Cognitive behavior therapy for health anxiety: systematic review and meta-analysis of clinical efficacy and health economic outcomes

Axelsson, Erland; Hedman‐Lagerlöf, Erik

doi:10.1080/14737167.2019.1703182

Cited by 61 publications

(38 citation statements)

References 68 publications

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“…There is some evidence on the cost-effectiveness of eHealth interventions for depression and anxiety in primary care settings when compared to care as usual and waiting list control conditions [51] as well as for a range of mental disorders when compared to conventional CBT [112,113]. However, as only a few systematic reviews have systematically investigated the cost-effectiveness of digital interventions to date, these findings should be interpreted with caution.…”

Section: Cost-effectivenessmentioning

confidence: 99%

Evidence Synthesis of Digital Interventions to Mitigate the Negative Impact of the COVID-19 Pandemic on Public Mental Health: Rapid Meta-review

Rauschenberg¹,

Schick²,

Hirjak³

et al. 2021

J Med Internet Res

169

122

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Background Accumulating evidence suggests the COVID-19 pandemic has negative effects on public mental health. Digital interventions that have been developed and evaluated in recent years may be used to mitigate the negative consequences of the pandemic. However, evidence-based recommendations on the use of existing telemedicine and internet-based (eHealth) and app-based mobile health (mHealth) interventions are lacking. Objective The aim of this study was to investigate the theoretical and empirical base, user perspective, safety, effectiveness, and cost-effectiveness of digital interventions related to public mental health provision (ie, mental health promotion, prevention, and treatment of mental disorders) that may help to reduce the consequences of the COVID-19 pandemic. Methods A rapid meta-review was conducted. The MEDLINE, PsycINFO, and CENTRAL databases were searched on May 11, 2020. Study inclusion criteria were broad and considered systematic reviews and meta-analyses that investigated digital tools for health promotion, prevention, or treatment of mental health conditions and determinants likely affected by the COVID-19 pandemic. Results Overall, 815 peer-reviewed systematic reviews and meta-analyses were identified, of which 83 met the inclusion criteria. Our findings suggest that there is good evidence on the usability, safety, acceptance/satisfaction, and effectiveness of eHealth interventions. Evidence on mHealth apps is promising, especially if social components (eg, blended care) and strategies to promote adherence are incorporated. Although most digital interventions focus on the prevention or treatment of mental disorders, there is some evidence on mental health promotion. However, evidence on process quality, cost-effectiveness, and long-term effects is very limited. Conclusions There is evidence that digital interventions are particularly suited to mitigating psychosocial consequences at the population level. In times of physical distancing, quarantine, and restrictions on social contacts, decision makers should develop digital strategies for continued mental health care and invest time and efforts in the development and implementation of mental health promotion and prevention programs.

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Section: Cost-effectivenessmentioning

confidence: 99%

Evidence Synthesis of Digital Interventions to Mitigate the Negative Impact of the COVID-19 Pandemic on Public Mental Health: Rapid Meta-review

Rauschenberg¹,

Schick²,

Hirjak³

et al. 2021

J Med Internet Res

169

122

View full text Add to dashboard Cite

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“…Severe health anxiety (SHA) is especially expected to increase, due to its association with COVID‐19‐related anxieties and public health measures (Asmundson & Taylor, 2020; Jungmann & Witthöft, 2020). Cognitive–behavioural therapy (CBT) is a well‐evidenced frontline treatment for SHA, which is evidenced as effective both face‐to‐face and remotely (Axelsson & Hedman‐Lagerlöf, 2019; Cooper, Gregory, Walker, Lambe, & Salkovskis, 2017). This includes evidence of the clinical‐ and cost‐effectiveness of remote‐CBT (rCBT) for SHA delivered over video conferencing (Morriss et al, 2019).…”

Section: Predicting Outcomes and Sudden Gains From Initial In‐session Interactions During Remote Cognitive–behavioural Therapy For Severementioning

confidence: 99%

Predicting outcomes and sudden gains from initial in‐session interactions during remote cognitive–behavioural therapy for severe health anxiety

