Drug use is a time-consuming endeavour, particularly for opioids, whereby substantial time is required to seek out, prepare and consume drugs. This prioritization of drug use reduces the time that is available for substance-free alternatives that contribute positively to quality of life, such as socialization, education, employment, physical activity and self-care (Acuff et al., 2019). Given the time commitments, daily supervised treatment of opioid use disorder has poor adherence (Strang et al., 2020). As such, there is an interest in long-acting injectable medications, which can overcome these adherence issues (Saunders et al 2020). However, little is known about how patients on long-acting medications for opioid use disorder adapt to the increased free-time they have, and where this has downstream impacts on their well-being, quality of life and experience of stigma.
 
In the current study, Trøstheim and colleagues plan to conduct an observational investigation of >500 individuals from Norway with opioid use disorder who were receiving pharmacological treatment. Their primary hypothesis is that individuals with opioid use disorder will exhibit distinct time use profiles, which will be examined using latent profile analysis to identify time use patterns based on 17 measured time use variables e.g. ‘How many days in the past week have you done paid work, voluntary work, or community service’. Secondary analyses will test the associations between medication type, time use (based on the latent profile analysis), well-being, stigma and life-satisfaction. Findings from this study will provide a greater understanding of how long-acting medications for opioid use disorder impact free-time and quality of life.

 

The Stage 1 manuscript was evaluated over two rounds of in-depth review by two reviewers and the recommender. Following a response and revision, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance (IPA).
 

 

Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI-RR-friendly journals:
 

 

 
1. Acuff, S. F., Dennhardt, A. A., Correia, C. J., & Murphy, J. G. (2019). Measurement of substance-free reinforcement in addiction: A systematic review. Clinical Psychology Review, 70, 79-90. https://doi.org/10.1016/j.cpr.2019.04.003

 

2. Saunders, E. C., Moore, S. K., Walsh, O., Metcalf, S. A., Budney, A. J., Scherer, E., & Marsch, L. A. (2020). Perceptions and preferences for long-acting injectable and implantable medications in comparison to short-acting medications for opioid use disorders. Journal of Substance Abuse Treatment, 111, 54-66. https://doi.org/10.1016/j.jsat.2020.01.009

 

3. Strang, J., Volkow, N. D., Degenhardt, L., Hickman, M., Johnson, K., Koob, G. F., ... & Walsh, S. L. (2020). Opioid use disorder. Nature Reviews Disease Primers, 6, 3. https://doi.org/10.1038/s41572-019-0137-5

 

4. Trøstheim, M., Leknes, S., Solli, K. K., Carlyle, M., Ernst, G., & Eikemo, M. (2024). The Importance of Long- and Short-Acting Pharmacological Treatment Options for Time Use and Quality of Life in Individuals with Opioid Use Disorder: An Observational, Cross-Sectional, Survey-Based Study. In principle acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/vbpjg

Amendola and colleagues (2024) plan to examine the usefulness of Harmful Dysfunction Analysis (HDA) in identifying individuals with pathological social media disorder. Harmful Dysfunction Analysis, proposed by Wakefield et al (1992), is a framework for constructing diagnostic criteria, and suggests a disorder is a harmful dysfunction, and defines a dysfunction as a failure of an internal mechanism to perform its naturally designed function. One important distinction of HDA is that harmful consequences of behaviour in the absence of dysfunction does not mean a disorder is present. Both dysfunction and harm are required for diagnosis of a disorder

 

This analysis may provide a useful perspective on how to separate pathological social media use from high involvement. To examine their aims, the authors will conduct secondary analysis on data from the Health Behaviour in School-aged Children study (specifically the Swiss sample, N = 7,510), which is a world health organisation collaborative cross-sectional study of adolescent well-being from 2018 (https://www.who.int/europe/initiatives/health-behaviour-in-school-aged-children-(hbsc)-study). They will examine the 9-item Social Media Disorder Scale under DSM-5 and HDA categories (dysfunction and harm), and examine convergence between the scoring methods. Subsequent analyses will focus on groups defined by each scoring method (DSM vs HDA, with no overlapping cases) will be compared on measures of physical and mental health. Sensitivity analyses will be conducted in an independent sample from Hungary in 2023 (N = 3,789).

The Stage 1 manuscript was evaluated by three expert reviewers across two rounds of review. Following in-depth review and responses from the authors, the recommender judged that the Stage 1 criteria were met and awarded in-principle acceptance (IPA).
 

URL to the preregistered Stage 1 protocol: https://osf.io/y3ub8
 
Level of bias control achieved: Level 3. At least some data/evidence that will be used to the answer the research question has been previously accessed by the authors (e.g. downloaded or otherwise received), but the authors certify that they have not yet observed ANY part of the data/evidence.
 
List of eligible PCI RR-friendly journals:

 

 

References
 
1. Amendola, S., Hengartner, M. P., & Wakefield, J. C. (2024). The Harmful Dysfunction Analysis applied to the concept of behavioural addiction: A secondary analysis of data from the Health Behaviour in School-aged Children 2018. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/y3ub8
 
2. Wakefield, J. C. (1992). Disorder as Harmful Dysfunction: A Conceptual Critique of DSM-III-R’s Definition of Mental Disorder. Psychological Review, 99, 232–247. https://psycnet.apa.org/doi/10.1037/0033-295X.99.2.232

Experimental research demonstrates that executing or inhibiting motor responses (or approaching / avoiding) towards a stimulus can alter the valuation of the stimulus (Yang et al., 2022). There are competing theories as to the proposed mechanisms of value change, such as increased response conflict or prediction errors (Houben & Aulbach, 2023). However, research has mostly examined response execution/inhibition and approach/avoidance in isolation and the few studies that have examined these together have focused on stimulus evaluation as an outcome.
 
