Skip to main content
  • Loading metrics

Effects of psychosocial support interventions on survival in inpatient and outpatient healthcare settings: A meta-analysis of 106 randomized controlled trials

  • Timothy B. Smith ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Department of Psychology, Brigham Young University, Provo, Utah, United States of America

  • Connor Workman,

    Roles Data curation, Investigation, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Department of Psychology, Brigham Young University, Provo, Utah, United States of America

  • Caleb Andrews,

    Roles Data curation, Investigation, Supervision, Validation, Writing – review & editing

    Affiliation Department of Psychology, Brigham Young University, Provo, Utah, United States of America

  • Bonnie Barton,

    Roles Data curation, Investigation, Validation, Writing – original draft, Writing – review & editing

    Affiliation Department of Psychology, Brigham Young University, Provo, Utah, United States of America

  • Matthew Cook,

    Roles Data curation, Investigation, Supervision, Writing – review & editing

    Affiliation Department of Psychology, Brigham Young University, Provo, Utah, United States of America

  • Ryan Layton,

    Roles Data curation, Investigation, Validation, Writing – original draft, Writing – review & editing

    Affiliation Department of Psychology, Brigham Young University, Provo, Utah, United States of America

  • Alexandra Morrey,

    Roles Data curation, Investigation, Supervision, Validation, Writing – review & editing

    Affiliation Department of Psychology, Brigham Young University, Provo, Utah, United States of America

  • Devin Petersen,

    Roles Data curation, Investigation, Supervision, Validation, Writing – original draft, Writing – review & editing

    Affiliation Department of Psychology, Brigham Young University, Provo, Utah, United States of America

  • Julianne Holt-Lunstad

    Roles Conceptualization, Investigation, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing

    Affiliation Department of Psychology, Brigham Young University, Provo, Utah, United States of America



Hospitals, clinics, and health organizations have provided psychosocial support interventions for medical patients to supplement curative care. Prior reviews of interventions augmenting psychosocial support in medical settings have reported mixed outcomes. This meta-analysis addresses the questions of how effective are psychosocial support interventions in improving patient survival and which potential moderating features are associated with greater effectiveness.

Methods and findings

We evaluated randomized controlled trials (RCTs) of psychosocial support interventions in inpatient and outpatient healthcare settings reporting survival data, including studies reporting disease-related or all-cause mortality. Literature searches included studies reported January 1980 through October 2020 accessed from Embase, Medline, Cochrane Library, CINAHL, Alt HealthWatch, PsycINFO, Social Work Abstracts, and Google Scholar databases. At least 2 reviewers screened studies, extracted data, and assessed study quality, with at least 2 independent reviewers also extracting data and assessing study quality. Odds ratio (OR) and hazard ratio (HR) data were analyzed separately using random effects weighted models. Of 42,054 studies searched, 106 RCTs including 40,280 patients met inclusion criteria. Patient average age was 57.2 years, with 52% females and 48% males; 42% had cardiovascular disease (CVD), 36% had cancer, and 22% had other conditions. Across 87 RCTs reporting data for discrete time periods, the average was OR = 1.20 (95% CI = 1.09 to 1.31, p < 0.001), indicating a 20% increased likelihood of survival among patients receiving psychosocial support compared to control groups receiving standard medical care. Among those studies, psychosocial interventions explicitly promoting health behaviors yielded improved likelihood of survival, whereas interventions without that primary focus did not. Across 22 RCTs reporting survival time, the average was HR = 1.29 (95% CI = 1.12 to 1.49, p < 0.001), indicating a 29% increased probability of survival over time among intervention recipients compared to controls. Among those studies, meta-regressions identified 3 moderating variables: control group type, patient disease severity, and risk of research bias. Studies in which control groups received health information/classes in addition to treatment as usual (TAU) averaged weaker effects than those in which control groups received only TAU. Studies with patients having relatively greater disease severity tended to yield smaller gains in survival time relative to control groups. In one of 3 analyses, studies with higher risk of research bias tended to report better outcomes. The main limitation of the data is that interventions very rarely blinded personnel and participants to study arm, such that expectations for improvement were not controlled.


In this meta-analysis, OR data indicated that psychosocial behavioral support interventions promoting patient motivation/coping to engage in health behaviors improved patient survival, but interventions focusing primarily on patients’ social or emotional outcomes did not prolong life. HR data indicated that psychosocial interventions, predominantly focused on social or emotional outcomes, improved survival but yielded similar effects to health information/classes and were less effective among patients with apparently greater disease severity. Risk of research bias remains a plausible threat to data interpretation.

Author summary

Why was this study done?

  • Medical patients may have difficulty coping with illness. Hospitals, clinics, and health organizations can provide psychosocial support interventions (e.g., calming patients and facilitating treatment adherence) to supplement medical care and possibly improve patient survival.
  • Variability exists among psychosocial interventions, and prior evidence about patient survival is mixed; thus, it may be useful to identify factors across research studies that are associated with greater effectiveness.

What did the researchers do and find?

  • A meta-analysis evaluated randomized controlled trials (RCTs) of psychosocial support interventions in medical settings. Separate analyses examined studies reporting patient survival by study end and studies reporting survival rates over time.
  • Compared to control groups, those receiving a psychosocial intervention were on average 20% more likely to be alive at study conclusion and had 29% increased likelihood of longer survival, but results varied widely across studies.
  • Secondary findings: Study interventions that also included a component supporting health behaviors improved likelihood of patient survival compared with interventions that did not. Studies with patients having relatively greater disease severity and studies comparing outcomes to groups receiving health information/classes tended to yield nonsignificant gains in survival time. Studies having a low risk of research bias were more likely to report smaller improvements in patient survival.

What do these findings mean?

  • These findings suggest that psychosocial support in medical settings generally promote survival and increase survival time to an extent comparable with rehabilitation programs.
  • Intended benefits of psychosocial interventions are to support patients emotionally and to behaviorally cope with their disease.
  • Although difficult to accomplish, future research should attempt to keep patients and personnel unaware of group comparisons to reduce the potential for bias due to different expectations for improvement.


Decades ago, researchers found that psychosocial support interventions (e.g., survivor groups and individual nurse support sessions) may improve not only patient quality of life but also patient survival [1,2]. Subsequent evidence regarding patient survival has been mixed [3].

Adequate support among medical patients has been linked to better outcomes, while those that lack adequate support systems have poorer outcomes including greater hospitalization, mortality, and medical costs—such that evaluations of supportive psychosocial interventions have been recommended in healthcare settings [4]. Substantial epidemiological evidence supports the link between psychosocial functioning and health outcomes, including meta-analyses indicating that presence or absence of social support predict all-cause mortality to an extent equivalent to other leading indicators of health (e.g., BMI and smoking cessation) [57]. The accumulated research evidence meets the Bradford Hill criteria, establishing low psychosocial support as a causal risk factor for premature mortality [8]. Level of psychosocial functioning has been shown to influence health risk through both emotional coping/resilience and behavioral modeling/motivation [9,10]. However, less is known concerning whether emotional and behavioral support from healthcare professionals can improve medical patients’ survival [4]. Given mounting evidence of health consequences of poor psychosocial functioning, the medical community can benefit from evaluating which psychosocial interventions most improve patient survival [11].

Over the past 4 decades, dozens of psychosocial support interventions have been evaluated for medical patients; accumulated literature on the topic is extensive but diverse. These include interventions conducted in patients’ homes, in support groups, or via telephone/online conversations. Some psychosocial interventions focus on behavior, explicitly supporting patients’ modification of health behaviors. This is based on evidence demonstrating that social support is linked to improved medical adherence [12,13], physical activity [14], sleep [15], and healthcare service utilization [16]. Other psychosocial interventions focus more specifically on emotion, explicitly supporting patients’ coping with distress. Abundant research evidence suggests that psychosocial distress co-occurs with physical disease, with bidirectional relationships that influence disease progression (e.g., appraisal and self-regulation ability) [4]. Research indicates that psychosocial functioning not only affects relevant social capital (e.g., access to health information and improved trust of healthcare) [17] but can also reduce inflammation and improve systemic circulation [1820]. More specifically, even short-term emotional management interventions can influence inflammatory gene expression [21]. The number of psychosocial interventions with medical patients has multiplied rapidly in recent years, with interventions including multiple overlapping components (e.g., reducing distress and enhancing healthcare utilization). Before the complexity increases further, it would be useful to take stock of extant data by comparing psychosocial interventions across study, intervention, and patient characteristics.

Prior meta-analyses of psychosocial support interventions have evaluated patient survival [2243]; however, these were susceptible to error due to low numbers of studies included (range = 1 to 36, M = 11.2). Also, few previous meta-analyses have identified effective/ineffective intervention attributes, and most have had limited scope (e.g., breast cancer survivor groups). Although specificity in research is usually optimal, an unintended consequence has been ignoring the reality that professionals across medical specialties use similar psychosocial interventions. Thus, to evaluate differences across contexts, we have conducted what to our knowledge is the largest meta-analytic review to date, including 3 times the number of studies of any prior meta-analysis that we could locate on the topic. We sought to evaluate the overall degree to which psychosocial support interventions improve survival among patients receiving curative or rehabilitative care—and to specifically compare psychosocial interventions emphasizing behavioral support (e.g., modeling/motivation to engage in health behaviors such as physical activity) with those focused primarily on social/emotional support (e.g., emotional resilience following surgery). We also investigated outcome differences across study risk of bias and (a) study characteristics: duration of intervention, length of follow-up, type of control group, and patient psychosocial improvement; (b) intervention type: group meetings, telephone/online support, home visits, and family inclusion; and (c) patient characteristics: age, gender, disease, and mortality rate.


