Transparent data-sharing is a powerful signal of study quality in pregnancy research

A global study led by researchers at the School of Clinical Sciences at Monash Health, Monash University, has found that clinical trials that share their raw data are significantly more likely to be trustworthy and well-conducted, raising fresh concerns about how evidence is selected and used in medical guidelines.

The research, published in eClinicalMedicine, analyzed 265 randomized controlled trials (RCTs) involving more than 65,000 women. These trials focused on different methods of labor induction, one of the most common interventions in maternity care.

But according to lead author Dr. Malitha Patabendige, Obstetrics and Gynecology Registrar at Monash Health and Ph.D. candidate at the School of Clinical Sciences at Monash Health, Monash University, this study wasn’t designed to answer whether or not someone should be induced. Instead, it looked at how we decide which studies to trust and how better transparency could lead to better care.

“As clinicians and patients, we make decisions based on research. But not all research is equally trustworthy,” said Dr. Patabendige. “We found that trials which shared their original datasets were far more likely to be well-designed, transparent, and reliable.”

The team used a tool called the TRACT checklist to evaluate each study across seven key areas, including ethical approvals, reporting quality, realistic timeframes and consistency of results. They also reviewed raw datasets, where available, to confirm that what was published matched the underlying data.

Only 24% of trials shared their original data. Of those, 84% met trustworthiness criteria. By contrast, more than half of the trials that didn’t share data raised serious concerns, including inconsistencies, missing information or red flags in study design.

“What we’ve built is essentially a filter for evidence—a way to separate strong, transparent trials from those that are harder to trust,” Dr. Patabendige said. “That’s important, not just in pregnancy care, but in any field where clinical guidelines rely on published studies.”

Labor induction, used to stimulate labor before it begins naturally, affects more than 1 in 3 births in Australia. While it is a safe and often necessary intervention, there’s ongoing debate about when and how it should be used. That makes the quality of the underlying evidence especially important—but this study shows that some trials included in current reviews may not be as reliable as they seem.

The authors emphasize that data sharing itself doesn’t guarantee quality, but that it allows deeper scrutiny and is one of the clearest signals that a study was conducted with scientific integrity.

They are calling for greater support and stronger expectations for sharing de-identified trial data, particularly in fields like pregnancy and women’s health where evidence directly influences clinical care.

“We need to stop assuming that all published research is equally sound,” Dr. Patabendige said. “Sharing data strengthens science, rebuilds trust, and ultimately leads to better decisions for patients.”

A global study led by researchers at the School of Clinical Sciences at Monash Health, Monash University, has found that clinical trials that share their raw data are significantly more likely to be trustworthy and well-conducted, raising fresh concerns about how evidence is selected and used in medical guidelines.

The research, published in eClinicalMedicine, analyzed 265 randomized controlled trials (RCTs) involving more than 65,000 women. These trials focused on different methods of labor induction, one of the most common interventions in maternity care.

But according to lead author Dr. Malitha Patabendige, Obstetrics and Gynecology Registrar at Monash Health and Ph.D. candidate at the School of Clinical Sciences at Monash Health, Monash University, this study wasn’t designed to answer whether or not someone should be induced. Instead, it looked at how we decide which studies to trust and how better transparency could lead to better care.

“As clinicians and patients, we make decisions based on research. But not all research is equally trustworthy,” said Dr. Patabendige. “We found that trials which shared their original datasets were far more likely to be well-designed, transparent, and reliable.”

The team used a tool called the TRACT checklist to evaluate each study across seven key areas, including ethical approvals, reporting quality, realistic timeframes and consistency of results. They also reviewed raw datasets, where available, to confirm that what was published matched the underlying data.

Only 24% of trials shared their original data. Of those, 84% met trustworthiness criteria. By contrast, more than half of the trials that didn’t share data raised serious concerns, including inconsistencies, missing information or red flags in study design.

“What we’ve built is essentially a filter for evidence—a way to separate strong, transparent trials from those that are harder to trust,” Dr. Patabendige said. “That’s important, not just in pregnancy care, but in any field where clinical guidelines rely on published studies.”

Labor induction, used to stimulate labor before it begins naturally, affects more than 1 in 3 births in Australia. While it is a safe and often necessary intervention, there’s ongoing debate about when and how it should be used. That makes the quality of the underlying evidence especially important—but this study shows that some trials included in current reviews may not be as reliable as they seem.

The authors emphasize that data sharing itself doesn’t guarantee quality, but that it allows deeper scrutiny and is one of the clearest signals that a study was conducted with scientific integrity.

They are calling for greater support and stronger expectations for sharing de-identified trial data, particularly in fields like pregnancy and women’s health where evidence directly influences clinical care.

“We need to stop assuming that all published research is equally sound,” Dr. Patabendige said. “Sharing data strengthens science, rebuilds trust, and ultimately leads to better decisions for patients.”