel plots for all outcome measures.

Results

Search strategy

The study extraction and selection process as recommended by the Quality of Reporting of Meta-analyses (QUOROM) statement Reference Moher, Cook, Eastwood, Olkin, Rennie and Stroup35 is shown in Fig. 1. The initial search yielded 1361 reference titles in PubMed, 2677 in PsycINFO and 604 in the Cochrane Library of which 305 titles were identified as having a possible relevance to the treatment of depression in people with an underlying somatic disease by M.W.B. or R.C.O.V. After screening of the abstracts and the full text, we excluded 266 papers. Of the 39 articles of interest, 13 papers did not provide sufficient information for the meta-analyses and we contacted the corresponding author for this. Of the 13 authors contacted, Reference Lustman, Griffith, Freedland, Kissel and Clouse2,Reference Tan and Bruni36Reference Doering, Cross, Vredevoe, Martínez-Maza and Cowan47 3 authors responded to our request and were included. Reference Edelman, Bell and Kidman42,Reference Lincoln and Flannaghan44,Reference Given, Given, Rahbar, Jeon, McCorkle and Cimprich45 Two authors claimed that the relevant study data were not available anymore Reference Tan and Bruni36,Reference Mulder, Emmelkamp, Antoni, Mulder, Sandfort and de Vries38 and 8 authors did not respond to our request, leaving 29 studies for the meta-analysis. Reference Edelman, Bell and Kidman42,Reference Lincoln and Flannaghan44,Reference Given, Given, Rahbar, Jeon, McCorkle and Cimprich45,Reference Larcombe and Wilson48Reference Safren, O'Cleirig, Tan, Raminani, Reilly and Otto73

Study quality

Online Tables DS1 and DS2 list the scores for methodological quality of the studies as assessed with the Amsterdam–Maastricht consensus list. The sum score (range 0–19) is taken to reflect study quality but as neither participants nor therapists can be masked to a psychological treatment condition, the maximum score in psychotherapy studies is 17. Interrater discrepancies were limited to a one-point difference in eight studies and a two-point difference in two studies. The broad range from 8 to 16 indicates a high variation of study quality, which emphasises the need for the (planned) sensitivity analyses to evaluate the effect of the most important issues of study quality.

Fig. 1 Flow diagram of randomised controlled trials (RCTs) included and excluded in meta-analysis. CBT, cognitive–behavioural therapy.

Study characteristics

The study characteristics are summarised in Table 1 for studies restricted to individuals with depressive disorder and Table 2 for studies of individuals with depressive symptoms. The 13 trials that included participants with depressive disorder Reference Lincoln and Flannaghan44,Reference Larcombe and Wilson48,Reference Kelly, Murphy, Bahr, Kalichman, Morgan and Stevenson51,Reference Evans and Connis52,Reference Markowitz, Kocsis, Fishman, Spielman, Jacobsberg and Frances55,Reference Mohr, Likosky, Bertagnolli, Goodkin, van der Wende and Dwyer57,Reference Mohr, Boudewyn, Goodkin, Bostrom and Epstein58,Reference Nezu, Nezu, Felgoise, McClure and Houts63,Reference Mohr, Hart, Julian, Catledge, Honos-Webb and Vella66,Reference Savard, Simard, Giguère, Ivers, Morin and Maunsell68,Reference Gellis, McGinty, Horowitz, Bruce and Misener69,Reference Kunik, Veazy, Cully, Souchek, Graham and Hopko72,Reference Safren, O'Cleirig, Tan, Raminani, Reilly and Otto73 comprised a total of 1139 people with a mean age of 51 years. These studies all had treatment of depression as their primary goal. In total, 252 participants (22%) dropped out prematurely; 112 (21%) in the CBT condition and 140 (23%) in the control condition (χ2 = 0.62, d.f. = 1, P = 0.43).

Table 1 Study characteristics of participants with depressive disorder

Study Included, n Dropped out, n (%) Completers, n Age, years: mean Male, % Somatic disease Sessions, n Group therapy Control condition(s) Setting
Larcombe (1984) Reference Larcombe and Wilson48 21 2 (10) 19 43 32 Multiple sclerosis 6 Yes WLC Out-patients
Kelly (1993) Reference Kelly, Murphy, Bahr, Kalichman, Morgan and Stevenson51 115 47 (41) 68 34 100 HIV 8 Yes TAU and OP Out-patients
Evans (1995) Reference Evans and Connis52 78 6 (8) 72 54 65 Cancer 8 Yes TAU and OP Out-patients
Markowitz (1998) Reference Markowitz, Kocsis, Fishman, Spielman, Jacobsberg and Frances55 75 23 (31) 52 37 83 HIV 16 No OP Out-patients
Mohr (2000) Reference Mohr, Likosky, Bertagnolli, Goodkin, van der Wende and Dwyer57 32 9 (28) 23 42 28 Multiple sclerosis 8 No TAU Out-patients
Mohr (2001) Reference Mohr, Boudewyn, Goodkin, Bostrom and Epstein58 42 3 (7) 39 44 27 Multiple sclerosis 16 No OP Out-patients
Lincoln (2003) Reference Lincoln and Flannaghan44 123 5 (4) 118 66 51 Heart disease 10 No TAU and OP In-patients
Nezu (2003) Reference Nezu, Nezu, Felgoise, McClure and Houts63 150 18 (12) 132 47 33 Cancer 10 No WLC In-patients
Mohr (2005) Reference Mohr, Hart, Julian, Catledge, Honos-Webb and Vella66 127 5 (4) 122 48 23 Multiple sclerosis 16 No OP Out-patients
Savard (2006) Reference Savard, Simard, Giguère, Ivers, Morin and Maunsell68 45 8 (18) 37 52 0 Cancer 8 No WLC Out-patients
Gellis (2007) Reference Gellis, McGinty, Horowitz, Bruce and Misener69 48 8 (17) 40 80 15 Medically Ill 6 No TAU Out-patients
Kunik (2008) Reference Kunik, Veazy, Cully, Souchek, Graham and Hopko72 238 115 (48) 123 66 96 COPD 8 Yes OP Out-patients
Safren (2008) Reference Safren, O'Cleirig, Tan, Raminani, Reilly and Otto73 45 3 (7) 42 n/a n/a HIV 12 No TAU Out-patients
Summary statistics 1139 252 (22) 887 51