Search strategy

This study is reported as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA guidelines [44]; S1 Checklist). We sought published and unpublished studies written in any language investigating the effects of psychosocial support interventions on medical patient survival. All authors participated in searching studies completed between January 1980 and October 2020, accessed using Embase, Medline, Cochrane Library, Alt HealthWatch, CINAHL, PsycINFO, Social Work Abstracts, and Google Scholar. To locate all relevant articles, we used an extensive list of search terms, manually examined the reference sections of both prior reviews and studies meeting the inclusion criteria, and contacted authors of included studies (S1 Text).

Study selection

The meta-analysis included randomized controlled trials (RCTs) reporting data of medical patients’ survival as a function of a real-time intervention providing psychological, emotional, and/or social support. We included studies of patients with a health condition likely to result in death if untreated, and who were recruited from healthcare settings (e.g., hospitals, rehabilitation clinics, or inpatient/outpatient databases). We excluded patients with solely mental health disorders (e.g., anxiety or dementia) because those conditions contribute indirectly to mortality, and we also excluded mortality resulting from accident, suicide, or violence as well as mortality data combined with morbidity/hospitalization.

As the majority of psychosocial support interventions described in the literature involve multiple components, we included interventions with mixed components (e.g., group psychotherapy, nurse visits, and telephone support) and coded for differences to compare outcomes. We excluded those providing only psychoeducation or disease management and those consisting solely of one-on-one psychotherapy, which historically has been a distinct kind of intervention deserving separate systematic review. We similarly excluded hospice or palliative care interventions which deserved separate review because of their focus on improving quality of life, not necessarily length of life, which is the observed outcome of this meta-analysis specific to curative and rehabilitative care. S1 Table provides detailed inclusion/exclusion criteria.

Data analysis

A team of 2 raters coded each article; subsequently, another team of 2 raters independently coded the same article. Teams resolved discrepancies through manuscript scrutiny until achieving consensus. Coders extracted (a) number of participants with composition by gender and average age; (b) length of intervention and follow-up; (c) type of intervention; and (d) multiple indicators of study risk of bias. Effect size data were hazard ratios (HRs) and odds ratios (ORs); when studies reported other values (e.g., regression coefficients or Cohen’s d), we transformed them to OR using multiple effect size calculators available online. Data were extracted from the longest follow-up period; when studies contained multiple effect sizes at the same time point (e.g., across subsamples), averaged values were weighted by SE. When reports explicitly tracked mortality but no participants died in either condition, we coded the effect size as OR = 1. We sought effect sizes from multivariable models but calculated OR from survival frequency counts when statistical models were unreported. Stata 16, SPSS 25, and Comprehensive Meta-Analysis 3 were used to calculate random effects weighted models in data aggregation and in subsequent subgroup analysis and meta-regressions.

Our data analysis plan (S2 Text) was to (a) report descriptive statistics of study characteristics; (b) calculate random effects weighted omnibus HR and OR values and also indicators of between-study heterogeneity (Q and I2); (c) conduct subgroup analysis across intervention type (behavior focused versus social/emotional focused); (d) report meta-regressions separately for study, intervention, and patient characteristics; and (e) estimate the likelihood of publication bias. We did not prespecify which variables to include in the meta-regressions but clustered them according to study, intervention, and participant characteristics. We reported a subgroup analysis contrasting behavioral support with social/emotional support as a result of reviewer feedback, not as a prespecified analysis. We prospectively planned to evaluate the likelihood of publication bias estimates using funnel plots, the trim and fill method, and Egger and Peters regression tests. This meta-analysis is registered with Open Science Framework (3nj8u), with data available at


Description of included studies

We located 42,054 studies and screened 909 using the full text (Fig 1). Nonredundant effect sizes were extracted from 106 RCTs [13, 45147] conducted in locations as follows: 50 (47%) in Europe, with 22 in Scandinavia, 11 in the United Kingdom, 6 in the Netherlands, 4 in Germany, and 7 other; 35% in North America, with 28 in the United States and 10 in Canada; 10 in Asia; 6 in Australia; and 2 in Africa. Data involved a total of 40,280 participants, whose average age was 57.2 years (SD = 9.9, range = 11 to 78), with an average of 52% females and 48% males. Across all studies, 81 (76%) involved medical outpatients, 20 (19%) recruited hospitalized inpatients, and 5 (5%) involved both. Patients had cardiovascular disease (CVD) in 44 studies (42%), cancer in 38 (36%) studies, or other conditions in 24 (22%) studies; a total of 102 (96%) reported all-cause mortality, with 2 reporting CVD mortality, 1 reporting cancer mortality, and 1 reporting HIV-related mortality.

Fig 1. PRISMA flow diagram of study selection process.

PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; RCT, randomized controlled trial.

Regarding intervention focus, 34 of the 106 studies (32%) provided psychosocial behavioral support, explicitly focusing on health behaviors, and 72 (68%) focused on social/emotional support. Many studies included only 1 form of intervention: 46 (43%) in-person group meetings, 11 (10%) telephone/online sessions, 9 (8%) home visits, and 7 (7%) in-person individual sessions; the remaining 34 (32%) provided a combination of formats. Interventions were conducted by nurses or medical staff in 37 studies (35%), social workers or mental health professionals in 32 studies (30%), peers with the same medical condition in 4 studies (4%), combinations of those groups in 24 studies (23%), and family members in 1 study, with 8 studies unspecified. Across all interventions, 67 (63%) intended to foster patient social relationships with previously unknown individuals; 20 (19%) provided support only from professional staff; and although 34 (32%) invited family members, only 10 of those focused on family–patient relationships. On average, each intervention session lasted 83 minutes (SD = 46.1; excluding 1 day-long intervention [97]), with 14.7 total sessions (SD = 15.9) over 7.5 months (SD = 8.0). Researchers followed participants after the intervention for an average of 25.6 months (SD = 38.5), during which an average of 13.6% of participants died (SD = 20.3).

Of the 106 RCTs, 87 reported survival data for discrete time periods (transformed to OR), and 22 reported data in terms of survival time (HRs), with 3 studies [74,85,124] reporting both metrics. These types of studies differed in several ways (Table 1). Compared with studies reporting only OR data, studies reporting HR data tended to have an earlier date of initiation and longer total duration, with more female participants, more sessions, longer follow-up, and a correspondingly higher proportion of patient mortality by study conclusion. S2 and S3 Tables contain detailed information about individual studies by data type.

Table 1. Study characteristics by type of survival data reported.

Main analyses

Across 87 observations at fixed time periods, the average was OR = 1.20 (95% CI = 1.09 to 1.31, p < 0.001), indicating a 20% increased likelihood of survival for intervention participants compared to controls. However, the observed effects differed (Q = 9.3, p = 0.002) between the 31 psychosocial behavioral support interventions having an explicit focus on improving coping/motivation to engage in health behaviors (OR = 1.35, 95% CI = 1.20 to 1.52, p < 0.001) and the 56 interventions emphasizing social/emotional support (OR = 1.01, 95% CI = 0.87 to 1.16, p = 0.94). The effect sizes for both kinds of interventions varied substantially, with broad confidence intervals (S1 and S2 Figs). However, in separate analyses specific to effect size heterogeneity, the percentage of variance explained by between-study heterogeneity was estimated to be zero for both the 31 psychosocial interventions based on behavior support (I2 = 0.0; Q(30) = 27.9, p = 0.57) and the 56 focused on social/emotional support (I2 = 0.0; Q(55) = 47.0, p = 0.77). Given the absence of between-studies heterogeneity, no further analyses were conducted with OR data.

The 22 RCTs reporting data in terms of survival time averaged HR = 1.29 (95% CI = 1.12 to 1.49, p < 0.001), indicating a 29% increased likelihood of longer survival compared to controls (S3 Fig). As only 4 of the 22 studies focused on supporting health behaviors, we did not analyze subgroup differences. Since the HR data were characterized by a moderate percentage of between-study heterogeneity (I2 = 54.0; Q(21) = 45.7, p = 0.001), we conducted meta-regressions to evaluate possible moderation by study, intervention, and patient attributes.

Meta-regressions of study, intervention, and patient characteristics

Due to the limited number of studies (k = 22), we evaluated study, intervention, and participant characteristics in 3 separate meta-regression models of HR data. The first model, which evaluated study characteristics (Table 2), explained 37.5% of the variance in effect sizes and reached statistical significance (p = 0.014). The model included 2 significant predictors: control group type (β = −0.42, p = 0.048) and estimated risk of research bias (β = 0.470, p = 0.018). The 8 studies in which control group members received health information/classes in addition to treatment as usual (TAU) averaged HR = 1.14 (95% CI = 0.92 to 1.40, p = 0.23), but the 14 studies with only TAU controls averaged HR = 1.38 (95% CI = 1.17 to 1.62, p < 0.001). Studies with relatively higher risk of research bias tended to report improved patient survival as a result of the intervention; given that finding, we included risk of bias in subsequent meta-regression models.

Table 2. Random effects meta-regression of HR estimates of study characteristics on patient survival.

The second meta-regression predicted HR data based on the type of intervention (Table 3). The model explained 10.3% of the variance in effect sizes and did not reach statistical significance (p = 0.69). Different kinds of interventions tended to yield similar likelihood of patient survival.

