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Lageyre Signs Professional Contract with Angel City in NWSL
LOS ANGELES, Calif. – Duke women’s soccer graduate Carina Lageyre signed her first professional contract this week with Angel City Football Club (ACFC) of the National Women’s Soccer League (NWSL).
Lageyre, who hails from Cooper City,…Continue Reading
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Professor Sir Aziz Sheikh: Towards next-generation pharmacovigilance capabilities for the UK
Foreword
For decades, the UK has been recognised for its leadership in pharmacovigilance, underpinned by the MHRA’s Yellow Card scheme, which continues to play a vital role in detecting important safety signals early.
As medicines and medical technologies become more complex, used by increasingly diverse populations, and reach patients at greater speed, there are exciting opportunities to further strengthen our safety monitoring systems.
As outlined by Professor Aziz Sheikh in the latest of our strategy blog series, the COVID-19 pandemic demonstrated the potential of a modern, agile safety system. We rapidly digitised the Yellow Card reporting platform, introduced AI to manage large volumes of reports, and combined enhanced passive surveillance with active monitoring of vaccine safety using national usage data and anonymised electronic health records.
With the launch of the Health Data Research Service on the horizon, we now have the opportunity to build on these achievements and apply the same approach across all medicines and medical products – enhancing the UK’s already world-leading, real-time surveillance capabilities and further safeguarding patient health.
Professor Sir Aziz Sheikh is Pro-Vice-Chancellor and Head of the Nuffield Department of Primary Care Health Sciences at the University of Oxford. A leading global authority on primary care, public health and the use of real-world data, he has played a central role in advancing the UK’s capabilities in drug safety, digital health and evidence-based policy.
Guest Blog: Professor Sir Aziz Sheikh
Our current approach to pharmacovigilance has proven invaluable, but it remains largely passive and could be greatly enhanced. Whilst we’ve moved on from relying on clinicians to tear out a Yellow Card from the back of the British National Formulary (BNF) to sophisticated reporting platforms, the voluntary nature of reporting of cases falls far short of what we should expect, meaning that detecting and assessing safety signals takes longer than we want.– We need a more proactive and systematic effort to identify medication (and related products) associated harm to inform approaches to reducing such risks at the earliest possible opportunity. With our digitised health infrastructure now covering virtually the entire UK population, we have a major opportunity to emerge as a world-leader in next-generation pharmacovigilance capabilities.
The process of digitising the NHS has been long and arduous, but is – thankfully – now nearing completion. This means that the real-world data emerging out of the back-end of these digitised health record systems can now be linked across the entire care continuum using the unique NHS number (or equivalent in the UK’s devolved administrations) providing an unprecedented foundation from which to build next generation pharmacovigilance systems. Such systems would allow, for example, the routine running of analyses to estimate the incidence of known adverse events identified during drug development or licensing processes, identification of sub-populations who may be at particularly high risk of drug adverse events, and running formal epidemiological analyses to investigate potential adverse events reported through the Yellow Card scheme or other routes. An example of such an analysis involved assessing the risk of varenicline, a potent smoking cessation aid, after small-scale analyses suggested that this may increase the risk of cardiovascular and neuropsychiatric risks resulting in a black box warning being issued by the US Food and Drug Administration (FDA) . Our national retrospective cohort study undertaken in the large, representative QRisk database however failed to confirm these heightened risks when compared with other pharmacological smoking cessation thereby supporting the continued use of varenicline.
The FDA Sentinel System is now one the largest electronic health record-based database in the world undertaking federated drug safety analyses on up to 170 million patients from around 70 health systems across the US. Whilst we would not be able to compete with the FDA Sentinel System in terms of numbers, with our UK population of 68 million people we would nonetheless be very well placed to run analyses on a scale that could detect most rare safety signals. Unlike the US, we also have the distinct advantage of being able to run such safety analyses on the total population thus reducing the risk of bias and maximising generalisability.
Once data pipelines have been built, and data curation and analyses processes have been standardised, there is the potential to automate the most common analyses such that the system of searching for drug related adverse events is in effect “always on” working away in the background.