Table 2 Study characteristics of participants with depressive symptoms

Study Included, n Dropped out, n (%) Completers, n Age, years: mean Male, % Somatic disease Sessions, n Group therapy Control condition(s) Setting
Foley (1987) Reference Foley, Bedell, LaRocca, Scheinberg and Reznikoff49 41 5 (12) 36 39 15 Multiple sclerosis 6 Yes OP Out-patients
Greer (1992) Reference Greer, Moorey, Baruch, Watson, Robertson and Mason50 174 23 (13) 151 52 21 Cancer 6 No TAU Out-patients
Kraaimaat (1995) Reference Kraaimaat, Brons, Geenen and Bijlsma53 77 6 (8) 71 57 32 Rheumatoid arthritis 10 Yes WLC and OP Out-patients
Henry (1997) Reference Henry, Wilson, Bruce, Chisholm and Rawling54 21 2 (10) 19 60 47 Diabetes mellitus 6 Yes WLC Out-patients
Edelman (1999a) Reference Edelman, Bell and Kidman42 119 27 (23) 92 50 0 Cancer 11 Yes TAU Out-patients
Edelman (1999b) Reference Edelman, Bell and Kidman56 60 13 (22) 47 48 0 Cancer 12 Yes OP Out-patients
Sharpe (2001) Reference Sharpe, Sensky, Timberlake, Ryan, Brewin and Allard59 53 8 (15) 45 55 29 Rheumatoid arthritis 8 No TAU Out-patients
Cruess (2002) Reference Cruess, Antoni, Hayes, Penedo, Ironson and Fletcher60 125 25 (20) 100 36 100 HIV 10 Yes WLC Out-patients
Evers (2002) Reference Evers, Kraaimaat, van Riel and de Jong61 64 5 (8) 59 54 29 Rheumatoid arthritis 20 No TAU Out-patients
Kissane (2003) Reference Kissane, Bloch, Smith, Miach, Clarke and Ikin62 303 24 (8) 279 46 0 Cancer 20 Yes OP Out-patients
Given (2004) Reference Given, Given, Rahbar, Jeon, McCorkle and Cimprich45 237 72 (30) 165 n/a 20 Cancer 10 No TAU Out-patients
Blumenthal (2005) Reference Blumenthal, Sherwood, Babyak, Watkins, Waugh and Georgiades64 134 10 (7) 124 63 69 Heart disease 16 Yes TAU and OP Out-patients
Chan (2005) Reference Chan, Kong, Leung, Au, Li and Chung65 16 3 (19) 13 38 100 HIV 7 Yes WLC Out-patients
Antoni (2006) Reference Antoni, Carrico, Duran, Spitzer, Penedo and Ironson67 130 52 (40) 78 50 100 HIV 10 Yes OP Out-patients
Lii (2007) Reference Lii, Tsay and Wang70 60 12 (20) 48 n/a 48 Renal failure 8 Yes TAU Out-patients
Koertge (2008) Reference Koertge, Janszky, Sundin, Blom, Georgiades and László71 247 83 (34) 164 62 0 Heart disease 20 Yes TAU In-patients
Summary statistics 1861 370 (20) 1491 51

The 16 trials including participants with depressive symptoms Reference Edelman, Bell and Kidman42,Reference Given, Given, Rahbar, Jeon, McCorkle and Cimprich45,Reference Foley, Bedell, LaRocca, Scheinberg and Reznikoff49,Reference Greer, Moorey, Baruch, Watson, Robertson and Mason50,Reference Kraaimaat, Brons, Geenen and Bijlsma53,Reference Henry, Wilson, Bruce, Chisholm and Rawling54,Reference Edelman, Bell and Kidman56,Reference Sharpe, Sensky, Timberlake, Ryan, Brewin and Allard59Reference Kissane, Bloch, Smith, Miach, Clarke and Ikin62,Reference Blumenthal, Sherwood, Babyak, Watkins, Waugh and Georgiades64,Reference Chan, Kong, Leung, Au, Li and Chung65,Reference Antoni, Carrico, Duran, Spitzer, Penedo and Ironson67,Reference Lii, Tsay and Wang70,Reference Koertge, Janszky, Sundin, Blom, Georgiades and László71 included 1861 people with a mean age of 51 years. A total of 370 participants (20%) dropped out before the outcome assessment; 192 (21%) in the CBT condition and 178 (19%) in the control condition (χ2 = 0.93, d.f. = 1, P = 0.34). In six (38%) of these studies the treatment of depressive symptoms was the primary goal Reference Edelman, Bell and Kidman42,Reference Given, Given, Rahbar, Jeon, McCorkle and Cimprich45,Reference Edelman, Bell and Kidman56,Reference Cruess, Antoni, Hayes, Penedo, Ironson and Fletcher60,Reference Lii, Tsay and Wang70,Reference Koertge, Janszky, Sundin, Blom, Georgiades and László71 and in 10 (62%) a secondary aim. Reference Foley, Bedell, LaRocca, Scheinberg and Reznikoff49,Reference Greer, Moorey, Baruch, Watson, Robertson and Mason50,Reference Kraaimaat, Brons, Geenen and Bijlsma53,Reference Henry, Wilson, Bruce, Chisholm and Rawling54,Reference Sharpe, Sensky, Timberlake, Ryan, Brewin and Allard59,Reference Evers, Kraaimaat, van Riel and de Jong61,Reference Kissane, Bloch, Smith, Miach, Clarke and Ikin62,Reference Blumenthal, Sherwood, Babyak, Watkins, Waugh and Georgiades64,Reference Chan, Kong, Leung, Au, Li and Chung65,Reference Antoni, Carrico, Duran, Spitzer, Penedo and Ironson67

Underlying somatic diseases in the different studies were: cancer (n = 8), HIV infection (n = 6), multiple sclerosis (n = 5), rheumatoid arthritis (n = 3), vascular disease (n = 3), diabetes mellitus (n = 1), chronic obstructive pulmonary disease (n = 1), chronic renal failure (n = 1) and various somatic diseases (n = 1).

