Measuring reconceptualization and reprioritization during France's first COVID-19-related lockdown in women with and without a history of cancer: an adaptation of the SeiQol-DW and PGI.

PURPOSE: This study aimed to provide a better understanding of the patient-perceived effects of France's first COVID-19-related lockdown on the quality of life (QoL) of women affected by cancer, and to test an ad hoc measurement scale for evaluating quasi-individualized QoL. QoL was measured for both during (i.e., current) and before (i.e., retrospectively) the lockdown. Respondents were women registered on the research platform Seintinelles. METHODS: A tool for measuring quasi-individualized QoL was adapted from the SeiQol-DW and PGI. It was distributed as part of a larger online self-questionnaire to a sample of 1303 women with a history of cancer (i.e., former or current) and with no such history. RESULTS: Current and retrospective QoL scores were not significantly different between the two respondent groups. An analysis of reconceptualization and reprioritization revealed a cancer-specific effect: women with a history of cancer reconceptualized more, while women with no such history reprioritized more. CONCLUSION: Our novel ad hoc quasi-qualitative tool made it possible to assess the QoL of women with a history of cancer, a particularly vulnerable population in the context of the COVID-19 pandemic. Furthermore, it highlighted a difference in reconceptualization and reprioritization between this population and women with no such history.

Psychometrics Anonymous: Does a Transparent Data Sharing Policy Affect Data Collection?

As researchers, we are advised to share our data to improve transparency and increase the reproducibility of experiments. Simultaneously, making data freely accessible can raise ethical questions regarding the participants' privacy. We first outline the challenges regarding "open data" for researchers in light of the GDPR. Then, we turn to the impact of an open-access data sharing policy on the participants: could the participants' knowledge about the future use of the data alter the data itself? Through two pre-registered studies (N = 193, collected on campus and N = 543, online participation), we investigate whether disclosing that anonymized data will be publicly shared vs. not shared influences a potential participants' intention to take part in the study. Using both frequentist and Bayesian analysis, we conclude towards an absence of effect of a difference in data sharing policy on scores in the Big Five questionnaire and social desirability, careless response behavior, and results in the anchoring paradigm. In the second study, a lexicometric analysis of participants' reactions to openly sharing data reveals a readiness to share data and support transparency under the condition of preserved anonymity. Hence, if anonymity can be ensured, there seems to be no methodological or ethical drawback in transparent and open data sharing policies for many psychological studies.