Whilst such aspirations might seem something of a pipe-dream at the moment, there has in recent years been considerable progress on a number of the essential elements, including: systematic use of the NHS number, developments in cloud-based dataset hosting, progress in deterministic and probabilistic data linkage approaches, and proof-of principle established during the COVID-19 pandemic that the UK can deliver high quality vaccine and drug safety work – at pace – including on the entire UK population.
The imminent launch of the Health Data Research Service (HDRS), with substantial political and financial support from the UK Government, offers an unprecedented opportunity to build on the UK’s outstanding strengths in pharmacovigilance to create near real-time whole population capability to support the safe and effective use of drugs to advance human health.
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Danny Mortimer appointed Director General for People
The DHSC announced Danny’s new appointment earlier today.
Danny Mortimer, chief executive of NHS Employers and deputy chief executive of the NHS Confederation, said: “I have worked in the NHS for over 30 years, and look forward to working with colleagues across government and the service to develop our shared ambitions for the people and patients served by the NHS. I look back on my time at NHS Employers and the NHS Confederation with real gratitude for the support of colleagues and our members.”
Matthew Taylor, chief executive of the NHS Confederation, said: “On behalf of our members and staff, I would offer my congratulations to Danny Mortimer on his appointment as the Department of Health and Social Care’s new director general for people”.
Next steps
NHS Employers will advertise for its new chief executive later this month and interim leadership arrangements will be confirmed in due course.
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Pakistan and Azerbaijan agrees to finalize mechanism allowing Azerbaijani investments in identified sectors of Pakistan's economy: Pakistan's Foreign Ministry – Azərtac
- Pakistan and Azerbaijan agrees to finalize mechanism allowing Azerbaijani investments in identified sectors of Pakistan’s economy: Pakistan’s Foreign Ministry Azərtac
- Pakistan, Azerbaijan to Finalize Investment Mechanism Caspian Post
- Pakistan,…
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PM announces to launch major development projects in Balochistan – RADIO PAKISTAN
- PM announces to launch major development projects in Balochistan RADIO PAKISTAN
- In Quetta, PM Shehbaz stresses ‘brotherhood and cooperation’ with provinces, especially those facing challenges Dawn
- Serious, result-oriented measures being taken…
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EBRD extends €13 million to support Kosovo’s Speeex international expansion
- EBRD lends up to €13 million to Speeex for the acquisition of three Swiss companies
- First merger and acquisition in Kosovo to support international expansion of a local company in the service and technology sector
- Project to promote a diverse and inclusive workforce through new strategy and action plan
The European Bank for Reconstruction and Development (EBRD) is providing a senior loan of up to €13 million to support the international expansion of Speeex, a leading Kosovo-based, tech-enabled business service provider with a strong focus on the Swiss market. This is the first merger and acquisition in Kosovo that supports the international expansion of a local company.
The financing will support Speeex’s acquisition of majority stakes in three Swiss companies – pdc Marketing + Information Technology, Profi Office and Profi Contact – through a newly established Swiss special purpose vehicle. This strategic move will enable Speeex to integrate artificial intelligence into its operations, diversify its already international client base and transfer Swiss best practices to its Kosovan operations, raising service standards above regional norms.
By supporting Speeex’s expansion, the EBRD aims to promote knowledge transfer and job creation in Kosovo, while reinforcing governance and financial discipline. In addition, the investment will strengthen cross-border trade and contribute to the country’s economic development.
Sergiy Maslichenko, EBRD Head of Kosovo, said: “Supporting the growth and internationalisation of dynamic companies like Speeex is at the heart of the EBRD’s mission in Kosovo. This investment will not only help Speeex expand its reach and capabilities, but also foster innovation, create jobs and promote gender equality in the local workforce. We are proud to back a project that strengthens cross-border ties and brings Swiss best practices to Kosovo’s service and technology sector.”
Holger Muent, EBRD Head of Telecoms, Media and Technology (TMT), commented: “We are very proud to expand our long-standing relationship with Speeex, one of the leaders of the tech-enabled services sector in Kosovo. The project will help to further develop Kosovo’s human capital base in the sector and strengthen its international competitiveness.”