Six studies Reference Lincoln and Flannaghan44,Reference Kelly, Murphy, Bahr, Kalichman, Morgan and Stevenson51Reference Kraaimaat, Brons, Geenen and Bijlsma53,Reference Markowitz, Kocsis, Fishman, Spielman, Jacobsberg and Frances55,Reference Blumenthal, Sherwood, Babyak, Watkins, Waugh and Georgiades64 compared an active treatment with two control conditions (e.g. an attention control, as well as a standard care group). We combined data from these control conditions and compared this with data for the treatment group. In the subgroup analysis of the control condition we used both control conditions separately. One study Reference Nezu, Nezu, Felgoise, McClure and Houts63 compared two active treatments (problem-solving therapy and problem-solving therapy with a significant other) with a waiting-list control condition. In this case we combined the two treatment conditions and compared this with the control condition.

Most studies evaluated a classic CBT intervention, five studies evaluated cognitive–behavioural stress management, Reference Henry, Wilson, Bruce, Chisholm and Rawling54,Reference Cruess, Antoni, Hayes, Penedo, Ironson and Fletcher60,Reference Blumenthal, Sherwood, Babyak, Watkins, Waugh and Georgiades64,Reference Antoni, Carrico, Duran, Spitzer, Penedo and Ironson67,Reference Koertge, Janszky, Sundin, Blom, Georgiades and László71 and two studies problem-solving therapy Reference Nezu, Nezu, Felgoise, McClure and Houts63,Reference Gellis, McGinty, Horowitz, Bruce and Misener69 (all studies fulfilling our inclusion criteria for CBT). The number of treatment sessions ranged from 6 to 20 weeks, delivered either in a group format (16 studies) or individually (13 studies). In two studies, the intervention was delivered exclusively by telephone. Reference Mohr, Likosky, Bertagnolli, Goodkin, van der Wende and Dwyer57,Reference Mohr, Hart, Julian, Catledge, Honos-Webb and Vella66

Meta-analyses

The results for the primary outcome variable are presented in Fig. 2 for studies of individuals with depressive disorder and Fig. 3 for studies of individuals with depressive symptoms. Because of significant heterogeneity in the studies restricted to participants with depressive disorder (χ2 = 170.12, d.f. = 12, P<0.001, I 2 = 93%), we used a random-effects model. We found a significant pooled standardised mean difference of –0.83 (95% CI –1.36 to –0.31) in favour of the CBT condition (Z = 3.13, P = 0.002). Inspection of the data showed that the heterogeneity of results could not be explained by the underlying somatic disease, but was caused by three positive outliers. Reference Larcombe and Wilson48,Reference Nezu, Nezu, Felgoise, McClure and Houts63,Reference Gellis, McGinty, Horowitz, Bruce and Misener69 Removal of these studies led to more homogeneous results, but reduced the effect size by –0.64 yielding a still significant pooled SMD of –0.19 (95% CI –0.33 to –0.05, Z = 2.69, P = 0.007).

The studies of individuals with depressive symptoms yielded a smaller but still significant pooled SMD of –0.16 (95% CI –0.27 to –0.06) in favour of the CBT condition (Z = 3.19, P = 0.001).

The funnel plots of both categories of papers were not suggestive of publication bias. The effect size was neither correlated with publication year nor with the quality score (all P>0.22). A strong correlation was found between publication year and quality score among studies restricted to participants with depressive disorder, showing an increase of study quality over the years (Spearman's rho = 0.67, P = 0.013). Based on Cochrane methodology, differences in quality score are addressed in sensitivity analyses as planned (see below) instead of excluding low-quality studies. We did not expect to find studies delivering CBT by telephone. This finding urged us to perform a post hoc subgroup analyses excluding these two studies, which yielded a higher effect size of –0.92 (95% CI –1.55 to –0.29) in favour of the CBT condition (Z = 2.86, P = 0.004) using a random-effects model.

Furthermore, the effect size was significantly correlated with the number of CBT sessions provided in the studies of participants with depressive symptoms (Spearman's rho = 0.53, P = 0.033), but not in the studies of participants with depressive disorder. In the studies of people with depressive symptoms, a post hoc subgroup analysis showed that the effect size in studies providing less than ten CBT sessions was –0.39 (95% CI –0.61 to –0.16) in favour of the CBT condition (Z = 3.34, P = 0.00008), compared with –0.11 (95% CI –0.22 to 0.00, Z = 1.89, P = 0.06) in studies providing ten or more sessions.

Fig. 2 Forrest plot of standard mean difference (with 95% CI) of effect of cognitive–behavioural therapy on depressive symptoms in studies including participants with depressive disorder, with overall effect (black diamond), based on meta-analysis. Std, standard.

Fig. 3 Forrest plot of standard mean difference (with 95% CI) of effect of cognitive–behavioural therapy on depressive symptoms in studies of participants with depressive symptoms, with overall effect (black diamond), based on meta-analysis. Std, standard.

Planned subgroup analyses

Type of CBT

Meta-analyses of studies that applied classic CBT achieved significant overall effects. For studies restricted to participants with depressive disorder, the SMD was –0.34 (95% CI –0.60 to –0.09, Z = 2.64, P = 0.008) using a random-effects model and for studies of participants with depressive symptoms the SMD was –0.31 (95% CI –0.46 to –0.16, Z = 4.10, P<0.001).

Two small studies evaluating problem-solving therapy yielded a pooled SMD of –2.86 (95% CI –4.11 to –1.61, Z = 4.49, P<0.001) based on a total of 172 participants. Five studies evaluating cognitive–behavioural stress management yielded a non-significant SMD of –0.12 (95% CI –0.30 to 0.05).

Control condition

Of the studies restricted to participants with depressive disorder, those using a waiting list or a treatment as usual care control condition had a significant pooled effect size of –2.38 (95% CI –4.41 to –0.36, Z = 2.31, P = 0.02) and –0.72 (95% CI –1.21 to –0.24, Z = 2.94, P = 0.003) respectively. A random-effects model was used, because there was considerable heterogeneity. The studies using other psychotherapy as a control group yielded a non-significant pooled SMD of –0.06 (95% CI –0.23 to 0.10, Z = 0.76, P = 0.45).

For studies of participants with depressive symptoms, only studies comparing CBT with treatment as usual yielded a significant pooled SMD of –0.28 (95% CI –0.41 to –0.15) in favour of the CBT condition (Z = 4.20, P<0.001), whereas no differences were found comparing CBT versus a waiting-list control condition: SMD = –0.13 (95% CI –0.44 to 0.17, Z = 0.87, P = 0.38); or versus other psychotherapies: SMD = 0.04 (95% CI –0.15 to 0.22, Z = 0.37, P = 0.71).