Table 3. Random effects meta-regression of HR estimates of intervention type on patient survival.

The third meta-regression predicted HR data from patient characteristics (Table 4). The model explained 41.0% of the variance in effect sizes (p = 0.025). One variable in the model reached statistical significance: Interventions with patients having more advanced disease severity (marked by percentage of patients dying per month) tended to yield lower effect sizes (β = −0.61, p = 0.007). That is, patients with greater disease severity tended to experience reduced benefits from a psychosocial intervention compared to participants in studies with relatively lower disease severity. To put this finding into perspective, 9 studies in which ≥0.5% of patients died per month averaged HR = 1.13 (95% CI = 0.95 to 1.34, p = 0.16), but 11 studies with lower rates of patient mortality averaged HR = 1.64 (95% CI = 1.37 to 1.97, p < 0.001). Risk of bias did not reach statistical significance; we conducted collinearity diagnostics and disconfirmed multicollinearity for all 3 meta-regressions.

Table 4. Random effects meta-regression of HR estimates of patient characteristics on patient survival.

Evaluation of risk of bias

Fig 2 summarizes sources of potential bias across all 106 studies (individual studies reported in S4 Fig). In intervention studies of psychosocial support, both personnel and participants know the conditions of the group to which they are assigned. However, it is difficult to limit personnel and/or participant awareness about the other arm of the study in order to diminish unbalanced expectations for improvement. Such blinding of personnel or participants occurred in very few of the 106 studies evaluated (7% blinding participants, 3% blinding personnel, and 2% blinding both). Thus, the results observed in this meta-analysis do not control for plausible expectation differences between treatment and control groups.

Fig 2. Risk of bias graph of characteristics across 106 studies.

Blinding of outcome assessment was unclear in 44% of studies. Although reports of patient death are reasonably reliable, optimally, researchers would confirm patient mortality through independent records. When independent confirmation does not occur, a plausible threat to study validity is that some participants who researchers are “unable to contact” have died. The impact of missing survival data depends on whether participant attrition remains low and balanced across groups. In this meta-analysis, medical patient attrition across all studies averaged 9.9%, with an average difference of 0.6% between the intervention and control groups, so the risk of bias due to attrition was generally low.

Most studies in this meta-analysis explicitly reported the randomization strategy (64%) and allocation concealment (61%). Participants in the intervention and control groups were typically balanced across variables measured at baseline (78%). The vast majority of studies reported intent-to-treat data (85%) as well as endpoint data on all measures administered (93%).

Estimate of publication bias

We evaluated the degree to which publication bias may have impacted the overall findings. Begg test, Egger test, and Peters test did not reach statistical significance for either HR or OR data. Inspection of the funnel plots (S5 and S6 Figs) did not suggest more than a few missing studies. Trim and fill analyses [148] of the HR data indicated only 1 missing study using the L0 estimator but 4 missing studies using the R0 estimator. When 4 studies were imputed in the distribution, the results remained statistically significant (HR = 1.22, 95% CI = 1.05 to 1.41, p = 0.009). Trim and fill analysis of the OR data identified no missing studies using the R0 estimator but 8 missing studies using the L0 estimator. When 8 studies were imputed in the distribution, the results of the OR data remained statistically significant (OR = 1.15, 95% CI = 1.03 to 1.29, p = 0.015). Overall, the results of this meta-analysis did not appear to be adversely impacted by publication bias.


Statement of principal findings

This meta-analysis, including 106 RCTs and 40,280 participants, examined the extent to which different types of psychosocial support interventions increased survival among medical patients receiving curative or rehabilitative care. Overall, the interventions increased odds of survival (OR = 1.20) and relative length of survival (HR = 1.29), with the magnitude of these data being comparable with other tertiary prevention interventions (Fig 3).

Fig 3. Comparison of odds (lnOR) and hazards (lnHR) of mortality across several tertiary prevention interventions.

Note: lnOR = natural logarithm of the OR of patient survival. lnHR = natural logarithm of the HR of patient survival. Effect size of 0 indicates no effect, and values above 1 favor the intervention group relative to the control group. Comparison effect sizes and 95% confidence intervals were reported in meta-analyses: A = McQueen et al. [149]; B = Wu et al. [150]; C = Taylor et al. [151]; D = Ma et al. [152]; E = Kritchevsky et al. [153]; F = Mons et al. [154]; G = Taylor et al. [155]; H = Calman et al. [156]; I = Hauner et al. [157]. CVD, cardiovascular disease; HR, hazard ratio; OR, odds ratio.

Across the 87 studies reporting survival data at a fixed point in time, the 31 psychosocial behavioral support interventions (e.g., motivation for treatment adherence) improved the likelihood of patient survival, but the 56 interventions emphasizing social/emotional support yielded results no better than those of control groups. It is unclear whether behaviorally focused interventions are more effective or whether these types of interventions merely involve more components (behavioral and social/emotional), thereby providing greater diversity of support. As only 4 of the studies reporting HR data were explicitly focused on promoting patient health behaviors, a similar subgroup comparison was not advisable until additional studies reporting HR data accrue in the literature. The HR data predominantly represented interventions focused on social/emotional outcomes (18 of 22 studies).

Other differences between the studies reporting OR and HR data can inform data interpretation. A primary difference involves the nature of ORs and HRs. ORs provide a snapshot at a fixed point in time, but HRs reflect changes across time. Moreover, Cox proportional hazards regression models typically include covariates, such that other variables (e.g., initial health status and socioeconomic status) are less likely to influence the reported outcomes. In terms of our data specifically, the 22 studies reporting HR data tended to have more female participants, twice as many sessions, and 5 more years of patient follow-up, with correspondingly lower rates of patient survival than the 87 studies reporting OR data. Future research is needed to confirm whether interventions with more sessions and longer follow-up yield greater benefits, as recommended in a National Academy of Science report [4].

Analyses with HR data indicated that patient disease severity (percentage of deaths per month) moderated the overall findings. Specifically, studies in which a relatively larger percentage of patients died each month tended to report fewer benefits from the psychosocial intervention in terms of patient survival compared to control conditions. Future research can investigate if the higher mortality rates are a function of more reliable outcomes when death is not uncommon in the distribution. Alternatively, psychosocial interventions might be more effective in improving survival among patients when conducted earlier in the disease trajectory, consistent with effectiveness of other medical treatment.

Meta-regression analyses with HR data indicated that effect sizes did not differ across the format of the intervention (support groups, telephone/online conversations, family involvement, or home visits). However, in one of the meta-regressions, the findings differed as a function of study risk of bias, with studies reporting more robust results also tending to have more indicators of research bias. Having disconfirmed multicollinearity, we cannot account for why that variable reached statistical significance in only one of 3 analyses, but the result provides a caution that qualifies the overall findings reported in the literature. The overall strength of evidence was mixed (Fig 2), with the primary limitation being the neglect of blinding personnel and participants to study conditions. Thus, it is difficult to distinguish between intervention effects and expectation effects when personnel and participants have knowledge of both study conditions. This concern was reinforced by the finding that 8 psychosocial support interventions reporting HR data did not show statistically significant differences from control groups receiving health information/classes.

Limitations of the study

This meta-analysis has several limitations. First, the results varied widely across individual studies (see S1S3 Figs). The omnibus results should be interpreted using their confidence intervals. Across the 87 studies reporting OR data, the confidence intervals for individual studies were so wide that there were no nonoverlapping values (I2 = 0.0). The wide confidence intervals for most of these OR studies corresponded with a numerically low percentage of patients who died across studies (8.1%, see Table 1); low mortality rates yielded high standard error values. Second, variability existed in the approach and delivery of support provided in the studies. Psychosocial support was offered via peer support groups, telephone calls, one-on-one nurse sessions, etc., with our statistical contrast being the mixed interventions. Third, only 10 of the 106 RCTs included support from naturally occurring relationships in at least half of the intervention, with 6 of those focusing specifically on family/partners, yet preexisting relationships constituted the epidemiological evidence that precipitated such interventions [5]. Strengthening preexisting close relationships may produce longer-lasting effects due to the chronic and often intimate nature of such relationships [158]; nonetheless, not all patients have supportive social networks. Fourth, we did not evaluate preexisting levels of patient psychosocial support because the literature inconsistently reported such data. Patients with strong social networks tend to fare better than others on multiple clinical markers [20,159] and outcomes [159161]. Failure to account for preexisting differences in social resources can be corrected in future research [162]. Fifth, although many of the studies reporting HR data included other variables in statistical models, such as patient age and health status, only 3 of the studies reporting OR data statistically controlled for other variables. The HR estimates were therefore more trustworthy than the OR estimates [43].

Implications for clinicians, researchers, and policy makers

Prior meta-analyses have reported mixed results [25,27,31,36], some concluding that psychosocial interventions did not improve patient survival [23,33,37]. Therefore, a major contribution of this meta-analysis was to clarify that although the vast majority of studies did not reach statistical significance (96 of 106 [91%]; see S5 and S6 Figs), psychosocial interventions overall tended to benefit survival with results comparable to rehabilitation programs (Fig 3). However, the extent of variability in results across studies suggests that care must be taken during design and implementation to maximize patient outcomes. In particular, this meta-analysis confirmed that the minority of interventions (32%) that explicitly promoted patient motivation/coping to engage in health behaviors tended to improve patient survival, with an observed effect (OR = 1.35) corresponding with a number needed to treat of 19.6. Rather than focus solely on emotional and psychological support, future psychosocial support interventions with medical patients should also address health behaviors (e.g., motivation for treatment adherence). The accumulated data now make it questionable to neglect including behavioral support when planning psychosocial interventions with medical patients receiving curative care.