Fikret Murati, founder and Chief Executive Officer of Speeex, said: “We are deeply grateful for our cooperation with the EBRD and for its support in enabling our international expansion into Switzerland. This marks the first-ever Kosovan-led acquisition in the service and technology sector, and we are proud to be setting this milestone. Beyond strategic growth, this partnership will drive innovation by strengthening cross-border knowledge exchange and advancing digital capabilities. Most importantly, it will create hundreds of new job opportunities for youngsters in both Kosovo and Switzerland, generating long-term social and economic impact. Hence, it will enhance Kosovo’s European competitiveness in the tech-enabled services sector.”
Founded in 2016, Speeex employs more than 1,600 staff across Kosovo and exports over 90 per cent of its services to Austria, Germany and Switzerland. The new investment will further strengthen Speeex’s position as a high-performing local enterprise scaling internationally.
The project aligns with the EBRD’s strategic priorities for Kosovo and the TMT sector, supporting the growth of information technology (IT) services companies and accelerating the digital transition. It also contains a dedicated focus on improving opportunities for women and promoting gender inclusion in the workforce.
The EBRD is a leading institutional investor in Kosovo, having invested €840 million through 138 projects to date.
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Creatine Supplements Are Everywhere. Do I Need Them? (2026)
Creatine monohydrate is typically sold as a flavorless, white powder that you can mix into water or a shake. According to Amati, the standard dose is three to five grams per day. Some athletes may “load” with higher doses, but studies show…
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Transcript of the Press Briefing by the Spokesperson on Thursday, 08 January 2026
Assalam-o-Alaikum,
Welcome to the Ministry of Foreign Affairs.
Let us begin with the roundup of last week’s activitiesOn 5 January the people of Pakistan joined the people of Jammu and Kashmir in commemorating…
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Delay discounting correlates with depression but does not predict relapse after antidepressant discontinuation
WHO. Depression and Other Common Mental Disorders: Global Health Estimates (World Health Organization, 2017).
GBD 2019 Mental Disorders Collaborators. Global. Regional, and National Burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of disease study 2019. The Lancet Psychiatry 2022;9,137–150.
Lépine J-P, Briley M. The increasing burden of depression. Neuropsychiatr Dis Treat. 2011;7:3.
Google Scholar
American Psychiatric Association, A.; Association, A. P. Diagnostic and Statistical Manual of Mental Disorders: DSM-5; Washington, DC: American psychiatric association, 2013; Vol. 10.
Geddes JR, Carney SM, Davies C, Furukawa TA, Kupfer DJ, Frank E, et al. Relapse prevention with antidepressant drug treatment in depressive disorders: a systematic review. Lancet. 2003;361:653–61.
Google Scholar
Kaymaz N, van Os J, Loonen AJ, Nolen WA. Evidence that patients with single versus recurrent depressive episodes are differentially sensitive to treatment discontinuation: a meta-analysis of placebo-controlled randomized trials. J Clin Psychiatry. 2008;69:6813.
Google Scholar
Glue P, Donovan MR, Kolluri S, Emir B. Meta-analysis of relapse prevention antidepressant trials in depressive disorders. Aust N Z J Psychiatry. 2010;44:697–705.
Google Scholar
Sim K, Lau WK, Sim J, Sum MY, Baldessarini RJ. Prevention of relapse and recurrence in adults with major depressive disorder: systematic review and meta-analyses of controlled trials. Int J Neuropsychopharmacol. 2016;19:pyv076.
Google Scholar
Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: A STAR* D report. Am J Psychiatry. 2006;163:1905–17.
Google Scholar
Olfson M, Marcus SC, Tedeschi M, Wan GJ. Continuity of antidepressant treatment for adults with depression in the United States. Am J Psychiatry. 2006;163:101–8.
Google Scholar
National Collaborating Centre for Mental Health (UK). Depression: The Treatment and Management of Depression in Adults (Updated Edition). Leicester (UK): British Psychological Society. 2010.
Recommendations Depression in adults: treatment and management | Guidance | NICE. https://www.nice.org.uk/guidance/ng222/chapter/Recommendations#preventing-relapse Accessed 2023-09-14.
Trinh N-HT, Shyu I, McGrath PJ, Clain A, Baer L, Fava M, et al. Examining the Role of Race and ethnicity in relapse rates of major depressive disorder. Compr Psychiatry. 2011;52:151–5.
