{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/31025"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/31025","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Risky decision-making in the Context of Contingency Management for Methamphetamine Use Disorder","abstract":"Background: Risky decision-making is strongly implicated in adverse real-world risk-taking behaviour, and is associated with Substance Use Disorder, including Methamphetamine Use Disorder. Laboratory neurocognitive tasks typically utilized to assess risky decision-making have been able to distinguish participants with Substance Use Disorder from controls, although considerable heterogeneity is still evident within substance-using populations, which remains largely unexplained. Preliminary evidence has also tied risky decision-making to treatment outcomes, although no research has investigated risk-decision-making within Methamphetamine Use Disorder in the context of Contingency Management treatment. Methods: This study aimed to investigate decision-making on the Iowa Gambling Task and the Balloon Analogue Risk at baseline as both a function and predictor of treatment response on an 8-week treatment of Contingency Management. Of 26 participants with Methamphetamine Use Disorder, 17 responded to Contingency Management treatment, whilst 9 were non-responders. Using various mixed-effect modelling techniques and ANCOVA, performance by nonresponders were compared to responders, as well as a group of 19 healthy, nonsubstance-using control participants. Results: Group differences between non-responders, responders and controls were exclusively obtained on the Iowa Gambling Task. A trend-level (p=.051), large effect size (g=-0.98) was observed in the effect of reward magnitude between non-responders and healthy controls. More specifically, non-responders tended to seek-out large short-term rewards in spite of long-term losses relative to controls, however, groups did not also differ in effect of short-term loss magnitude. Non-responders also appeared to demonstrate poorer learning than healthy controls, although this finding was also at trend-level (p=.081) with a medium effect size (g =-0.63). In addition, results showed that responders and non-responders were differentially influenced by the frequency of outcomes, where responders demonstrated a greater preference for frequent rewards and infrequent losses relative to non-responders. This difference was at trend-level (p=.053) and the effect was moderately sized (g =-0.74). Impulsivity did not moderate group differences in decision-making, but did positively predict a greater likelihood of relapse at least once during Contingency Management (p =.035), although this effect was small (OR=1.10). Poor overall performance on the IGT appeared to predict a greater likelihood of prolonged relapse on Contingency Management following initial relapse, although this was at trend-level (p =.071) with a small effect size (OR=1.80). Conclusion: Findings provide evidence for individual differences in risky decision-making within Methamphetamine User Disorder, suggesting that risky decision-making is unlikely to be a homogeneous characteristic of substance-using populations, as is typically treated in the literature. Risky decision-making may also act as a risk factor for poor treatment success on Contingency Management, which in turn suggests that assessing risky decision-making of individuals with Methamphetamine Use disorder prior to commencing Contingency Management treatment might assist in identifying those at high risk.","abstract_html":"Background: Risky decision-making is strongly implicated in adverse real-world risk-taking behaviour, and is associated with Substance Use Disorder, including Methamphetamine Use Disorder. Laboratory neurocognitive tasks typically utilized to assess risky decision-making have been able to distinguish participants with Substance Use Disorder from controls, although considerable heterogeneity is still evident within substance-using populations, which remains largely unexplained. Preliminary evidence has also tied risky decision-making to treatment outcomes, although no research has investigated risk-decision-making within Methamphetamine Use Disorder in the context of Contingency Management treatment. Methods: This study aimed to investigate decision-making on the Iowa Gambling Task and the Balloon Analogue Risk at baseline as both a function and predictor of treatment response on an 8-week treatment of Contingency Management. Of 26 participants with Methamphetamine Use Disorder, 17 responded to Contingency Management treatment, whilst 9 were non-responders. Using various mixed-effect modelling techniques and ANCOVA, performance by nonresponders were compared to responders, as well as a group of 19 healthy, nonsubstance-using control participants. Results: Group differences between non-responders, responders and controls were exclusively obtained on the Iowa Gambling Task. A trend-level (p=.051), large effect size (g=-0.98) was observed in the effect of reward magnitude between non-responders and healthy