Given the concerns raised in this meta-analysis about study risk of bias adversely impacting the reported results, future research should specifically address that issue. Although blinding personnel and participants to the other study arm may be challenging, this gap needs to be addressed to advance the science beyond its current state. Other scholars have recommended that future research identify patient existing psychosocial supports and needs, evaluate specific causal pathways influencing disease progression [9,10,163], focus on strengthening naturally occurring relationships [158], and refine interventions utilizing the Multiphase Optimization Strategy [164,165].

Despite the multiple qualifications and concerns raised in this meta-analysis, psychosocial support interventions improved medical patient survival to a degree comparable with other tertiary prevention methods (Fig 3), with the findings being equivalent to a meta-analysis of epidemiological data on the effects of social isolation on mortality [6]. Taken together with prior research documenting that social isolation increases healthcare costs [166] and excessive utilization [16,167], and with increasing social isolation in recent years [168], this meta-analysis urges increased methodological rigor but tentatively supports recommendations [4] to consider psychosocial interventions in promoting health behavior in a public health framework.

Supporting information

S1 Checklist. PRISMA 2009 checklist.

PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.


S1 Alternative Language Abstract. Spanish translation of the abstract by Laura Melgarejo Perez and Juan Valladares.


S2 Alternative Language Abstract. Traditional Chinese Characters translation of the abstract by Cheng Wai Man.


S3 Alternative Language Abstract. Simplified Chinese Characters translation of the abstract by Li Zhen.


S4 Alternative Language Abstract. Tamil translation of the abstract by Babu Manuel Abel.


S5 Alternative Language Abstract. Italian translation of the abstract by Claudia Mencarelli and Tommaso Cardullo.


S6 Alternative Language Abstract. Turkish translation of the abstract by Murat Çakır.


S7 Alternative Language Abstract. German translation of the abstract by Samira Herber.


S8 Alternative Language Abstract. Indonesian translation of the abstract by Pungki Lupiyaningdyah.


S9 Alternative Language Abstract. Arabic translation of the abstract by Sara Abu Al-Samen.


S10 Alternative Language Abstract. Portuguese translation of the abstract by Solange Andrezzo and Larissa Vecchi.


S1 Text. Literature search strategies and selection criteria.


S2 Table. Characteristics of 87 psychosocial intervention studies reporting ORs of medical patient survival.

OR, odds ratio.


S3 Table. Characteristics of 22 psychosocial intervention studies reporting HRs of medical patient survival.

HR, hazard ratio.


S1 Fig. Forest plot of 56 social/emotional support focused RCTs reporting OR.

OR, odds ratio; RCT, randomized controlled trial.


S2 Fig. Forest plot of 31 behavioral support RCTs reporting ORs.

OR, odds ratio; RCT, randomized controlled trial.


S3 Fig. Forest plot of 22 RCTs reporting HRs.

HR, hazard ratio; RCT, randomized controlled trial.


S5 Fig. Contour-enhanced funnel plot of 89 RCTs, OR data.

OR, odds ratio; RCT, randomized controlled trial.


S6 Fig. Contour-enhanced funnel plot of 22 RCTs, HR data.

HR, hazard ratio; RCT, randomized controlled trial.



We thank our research assistants for their many contributions to this project.