Google Scholar
McGrath PJ, Stewart JW, Petkova E, Quitkin FM, Amsterdam JD, Fawcett J, et al. Predictors of relapse during fluoxetine continuation or maintenance treatment of major depression. J Clin Psychiat. 2000;61:518–24.
Google Scholar
Joliat MJ, Schmidt ME, Fava M, Zhang S, Michelson D, Trapp NJ, et al. Long-term treatment outcomes of depression with associated anxiety: efficacy of continuation treatment with fluoxetine. J Clin Psychiatry. 2004;65:1080.
Google Scholar
Fava M, Wiltse C, Walker D, Brecht S, Chen A, Perahia D. Predictors of relapse in a study of duloxetine treatment in patients with major depressive disorder. J Affect Disord. 2009;113:263–71.
Google Scholar
Stewart JW, Quitkin FM, McGrath PJ, Amsterdam J, Fava M, Fawcett J, et al. Use of pattern analysis to predict differential relapse of remitted patients with major depression during 1 year of treatment with fluoxetine or placebo. Arch Gen Psychiat. 1998;55:334–43.
Google Scholar
Berwian IM, Walter H, Seifritz E, Huys QJ. Predicting relapse after antidepressant withdrawal–a systematic review. Psychol Med. 2017;47:426–37.
Google Scholar
Viguera AC, Baldessarini RJ, Friedberg J. Discontinuing antidepressant treatment in major depression. Harv Rev Psychiatry. 1998;5:293–306.
Google Scholar
Bickel WK, Athamneh LN, Basso JC, Mellis AM, DeHart WB, Craft WH, et al. Excessive discounting of delayed reinforcers as a trans-disease process: update on the state of the science. Curr Opin Psychol. 2019;30:59–64.
Google Scholar
Frost R, McNaughton N. The neural basis of delay discounting: a review and preliminary model. Neurosci Biobehav Rev. 2017;79:48–65.
Google Scholar
Critchfield TS, Kollins SH. Temporal discounting: basic research and the analysis of socially important behavior. J Appl Behav Anal. 2001;34:101–22. https://doi.org/10.1901/jaba.2001.34-101
Google Scholar
Koffarnus MN, Jarmolowicz DP, Mueller ET, Bickel WK. Changing delay discounting in the light of the competing neurobehavioral decision systems theory: a review: changing delay discounting. J Exp Anal Behav. 2013;99:32–57. https://doi.org/10.1002/jeab.2
Google Scholar
Cáceda R, Durand D, Cortes E, Prendes-Alvarez S, Moskovciak T, Harvey PD, et al. Impulsive choice and psychological pain in acutely suicidal depressed patients. Psychosom Med. 2014;76:445–51. https://doi.org/10.1097/PSY.0000000000000075
Google Scholar
Engelmann JB, Maciuba B, Vaughan C, Paulus MP, Dunlop BW. Posttraumatic stress disorder increases sensitivity to long term losses among patients with major depressive disorder. PLoS ONE. 2013;8:e78292 https://doi.org/10.1371/journal.pone.0078292
Google Scholar
Pulcu E, Trotter PD, Thomas EJ, McFarquhar M, Juhász G, Sahakian BJ, et al. Temporal discounting in major depressive disorder. Psychol Med. 2014;44:1825–34.
Google Scholar
Imhoff S, Harris M, Weiser J, Reynolds B. Delay discounting by depressed and non-depressed adolescent smokers and non-smokers. Drug Alcohol Depend. 2014;135:152–5.
Google Scholar
Brown HE, Hart KL, Snapper LA, Roffman JL, Perlis RH. Impairment in delay discounting in schizophrenia and schizoaffective disorder but not primary mood disorders. npj Schizophr. 2018;4:9 https://doi.org/10.1038/s41537-018-0050-z
Google Scholar
Weidberg S, García-Rodríguez O, Yoon JH, Secades-Villa R. Interaction of depressive symptoms and smoking abstinence on delay discounting rates. Psychol Addictive Behav. 2015;29:1041–7. https://doi.org/10.1037/adb0000073
Google Scholar
Amlung M, Marsden E, Holshausen K, Morris V, Patel H, Vedelago L, et al. Delay discounting as a transdiagnostic process in psychiatric disorders: a meta-analysis. JAMA Psychiatry. 2019;76:1176–86.
