Completeness of Intervention Reporting of Clinical Trials Published in Highly Ranked Obesity Journals

Rauh, Shelby; Turner, D’Arcy; Jellison, Samuel; Allison, David B.; Fugate, Colony; Foote, Greyson; Vassar, Matt

doi:10.1002/oby.23054

Cited by 7 publications

(4 citation statements)

References 28 publications

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“…Second, the coding of the RGBs relied upon authors to clearly provide information upon which to judge their presence/absence. A recent study found only 12 of 200 randomized controlled trials (RCT) provided sufficient information about who delivered the intervention 39 . Other aspects of intervention reporting, such as the location of where the intervention occurred, are also poorly detailed in published RCTs.…”

Section: Discussionmentioning

confidence: 99%

“…A recent study found only 12 of 200 randomized controlled trials (RCT) provided sufficient information about who delivered the intervention. 39 Other aspects of intervention reporting, such as the location of where the intervention occurred, are also poorly detailed in published RCTs. The ambiguousness or absence of this information makes identification of the RGBs difficult.…”

Section: Acknowledgmentsmentioning

confidence: 99%

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Impact of risk of generalizability biases in adult obesity interventions: A meta‐epidemiological review and meta‐analysis

et al. 2021

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Biases introduced in early-stage studies can lead to inflated early discoveries. The risk of generalizability biases (RGBs) identifies key features of feasibility studies that, when present, lead to reduced impact in a larger trial. This meta-study examined the influence of RGBs in adult obesity interventions. Behavioral interventions with a published feasibility study and a larger scale trial of the same intervention (e.g., pairs) were identified. Each pair was coded for the presence of RGBs. Quantitative outcomes were extracted. Multilevel meta-regression models were used to examine the impact of RGBs on the difference in the effect size (ES, standardized mean difference) from pilot to larger scale trial. A total of 114 pairs, representing 230 studies, were identified. Overall, 75% of the pairs had at least one RGB present. The four most prevalent RGBs were duration (33%), delivery agent (30%), implementation support (23%), and target audience (22%) bias. The largest reductions in the ES were observed in pairs where an RGB was present in the pilot and removed in the larger scale trial (average reduction ES À0.41, range À1.06 to 0.01), compared with pairs without an RGB (average reduction ES À0.15, range À0.18 to À0.14). Eliminating RGBs during early-stage testing may result in improved evidence.

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Section: Discussionmentioning

confidence: 99%

Section: Acknowledgmentsmentioning

confidence: 99%

Impact of risk of generalizability biases in adult obesity interventions: A meta‐epidemiological review and meta‐analysis

et al. 2021

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“…Previous obesity research has examined the completeness of intervention reporting, 29 yet no study has analysed the relevance of specific taxonomies in obesity literature. Prior to the creation of behavioural change taxonomies, there was no standardization of weight loss techniques and inconsistent reporting of results.…”

Section: Introductionmentioning

confidence: 99%

Use of behavioural change taxonomies in systematic reviews and meta‐analyses regarding obesity management

et al. 2022

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Summary We investigated the prevalence of behavioural change taxonomies in systematic reviews and meta‐analyses related to obesity management. In addition, we analysed the funding sources, author conflicts of interest statements, risk of bias, and favorability of the results in such studies to determine if there was a relationship between methodological quality and taxonomy use. We searched several databases including MEDLINE, Epistemonikos, Cochrane EDSR, Pubmed and Embase for systematic reviews and meta‐analyses regarding the behavioural treatment of obesity. Screening and data extraction was performed in a masked, duplicate fashion. We performed statistical analyses to determine any significant association between use of taxonomy and study characteristics. Fifteen (of 186; 8.06%) systematic reviews used a taxonomy—nine used the BCTTv1, three used OXFAB, two used the CALO‐RE and one used “Taxonomy of choice architecture techniques.” Most interventions that referenced a taxonomy were self‐mediated (6/60, 10%). Behavioural change taxonomies were mentioned in 10 (of 87, 11.49%) studies with a public funding source. Of the studies with favourable results, 14 studies (of 181, 7.73%) referred to a taxonomy. We found no statistically significant relationships between use of taxonomy and study characteristics. We found that systematic reviews regarding the management of obesity rarely mention a behavioural change taxonomy. Given the global burden of obesity, it is crucial that behavioural change techniques are reproducible and translatable. We recommend that researchers look further into how taxonomies affect the quality and reproducibility of behavioural interventions in an effort to improve patient outcomes.

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“…The reporting of source characteristics within intervention reports using these brief guidelines is often poor. For example, specification of intervention providers was found to be one of four areas requiring improvement in obesity interventions ( Rauh et al , 2021 ). We currently lack a method for specifying characteristics of an intervention’s source within behaviour change interventions.…”

Section: Introductionmentioning

confidence: 99%

Specifying who delivers behaviour change interventions: development of an Intervention Source Ontology

et al. 2021

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Background: Identifying how behaviour change interventions are delivered, including by whom, is key to understanding intervention effectiveness. However, information about who delivers interventions is reported inconsistently in intervention evaluations, limiting communication and knowledge accumulation. This paper reports a method for consistent reporting: The Intervention Source Ontology. This forms one part of the Behaviour Change Intervention Ontology, which aims to cover all aspects of behaviour change interventions. Methods: The Intervention Source Ontology was developed following methods for ontology development and maintenance used in the Human Behaviour-Change Project, with seven key steps: 1) define the scope of the ontology, 2) identify key entities and develop their preliminary definitions by reviewing existing classification systems (top-down) and reviewing 100 behaviour change intervention reports (bottom-up), 3) refine the ontology by piloting the preliminary ontology on 100 reports, 4) stakeholder review by 34 behavioural science and public health experts, 5) inter-rater reliability testing of annotating intervention reports using the ontology, 6) specify ontological relationships between entities and 7) disseminate and maintain the Intervention Source Ontology. Results: The Intervention Source Ontology consists of 140 entities. Key areas of the ontology include Occupational Role of Source, Relatedness between Person Source and the Target Population, Sociodemographic attributes and Expertise. Inter-rater reliability was found to be 0.60 for those familiar with the ontology and 0.59 for those unfamiliar with it, levels of agreement considered ‘acceptable’. Conclusions: Information about who delivers behaviour change interventions can be reliably specified using the Intervention Source Ontology. For human-delivered interventions, the ontology can be used to classify source characteristics in existing behaviour change reports and enable clearer specification of intervention sources in reporting.

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Completeness of Intervention Reporting of Clinical Trials Published in Highly Ranked Obesity Journals

Cited by 7 publications

References 28 publications

Impact of risk of generalizability biases in adult obesity interventions: A meta‐epidemiological review and meta‐analysis

Impact of risk of generalizability biases in adult obesity interventions: A meta‐epidemiological review and meta‐analysis

Use of behavioural change taxonomies in systematic reviews and meta‐analyses regarding obesity management

Specifying who delivers behaviour change interventions: development of an Intervention Source Ontology

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