Treatment delivery in group versus individual format

Only individual treatment delivery led to a significant effect in favour of CBT for both studies of participants with depressive disorder and depressive symptoms. The pooled SMD was –0.91 (95 % CI –1.65 to –0.17, Z = 2.41, P = 0.02) and –0.30 (95% CI –0.50 to –0.11, Z = 3.10, P = 0.002) respectively.

Sensitivity analyses

Drop-out rate ≥20%

Sensitivity analyses were performed excluding studies that had a drop-out rate higher or equal to 20%. Reference Edelman, Bell and Kidman42,Reference Given, Given, Rahbar, Jeon, McCorkle and Cimprich45,Reference Kelly, Murphy, Bahr, Kalichman, Morgan and Stevenson51,Reference Markowitz, Kocsis, Fishman, Spielman, Jacobsberg and Frances55Reference Mohr, Likosky, Bertagnolli, Goodkin, van der Wende and Dwyer57,Reference Cruess, Antoni, Hayes, Penedo, Ironson and Fletcher60,Reference Antoni, Carrico, Duran, Spitzer, Penedo and Ironson67,Reference Lii, Tsay and Wang70Reference Kunik, Veazy, Cully, Souchek, Graham and Hopko72 In the studies restricted to individuals with depressive disorder, the pooled SMD was –1.18 (95 % CI –1.96 to –0.41) in favour of the CBT condition (Z = 2.99, P = 0.003) using a random-effects model. A non-significant pooled SMD of –0.11 (95% CI –0.25 to –0.03, Z = 1.54, P = 0.12) was found in studies of individuals with depressive symptoms.

Intent-to-treat data

After excluding studies that did not provide intention-to-treat data Reference Edelman, Bell and Kidman42,Reference Lincoln and Flannaghan44,Reference Given, Given, Rahbar, Jeon, McCorkle and Cimprich45,Reference Larcombe and Wilson48Reference Henry, Wilson, Bruce, Chisholm and Rawling54,Reference Edelman, Bell and Kidman56,Reference Mohr, Boudewyn, Goodkin, Bostrom and Epstein58Reference Evers, Kraaimaat, van Riel and de Jong61,Reference Nezu, Nezu, Felgoise, McClure and Houts63,Reference Chan, Kong, Leung, Au, Li and Chung65Reference Koertge, Janszky, Sundin, Blom, Georgiades and László71 a non-significant pooled SMD was found of –0.11 (95% CI –0.31 to 0.09, Z = 1.05, P = 0.29) for studies restricted to individuals with depressive disorder, as well as for the studies of individuals with depressive symptoms: SMD = 0.03 (95% CI –0.16 to 0.22, Z = 0.27, P = 0.79).

Outcome assessment with a depression subscale

After excluding studies that only measured depression with a subscale of a (generic) outcome measure, Reference Edelman, Bell and Kidman42,Reference Greer, Moorey, Baruch, Watson, Robertson and Mason50,Reference Kraaimaat, Brons, Geenen and Bijlsma53,Reference Edelman, Bell and Kidman56,Reference Mohr, Likosky, Bertagnolli, Goodkin, van der Wende and Dwyer57,Reference Sharpe, Sensky, Timberlake, Ryan, Brewin and Allard59,Reference Kissane, Bloch, Smith, Miach, Clarke and Ikin62 a significant pooled SMD of –0.86 (95% CI –1.41 to –0.30) was found in favour of the CBT condition (Z = 3.03, P = 0.002) in studies of participants with depressive disorder. The studies of participants with depressive symptoms yielded a significant SMD of –0.25 (95% CI –0.38 to –0.11) in favour of the CBT condition (Z = 3.48, P<0.001).

Discussion

This meta-analysis of 29 RCTs investigated the effect of CBT on depressive symptoms in 1247 people with a somatic disease and 1338 controls. Our two main meta-analyses of CBT both showed that CBT is effective in treating depressive symptoms in people with a variety of somatic diseases. As expected, the pooled results of studies restricted to individuals with depressive disorder had a stronger significant effect (–0.83) than those including people with depressive symptoms (–0.16). However, the lower the level of depressive symptoms at baseline, the less likely treatment will result in a significant reduction of these symptoms. So, the difference between both meta-analyses may in fact reflect a floor effect.

Reported effect-sizes in meta-analyses of CBT for depressive symptoms or general distress in people with a specific underlying somatic disease are 0.37 for individuals with HIV infection, Reference Himelhoch, Medoff and Oyeniyi10 0.36–0.44 for people with cancer, Reference Sheard and Maguire15,Reference Akechi, Okuyama, Onishi, Morita and Furukawa74 0.29 for those with rheumatoid arthritis, Reference Astin, Beckner, Soeken, Hochberg and Berman12 and 0.31 for those with breast cancer. Reference Tatrow and Montgomery13 The similarity of effect sizes in different populations is suggestive of a general underlying mechanism for depressive symptoms in people with a somatic disease. Coping style might be an important mediating mechanism, Reference Caplette-Gingras and Savard75,Reference MacMahon and Lip76 as somatically ill individuals with a higher perceived level of control, higher self-efficacy and active coping styles are better adjusted to the somatic illness Reference Dunkel-Schetter, Feinstein, Taylor and Falke77,Reference Hirai, Suzuki, Tsuneto, Ikenega, Hosaka and Kashiwagi78 and are less depressed. Reference Hirai, Suzuki, Tsuneto, Ikenega, Hosaka and Kashiwagi78,Reference Ranchor, Sanderman, Steptoe, Wardle, Miedema and Ormel79 The reported effect sizes are all in between our effect sizes of –0.83 for studies including participants with depressive disorder and –0.16 for studies including those with depressive symptoms. Pooling of all studies in our meta-analysis yields a significant overall effect size of –0.49 (data not shown), which is in line with these previous meta-analyses and emphasises the relevance of looking specifically at the definition of depression at baseline.