  1. 1. Spiegel D, Bloom JR, Kraemer HC, Gottheil E. Effect of psychosocial treatment on survival of patients with metastatic breast cancer. Lancet 1989;334 (8668):888–91. pmid:2571815
  2. 2. Stern MJ, Gorman PA, Kaslow L. The group counseling v exercise therapy study: a controlled intervention with subjects following myocardial infarction. Arch Intern Med 1983;143 (9):1719–25. pmid:6615094
  3. 3. Fawzy FI, Fawzy NW. Malignant melanoma: effects of a brief, structured psychiatric intervention on survival and recurrence at 10-year follow-up. Arch Gen Psychiatry 2003;60 (1):100–3. pmid:12511177
  4. 4. National Academies of Sciences, Engineering, and Medicine. Social isolation and loneliness in older adults: Opportunities for the health care system. National Academies Press; 2020 Jun 14. pmid:32510896
  5. 5. Holt-Lunstad J, Smith TB, Layton JB. Social relationships and mortality risk: a meta-analytic review. PLoS Med 2010;7 (7):e1000316. pmid:20668659
  6. 6. Holt-Lunstad J, Smith TB, Baker M, Harris T, Stephenson D. Loneliness and social isolation as risk factors for mortality: a meta-analytic review. Perspect Psychol Sci 2015;10 (2):227–37. pmid:25910392
  7. 7. House JS, Landis KR, Umberson D. Social relationships and health. Science 1988;241 (4865):540–5. pmid:3399889
  8. 8. Howick J, Kelly P, Kelly M. Establishing a causal link between social relationships and health using the Bradford Hill Guidelines. SSM Popul Health 2019;8:100402. pmid:31193417
  9. 9. Uchino BN. Understanding the links between social support and physical health: a life-span perspective with emphasis on the separability of perceived and received support. Perspect Psychol Sci 2009;4 (3):236–55. pmid:26158961
  10. 10. Holt-Lunstad J. Why social relationships are important for physical health: a systems approach to understanding and modifying risk and protection. Annu Rev Psychol 2018;69:437–58. pmid:29035688
  11. 11. Fakoya OA, McCorry NK, Donnelly M. Loneliness and social isolation interventions for older adults: a scoping review of reviews. BMC Public Health 2020;20 (1):129. pmid:32054474
  12. 12. DiMatteo MR. Social support and patient adherence to medical treatment: a meta-analysis. Health Psychol 2004;23 (2):207–18. pmid:15008666
  13. 13. Magrin ME, D’addario M, Greco A, Miglioretti M, Sarini M, Scrignaro M, et al. Social support and adherence to treatment in hypertensive patients: a meta-analysis. Ann Behav Med 2015;49 (3):307–18. pmid:25341642
  14. 14. Lindsay Smith G, Banting L, Eime R, O’Sullivan G, Van Uffelen JG. The association between social support and physical activity in older adults: a systematic review. Int J Behav Nutr Phys Act 2017;14(1): 56. pmid:28449673
  15. 15. Kent de Grey RG, Uchino BN, Trettevik R, Cronan S, Hogan JN. Social support and sleep: a meta-analysis. Health Psychol 2018;37 (8):787–98. pmid:29809022
  16. 16. Valtorta NK, Moore DC, Barron L, Stow D, Hanratty B. Older adults’ social relationships and health care utilization: a systematic review. Am J Public Health 2018;108 (4):e1–e10. pmid:29470115
  17. 17. Kawachi I, Subramanian SV, Kim D. Social capital and health. New York: Springer; 2008.
  18. 18. Jutagir DR, Blomberg BB, Carver CS, Lechner SC, Timpano KR, Bouchard LC, et al. Social well-being is associated with less pro-inflammatory and pro-metastatic leukocyte gene expression in women after surgery for breast cancer. Breast Cancer Res Treat 2017;165 (1):169–80. pmid:28560656
  19. 19. Cole SW, Capitanio JP, Chun K, Arevalo JM, Ma J, Cacioppo JT. Myeloid differentiation architecture of leukocyte transcriptome dynamics in perceived social isolation. Proc Natl Acad Sci 2015;112 (49):15142–7. pmid:26598672
  20. 20. Uchino BN, Trettevik R. Kent de Grey RG, Cronan S, Hogan J, Baucom BR. Social support, social integration, and inflammatory cytokines: A meta-analysis. Health Psychol 2018;37 (5):462–71. pmid:29565600
  21. 21. Laudenslager ML, Simoneau TL, Philips S, Benitez P, Natvig C, Cole S. A randomized controlled pilot study of inflammatory gene expression in response to a stress management intervention for stem cell transplant caregivers. J Behav Med 2016;39 (2):346–54. pmid:26733011
  22. 22. Chew BH, Vos RC, Metzendorf MI, Scholten RJ, Rutten GE. Psychological interventions for diabetes-related distress in adults with type 2 diabetes mellitus. Cochrane Database Syst Rev 2017;9. pmid:28954185
  23. 23. Chow E, Tsao MN, Harth T. Does psychosocial intervention improve survival in cancer? A meta-analysis Palliat Med 2004;18 (1):25–31. pmid:14982204
  24. 24. Edwards AG, Hulbert-Williams N, Neal RD. Psychological interventions for women with metastatic breast cancer. Cochrane Database Syst Rev. 2008;3. CD004253, pmid:18646104
  25. 25. Fu WW, Popovic M, Agarwal A, Milakovic M, Fu TS, McDonald R. The impact of psychosocial intervention on survival in cancer: a meta-analysis. Ann Palliat Med 2016;5 (2):93–106. pmid:27121737
  26. 26. Jassim GA, Whitford DL, Hickey A, Carter B. Psychological interventions for women with non-metastatic breast cancer. Cochrane Database Syst Rev. 2015;5. CD008729 pmid:26017383
  27. 27. Linden W, Phillips MJ, Leclerc J. Psychological treatment of cardiac patients: a meta-analysis. Eur Heart J 2007;28 (24):2972–84. pmid:17984133
  28. 28. Linden W, Stossel C, Maurice J. Psychosocial interventions for patients with coronary artery disease: a meta-analysis. Arch Intern Med 1996;156 (7):745–52. pmid:8615707
  29. 29. Martire LM, Lustig AP, Schulz R, Miller GE, Helgeson VS. Is it beneficial to involve a family member? A meta-analysis of psychosocial interventions for chronic illness. Health Psychol 2004;23 (6):599–611. pmid:15546228
  30. 30. Mustafa M, Carson-Stevens A, Gillespie D, Edwards AG. Psychological interventions for women with metastatic breast cancer. Cochrane Database Syst Rev. 2013;6. CD004253 pmid:23737397
  31. 31. Oh PJ, Shin SR, Ahn HS, Kim HJ. Meta-analysis of psychosocial interventions on survival time in patients with cancer. Psychol Health 2016;31 (4):396–419. pmid:26518363
  32. 32. Whalley B, Rees K, Davies P, Bennett P, Ebrahim S, Liu Z, et al. Psychological interventions for coronary heart disease. Cochrane Database Syst Rev 2011;8:CD002902. pmid:21833943
  33. 33. Richards SH, Anderson L, Jenkinson CE, Whalley B, Rees K, Davies P. Psychological interventions for coronary heart disease. Cochrane Database Syst Rev. 2017;4. CD002902
  34. 34. Ski CF, Jelinek M, Jackson AC, Murphy BM, Thompson DR. Psychosocial interventions for patients with coronary heart disease and depression: A systematic review and meta-analysis. Eur J Cardiovasc Nurs 2016;15 (5):305–16. pmid:26475227
  35. 35. Smedslund G, Ringdal GI. Meta-analysis of the effects of psychosocial interventions on survival time in cancer patients. J Psychosom Res 2004;57 (2):123–31. pmid:15465065
  36. 36. Welton NJ, Caldwell DM, Adamopoulos E, Vedhara K. Mixed treatment comparison meta-analysis of complex interventions: psychological interventions in coronary heart disease. Am J Epidemiol 2009;169 (9):1158–65. pmid:19258485
  37. 37. Whalley B, Thompson DR, Taylor RS. Psychological interventions for coronary heart disease: cochrane systematic review and meta-analysis. Int J Behav Med 2014;21 (1):109–21. pmid:23179678
  38. 38. Xia Y, Tong G, Feng R, Chai J, Cheng J, Wang D. Psychosocial and behavioral interventions and cancer patient survival again: hints of an adjusted meta-analysis. Integr Cancer Ther 2014;13 (4):301–9. pmid:24613928
  39. 39. Albus C, Herrmann-Lingen C, Jensen K, Hackbusch M, Münch N, Kuncewicz C. Additional effects of psychological interventions on subjective and objective outcomes compared with exercise-based cardiac rehabilitation alone in patients with cardiovascular disease: a systematic review and meta-analysis. Eur J Prev Cardiol 2019;26 (10):1035–49. pmid:30857429
  40. 40. Hu Y, Liu T, Li F. Association between dyadic interventions and outcomes in cancer patients: a meta-analysis. Support Care Cancer 2019;27 (3):745–61. pmid:30604008
  41. 41. Das A, Bhaskar R, Schwarzer G, Silverman MG, Zieglar O, Bandyopadhyay D. Comparison of treatment options for depression in heart failure: a network meta-analysis. J Psychiatr Res 2019;108:7–23. pmid:30419488
  42. 42. Jeyanantham K, Kotecha D, Thanki D, Dekker R, Lane DA. Effects of cognitive behavioural therapy for depression in heart failure patients: a systematic review and meta-analysis. Heart Fail Rev 2017;22 (6):731–41. pmid:28733911
  43. 43. Mirosevic S, Jo B, Kraemer HC, Ershadi M, Neri E, Spiegel D. "Not just another meta-analysis": sources of heterogeneity in psychosocial treatment effect on cancer survival. Cancer Med 2019;8 (1):363–73. pmid:30600642
  44. 44. Moher D, Liberati A, Tetzlaff J, Altman DG. Prisma Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol 2009;62 (10):1006–12. pmid:19631508
  45. 45. Albus C, Theissen P, Hellmich M, Griebenow R, Wilhelm B, Aslim D. Long-term effects of a multimodal behavioral intervention on myocardial perfusion—a randomized controlled trial. Int J Behav Med 2009;16 (3):219–26. pmid:19424808
  46. 46. Andersen BL, Yang H, Farrar WB, Golden-Kreutz DM, Emery CF, Thornton LM. Psychologic intervention improves survival for breast cancer patients: a randomized clinical trial. Cancer 2008;113 (12):3450–8. pmid:19016270
  47. 47. Andryukhin A, Frolova E, Vaes B, Degryse J. The impact of a nurse-led care programme on events and physical and psychosocial parameters in patients with heart failure with preserved ejection fraction: a randomized clinical trial in primary care in Russia. Eur J Gen Pract 2010;16 (4):205–14. pmid:21073267
  48. 48. Aranda S, Schofield P, Weih L, Milne D, Yates P, Faulkner R. Meeting the support and information needs of women with advanced breast cancer: a randomised controlled trial. BJC 2006;95 (6):667–73. pmid:16967054