In the present study, Chen et al. (2024) will use a novel version of a combined go/no-go / approach avoidance paradigm to test the effects on choice of consumable candy. In this task, participants are randomly assigned to make a response framed as a go / no-go action or an approach / avoidance action to control a shopping cart (Chen & Van Dessel, 2024). Following this they will complete a food choice task in which participants make a series of binary choices for different candies. Their performance on this task will lead to the receipt of real-world candy. The authors aim to test whether the same responses will lead to different effects on food choice, depending on how the response was interpreted (e.g. participants in the approach/avoidance instruction group will select Approach items more often than those in the go/no-go instruction group). The study is well powered to detect the proposed effect size of interest, and data will be analysed using Bayesian mixed-effect models.
 
This study will shed light onto theoretical predictions of action interpretation on stimulus value and choice, which may improve the efficacy of behaviour change tools such as approach bias training in future.  
 

The Stage 1 manuscript was evaluated over two rounds of in-depth review. Based on detailed responses to the recommender and reviewers' comments, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/bn5xa (under temporary private embargo)

 

Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA. 
 
List of eligible PCI RR-friendly journals:
 

 

 
1. Chen, Z. and Van Dessel, P. (2024). Action interpretation determines the effects of go/no-go and approach/avoidance actions on stimulus evaluation. Open Mind, 8, 898-923.  https://doi.org/10.1162/opmi_a_00151

 

2. Chen, Z., Van Dessel, P., and Figner, B. (2024). Examining the role of action interpretation in changes in choice induced by go/no-go and approach/avoidance responses. In principle acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/bn5xa
 
3. Houben, K. and Aulbach, M. (2023). Is there a difference between stopping and avoiding? A review of the mechanisms underlying Go/No-Go and Approach-Avoidance training for food choice. Current Opinion in Behavioral Sciences, 49, 101245. https://doi.org/10.1016/j.cobeha.2022.101245
 
4. Yang, Y., Qi, L., Morys, F., Wu, Q. and Chen, H. (2022). Food-Specific Inhibition Training for Food Devaluation: A Meta-Analysis. Nutrients, 14, 1363. https://doi.org/10.3390/nu14071363
 

This study aims to examine the associations between personality traits, using the big-5 personality model (Costa & McCrae, 1992), and compliance with pandemic measures (e.g. handwashing), and perceived risk of the pandemic to the individual, in a representative sample of the adult Norwegian population.

 

Several previous studies have examined associations between personality and adherence to medical advice using measures administered at the same point in time the during COVID-19 pandemic (e.g. Götz et al., 2021), however the dataset the current investigators plan to use assessed personality one year prior to the pandemic (May/June 2019) and the risk and compliance measures four months into the pandemic (August/September 2020). 
 
Here, Sætrevik et al. (2024) make a number of hypotheses, including that conscientiousness, agreeableness, openness and neuroticism will be positively associated with compliance; extraversion will be negatively associated with compliance; extraversion and openness will be negatively associated with perceived risk; and finally, neuroticism will be positively associated with perceived risk. They plan to test their hypotheses using linear regression analyses.
 
Importantly, given the topic, the data for this study already exists and some response distributions of the compliance and risk measures have been examined. However, the authors have yet to link the data on personality to the data on compliance and risk, which is the focus of their hypotheses.  
 
The findings from this study will help us to understand the personality characteristics associated with infection control measures and individual risk perceptions of viral illnesses during a pandemic. 
 
The Stage 1 manuscript was evaluated by two expert reviewers in two rounds of in-depth review. Following responses from the authors, the recommender determined that Stage 1 criteria were met and awarded in-principle acceptance (IPA).

 

 

Level of bias control achieved: Level 1. At least some of the data/evidence that will be used to the answer the research question has been accessed and observed by the authors, including key variables, but the authors certify that they have not yet performed any of their preregistered analyses, and in addition they have taken stringent steps to reduce the risk of bias.
 
List of eligible PCI RR-friendly journals:
 

• Peer Community Journal
• PeerJ
• Personality Science
  
• Studia Psychologica
• Swiss Psychology Open

 

1. Costa, P. T., and McCrae, R. R. (1992). The five-factor model of personality and its relevance to personality disorders. Journal of Personality Disorders, 6, 343–359. https://doi.org/10.1521/pedi.1992.6.4.343
 
2. Götz, F. M., Gvirtz, A., Galinsky, A. D., and Jachimowicz, J. M. (2021). How personality and policy predict pandemic behavior: Understanding sheltering-in-place in 55 countries at the onset of COVID-19. The American psychologist, 76, 39–49. https://doi.org/10.1037/amp0000740

 

3. Sætrevik, B., Erevik, E. K., and Bjørkheim, S. B. (2024). Personality traits predict perception of pandemic risk and compliance with infection control measures. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/p5sjb