Google Scholar
Lempert KM, Pizzagalli DA. Delay discounting and future-directed thinking in anhedonic individuals. J Behav Ther Exp Psychiatry. 2010;41:258–64.
Google Scholar
Szuhany KL, MacKenzie Jr D, Otto MW. The impact of depressed mood, working memory capacity, and priming on delay discounting. J Behav Ther Exp Psychiatry. 2018;60:37–41.
Google Scholar
Felton JW, Strutz KL, McCauley HL, Poland CA, Barnhart KJ, Lejuez CW. Delay discounting interacts with distress tolerance to predict depression and alcohol use disorders among individuals receiving inpatient substance use services. Int J Ment Health Addict. 2020;18:1416–21.
Google Scholar
Moody L, Franck C, Bickel WK. Comorbid depression, antisocial personality, and substance dependence: relationship with delay discounting. Drug Alcohol Depend. 2016;160:190–6.
Google Scholar
Dombrovski AY, Szanto K, Siegle GJ, Wallace ML, Forman SD, Sahakian B, et al. Lethal forethought: delayed reward discounting differentiates high-and low-lethality suicide attempts in old age. Biol Psychiatry. 2011;70:138–44.
Google Scholar
Takahashi T, Oono H, Inoue T, Boku S, Kako Y, Kitaichi Y, et al. Depressive patients are more impulsive and inconsistent in intertemporal choice behavior for monetary gain and loss than healthy subjects–an analysis based on Tsallis’ statistics. Neuro Endocrinology Letters 2008;29:351–8.
Owen GS, Martin W, Gergel T. Misevaluating the future: affective disorder and decision-making capacity for treatment–a temporal understanding. Psychopathology. 2019;51:371–9.
Google Scholar
Cowen PJ, Browning M. What has serotonin to do with depression? World Psychiatry. 2015;14:158.
Google Scholar
Ruhé HG, Frokjaer VG, Haarman BCM, Jacobs GE, Booij J, Molecular Imaging of Depressive Disorders. In PET and SPECT in Psychiatry; Dierckx, RAJO, Otte, A, et al. Eds.; Cham: Springer International Publishing:, 2021; pp 85–207.
Neumeister A, Nugent AC, Waldeck T, Geraci M, Schwarz M, Bonne O, et al. Neural and behavioral responses to tryptophan depletion in unmedicated patients with remitted major depressive disorder and controls. Arch Gen Psychiatry. 2004;61:765–73.
Google Scholar
Cowen PJ. Serotonin and depression: pathophysiological mechanism or marketing myth? Trends Pharmacol Sci. 2008;29:433–6.
Google Scholar
Schweighofer N, Bertin M, Shishida K, Okamoto Y, Tanaka SC, Yamawaki S, et al. Low-serotonin levels increase delayed reward discounting in humans. J Neurosci. 2008;28:4528–32.
Google Scholar
Crockett MJ, Clark L, Lieberman MD, Tabibnia G, Robbins TW. Impulsive choice and altruistic punishment are correlated and increase in tandem with serotonin depletion. Emotion. 2010;10:855–62.
Google Scholar
Tanaka SC, Schweighofer N, Asahi S, Shishida K, Okamoto Y, Yamawaki S, et al. Serotonin differentially regulates short- and long-term prediction of rewards in the ventral and dorsal striatum. PLoS ONE. 2007;2:e1333.
Google Scholar
Carlisi CO, Chantiluke K, Norman L, Christakou A, Barrett N, Giampietro V, et al. The effects of acute fluoxetine administration on temporal discounting in youth with ADHD. Psychological Med. 2016;46:1197–209.
Google Scholar
Miyazaki KW, Miyazaki K, Tanaka KF, Yamanaka A, Takahashi A, Tabuchi S, et al. Optogenetic activation of dorsal raphe serotonin neurons enhances patience for future rewards. Curr Biol. 2014;24:2033–40.