  49. 49. Armes J, Chalder T, Addington-Hall J, Richardson A, Hotopf M. A randomized controlled trial to evaluate the effectiveness of a brief, behaviorally oriented intervention for cancer-related fatigue. Cancer 2007;110 (6):1385–95. pmid:17661342
  50. 50. Arving C, Sjode PO, Bergh J, Hellbom M, Johansson B, Glimelius B. Individual psychosocial support for breast cancer patients: a randomized study of nurse versus psychologist interventions and standard care. Cancer Nurs 2007;30 (3):e10–9. pmid:17510577
  51. 51. Badger TA, Segrin C, Hepworth JT, Pasvogel A, Weihs K, Lopez AM. Telephone-delivered health education and interpersonal counseling improve quality of life for Latinas with breast cancer and their supportive partners. Psychooncology 2013;22 (5):1035–42. pmid:22573418
  52. 52. Bambauer KZ, Aupont O, Stone PH, Locke SE, Mullan MG, Colagiovanni J. The effect of a telephone counseling intervention on self-rated health of cardiac patients. Psychosom Med 2005;67 (4):539–45. pmid:16046365
  53. 53. Baucom DH, Porter LS, Kirby JS, Gremore TM, Wiesenthal N, Aldridge W. A couple-based intervention for female breast cancer. Psychooncology 2009;18 (3):276–83. pmid:18702064
  54. 54. Beresnevaite M. Exploring the benefits of group psychotherapy in reducing alexithymia in coronary heart disease patients: a preliminary study. Psychother Psychosom 2000;69 (3):117–22. pmid:10773774
  55. 55. Berger S, Schad T, von Wyl V, Ehlert U, Zellweger C, Furrer H. Effects of cognitive behavioral stress management on HIV-1 RNA, CD4 cell counts and psychosocial parameters of HIV-infected persons. AIDS 2008;22(6): 767–775. pmid:18356607
  56. 56. Björneklett H, Rosenblad A, Lindemalm C, Ojutkangas ML, Letocha H, Strang P. Long-term follow-up of a randomized study of support group intervention in women with primary breast cancer. J Psychosom Res 2013;74 (4):346–53. pmid:23497838
  57. 57. Blumenthal JA, Sherwood A, Babyak MA, Watkins LL, Waugh R, Georgiades A. 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 (13):1626–34. pmid:15811982
  58. 58. Blumenthal JA, Babyak MA, Carney RM, Keefe FJ, Davis RD, LaCaille RA. Telephone-based coping skills training for patients awaiting lung transplantation. J Consult Clin Psychol 2006;74 (3):535–44. pmid:16822110
  59. 59. Blumenthal JA, Emery CF, Smith PJ, Keefe FJ, Welty-Wolf K, Mabe S. The effects of a telehealth coping skills intervention on outcomes in chronic obstructive pulmonary disease: primary results from the INSPIRE-II study. Psychosom Med 2014;76 (8):581–92. pmid:25251888
  60. 60. Blumenthal JA, Sherwood A, Smith PJ, Watkins L, Mabe S, Kraus WE. Enhancing cardiac rehabilitation with stress management training: a randomized, clinical efficacy trial. Circulation 2016;133 (14):1341–50. pmid:27045127
  61. 61. Boesen EH, Karlsen R, Christensen J, Paaschburg B, Nielsen D, Bloch IS. Psychosocial group intervention for patients with primary breast cancer: a randomised trial. Eur J Cancer 2011;47 (9):1363–72. pmid:21458989
  62. 62. Burell G. Modification of the type A behavior pattern in post-myocardial infarction patients: a route to cardiac rehabilitation. Int J Behav Med 1994;1 (1):32–54. pmid:16250804
  63. 63. Burell G. Group psychotherapy in Project New Life: treatment of coronary-prone behaviors for patients who have had coronary artery bypass graft surgery. In: Allan R, Scheidt SS, editors. Heart & mind: the practice of cardiac psychology. Washington, DC: APA; 1996. pp. 291–310.
  64. 64. Chan JC, Sui Y, Oldenburg B, Zhang Y, Chung HH, Goggins W, et al. Effects of telephone-based peer support in patients with type 2 diabetes mellitus receiving integrated care: a randomized clinical trial. JAMA Int Med 2014;174 (6):972–81. pmid:24781960
  65. 65. Choi J, Kuo C-WJ, Sikorskii A, You M, Ren D, Sherwood PR, et al. Cognitive behavioral symptom management intervention in patients with cancer: survival analysis. Support Care Cancer 2012;20 (6):1243–50. pmid:21667048
  66. 66. Claesson M. Women’s hearts: ischaemic heart disease and stress management in women: Folkhälsa och klinisk medicin; Doctoral thesis, Umeå University. 2006. Available from: = diva2%3A144325
  67. 67. Classen CC, Kraemer HC, Blasey C, Giese-Davis J, Koopman C, Palesh OG, et al. Supportive–expressive group therapy for primary breast cancer patients: a randomized prospective multicenter trial. Psychooncology 2008;17 (5):438–47. pmid:17935144
  68. 68. Cockcroft A, Bagnall P, Heslop A, Andersson N, Heaton R, Batstone J, et al. Controlled trial of respiratory health worker visiting patients with chronic respiratory disability. Br Med J (Clin Res Ed) 1987;294 (6566):225–8. pmid:3101821
  69. 69. Colella TJ. The effect of a professionally-guided telephone peer support intervention on early recovery outcomes in men following coronary artery bypass graft surgery. Doctoral thesis, University of Calgary. 2009.
  70. 70. Cowan MJ, Pike KC, Budzynski HK. Psychosocial nursing therapy following sudden cardiac arrest: impact on two-year survival. Nurs Res 2001;50 (2):68–76. pmid:11302295
  71. 71. Creber RM, Patey M, Lee CS, Kuan A, Jurgens C, Riegel B. Motivational interviewing to improve self-care for patients with chronic heart failure: MITI-HF randomized controlled trial. Patient Educ Couns 2016;99 (2):256–64. pmid:26358533
  72. 72. Cunningham A, Edmonds C, Jenkins G, Pollack H, Lockwood G, Warr D. A randomized controlled trial of the effects of group psychological therapy on survival in women with metastatic breast cancer. Psychooncology 1998;7 (6):508–17. pmid:9885092
  73. 73. Cuong DD, Sonnerborg A, Van Tam V, El-Khatib Z, Santacatterina M, Marrone G, et al. Impact of peer support on virologic failure in HIV-infected patients on antiretroviral therapy—a cluster randomized controlled trial in Vietnam. BMC Infect Dis 2016;16:759. pmid:27986077
  74. 74. Edelman S, Lemon J, Bell DR, Kidman AD. Effects of group CBT on the survival time of patients with metastatic breast cancer. Psychooncology 1999;8 (6):474–81. pmid:10607980
  75. 75. Evans RL, Connis RT. Comparison of brief group therapies for depressed cancer patients receiving radiation treatment. Public Health Rep 1995;110 (3):306. pmid:7610222
  76. 76. Foley E, Baillie A, Huxter M, Price M, Sinclair E. Mindfulness-based cognitive therapy for individuals whose lives have been affected by cancer: a randomized controlled trial. Journal Cons Clin Psych 2010;78 (1):72. pmid:20099952
  77. 77. Fors A, Blanck E, Ali L, Ekberg-Jansson A, Fu M, Lindström KI. Effects of a person-centred telephone-support in patients with chronic obstructive pulmonary disease and/or chronic heart failure—A randomized controlled trial. PLoS ONE 2018;13 (8):e0203031. pmid:30169539
  78. 78. Frasure-Smith N, Lespérance F, Prince RH, Verrier P, Garber RA, Juneau M, et al. Randomised trial of home-based psychosocial nursing intervention for patients recovering from myocardial infarction. Lancet 1997;350 (9076):473–9. pmid:9274583
  79. 79. Friedman M, Thoresen CE, Gill JJ, Ulmer D, Powell LH, Price VA, et al. Alteration of type A behavior and its effect on cardiac recurrences in post myocardial infarction patients: summary results of the recurrent coronary prevention project. Am Heart J 1986;112 (4):653–65. pmid:3766365
  80. 80. Frizelle D, Lewin R, Kaye G, Hargreaves C, Hasney K, Beaumont N, et al. Cognitive-behavioural rehabilitation programme for patients with an implanted cardioverter defibrillator: A pilot study. British J Health Psych 2004;9 (3):381–92. pmid:15296684
  81. 81. Giese-Davis J, Collie K, Rancourt KM, Neri E, Kraemer HC, Spiegel D. Decrease in depression symptoms is associated with longer survival in patients with metastatic breast cancer: a secondary analysis. J Clin Oncol 2011;29 (4):413. pmid:21149651
  82. 82. Goodwin PJ, Leszcz M, Ennis M, Koopmans J, Vincent L, Guther H, et al. The effect of group psychosocial support on survival in metastatic breast cancer. NEJM 2001;345 (24):1719–26. pmid:11742045
  83. 83. Gulliksson M, Burell G, Vessby B, Lundin L, Toss H, Svärdsudd K. Randomized controlled trial of cognitive behavioral therapy vs standard treatment to prevent recurrent cardiovascular events in patients with coronary heart disease: secondary prevention in Uppsala primary health care project (SUPRIM). Arch Intern Med 2011;171 (2):134–40. pmid:21263103
  84. 84. Guo Z, Tang H, Li H, Tan S, Feng K, Huang Y, et al. The benefits of psychosocial interventions for cancer patients undergoing radiotherapy. Health Qual Life Outcomes 2013;11 (1):121. pmid:23866850
  85. 85. Härter M, Dirmaier J, Dwinger S, Kriston L, Herbarth L, Siegmund-Schultze E, et al. Effectiveness of telephone-based health coaching for patients with chronic conditions: a randomised controlled trial. PLoS ONE 2016 Sep 15;11 (9):e0161269. pmid:27632360
  86. 86. Hanssen TA, Nordrehaug JE, Eide GE, Hanestad BR. Does a telephone follow-up intervention for patients discharged with acute myocardial infarction have long-term effects on health-related quality of life? a randomised controlled trial. J Clin Nurs 2009;18 (9):1334–45. pmid:19220616
  87. 87. Hawkes AL, Patrao TA, Atherton J, Ware RS, Taylor CB, O’Neil A, et al. Effect of a telephone-delivered coronary heart disease secondary prevention program (proactive heart) on quality of life and health behaviours: primary outcomes of a randomised controlled trial. Int J Behav Med 2013;20 (3):413–24. pmid:23012159
  88. 88. Heisler M, Halasyamani L, Cowen ME, Davis MD, Resnicow K, Strawderman RL, et al. Randomized controlled effectiveness trial of reciprocal peer support in heart failure. Circ Heart Fail 2013;6 (2):246–53. pmid:23388114