By performing a comprehensive review and meta-analysis of CBT for the treatment of depressive symptoms in people with a somatic disease, we did not restrict our inclusion criteria to studies which included only individuals with a diagnosis of depression according to the diagnostic criteria of the DSM. In contrast to previous meta-analyses on depressive symptoms in people with a specific somatic disease, we a priori decided to perform separately meta-analyses for studies using predefined criteria for depressive disorder at baseline and those studies including participants with somatic diseases with depressive symptoms in general (in these studies, authors generally assume that a somatic disease is stress-provoking and thus all patients may benefit from CBT).

Furthermore, we included different types of CBT for the following reasons. First, we considered the content of the psychotherapy more important than the name given to it by the study authors. In this paper, CBT was defined as all psychotherapies that included both cognitive restructuring and behavioural activation. Second, we intended to perform a comprehensive review and meta-analysis on this important topic, thereby precluding the emergence of different smaller meta-analyses confined to specific subtypes of CBT. The first subgroup analyses on subtypes of CBT, for instance, might have been published as separate papers. In our opinion nobody would gain by this strategy. Problem-solving therapy is generally seen as a derivative of CBT. Reference Hawton, Kirk, Hawton, Salkovskis, Kirk and Clark80 Although we identified only two studies that evaluated problem-solving therapy in this population, the pooled effect size was very large, which may suggest the high value of problem-solving therapy for this particular patient group. In patients with a somatic disease (and thus more handicaps or limitations), the more pragmatic approach of problem-solving therapy may be particularly favourable. Exclusion of these studies would have led to a less informative paper.

Subgroup analyses of CBT versus the different control conditions showed that CBT was superior to treatment as usual as well as a waiting-list control condition. Cognitive–behavioural therapy, however, was not superior to studies using a control condition with another psychological therapy, which consisted mainly of supportive-expressive therapies. Therefore, the effects we found might be caused by non-specific therapeutic effects that are not exclusive for CBT. A recent meta-analysis on the comparison of seven kinds of psychological therapies for depressive disorder in general also found similar effect sizes for the different modalities (CBT, non-directive supportive treatment, behavioural activation treatment, psychodynamic treatment, problem-solving therapy, interpersonal psychotherapy and social skills training). Reference Cuijpers, van Straten, Andersson and van Oppen81 Interestingly, only individual CBT yielded a significant effect size in studies of both participants with depressive disorder and depressive symptoms. This finding is in contrast with CBT for depression in general. Reference McDermut, Miller and Brown82 Individual therapy might be more suitable than group therapy for people with depression with a comorbid somatic disorder.

Methodological considerations

The study has some limitations. First, the methodological quality of the included studies was highly variable. The sensitivity analyses showed that the results were partly biased by methodological shortcomings, but the overall conclusions seem valid. For example, exclusion of studies with a drop-out rate of 20% or more led to an increased effect size in studies restricted to individuals with depressive disorder (from –0.83 to –1.18), whereas in studies of participants with depressive symptoms the effect size didn't change very much (–0.17 v. –0.13). Second, analysing only studies providing intent-to-treat data reduced the effect size in the studies of people with depressive disorder from –0.83 to a non-significant –0.11. This was also the case in studies of people with depressive symptoms. Third, neither exclusion of studies that did not use a specific instrument for assessing depression, nor exclusion of studies that used depressive symptoms as a secondary outcome measure influenced the effect size. In addition to the high variability of the quality, we did find heterogeneity among studies restricted to participants with depressive disorder, caused by three studies with extreme positive results. After removal of these outliers the results remained significant. As a last limitation, we should mention that we could not control for the stage of the underlying disease.

Implications

Cognitive–behavioural therapy significantly reduces depressive symptoms in people with an underlying somatic disease. The effect size, however, was clearly dependent on the severity of depressive symptoms at the time of inclusion in the study, with less of an effect in individuals with a lower level of depressive symptoms. A significant gap in knowledge, that might contribute to this difference, is the lack of studies that address which components of CBT might be most helpful in this population and by which personality characteristics or coping styles these effects are mediated. Currently, we cannot conclude that the positive effects are specific for CBT-oriented interventions. However, the findings of our meta-analysis support the effectiveness of CBT and therefore as the treatment of choice in people with underlying somatic diseases. The results also suggest that individual treatment might be more effective than group therapy in somatically ill people with depressive disorder. This hypothesis, however, should be further examined in future research. In addition to the need to focus more specifically on which CBT-components are most efficacious, further research should also include long-term follow-up data with respect to both depressive symptoms and the prognosis of the underlying somatic disease.

Footnotes

Declaration of interest

None.