Google Scholar
Miyazaki K, Miyazaki KW, Sivori G, Yamanaka A, Tanaka KF, Doya K. Serotonergic projections to the orbitofrontal and medial prefrontal cortices differentially modulate waiting for future rewards. Sci Adv. 2020;6:eabc7246.
Google Scholar
Wogar MA, Bradshaw CM, Szabadi E. Effect of lesions of the ascending 5-hydroxytryptaminergic pathways on choice between delayed reinforcers. Psychopharmacology. 1993;111:239–43.
Google Scholar
Mobini S, Chiang T-J, Ho M-Y, Bradshaw CM, Szabadi E. Effects of central 5-hydroxytryptamine depletion on sensitivity to delayed and probabilistic reinforcement. Psychopharmacology. 2000;152:390–7.
Google Scholar
Denk F, Walton ME, Jennings KA, Sharp T, Rushworth MFS, Bannerman DM. Differential involvement of serotonin and dopamine systems in cost-benefit decisions about delay or effort. Psychopharmacology. 2005;179:587–96.
Google Scholar
Berwian IM, Wenzel JG, Kuehn L, Schnuerer I, Seifritz E, Stephan KE, et al. Low predictive power of clinical features for relapse prediction after antidepressant discontinuation in a naturalistic setting. Sci Rep. 2022;12:1–11.
Google Scholar
Berwian IM, Wenzel JG, Collins AG, Seifritz E, Stephan KE, Walter H, et al. Computational mechanisms of effort and reward decisions in patients with depression and their association with relapse after antidepressant discontinuation. JAMA Psychiatry. 2020;77:513–22.
Google Scholar
Berwian IM, Wenzel JG, Kuehn L, Schnuerer I, Kasper L, Veer IM, et al. The relationship between resting-state functional connectivity, antidepressant discontinuation and depression relapse. Sci Rep. 2020;10:1–10.
Google Scholar
Wakefield JC, Schmitz MF. When does depression become a disorder? using recurrence rates to evaluate the validity of proposed changes in major depression diagnostic thresholds. World Psychiatry. 2013;12:44–52.
Google Scholar
Williams JB. A structured interview guide for the hamilton depression rating scale. Arch Gen Psychiatry. 1988;45:742–7.
Google Scholar
Delay Discounting Analysis Plan. https://github.com/doronelad/AIDA_analysis_discouting/blob/main/AnalysisPlan_Discounting.pdf.
Kirby KN, Petry NM, Bickel WK. Heroin addicts have higher discount rates for delayed rewards than non-drug-using controls. J Exp Psychol Gen. 1999;128:78.
Google Scholar
Pooseh S, Bernhardt N, Guevara A, Huys QJ, Smolka MN. Value-based decision-making battery: a bayesian adaptive approach to assess impulsive and risky behavior. Behav Res Methods. 2018;50:236–49.
Google Scholar
Hinvest NS, Anderson IM. The effects of real versus hypothetical reward on delay and probability discounting. Q J Exp Psychol. 2010;63:1072–84. https://doi.org/10.1080/17470210903276350
Google Scholar
Johnson MW, Bickel WK. Within-subject comparison of real and hypothetical money rewards in delay discounting. J Exp Anal Behav. 2002;77:129–46. https://doi.org/10.1901/jeab.2002.77-129
Google Scholar
Madden GJ, Raiff BR, Lagorio CH, Begotka AM, Mueller AM, Hehli DJ, et al. Delay discounting of potentially real and hypothetical rewards: II. Between- and within-subject comparisons. Exp Clin Psychopharmacol. 2004;12:251–61. https://doi.org/10.1037/1064-1297.12.4.251
Google Scholar
Lagorio CH, Madden GJ. Delay discounting of real and hypothetical rewards III: steady-state assessments, forced-choice trials, and all real rewards. Behav Process. 2005;69:173–87. https://doi.org/10.1016/j.beproc.2005.02.003
Google Scholar
Mazur JE. An adjusting procedure for studying delayed reinforcement. Quant Anal Behav. 1987;5:55–73.
Van den Bos W, McClure SM. Towards a general model of temporal discounting. J Exp Anal Behav. 2013;99:58–73.
Google Scholar
McKerchar TL, Green L, Myerson J, Pickford TS, Hill JC, Stout SC. A comparison of four models of delay discounting in humans. Behav Process. 2009;81:256–9.