  89. 89. Herrmann-Lingen C, Beutel ME, Bosbach A, Deter H-C, Fritzsche K, Hellmich M, et al. A stepwise psychotherapy intervention for reducing risk in coronary artery disease (SPIRR-CAD): results of an observer-blinded, multicenter, randomized trial in depressed patients with coronary artery disease. Psychosom Med 2016;78 (6):704–15. pmid:27187851
  90. 90. Hjelle EG, Bragstad LK, Kirkevold M, Zucknick M, Bronken BA, Martinsen R, et al. Effect of a dialogue-based intervention on psychosocial well-being 6 months after stroke in Norway: a randomized controlled trial. J Rehabil Med 2019;51 (8):557–65. pmid:31411337
  91. 91. Holtmaat K, van der Spek N, Lissenberg-Witte B, Breitbart W, Cuijpers P, Verdonck-de Leeuw I. Long-term efficacy of meaning-centered group psychotherapy for cancer survivors: 2-year follow-up results of a randomized controlled trial. Psychooncology 2020;29(4): 711–8. pmid:31876012
  92. 92. Horlick L, Cameron R, Firor W, Bhalerao U, Baltzan R. The effects of education and group discussion in the post myocardial infarction patient. J Psychosom Res 1984;28 (6):485–92. pmid:6520804
  93. 93. Hossain M, Harvey L, Rahman M, Bowden J, Islam M, Taylor V, et al. A pilot randomised trial of community-based care following discharge from hospital with a recent spinal cord injury in Bangladesh. Clin Rehabil 2017;31 (6):781–9. pmid:27311454
  94. 94. Hossain MS, Harvey LA, Islam MS, Rahman MA, Muldoon S, Biering-Sorensen F, et al. A community-based intervention to prevent serious complications and death 2 years after discharge in people with spinal cord injury in Bangladesh (CIVIC): a randomised trial. Spinal Cord. 2020. pmid:32917948
  95. 95. Høybye MT, Dalton SO, Deltour I, Bidstrup PE, Frederiksen K, Johansen C. Effect of internet peer-support groups on psychosocial adjustment to cancer: a randomised study. British J Cancer 2010;102 (9):1348–54. pmid:20424614
  96. 96. Hynninen MJ, Bjerke N, Pallesen S, Bakke PS, Nordhus IH. A randomized controlled trial of cognitive behavioral therapy for anxiety and depression in COPD. Respir Med 2010;104 (7):986–94. pmid:20346640
  97. 97. Ibfelt E, Rottmann N, Kjaer T, Høybye MT, Ross L, Frederiksen K, et al. No change in health behavior, BMI or self-rated health after a psychosocial cancer rehabilitation: results of a randomized trial. Acta Oncol 2011;50 (2):289–98. pmid:21231790
  98. 98. Ilnyckyj A, Farber J, Cheang M, Weinerman B. A randomized controlled trial of psychotherapeutic intervention in cancer patients. Annals Royal College Physicians Surgeons Canada 1994;27 (2):93–6.
  99. 99. Irvine J, Stanley J, Ong L, Cribbie R, Ritvo P, Katz J, et al. Acceptability of a cognitive behavior therapy intervention to implantable cardioverter defibrillator recipients. J Cog Psychotherapy 2010;24 (4):246–64.
  100. 100. Jaarsma T, van der Wal MH, Lesman-Leegte I, Luttik M-L, Hogenhuis J, Veeger NJ, et al. Effect of moderate or intensive disease management program on outcome in patients with heart failure: Coordinating Study Evaluating Outcomes of Advising and Counseling in Heart Failure (COACH). Arch Intern Med 2008;168 (3):316–24. pmid:18268174
  101. 101. Johansen SMB, Baumbach LA, Jørgensen T, Willaing I. Effekt af psykosocial rehabilitering efter akut myokardieinfarkt. En randomiseret undersøgelse. Ugeskr Laeger 2003;165 (34):3229–33.
  102. 102. Johansson T, Keller S, Winkler H, Ostermann T, Weitgasser R, Sönnichsen AC. Effectiveness of a peer support programme versus usual care in disease management of diabetes mellitus type 2 regarding improvement of metabolic control: a cluster-randomised controlled trial. J Diabetes Res 2016;2016:3248547. pmid:26858958
  103. 103. Jones D, West R. Psychological rehabilitation after myocardial infarction: multicentre randomised controlled trial. BMJ 1996;313 (7071):1517–21. pmid:8978226
  104. 104. Kissane DW, Grabsch B, Clarke DM, Smith GC, Love AW, Bloch S, et al. Supportive-expressive group therapy for women with metastatic breast cancer: survival and psychosocial outcome from a randomized controlled trial. Psychooncology 2007;16 (4):277–86. pmid:17385190
  105. 105. Kissane DW, Love A, Hatton A, Bloch S, Smith G, Clarke DM, et al. Effect of cognitive-existential group therapy on survival in early-stage breast cancer. J Clin Oncol 2004;22 (21):4255–60. pmid:15452189
  106. 106. Koertge J, Janszky I, Sundin Ö, Blom M, Georgiades A, Laszlo K, 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 (3):281–93. pmid:18067552
  107. 107. Kuchler T, Bestmann B, Rappat S, Henne-Bruns D, Wood-Dauphinee S. Impact of psychotherapeutic support for patients with gastrointestinal cancer undergoing surgery: 10-year survival results of a randomized trial. J Clin Oncol 2007;25 (19):2702–8. pmid:17602075
  108. 108. Lamers F, Jonkers CC, Bosma H, Kempen GI, Meijer JA, Penninx BW, et al. A minimal psychological intervention in chronically ill elderly patients with depression: a randomized trial. Psychother Psychosom 2010;79 (4):217–26. pmid:20424499
  109. 109. Lee V, Cohen SR, Edgar L, Laizner AM, Gagnon AJ. Meaning-making intervention during breast or colorectal cancer treatment improves self-esteem, optimism, and self-efficacy. Soc Sci Med 2006;62 (12):3133–45. pmid:16413644
  110. 110. Lewin RJ, Coulton S, Frizelle DJ, Kaye G, Cox H. A brief cognitive behavioural preimplantation and rehabilitation programme for patients receiving an implantable cardioverter-defibrillator improves physical health and reduces psychological morbidity and unplanned readmissions. Heart 2009;95 (1):63–9. pmid:18070951
  111. 111. Liljeroos M, Ågren S, Jaarsma T, Årestedt K, Strömberg A. Long term follow-up after a randomized integrated educational and psychosocial intervention in patient-partner dyads affected by heart failure. PLoS ONE 2015;10 (9):e0138058. pmid:26406475
  112. 112. Lin C, Yaseri M, Pakpour AH, Malm D, Broström A, Fridlund B, et al. Can a multifaceted intervention including motivational interviewing improve medication adherence, quality of life, and mortality rates in older patients undergoing coronary artery bypass surgery? a multicenter, randomized controlled trial with 18-month follow-up. Drugs Aging 2017;34 (2):143–56. pmid:28004259
  113. 113. Lindley RI, Anderson CS, Billot L, Forster A, Hackett ML, Harvey LA, et al. Family-led rehabilitation after stroke in India (ATTEND): a randomised controlled trial. Lancet 2017;390 (10094):588–99. pmid:28666682
  114. 114. Liu W, Gong Y, Gong Y. Effect evaluation of continuing care and psychological intervention in convalescent phase of stroke. Int J Clin Exp Med 2018;11 (3):2636–41.
  115. 115. May AM, Korstjens I, van Weert E, van den Borne B, Hoekstra-Weebers JE, van der Schans CP, et al. Long-term effects on cancer survivors’ quality of life of physical training versus physical training combined with cognitive-behavioral therapy: results from a randomized trial. Support Care Cancer 2009;17 (6):653–63. pmid:18953578
  116. 116. Mayou RA, Thompson DR, Clements A, Davies CH, Goodwin SJ, Normington K, et al. Guideline-based early rehabilitation after myocardial infarction: A pragmatic randomised controlled trial. J Psychosom Res 2002;52 (2):89–95. pmid:11832254
  117. 117. McArdle JM, George WD, McArdle CS, Smith DC, Moodie AR, Hughson AM, et al. Psychological support for patients undergoing breast cancer surgery: a randomised study. BMJ 1996;312 (7034):813–6. pmid:8608288
  118. 118. McKinley S, Dracup K, Moser DK, Riegel B, Doering LV, Meischke H, et al. The effect of a short one-on-one nursing intervention on knowledge, attitudes and beliefs related to response to acute coronary syndrome in people with coronary heart disease: a randomized controlled trial. Int J Nurs Stud 2009;46 (8):1037–46. pmid:19243778
  119. 119. Meneses KD, McNees P, Loerzel VW, Su X, Zhang Y, Hassey LA. editors. Transition from treatment to survivorship: effects of a psychoeducational intervention on quality of life in breast cancer survivors. Oncol Nurs Forum 2007 Sep;34 (5):1007–16. pmid:17878129
  120. 120. Minet LR, Wagner L, Lønvig E, Hjelmborg J, Henriksen J. The effect of motivational interviewing on glycaemic control and perceived competence of diabetes self-management in patients with type 1 and type 2 diabetes mellitus after attending a group education programme: a randomised controlled trial. Diabetologia 2011;54 (7):1620–9. pmid:21455729
  121. 121. Nakimuli-Mpungu E, Wamala K, Okello J, Alderman S, Odokonyero R, Mojtabi R, et al. Group support psychotherapy for depression treatment in people with HIV/AIDS in northern Uganda: a single-centre randomised controlled trial. Lancet HIV 2015;2 (5):e190–9. pmid:26423001
  122. 122. Nakimuli-Mpungu E, Musisi S, Wamala K, Okello J, Ndyanabangi S, Birungi J, et al. Effectiveness and cost-effectiveness of group support psychotherapy delivered by trained lay health workers for depression treatment among people with HIV in Uganda: a cluster-randomised trial. Lancet Glob Health 2020;8 (3):e387–98. pmid:32035035
  123. 123. Oranta O, Luutonen S, Salokangas RK, Vahlberg T, Leino-Kilpi H. The outcomes of interpersonal counselling on depressive symptoms and distress after myocardial infarction. Nord J Psychiatry 2010;64 (2):78–86. pmid:19919291
  124. 124. Orth-Gomér K, Schneiderman N, Wang H-X, Walldin C, Blom M, Jernberg T. Stress reduction prolongs life in women with coronary disease: the Stockholm Women’s Intervention Trial for Coronary Heart Disease (SWITCHD). Circ Cardiovasc Qual Outcomes 2009;2 (1):25–32. pmid:20031809
  125. 125. Powell LH, Calvin JE, Richardson D, Janssen I. Mendes de Leon CF, Flynn KJ, et al. Self-management counseling in patients with heart failure: the heart failure adherence and retention randomized behavioral trial. JAMA 2010;304 (12):1331–8. pmid:20858878
  126. 126. Pristipino C, Roncella A, Pasceri V, Speciale G. Short-term psychotherapy in acute myocardial infarction (STEP-IN-AMI) trial: final results. Am J Med. 2019;132 (5):639–46. e5. pmid:30659815