References

1 Katon, W, Schulberg, H. Epidemiology of depression in primary care. Gen Hosp Psychiatry 1992; 14: 237–47.CrossRefGoogle ScholarPubMed
2 Lustman, PJ, Griffith, LS, Freedland, KE, Kissel, SS, Clouse, RE. Cognitive behavior therapy for depression in type 2 diabetes mellitus. A randomized, controlled trial. Ann Intern Med 1998; 129: 613–21.Google Scholar
3 Hotopf, M, Chidgey, J, Addington-Hall, J, Ly, KL. Depression in advanced disease: a systematic review Part 1. Prevalence and case finding. Palliat Med 2002; 16: 8197.Google Scholar
4 Saravay, SM, Pollack, S, Steinberg, MD, Weinschel, B, Habert, M. Four-year follow-up of the influence of psychological comorbidity on medical rehospitalization. Am J Psychiatry 1996; 153: 397403.Google Scholar
5 Henk, HJ, Katzelnick, DJ, Kobak, KA, Greist, JH, Jefferson, JW. Medical costs attributed to depression among patients with a history of high medical expenses in a health maintenance organization. Arch Gen Psychiatry 1996; 53: 899904.Google Scholar
6 Katon, W, Sullivan, MD. Depression and chronic medical illness. J Clin Psychiatry 1990; 51 (suppl): s311.Google Scholar
7 American Psychiatric Association. Practice guideline for the treatment of patients with major depressive disorder (revision). Am J Psychiatry 2000; 157 (suppl): s145.Google Scholar
8 Berkman, LF, Blumenthal, JA, Burg, M, Carney, RM, Catellier, D, Cowan, MJ, et al. Effects of treating depression and low perceived social support on clinical events after myocardial infarction: the Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) Randomized Trial. JAMA 2003; 289: 3106–16.Google Scholar
9 Yohannes, AM, Connolly, MJ, Baldwin, RC. A feasibility study of antidepressant drug therapy in depressed elderly patients with chronic obstructive pulmonary disease. Int J Geriatr Psychiatry 2001; 16: 451–4.Google Scholar
10 Himelhoch, S, Medoff, DR, Oyeniyi, G. Efficacy of group psychotherapy to reduce depressive symptoms among HIV–infected individuals: a systematic review and meta-analysis. Aids Patient Care STDS 2007; 21: 732–9.Google Scholar
11 Dusseldorp, E, van Elderen, T, Maes, S, Meulman, J, Kraaij, V. A meta-analysis of psychoeducational programs for coronary heart disease patients. Health Psychol 1999; 18: 506–19.CrossRefGoogle ScholarPubMed
12 Astin, JA, Beckner, W, Soeken, K, Hochberg, MC, Berman, BM. Psychological interventions for rheumatoid arthritis: a meta-analysis of randomized controlled trials. Arthritis Care Res 2002; 47: 291302.Google Scholar
13 Tatrow, K, Montgomery, G. Cognitive behavioral therapy techniques for distress and pain in breast cancer patients: a meta-analysis. J Behav Med 2006; 29: 1727.Google Scholar
14 Linden, W, Phillips, MJ, Leclerc, J. Psychological treatment of cardiac patients: a meta-analysis. Eur Heart J 2007; 28: 2972–84.Google Scholar
15 Sheard, T, Maguire, P. The effect of psychological interventions on anxiety and depression in cancer patients: results of two meta-analyses. Br J Cancer 1999; 80: 1770–80.Google Scholar
16 Meyer, TJ, Mark, MM. Effects of psychosocial interventions with adult cancer patients: a meta-analysis of randomized experiments. Health Psychol 1995; 14: 101–8.CrossRefGoogle ScholarPubMed
17 National Collaborating Centre for Mental Health. Depression: Management of Depression in Primary and Secondary Care. National Institute for Health and Clinical Excellence, 2007.Google Scholar
18 Werkgroep Multidisciplinaire richtlijn Depressie. Multidisciplinaire Richtlijn Depressie [Multidisciplinary Guideline for Depression]. Landelijke Stuurgroep Multidisciplinaire Richtlijnontwikkeling in de GGZ/Trimbos-instituut, 2007 (http://www.ggzrichtlijnen.nl/uploaded/docs/MDR%20Depressie%20eerste%20update%202010.pdf).Google Scholar
19 American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (4th edn) (DSM–IV). APA, 1994.Google Scholar
20 Deeks, JJ. Are You Sure That's a Standard Deviation? (Part 1). Cochrane News, 1997 (http://www.cochrane.org/newslett/ccnewsbi.htm).Google Scholar
21 Deeks, JJ. Are You Sure That's a Standard Deviation? (Part 2). Cochrane News, 1997 (http://www.cochrane.org/newslett/ccnewsbi.htm).Google Scholar
22 van Tulder, MW, Assendelft, WJ, Koes, BW, Bouter, LM. Method guidelines for systematic reviews in the Cochrane Collaboration Back Review Group for Spinal Disorders. Spine 1997; 22: 2323–30.Google Scholar
23 van Boeijen, CA, van Balkom, AJLM, van Oppen, P, Blankenstein, N, Cherpanath, A, van Dyck, R. Efficacy of self-help manuals for anxiety disorders in primary care: a systematic review. Fam Pract 2005; 22: 192–6.CrossRefGoogle ScholarPubMed
24 Oude Voshaar, RC, Couvée, JE, Van Balkom, AJLM, Mulder, PGH, Zitman, FG. Strategies for discontinuing long-term benzodiazepine use. Meta-analysis. Br J Psychiatry 2006; 189: 213–20.Google Scholar
25 Chalmers, TC, Smith, H, Blackburn, B, Silverman, B, Schroeder, B, Reitman, D, et al. A method for assessing the quality of a randomized control trial. Control Clin Trials 1981; 2: 3149.Google Scholar
26 Beck, AT, Ward, CH, Mendelson, M, Mock, J, Erbaugh, J. An inventory for measuring depression. Arch Gen Psychiatry 1961; 4: 561–71.Google Scholar
27 Beck, AT, Steer, RA, Brown, GK. Beck Depression Inventory (2nd edn): Manual. Psychological Corp, 1996.Google Scholar
28 Hamilton, M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960; 23: 5662.Google Scholar
29 Radloff, LS. The CES-D Scale: A self-report depression scale for research in the general population. Appl Psychol Meas 1977; 1: 385401.Google Scholar
30 Zigmond, AS, Snaith, RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983; 67: 361–70.Google Scholar
31 McNair, PM, Lorr, M, Drappelman, L. POMS Manual. Education and Industrial Testing, 1971.Google Scholar
32 Derogatis, LR. SCL-90-R Administration, Scoring and Procedures Manual. NSC Pearson, 1994.Google Scholar
33 Huiskes, CJAE, Kraaimaat, FW, Bijlsma, JWJ. Invloed van Reuma op Gezondheid en Leefwijze: Een Zelfbeoordelingslijst voor het Meten van de Invloed van Reuma op Gezondheid en Leefwijze [Impact of Rheumatic Diseases on Health and Lifestyle]. Swets & Zeitlinger, 1990.Google Scholar