Google Scholar
Huys QJ, Cools R, Gölzer M, Friedel E, Heinz A, Dolan RJ, et al. Disentangling the roles of approach, activation and valence in instrumental and pavlovian responding. PLoS Comput Biol. 2011;7:e1002028.
Google Scholar
Guitart-Masip M, Huys QJ, Fuentemilla L, Dayan P, Duzel E, Dolan RJ. Go and No-Go learning in reward and punishment: interactions between affect and effect. Neuroimage. 2012;62:154–66.
Google Scholar
Gillan CM, Kosinski M, Whelan R, Phelps EA, Daw ND. Characterizing a psychiatric symptom dimension related to deficits in goal-directed control. elife. 2016;5:e11305.
Google Scholar
Akam T, Rodrigues-Vaz I, Marcelo I, Zhang X, Pereira M, Oliveira RF, et al. The anterior cingulate cortex predicts future states to mediate model-based action selection. Neuron. 2021;109:149–63.
Google Scholar
McFadden, D Conditional Logit Analysis of Qualitative Choice Behavior. 1973.
Myerson J, Baumann AA, Green L. Discounting of delayed rewards:(A) theoretical interpretation of the kirby questionnaire. Behav Process. 2014;107:99–105.
Google Scholar
Wilson AG, Franck CT, Mueller ET, Landes RD, Kowal BP, Yi R, et al. Predictors of delay discounting among smokers: education level and a utility measure of cigarette reinforcement efficacy are better predictors than demographics, smoking characteristics, executive functioning, impulsivity, or time perception. Addict Behav. 2015;45:124–33.
Google Scholar
Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc Ser B Stat Methodol. 1996;58:267–88.
Google Scholar
Saddichha S, Schuetz C. Impulsivity in remitted depression: a meta-analytical review. Asian J Psychiatry. 2014;9:13–16.
Google Scholar
Altaweel N, Upthegrove R, Surtees A, Durdurak B, Marwaha S. Personality traits as risk factors for relapse or recurrence in major depression: a systematic review. Front Psychiatry. 2023;14:709.
Google Scholar
Odum AL. Delay discounting: trait variable? Behav Proc. 2011;87:1–9.
Google Scholar
Gelino BW, Schlitzer RD, Reed DD, Strickland JC. A systematic review and meta‐analysis of test–retest reliability and stability of delay and probability discounting. J Exp Anal Behav. 2024;121:358–72.
Google Scholar
Faul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41:1149–60.
Google Scholar
Guiard BP, Mansari ME, Murphy DL, Blier P. Altered response to the selective serotonin reuptake inhibitor escitalopram in mice heterozygous for the serotonin transporter: an electrophysiological and neurochemical study. Int J Neuropsychopharmacol. 2012;15:349–61.
Google Scholar
Collins, HM Investigation of the Behavioural and Neurobiological Effects of SSRI Discontinuation in Mice. PhD Thesis, University of Oxford, 2023. https://ora.ox.ac.uk/objects/uuid:97caafe1-ea12-460b-8c1d-0de202db5592. Accessed 2023-09-24)
Trouvin JH, Gardier AM, Chanut E, Pages N, Jacquot C. Time course of brain serotonin metabolism after cessation of long-term fluoxetine treatment in the rat. Life Sci. 1993;52:PL187–PL192.
Google Scholar
Caccia S, Fracasso C, Garattini S, Guiso G, Sarati S. Effects of short-and long-term administration of fluoxetine on the monoamine content of rat brain. Neuropharmacology. 1992;31:343–7.
Google Scholar
Bosker FJ, Tanke MA, Jongsma ME, Cremers TI, Jagtman E, Pietersen CY, et al. Biochemical and behavioral effects of long-term citalopram administration and discontinuation in rats: role of serotonin synthesis. Neurochem Int. 2010;57:948–57.
Google Scholar
Elad, D; Story, GW; Berwian, IM; Stephan, KE; Walter, H; Huys, Q Delay discounting correlates with depression but does not predict relapse after antidepressant discontinuation. OSF. 2024. https://doi.org/10.31234/osf.io/5buq4.
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