controls. More specifically, non-responders tended to seek-out large short-term rewards in spite of long-term losses relative to controls, however, groups did not also differ in effect of short-term loss magnitude. Non-responders also appeared to demonstrate poorer learning than healthy controls, although this finding was also at trend-level (p=.081) with a medium effect size (g =-0.63). In addition, results showed that responders and non-responders were differentially influenced by the frequency of outcomes, where responders demonstrated a greater preference for frequent rewards and infrequent losses relative to non-responders. This difference was at trend-level (p=.053) and the effect was moderately sized (g =-0.74). Impulsivity did not moderate group differences in decision-making, but did positively predict a greater likelihood of relapse at least once during Contingency Management (p =.035), although this effect was small (OR=1.10). Poor overall performance on the IGT appeared to predict a greater likelihood of prolonged relapse on Contingency Management following initial relapse, although this was at trend-level (p =.071) with a small effect size (OR=1.80). Conclusion: Findings provide evidence for individual differences in risky decision-making within Methamphetamine User Disorder, suggesting that risky decision-making is unlikely to be a homogeneous characteristic of substance-using populations, as is typically treated in the literature. Risky decision-making may also act as a risk factor for poor treatment success on Contingency Management, which in turn suggests that assessing risky decision-making of individuals with Methamphetamine Use disorder prior to commencing Contingency Management treatment might assist in identifying those at high risk.","abstract_has_math":false,"creators":["Lake, Marilyn Toni"],"institution":"Department of Psychology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Lipinska, Gosia","Ipser, Jonathan C."],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019","date_published":"2019","updated_at":"2026-07-22T22:22:39Z","subjects":["Psychological Research"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/31025","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Lipinska, Gosia","Ipser, Jonathan C."]},{"key":"dc:creator","label":"Author","values":["Lake, Marilyn Toni"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2020-02-11T12:05:22Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2020-02-11T12:05:22Z"]},{"key":"dc:date.issued","label":"Date","values":["2019"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Psychology"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MSocSci"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Psychological Research"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/31025"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Background: Risky decision-making is strongly implicated in adverse real-world risk-taking behaviour, and is associated with Substance Use Disorder, including Methamphetamine Use Disorder. Laboratory neurocognitive tasks typically utilized to assess risky decision-making have been able to distinguish participants with Substance Use Disorder from controls, although considerable heterogeneity is still evident within substance-using populations, which remains largely unexplained. Preliminary evidence has also tied risky decision-making to treatment outcomes, although no research has investigated risk-decision-making within Methamphetamine Use Disorder in the context of Contingency Management treatment. Methods: This study aimed to investigate decision-making on the Iowa Gambling Task and the Balloon Analogue Risk at baseline as both a function and predictor of treatment response on an 8-week treatment of Contingency Management. Of 26 participants with Methamphetamine Use Disorder, 17 responded to Contingency Management treatment, whilst 9 were non-responders. Using various mixed-effect modelling techniques and ANCOVA, performance by nonresponders were compared to responders, as well as a group of 19 healthy, nonsubstance-using control participants. Results: Group differences between non-responders, responders and controls were exclusively obtained on the Iowa Gambling Task. A trend-level (p=.051), large effect size (g=-0.98) was observed in the effect of reward magnitude between non-responders and healthy controls. More specifically, non-responders tended to seek-out large short-term rewards in spite of long-term losses relative to controls, however, groups did not also differ in effect of short-term loss magnitude. Non-responders also appeared to demonstrate poorer learning than healthy controls, although this finding was also at trend-level (p=.081) with a medium effect size (g =-0.63). In addition, results showed that responders and non-responders were differentially influenced by the frequency of outcomes, where responders demonstrated a greater preference for frequent rewards and infrequent losses relative to non-responders. This difference was at trend-level (p=.053) and the effect was moderately sized (g =-0.74). Impulsivity