  127. 127. Ries AL, Kaplan RM, Limberg TM, Prewitt LM. Effects of pulmonary rehabilitation on physiologic and psychosocial outcomes in patients with chronic obstructive pulmonary disease. Ann Intern Med 1995;122 (11):823–32. pmid:7741366
  128. 128. Rodin G, Lo C, Rydall A, Shnall J, Malfitano C, Chiu A, et al. Managing cancer and living meaningfully (CALM): a randomized controlled trial of a psychological intervention for patients with advanced cancer. J Clin Oncol 2018;36 (23):2422–32. pmid:29958037
  129. 129. Ross L et al. No effect on survival of home psychosocial intervention in a randomized study of Danish colorectal cancer patients. Psychooncology 2009;18 (8):875–85. pmid:19137506
  130. 130. Saab PG, Bang H, Williams RB, Powell LH, Schneiderman N, Thoreson C, et al. The impact of cognitive behavioral group training on event-free survival in patients with myocardial infarction: the ENRICHD experience. J Psychosom Res 2009;67 (1):45–56. pmid:19539818
  131. 131. Salem H, Johansen C, Schmiegelow K, Falck Winther J, Wehner P, Hasle H, et al. FAMily-Oriented Support (FAMOS): development and feasibility of a psychosocial intervention for families of childhood cancer survivors. Acta Oncol 2017;56 (2):367–74. pmid:28080169
  132. 132. Sebregts EH, Falger PR, Appels A, Kester AD, Bär FW. Psychological effects of a short behavior modification program in patients with acute myocardial infarction or coronary artery bypass grafting: a randomized controlled trial. J Psychosom Res 2005;58 (5):417–24. pmid:16026656
  133. 133. Simpson JSA, Carlson LE, Trew ME. Effect of group therapy for breast cancer on healthcare utilization. Cancer Pract 2001;9 (1):19–26. pmid:11879269
  134. 134. Sinclair AJ, Conroy SP, Davies M, Bayer AJ. Post-discharge home-based support for older cardiac patients: a randomised controlled trial. Age Ageing 2005;34 (4):338–43. pmid:15955757
  135. 135. Sjobom P, Philips A, Bell F, Werr J, Landstom S. Transferability of innovative care models: Results from a large scale telephone based health coaching RCT. Int J Integr Care 2017;17 (5):a465.
  136. 136. Smeulders ES, van Haastregt JC, Ambergen T, Uszko-Lencer N, Janssen-Boyne J, Gorgels A, et al. Nurse-led self-management group programme for patients with congestive heart failure: randomized controlled trial. J Adv Nurs 2010;66 (7):1487–99. pmid:20492026
  137. 137. Smith S, Paul G, Kelly A, Whitford DL, O’Shea E, O’Dowd T. Peer support for patients with type 2 diabetes: cluster randomised controlled trial. BMJ 2011;342:d715. pmid:21324992
  138. 138. Spiegel D, Butler LD, Giese-Davis J, Koopman C, Miller E, DiMiceli S, et al. Effects of supportive-expressive group therapy on survival of patients with metastatic breast cancer: a randomized prospective trial. Cancer 2007;110 (5):1130–8. pmid:17647221
  139. 139. Stagl JM, Lechner SC, Carver CS, Bouchard LC, Gudenkauf LM, Jutagir DR, et al. A randomized controlled trial of cognitive-behavioral stress management in breast cancer: survival and recurrence at 11-year follow-up. Breast Cancer Res Treat 2015;154 (2):319–28. pmid:26518021
  140. 140. Steel JL, Nadeau K, Olek M, Carr BI. Preliminary results of an individually tailored psychosocial intervention for patients with advanced hepatobiliary carcinoma. J Psychosoc Oncol 2007;25 (3):19–42. pmid:19341012
  141. 141. Strömberg A, Mårtensson J, Fridlund B, Levin L-Å, Karlsson J-E, Dahlström U. Nurse-led heart failure clinics improve survival and self-care behaviour in patients with heart failure: results from a prospective, randomised trial. Eur Heart J 2003;24 (11):1014–23. pmid:12788301
  142. 142. Thompson DR. Effect of in-hospital counseling on knowledge in myocardial infarction patients and spouses. Patient Ed Counseling 1991;18 (2):171–7.
  143. 143. van der Meulen IC, May AM, Ros WJ, Oosterom M, Hordik G, Koole R, et al. One-year effect of a nurse-led psychosocial intervention on depressive symptoms in patients with head and neck cancer: a randomized controlled trial. Oncologist 2013;18 (3):336. pmid:23429740
  144. 144. Vahedian-Azimi A, Miller AC, Hajiesmaieli M, Kangasniemi M, Alhani F, Jelvehmoghaddam H, et al. Cardiac rehabilitation using the Family-Centered Empowerment Model versus home-based cardiac rehabilitation in patients with myocardial infarction: a randomised controlled trial. Open Heart 2016;3 (1):e000349. pmid:27110376
  145. 145. van der Spek N, Jansen F, Holtmaat K, Vos J, Breitbart W, van Uden-Kraan CF, et al. Cost-utility analysis of meaning-centered group psychotherapy for cancer survivors. Psychooncology 2018;27 (7):1772–9. pmid:29624807
  146. 146. Wade DM, Mouncey PR, Richards-Belle A, Wulff J, Harrison DA, Sadique MZ, et al. Effect of a nurse-led preventive psychological intervention on symptoms of posttraumatic stress disorder among critically ill patients: a randomized clinical trial. JAMA 2019;321 (7):665–75. pmid:30776295
  147. 147. Xavier D, Gupta R, Kamath D, Sigamani A, Devereaux PJ, George N, et al. Community health worker-based intervention for adherence to drugs and lifestyle change after acute coronary syndrome: a multicentre, open, randomised controlled trial. Lancet Diabetes Endocrinol 2016;4 (3):244–53. pmid:26857999
  148. 148. Duval S, Tweedie R. A nonparametric “trim and fill” method of accounting for publication bias in meta-analysis. J Am Stat Assoc 2000;95 (449):89–98.
  149. 149. McQueen J, Howe TE, Allan L, Mains D, Hardy V. Brief interventions for heavy alcohol users admitted to general hospital wards. Cochrane Database Syst Rev. 2011;8. CD005191 pmid:21833953
  150. 150. Wu W, Guo F, Ye J, Li Y, Shi D, Fang D, et al. Pre-and post-diagnosis physical activity is associated with survival benefits of colorectal cancer patients: a systematic review and meta-analysis. Oncotarget 2016;7 (32):52095. pmid:27437765
  151. 151. Taylor RS, Brown A, Ebrahim S, Jolliffe J, Noorani H, Rees K, et al. Exercise-based rehabilitation for patients with coronary heart disease: systematic review and meta-analysis of randomized controlled trials. Amer J Med 2004;116 (10):682–92. pmid:15121495
  152. 152. Ma C, Avenell A, Bolland M, Hudson J, Stewart F, Robertson C, et al. Effects of weight loss interventions for adults who are obese on mortality, cardiovascular disease, and cancer: systematic review and meta-analysis. BMJ 2017;j4849:359. pmid:29138133
  153. 153. Kritchevsky SB, Beavers KM, Miller ME, Shea MK, Houston DK, Kitzman DW, et al. Intentional weight loss and all-cause mortality: a meta-analysis of randomized clinical trials. PLoS ONE 2015;10 (3):e0121993. pmid:25794148
  154. 154. Mons U, Müezzinler A, Gellert C, Schöttker B, Abnet CC, Bobak M, et al. Impact of smoking and smoking cessation on cardiovascular events and mortality among older adults: meta-analysis of individual participant data from prospective cohort studies of the CHANCES consortium. BMJ 2015;h1551:350. pmid:25896935
  155. 155. Taylor RS, Walker S, Smart NA, Piepoli MF, Warren FC, Ciani O, et al. Impact of exercise rehabilitation on exercise capacity and quality-of-life in heart failure: individual participant meta-analysis. J Am Coll Cardiol 2019;73 (12):1430–43. pmid:30922474
  156. 156. Calman L, Beaver K, Hind D, Lorigan P, Roberts C, Lloyd-Jones M. Survival benefits from follow-up of patients with lung cancer: a systematic review and meta-analysis. J Thorac Oncol 2011;6 (12):1993–2004. pmid:21892108
  157. 157. Xing MY, Xu SZ, Shen P. Effect of low-fat diet on breast cancer survival: a meta-analysis. Asian Pac J Cancer Prev 2014;15 (3):1141–4. pmid:24606431
  158. 158. Mohanan P, Kamath A. Family support for reducing morbidity and mortality in people with HIV/AIDS. Cochrane Database Syst Rev 2009;3. CD006046 pmid:19588378
  159. 159. Yang YC, Boen C, Gerken K, Li T, Schorpp K, Harris KM. Social relationships and physiological determinants of longevity across the human life span. Proc Natl Acad Sci U S A 2016;113 (3):578–83. pmid:26729882
  160. 160. Arthur HM. Depression, isolation, social support, and cardiovascular disease in older adults. J Cardiovasc Nurs 2006;21 (5 Suppl 1):S2–7.
  161. 161. Valtorta NK, Kanaan M, Gilbody S, Ronzi S, Hanratty B. Loneliness and social isolation as risk factors for coronary heart disease and stroke: systematic review and meta-analysis of longitudinal observational studies. Heart 2016;102 (13):1009–16. pmid:27091846
  162. 162. Lane DA, Millane TA, Lip GY. Psychological interventions for depression in adolescent and adult congenital heart disease. Cochrane Database Syst Rev 2013;10. CD004372 pmid:24163137
  163. 163. Uchino BN. Social support and health: a review of physiological processes potentially underlying links to disease outcomes. J Behav Med 2006;29 (4):377–87. pmid:16758315
  164. 164. Collins LM, Baker TB, Mermelstein RJ, Piper ME, Jorenby DE, Smith SS, et al. The multiphase optimization strategy for engineering effective tobacco use interventions. Ann Behav Med 2011;41 (2):208–26. pmid:21132416
  165. 165. Collins LM, Murphy SA, Strecher V. The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. Am J Prev Med 2007;32 (5 Suppl):S112–8.
  166. 166. Shaw JG, Farid M, Noel-Miller C, Joseph N, Houser A, Asch SM, et al. Social isolation and medicare spending: among older adults, objective social isolation increases expenditures while loneliness does not. J Aging Health 2017;29 (7):1119–43. pmid:29545676
  167. 167. Hawker M, Romero-Ortuno R. Social determinants of discharge outcomes in older people admitted to a geriatric medicine ward. J Frailty Aging 2016;5 (2):118–20. pmid:27224503
  168. 168. Holt-Lunstad J, Robles TF, Sbarra DA. Advancing social connection as a public health priority in the United States. Am Psychol 2017;72 (6):517–30. pmid:28880099