Malins

Moghaddam

Morriss

et al. 2021

Clin Psychology and Psychoth

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There has been a dramatic increase in remote psychotherapy since the onset of the COVID‐19 crisis. There is also expected to be an increase in mental health problems in the wake of the COVID‐19 pandemic. An increase in severe health anxiety (SHA) is particularly anticipated, for which cognitive–behavioural therapy (CBT) is a frontline treatment. However, it is unclear what interaction types are associated with outcome‐improvement in remote‐CBT (rCBT) for SHA. This study aimed to identify interaction types that predict outcomes and sudden gains in rCBT for SHA using initial therapy session content. Forty‐eight participants in rCBT for SHA had interactions at their first sessions categorized and rated in terms of patient activation: an individual's confidence and ability to manage their health. Multilevel modelling assessed whether early interaction types predicted session‐by‐session wellbeing. For participants experiencing sudden gains (n = 12) interactions at the session directly prior to the gain were similarly categorized and rated. The scores were then compared with ratings for the preceding session. A smaller proportion of early sessions was taken up with problem descriptions among those with greater outcome improvements. There was also a significant reduction in the proportion of the session spent describing problems in the session directly prior to a sudden gain, as compared with the previous session. Conversely, clients with better outcomes made more positive evaluations of themselves and therapy, noticed more positive changes and made more contributions to structuring interactions at initial sessions. Specific early interaction types predict session‐by‐session outcomes and precede sudden gains in rCBT for SHA.

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“…It is estimated that 3.4% of the total population and 20% of patients referred to health clinics suffer from HA (2,3). Persistent and excessive fear or extreme anxiety about the disease not only leads to suffering and dysfunction, but also causes a significant increase in health and social costs (4). It has been found that the cost of healthcare for HA patients referring to physicians is 41%-78% higher than patients who refer to physicians with a specific disease (4), which indicates the HA-related financial burden imposed on the individual and society.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Health Anxiety in Healthcare Workers During Coronavirus Disease 2019 (COVID-19) Pandemic

et al. 2021

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Background: Considering the importance of health anxiety (HA) and its impact on the management of a pandemic, the present study investigated HA among healthcare workers during coronavirus disease 2019 (COVID-19) pandemic. Materials and Methods: The sample of this cross-sectional study consisted of 220 healthcare staff working in health centers and hospitals in Iran. Participants were selected using convenience sampling method. The data collection tool was a two-part questionnaire. The first part contained demographic information and the second part included a health anxiety questionnaire (HAQ). This questionnaire was provided to the target community through social media and the required data was collected. Data analysis was carried out using IBM SPSS Statistics for Windows, version 21 (IBM Corp., Armonk, N.Y., USA). Results: In the present study, out of 220 participants 128 (58.2%) were employed in health centers and 92 (41.8%) in hospitals. The mean HA score was 17.36 ± 7.66. Moreover, the mean HA scores in health center and hospital personnel was 17.81± 8.02 and 16.52 ± 6.78, respectively, which were not significantly different (P=0.217). The results showed that exercise and chronic disease are significant predictors of HA (P=0.0001 and P=0.043, respectively). Conclusion: The HA level was very high in healthcare personnel during the COVID-19 pandemic. This study showed that physical activity and having an underlying disease are important predictors of HA. Hence, in order to reduce the level of anxiety in healthcare personnel, it is recommended to plan regular physical activity programs and make changes in the work schedule of personnel with underlying disease.

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Cognitive behavior therapy for health anxiety: systematic review and meta-analysis of clinical efficacy and health economic outcomes

Cited by 61 publications

References 68 publications

Evidence Synthesis of Digital Interventions to Mitigate the Negative Impact of the COVID-19 Pandemic on Public Mental Health: Rapid Meta-review

Evidence Synthesis of Digital Interventions to Mitigate the Negative Impact of the COVID-19 Pandemic on Public Mental Health: Rapid Meta-review

Predicting outcomes and sudden gains from initial in‐session interactions during remote cognitive–behavioural therapy for severe health anxiety

Evaluation of Health Anxiety in Healthcare Workers During Coronavirus Disease 2019 (COVID-19) Pandemic

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