34 Higgins, JPT, Green, S. Cochrane Handbook for Systematic Reviews of Interventions Version 5.0.2 [updated September 2009]. The Cochrane Collaboration, 2009 (http://www.cochrane-handbook.org).Google Scholar
35 Moher, D, Cook, DJ, Eastwood, S, Olkin, I, Rennie, D, Stroup, DF. Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. Lancet 1999; 354: 1896–900.Google Scholar
36 Tan, SY, Bruni, J. Cognitive-behavior therapy with adult patients with epilepsy: a controlled outcome study. Epilepsia 1986; 27: 225–33.Google Scholar
37 Brown, MA, Munford, AM, Munford, PR. Behavior therapy of psychological distress in patients after myocardial infarction or coronary bypass. J Cardiopulm Rehabil 1993; 13: 201–10.Google Scholar
38 Mulder, CL, Emmelkamp, PM, Antoni, MH, Mulder, JW, Sandfort, TG, de Vries, MJ. Cognitive-behavioral and experiential group psychotherapy for HIV-infected homosexual men: a comparative study. Psychosom Med 1994; 56: 423–31.CrossRefGoogle ScholarPubMed
39 Parker, JC, Smarr, KL, Buckelew, SP, Stucky-Ropp, RC, Hewett, JE, Johnson, JC, et al. Effects of stress management on clinical outcomes in rheumatoid arthritis. Arthritis Rheum 1995; 38: 1807–18.Google Scholar
40 Moynihan, C, Bliss, JM, Davidson, J, Burchell, L, Horwich, A. Evaluation of adjuvant psychological therapy in patients with testicular cancer: randomised controlled trial. BMJ 1998; 316: 429–35.Google Scholar
41 Leibing, ED, Pfingsten, M, Bartmann, U, Rueger, U, Schuessler, G. Cognitive–behavioral treatment in unselected rheumatoid arthritis outpatients. Clin J Pain 1999; 15: 5866.Google Scholar
42 Edelman, S, Bell, DR, Kidman, AD. A group cognitive behaviour therapy programme with metastatic breast cancer patients. Psychooncology 1999; 8: 295305.Google Scholar
43 Antoni, MH, Lehman, JM, Kilbourn, KM, Boyers, AE, Culver, JL, Alferi, SM, et al. Cognitive-behavioral stress management intervention decreases the prevalence of depression and enhances benefit finding among women under treatment for early-stage breast cancer. Health Psychol 2001; 20: 2032.Google Scholar
44 Lincoln, NB, Flannaghan, T. Cognitive behavioral psychotherapy for depression following stroke: a randomized controlled trial. Stroke 2003; 34: 111–5.Google Scholar
45 Given, C, Given, B, Rahbar, M, Jeon, S, McCorkle, R, Cimprich, B, et al. Does a symptom management intervention affect depression among cancer patients: results from a clinical trial. Psychooncology 2004; 13: 818–30.Google Scholar
46 Claesson, MM, Birgander, LS, Lindahl, B, Nasic, S, Astrom, M, Asplund, K, et al. Women's hearts-stress management for women with ischemic heart disease: explanatory analyses of a randomized controlled trial. J Cardiopulm Rehabil 2005; 25: 93102.CrossRefGoogle ScholarPubMed
47 Doering, LV, Cross, R, Vredevoe, D, Martínez-Maza, O, Cowan, MJ. Infection, depression, and immunity in women after coronary artery bypass: a pilot study of cognitive behavioral therapy. Altern Ther Health Med 2007; 13: 1821.Google Scholar
48 Larcombe, NA, Wilson, PH. An evaluation of cognitive-behaviour therapy for depression in patients with multiple sclerosis. Br J Psychiatry 1984; 145: 366–71.Google Scholar
49 Foley, FW, Bedell, JR, LaRocca, NG, Scheinberg, LC, Reznikoff, M. Efficacy of stress-inoculation training in coping with multiple sclerosis. J Consult Clin Psychol 1987; 55: 919–22.Google Scholar
50 Greer, S, Moorey, S, Baruch, JD, Watson, M, Robertson, BM, Mason, A, et al. Adjuvant psychological therapy for patients with cancer: a prospective randomised trial. BMJ 1992; 304: 675–80.Google Scholar
51 Kelly, JA, Murphy, DA, Bahr, GR, Kalichman, SC, Morgan, MG, Stevenson, LY, et al. Outcome of cognitive-behavioral and support group brief therapies for depressed, HIV-infected persons. Am J Psychiatry 1993; 150: 1679–86.Google Scholar
52 Evans, RL, Connis, RT. Comparison of brief group therapies for depressed cancer patients receiving radiation treatment. Public Health Rep 1995; 110: 306–11.Google Scholar
53 Kraaimaat, FW, Brons, MR, Geenen, R, Bijlsma, JWJ. The effect of cognitive behavior therapy in patients with rheumatoid arthritis. Behav Res Ther 1995; 33: 487–95.Google Scholar
54 Henry, JL, Wilson, PH, Bruce, DG, Chisholm, DJ, Rawling, PJ. Cognitive-behavioural stress management for patients with non-insulin dependent diabetes mellitus. Psychol Health Med 1997; 2: 109–18.Google Scholar
55 Markowitz, JC, Kocsis, JH, Fishman, B, Spielman, LA, Jacobsberg, LB, Frances, AJ, et al. Treatment of depressive symptoms in human immunodeficiency virus-positive patients. Arch Gen Psychiatry 1998; 55: 452–7.Google Scholar
56 Edelman, S, Bell, DR, Kidman, AD. Group CBT versus supportive therapy with patients who have primary breast cancer. J Cogn Psychother: Int Q 1999; 13: 189202.Google Scholar
57 Mohr, DC, Likosky, W, Bertagnolli, A, Goodkin, DE, van der Wende, J, Dwyer, P, et al. Telephone-administered cognitive-behavioral therapy for the treatment of depressive symptoms in multiple sclerosis. J Consult Clin Psychol 2000; 68: 356–61.Google Scholar
58 Mohr, DC, Boudewyn, AC, Goodkin, DE, Bostrom, A, Epstein, L. Comparative outcomes for individual cognitive-behavior therapy, supportive-expressive group psychotherapy, and sertraline for the treatment of depression in multiple sclerosis. J Consult Clin Psychol 2001; 69: 942–9.Google Scholar
59 Sharpe, L, Sensky, T, Timberlake, N, Ryan, B, Brewin, CR, Allard, S. A blind, randomized, controlled trial of cognitive-behavioural intervention for patients with recent onset rheumatoid arthritis: preventing psychological and physical morbidity. Pain 2001; 89: 275–83.Google Scholar
60 Cruess, S, Antoni, MH, Hayes, A, Penedo, F, Ironson, G, Fletcher, MA, et al. Changes in mood and depressive symptoms and related change processes during cognitive-behavioral stress management in HIV-infected men. Cognit Ther Res 2002; 26: 373–92.Google Scholar