did not moderate group differences in decision-making, but did positively predict a greater likelihood of relapse at least once during Contingency Management (p =.035), although this effect was small (OR=1.10). Poor overall performance on the IGT appeared to predict a greater likelihood of prolonged relapse on Contingency Management following initial relapse, although this was at trend-level (p =.071) with a small effect size (OR=1.80). Conclusion: Findings provide evidence for individual differences in risky decision-making within Methamphetamine User Disorder, suggesting that risky decision-making is unlikely to be a homogeneous characteristic of substance-using populations, as is typically treated in the literature. Risky decision-making may also act as a risk factor for poor treatment success on Contingency Management, which in turn suggests that assessing risky decision-making of individuals with Methamphetamine Use disorder prior to commencing Contingency Management treatment might assist in identifying those at high risk."]},{"key":"dc:title","label":"Title","values":["Risky decision-making in the Context of Contingency Management for Methamphetamine Use Disorder"]}]}],"canonical_facts":{"dc:contributor.advisor":["Lipinska, Gosia","Ipser, Jonathan C."],"dc:creator":["Lake, Marilyn Toni"],"dc:date.accessioned":["2020-02-11T12:05:22Z"],"dc:date.available":["2020-02-11T12:05:22Z"],"dc:date.issued":["2019"],"dc:description.abstract":["Background: Risky decision-making is strongly implicated in adverse real-world risk-taking behaviour, and is associated with Substance Use Disorder, including Methamphetamine Use Disorder. Laboratory neurocognitive tasks typically utilized to assess risky decision-making have been able to distinguish participants with Substance Use Disorder from controls, although considerable heterogeneity is still evident within substance-using populations, which remains largely unexplained. Preliminary evidence has also tied risky decision-making to treatment outcomes, although no research has investigated risk-decision-making within Methamphetamine Use Disorder in the context of Contingency Management treatment. Methods: This study aimed to investigate decision-making on the Iowa Gambling Task and the Balloon Analogue Risk at baseline as both a function and predictor of treatment response on an 8-week treatment of Contingency Management. Of 26 participants with Methamphetamine Use Disorder, 17 responded to Contingency Management treatment, whilst 9 were non-responders. Using various mixed-effect modelling techniques and ANCOVA, performance by nonresponders were compared to responders, as well as a group of 19 healthy, nonsubstance-using control participants. Results: Group differences between non-responders, responders and controls were exclusively obtained on the Iowa Gambling Task. A trend-level (p=.051), large effect size (g=-0.98) was observed in the effect of reward magnitude between non-responders and healthy controls. More specifically, non-responders tended to seek-out large short-term rewards in spite of long-term losses relative to controls, however, groups did not also differ in effect of short-term loss magnitude. Non-responders also appeared to demonstrate poorer learning than healthy controls, although this finding was also at trend-level (p=.081) with a medium effect size (g =-0.63). In addition, results showed that responders and non-responders were differentially influenced by the frequency of outcomes, where responders demonstrated a greater preference for frequent rewards and infrequent losses relative to non-responders. This difference was at trend-level (p=.053) and the effect was moderately sized (g =-0.74). Impulsivity did not moderate group differences in decision-making, but did positively predict a greater likelihood of relapse at least once during Contingency Management (p =.035), although this effect was small (OR=1.10). Poor overall performance on the IGT appeared to predict a greater likelihood of prolonged relapse on Contingency Management following initial relapse, although this was at trend-level (p =.071) with a small effect size (OR=1.80). Conclusion: Findings provide evidence for individual differences in risky decision-making within Methamphetamine User Disorder, suggesting that risky decision-making is unlikely to be a homogeneous characteristic of substance-using populations, as is typically treated in the literature. Risky decision-making may also act as a risk factor for poor treatment success on Contingency Management, which in turn suggests that assessing risky decision-making of individuals with Methamphetamine Use disorder prior to commencing Contingency Management treatment might assist in identifying those at high risk."],"dc:identifier.uri":["http://hdl.handle.net/11427/31025"],"dc:publisher.department":["Department of Psychology"],"dc:subject":["Psychological Research"],"dc:title":["Risky decision-making in the Context of Contingency Management for Methamphetamine Use Disorder"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MSocSci"]},"updated_at":"2026-07-22T22:22:39Z"}