61 Evers, AWM, Kraaimaat, FW, van Riel, PLCM, de Jong, AJL. Tailored cognitive-behavioral therapy in early rheumatoid arthritis for patients at risk: a randomized controlled trial. Pain 2002; 100: 141–53.Google Scholar
62 Kissane, DW, Bloch, S, Smith, GC, Miach, P, Clarke, DM, Ikin, J, et al. Cognitive-existential group psychotherapy for women with primary breast cancer: a randomised controlled trial. Psychooncology 2003; 12: 532–46.CrossRefGoogle ScholarPubMed
63 Nezu, AM, Nezu, CM, Felgoise, SH, McClure, KS, Houts, PS. Project Genesis: assessing the efficacy of problem-solving therapy for distressed adult cancer patients. J Consult Clin Psychol 2003; 71: 1036–48.CrossRefGoogle ScholarPubMed
64 Blumenthal, JA, Sherwood, A, Babyak, MA, Watkins, LL, Waugh, R, Georgiades, A, et al. Effects of exercise and stress management training on markers of cardiovascular risk in patients with ischemic heart disease: a randomized controlled trial. JAMA 2005; 293: 1626–34.Google Scholar
65 Chan, I, Kong, P, Leung, P, Au, A, Li, P, Chung, R, et al. Cognitive-behavioral group program for Chinese heterosexual HIV-infected men in Hong Kong. Patient Educ Couns 2005; 56: 7884.CrossRefGoogle ScholarPubMed
66 Mohr, DC, Hart, SL, Julian, L, Catledge, C, Honos-Webb, L, Vella, L, et al. Telephone-administered psychotherapy for depression. Arch Gen Psychiatry 2005; 62: 1007–14.Google Scholar
67 Antoni, MH, Carrico, AW, Duran, RE, Spitzer, S, Penedo, F, Ironson, G, et al. Randomized clinical trial of cognitive behavioral stress management on human immunodeficiency virus viral load in gay men treated with highly active antiretroviral therapy. Psychosom Med 2006; 68: 143–51.Google Scholar
68 Savard, J, Simard, S, Giguère, I, Ivers, H, Morin, CM, Maunsell, E, et al. Randomized clinical trial on cognitive therapy for depression in women with metastatic breast cancer: psychological and immunological effects. Palliat Support Care 2006; 4: 219–37.CrossRefGoogle ScholarPubMed
69 Gellis, ZD, McGinty, J, Horowitz, A, Bruce, ML, Misener, E. Problem-solving therapy for late-life depression in home care: a randomized field trial. Am J Geriatr Psychiatry 2007; 15: 968–78.Google Scholar
70 Lii, YC, Tsay, SL, Wang, TJ. Group intervention to improve quality of life in haemodialysis patients. J Clin Nurs 2007; 16: 268–75.Google Scholar
71 Koertge, J, Janszky, I, Sundin, Ö, Blom, M, Georgiades, A, László, KD, et al. Effects of a stress management program on vital exhaustion and depression in women with coronary heart disease: a randomized controlled intervention study. J Intern Med 2008; 263: 281–93.Google Scholar
72 Kunik, ME, Veazy, C, Cully, JA, Souchek, J, Graham, DP, Hopko, D, et al. COPD education and cognitive behavioral therapy group treatment for clinically significant symptoms of depression and anxiety in COPD patients: a randomized controlled trial. Psychol Med 2008; 38: 385–96.CrossRefGoogle ScholarPubMed
73 Safren, SA, O'Cleirig, C, Tan, J, Raminani, S, Reilly, LC, Otto, MW, et al. A randomized controlled trial of cognitive behavioral therapy for adherence and depression (CBT-AD) in HIV-infected individuals. Health Psychol 2009; 28: 110.Google Scholar
74 Akechi, T, Okuyama, T, Onishi, J, Morita, T, Furukawa, TA. Psychotherapy for depression among incurable cancer patients. Cochrane Database Syst Rev 2008; 2: CD005537.Google Scholar
75 Caplette-Gingras, A, Savard, J. Depression in women with metastatic breast cancer: a review of the literature. Palliat Support Care 2008; 6: 377–87.Google Scholar
76 MacMahon, KMA, Lip, GYH. Psychological factors in heart failure: a review of the literature. Arch Intern Med 2002; 162: 509–16.Google Scholar
77 Dunkel-Schetter, C, Feinstein, LG, Taylor, SE, Falke, RL. Patterns of coping with cancer. Health Psychol 1992; 11: 7987.Google Scholar
78 Hirai, K, Suzuki, Y, Tsuneto, S, Ikenega, M, Hosaka, T, Kashiwagi, T. A structural model of the relationships among self-efficacy, psychological adjustment, and physical condition in Japanese advanced cancer patients. Psychooncology 2002; 11: 221–9.Google Scholar
79 Ranchor, AV, Sanderman, R, Steptoe, A, Wardle, J, Miedema, I, Ormel, J. Pre-morbid predictors of psychological adjustment to cancer. Qual Life Res 2002; 11: 101–13.Google Scholar
80 Hawton, K, Kirk, J. Problem-solving. In Cognitive Behaviour Therapy for Psychiatric Problems: A Practial Guide (eds Hawton, K, Salkovskis, PM, Kirk, J, Clark, DM): 406–26. Oxford University Press, 1989.Google Scholar
81 Cuijpers, P, van Straten, A, Andersson, G, van Oppen, P. Psychotherapy for depression in adults: a meta-analysis of comparative outcome studies. J Consult Clin Psychol 2008; 76: 909–22.Google Scholar
82 McDermut, W, Miller, IW, Brown, RA. The efficacy of group psychotherapy for depression: a meta-analysis and review of the empirical research. Clin Psychol Sci Pract 2001; 8: 98116.Google Scholar
Figure 0

Fig. 1 Flow diagram of randomised controlled trials (RCTs) included and excluded in meta-analysis. CBT, cognitive–behavioural therapy.

Figure 1

Table 1 Study characteristics of participants with depressive disorder

Figure 2

Table 2 Study characteristics of participants with depressive symptoms

Figure 3

Fig. 2 Forrest plot of standard mean difference (with 95% CI) of effect of cognitive–behavioural therapy on depressive symptoms in studies including participants with depressive disorder, with overall effect (black diamond), based on meta-analysis. Std, standard.

Figure 4

Fig. 3 Forrest plot of standard mean difference (with 95% CI) of effect of cognitive–behavioural therapy on depressive symptoms in studies of participants with depressive symptoms, with overall effect (black diamond), based on meta-analysis. Std, standard.

Supplementary material: PDF

Beltman et al. supplementary material

Supplementary Table S1-S2

Download Beltman et al. supplementary material(PDF)
PDF 35.5 KB
Submit a response

eLetters

No eLetters have been published for this article.